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Welcome to the NICE conference call discussing second quarter 2026 results, and thank you all for holding. [Operator Instructions] Following management's formal presentation, instructions will be given for the question-and-answer session. As a reminder, this conference is being recorded August 5, 2026.

I would now like turn this call over to Mr. Ryan Gilligan, Vice President, Investor Relations at NICE. Please go ahead.

Thank you, operator. With me on today's call are Scott Russell, Chief Executive Officer and Beth Gaspich, Chief Financial Officer.

Before we start, I would like to point out that some of the statements made on this call will constitute forward-looking statements in accordance with the safe harbor provision of the Private Securities Litigation Reform Act of 1995, please be advised that the company's actual results could differ materially from these forward-looking statements. Additional information regarding the factors that could cause actual results or performance of the company to differ materially is contained in the section entitled Risk Factors in Item 3 of the company's 2025 annual report on Form 20-F as filed with the Securities and Exchange Commission on February 26, 2026.

During today's call, we will present a more detailed discussion of second quarter 2026 results and the company's guidance for the third quarter and full year 2026. A copy of today's press release, investor presentation can be found on NICE's Investor Relations website. Following our comments, there will be an opportunity for questions. Let me remind you that unless otherwise noted on this call, we will be commenting on our adjusted results of operations, which differ in certain respects from generally accepted accounting principles as reflected mainly in accounting for share-based compensation, amortization of acquired intangible assets, acquisition and divestiture-related expenses, gains on intercompany foreign currency transactions, amortization of deferred financing costs, amortization of discount on debt, the tax effect of the non-GAAP adjustments and the tax rate impact resulting from the non-U.S. intercompany transaction. The differences between the non-GAAP adjusted results and the equivalent GAAP figures are detailed in today's press release.

The information and some of our comments discussed on this call may contain forward-looking statements that are subject to risks, uncertainties and assumptions.

I will now turn the call over to Scott.

Thank you, Ryan, and good morning, everyone. I'm encouraged by our execution in the second quarter as we continue to strengthen our leadership position in the CX AI market. We're still in the early stages of our growth opportunity and our second quarter results reinforce that underlying demand trends in our business continue to build strong momentum. In Q2, we delivered total revenue of $782 million above the high end of our guidance range and non-GAAP EPS of $2.70 at the high end of the range. Cloud revenue grew 12.6% year-over-year as customers increasingly consolidate around a single enterprise CX AI platform that powers seamless experiences across every channel. That trend reflects a broader reality.

Customer engagement is a category in its own right. It connects with broader enterprise workflows, but it remains a distinct system of engagement where every interaction happens in real time, and every customer experience matters. It requires a different level of specialization than enterprise workflow automation or AI only interaction models, and that's exactly where NICE has built its leadership. As customer interactions continue to grow with AI interactions growing even faster, customer engagement is becoming a more strategic capability for the enterprise. That shift is driving enterprises to scale customer engagement and AI across their organizations, expanding their investment in NICE.

This is reflected in continued CXone seat growth, a record Q2 for new cloud ACV bookings, including another record quarter for AI bookings, a strong cloud backlog growth of 19% and AI backlog growth of 72%. One additional point. These backlog metrics do not include our recently signed HMRC deal. Had HMRC being included, cloud backlog growth would have been similar to last quarter, while AI backlog growth would have accelerated above Q1. In Q2, nearly every CXone enterprise deal included AI. Customers are choosing NICE Cognigy because of its proven success operating at enterprise scale. AI deal volumes and average deal sizes continue to grow substantially. And we're seeing our installed base increasingly choose NICE Cognigy. Win rates are very high with existing CXone customers as these enterprises view NICE as a trusted partner and see the benefit of a single CX AI platform. And the beauty of NICE Cognigy is it also continues to compete well on a stand-alone basis. ARR increased 52% year-over-year, and AI now represents 15% of cloud revenue.

Within that, our Agentic AI solutions grew even further. As enterprises scale AI across their organizations, adoption naturally ramps over time. While the technology can be implemented quickly customers are preparing their data, governance and operating models before scaling AI across mission-critical workflows. Our deployed engineers and NICE Labs engagement models proactively help our customers accelerate that journey. Importantly, virtually all of our AI revenue already comes from production deployments rather than pilots, where customers are achieving meaningful results at scale.

International is another area of strength. In Q2, international revenue increased 22% year-over-year, and our recently announced HMRC win is another example of the large-scale enterprise transformations we're increasingly winning. Cloud migrations, our expanding partner ecosystem and growing demand for sovereign cloud deployments, particularly in Europe, are creating multiple durable drivers of international growth. Broadly speaking, our Q2 results reinforce what we recently discussed with customers and partners at NICE World Orlando and NICE World London. Attendance at both events increased more than 20% year-over-year, evidence of the growing interest in our fully AI-native CX platform.

It is clear enterprises are no longer valuing AI based on what it can demonstrate. They're evaluating it based on what it can deliver in production, accuracy, governance, scalability, measurable business outcomes are now the criteria that matter. As a result, customers are moving away from fragmented point solutions towards a single platform that orchestrates every customer experience across voice, digital, human and AI. That plays directly to NICE's leadership with a unified operating platform.

And we're continuing to strengthen that platform advantage through innovation. At NICE World, we announced that Cognigy is now fully native to CXone, ahead of schedule, making it the platform's foundational conversation on the Agentic AI engine, one application, one shared data layer, one deployment experience. Customers can activate AI faster, eliminate integration complexity and build AI agents directly on CXone data.

The native integration of Cognigy is also accelerating innovation across CXone in ways that simply aren't possible when AI and customer engagement sit on separate platforms. At NICE world, we showcased the agentic analytics, which continually analyzes data across the platform to identify new automation opportunities and improve existing automations. We also introduced the agentic engagement plan, purpose built for an emerging hybrid workforce, enabling human and AI agents to operate together seamlessly This capability is unique to NICE and our single natively integrated platform. Combined with learning loops and Guardian AI, these innovations continually improve AI performance while giving enterprises the governance control and operational confidence required to scale AI across every customer interaction.

To sustain that pace of innovation, we also launched NICE Labs. Our dedicated AI lab focused on furthering agentic customer experience through advanced research, rigorous benchmark and rapid prototyping. Working closely with customers and partners, NICE Labs is designed to help close the gap between what's possible with AI and what enterprises can reliably deploy in production. Importantly, we built that innovation without sacrificing flexibility for our customers. Our platform is model agnostic, allowing enterprises to take advantage of proprietary open weight and future models as they evolve, without locking themselves into a single LLM. That gives customers the freedom to adopt the best models for each use case while protecting long-term flexibility and cost efficiency.

Ultimately, our strategy is delivering measurable results for our customers. TripAdvisor an existing CXone customer deployed NICE Cognigy AI agents moving from concept to its first live automated voice calls in just 2.5 months. Today, it's AI agent delivers a 90 customer sentiment score, well above the 71% achieved by human agents.

GXBank, Malaysia's first operational digital bank with over 1 million customers built its customer experience operation on CXone, where the platform now delivers 95% customer satisfaction and 95% first contact resolution, while AI autonomously resolve 70% of customer chat interactions. These outcomes are not isolated success stories. They reflect a broader pattern that we're seeing across our customer base. Enterprise is achieving measurable business outcomes with AI in production. We're translating these outcomes into continued competitive momentum. Our CCaaS win rates remained strong in Q2 and improved year-over-year as more enterprises selected NICE to modernize customer engagement with AI.

In Q2, we secured an 8-digit ACV win with HMRC, making it the largest CXone deal and largest Cognigy deal ever. Delivered in partnership with Capgemini, HMRC selected NICE's unified CX AI platform to help modernize and enhance citizen engagement at scale. We also secured another 8-digit ACV win with one of the largest health care organizations in the U.S., which selected NICE CXone and Cognigy to advance customer engagement on a unified AI platform. Working together with Accenture, the customer chose NICE to accelerate AI adoption scale while enhancing member experiences and driving greater operational efficiency. Stand-alone Cognigy also continues to compete favorably. Recent wins, including displacing AI-native point solution at a large multinational utility, where our platform delivered stronger automation performance while giving the customer greater flexibility and faster time to market for new use cases.

We also replaced an incumbent AI native solution at a large insurance company after winning a competitive evaluation against an AI native solution and a large enterprise software platform. Together, these wins across both our unified platform and stand-alone AI offerings underscore the strength of our strategy, the competitive differentiation of NICE Cognigy and the growing leverage of our global partner ecosystem in driving large-scale enterprise transformation.

Speaking of our partners, our partner ecosystem continues to be an increasingly important driver of our success. ACV booked through our GSI partners in Q2 was multiples higher than the prior year. With AWS, customers are leveraging AWS marketplace and committed cloud spend programs as a part of their procurement processes with NICE, making it easier to adopt our platform while expanding our commercial reach across both new customer deployments and renewals. And we've also expanded our long-standing partnership with RingCentral. Building on nearly a decade of collaboration, NICE will now offer RingCentral's UCaaS solution while RingCentral continues to offer NICE's CXone platform.

This gives organizations that prefer an integrated UCaaS and CCaaS deployment the flexibility to use a unified solution without compromising on the capabilities of either platform. And we've also strengthened our position in health care through our recent EPIC integration by embedding patient engagement into the clinical workflow, we've made it easier for health care providers to adopt a NICE platform positioning us for additional growth in this strategic vertical. Collectively, these partnerships make it easier for customers to buy, deploy and expand their investments in NICE, while expanding our reach into new industries and buying centers.

Before I turn it over to Beth, I'd like to leave you with one final point. The future of customer engagement is on a single platform, delivering production at scale. That's where NICE is uniquely differentiated, and it's why we continue to win enterprise transformation deals, large ones. That differentiation compounds as customers expand their usage of the platform because our capabilities are natively integrated. Customers can activate AI solutions quickly without the complexity of deploying separate platforms. We are incredibly excited by the accelerating momentum we're seeing in product innovation and customer demand. These trends continue with our expanding partner ecosystem, reinforce our confidence in the significant opportunity ahead.

With that, I'll turn the call over to Beth.

Thank you, Scott. We continue to execute on the strategic priorities we outlined earlier this year second quarter revenue coming in above the high end of our guidance range and non-GAAP EPS delivered at the high end of our expectations. Let me now turn to our second quarter results. Total revenue for the second quarter was $782 million, up 8% year-over-year. The outperformance relative to our guidance was primarily driven by stronger-than-expected product revenue, while cloud revenue performed in line with our expectations. Foreign exchange provided a modest benefit of 40 basis points to revenue growth in the quarter, lower than the approximately 1 point tailwind experienced in the first quarter.

Starting with revenue by business line. Cloud revenue totaled $609 million, representing 78% of total revenue and growing 12.6% year-over-year, including approximately 250 basis points of contribution from Cognigy. Cloud growth was driven by the successful expansion of CX AI offerings into our existing installed base new CXone logos and strong international performance, partly offset by the strategic renewals we completed. Within cloud, CX AI and Self-Service ARR reached $362 million, growing 52% year-over-year and now representing 15% of our cloud revenue.

As we continue to move further upmarket and win larger enterprise AI opportunities, many customers remain in the early stages of deployment, creating a lag between the strong bookings momentum we see and timing of customer adoption. Customer demand remains strong, and we continue to see significant momentum across our AI business.

Looking ahead, we're encouraged by the continued strength of our land-and-expand strategy. We delivered a record quarter for AI bookings with approximately 75% of NICE Cognigy bookings attached to CXone. This reinforces our strategy to deliver the market-leading end-to-end CX AI platform. These leading indicators combined with the continued ramp and existing deployments reinforce the confidence in our long-term AI expansion opportunity. As Scott mentioned, cloud backlog increased 19% year-over-year. Our cloud backlog at the end of Q2 does not include our recently signed 9-digit TCV HMRC deal due to customary public sector contractual agreement requirements. As anticipated, Cloud Net revenue retention remained healthy at 106%.

Turning to our premise-based revenue streams. Services revenue was $125 million, representing 16% of total revenue and declining 11% year-over-year. This reflects the migration of customers from on-premise deployments to cloud, which naturally reduces the services activity associated with legacy implementations. Product revenue was $49 million, representing 6% of total revenue and increased 7% year-over-year, primarily driven by greater-than-expected term renewals in our non-CX businesses.

Turning to our geographic performance. The Americas region, which represented 82% of total revenue, grew 5% year-over-year, supported by healthy cloud growth and continued adoption of our CXone platform, partly offset by anticipated decline in services revenue. International remained an important contributor to growth during the quarter. EMEA revenue representing 13% of total grew 30% year-over-year or 28% on a constant currency basis. APAC revenue, representing 5% of total revenue grew 8% year-over-year or 5% on a constant currency basis, reflecting the lapping of a large public sector cloud deployment that began in the second quarter of last year.

International cloud revenue increased 34% year-over-year on a constant currency basis, reflecting continued adoption of our cloud and AI solutions across underpenetrated international markets. Supported by an expanding partner ecosystem and the ramp of recently secured strategic wins, we remain confident that international expansion will continue to be a durable long-term growth driver for NICE. Turning to our business segments. Customer engagement revenue totaled $645 million, representing 82% of total revenue and increased 8% year-over-year. Growth was driven by continued double-digit cloud revenue expansion from both our large installed base as well as new logos, which more than offset the expected decline in maintenance revenue. Financial Crime and Compliance revenue totaled $137 million, representing 18% of total revenue and increased 6% year-over-year, driven by continued demand for our financial crime prevention solutions.

Turning to profitability. Gross margin for the quarter was 68.4%, in line with our expectations. Cloud gross margin improved 40 basis points year-over-year to 69%, reflecting improvements in the efficiency and scale of our cloud operations while continuing to support growing AI adoption across the platform. Operating income was $198 million, resulting in an operating margin of 25.3%. Consistent with the investment framework we outlined earlier this year, we continue to invest in AI innovation, go-to-market initiatives and our partner ecosystem.

The second quarter also included elevated marketing investments associated with our annual customer conferences, resulting in some quarterly variability within our target operating margin range as we continue to support our long-term growth strategy. Earnings per share for the second quarter were $2.70, coming in at the high end of our guidance range due to outperformance in total revenue and in line operating margin.

Turning to cash flow. Operating cash flow for the quarter was $123 million and free cash flow totaled $93 million. Cash generation during the quarter reflected the timing of working capital movement, including prepaying certain expenses and capital expenditures, which can create variability from quarter-to-quarter. We remain confident in our full year free cash flow outlook and continue to expect to finish the year at the higher end of the 18% to 19% free cash flow margin range. We ended the quarter with $355 million in cash and short-term investments.

Turning to capital allocation. We repurchased $58 million of our shares during the second quarter. Shares outstanding at the end of June were approximately 58.1 million shares, a decline of 6% year-over-year. Year-to-date, we have executed $311 million of share repurchases, representing 5% of our market capitalization, with our repurchases increasing approximately 10% from the first half of 2025, reflecting our continued commitment to returning capital to shareholders.

Turning to guidance. For the full year 2026, we are reiterating our total revenue guidance and raising our EPS guidance to reflect an expected operating margin at the higher end of the 25% to 26% range we previously shared. Full year 2026 total revenue is expected to be in the range of $3.170 billion to $3.190 billion, which represents an increase of 8% at the midpoint. We continue to expect 2026 cloud revenue growth to be in the range of 13% to 15% with Q3 cloud growth expected to be similar to Q2.

As we look to the second half, demand across our cloud and AI portfolio remains very strong. At the same time, many customers are still in the early stages of AI adoption and the pace at which they move into production can influence the timing of monetization. We also continue to see stronger-than-expected on-premise demand within our non-CX business from several large financial institutions. While we remain confident in the long-term cloud migration opportunity there, the timing of these migrations can affect the mix between product and cloud revenue. These factors may influence the timing of cloud revenue growth and where we land within our guidance range, but they do not change our confidence in the business.

Our strong H1 bookings and continued backlog growth reinforce the healthy demand environment we see for our cloud and AI portfolio. Full year fully diluted earnings per share are now expected to be in the range of $11.06 to $11.26. For the third quarter of 2026, we expect total revenue to be in the range of $780 million to $790 million, representing a 7% year-over-year growth at the midpoint. We expect third quarter fully diluted earnings per share to be in the range of $2.73 to $2.83. In summary, we are pleased with our execution in Q2. As we look ahead, we are encouraged by the strength of our cloud and AI bookings, backlog and pipeline, which continue to support our long-term growth outlook. Combined with disciplined execution, strong cash generation and a healthy balance sheet. We remain confident in our ability to capitalize on the significant opportunities ahead.

With that, I'll turn the call back to the operator for questions. Operator?

[Operator Instructions] Your first question comes from the line of Siti Panigrahi with Mizuho.

You guys talked about that concept of offering this legacy

product discount to a large customer in extent of multiyear commitment. And how is that impact -- are you seeing the same trend continues after that in Q2 and second half, a similar kind of trend from other market customers that's going to coming up for renewal in the second half? And how confident are you on your second half cloud growth as you guided? Do you expect that to reaccelerate?

Yes, thanks. Let me take these questions. So first of all, on the renewals. The renewals we've completed have gone exactly as we expected. And just as a reminder, this was not a large scale. This was more about smart commercial decisions that we designed and work with our strategic customers to accelerate AI adoption and secure long-term commitments. And so none of those changes reflects any deterioration or concern about the underlying demand. In fact, the underlying CCaaS market is really strong. The AI market is really strong. Customer interaction volumes grow. And the voice channel is really critical.

So these were very targeted strategic decisions, not a broad change in commercial approach, and we've completed those as we expected with no further concern for the remainder of the year. As it relates to our cloud revenue growth, of course, we've continued to guide within the range. And as Beth mentioned, we feel really -- we feel great about the backlog. We've got record backlog. We've got record bookings. Our AI backlog continues to expand. And if you include HMRC, our backlog is actually accelerating in AI compared to where it was in Q1, it's a great problem to have. Now we've got work to do with our customers to take that backlog and put it into deployments and ultimately convert it to revenue.

And the reality is, and you can see it with our wins that we talk to, we're dealing with some of the largest enterprise deployments that are on the planet. And they take some work to be able to deploy them at scale. So customers are taking measured approach as they prepare their data, the governance, the operating models before they scale AI across all the use cases of which they've signed up to. So -- it's not a challenge from a NICE perspective. We've got all the capabilities. We've launched NICE labs. We've got great examples in customers like TripAdvisor and others that are able to deploy quickly. But the reality is we're dealing with complex not simple use cases and those ones require a measured deployment approach, which does have some impact on the revenue in the short term, but in the long term, it's very secure.

Your next question comes from the line of Rishi Jaluria with RBC.

Wonderful. Maybe just start with, look, I get the AI story, obviously, good to see some of these large deals and backlog building. Maybe I want to understand, as we're talking to a lot of our customers, the AI decision is not an all or nothing, right? It's not, hey, we need to buy everything from one vendor. In a lot of cases, you have these high-profile AI native companies out there that might be on call deflection, voice AI agents, et cetera. And to a certain extent, you're competing with them, but to a certain extent, it feels like there's maybe partnership opportunities where you can maybe see certain parts of the market, but still have the connectivity, you still have the hooks still kind of integrate.

Maybe can you talk us through your philosophy as it pertains to either working with or integrating with some of those AI native so that it becomes less of a factor of maybe crowding out or delaying some of these decisions. Maybe just help me understand that, and then I've got a quick follow-up.

Sure. It's a great question. So you're right that it is a highly competitive market. And in some respects, when you take just the pure AI story alone, everyone sounds pretty similar. I find it remarkable -- and part of it is because creating voice agents and creating agents. Look, on Cognigy, all I can say is it literally takes seconds. It's -- this is not a difficult activity. So we really focus on our competitive positioning on what makes us unique, what makes NICE unique? Well, it's the only platform that can run a hybrid workforce at scale. It's the only platform that has a best-in-class AI capability if you want to do that independent. But when you want to orchestrate it with the millions of voice interactions, the digital channels, the human workforce, you can do it in an interoperable way without any lag, without any integration, without any latency.

We also focus on mission-critical scale. I think a lot of these companies are realizing these AI native companies are realizing that when you get to mission-critical scale, it can't drop. It can't fail. Quality matters. And we've been doing this for decades in our voice and digital and -- in the CXone platform. So taking those same capabilities and doing it in the AI space really does differentiate us. And I think that's why you can understandably see large companies, complex transformational engagements around the world really are where those companies are looking for that capability.

Now to your second part of your question, which is a great one. We very much -- our philosophy is very much being a company that is able to interoperate within a competitive ecosystem. Our CCaaS platform, of course, integrates beautifully with other AI native solutions. We operate with open LLM, different LLMs, open source, open weight models. We offer our own speech transcription, text-to-speech service that all we offer, others that can be integrated into our platform. And if you think of it from our point of view, NICE Cognigy works beautifully with every other CCaaS platform. It works beautifully with other enterprise workflow solutions. So we very much look at an interoperable way and then really zero in on the value drivers that we can bring.

And then last but not least, the thing that we have the most that everybody needs that is native to our platform is our data. You can't run an AI platform without all the knowledge of all of the intent, the interactions, all the things that happens on voice is a requirement for any of those AI natives to be able to have an insightful way of being able to do containment deflection and others. So our advantage is we can provide that natively with AI agents, human agents interoperable platform all within the one data platform that is easy for our customers to use and deploy. So we take an open approach. We back ourselves with our competitive differentiation, but we also look at ways that we can collaborate with both AI native players and even other CX players because we know that we've got value to provide even if it's not the full suite, there are parts of our portfolio that are evaluating to our customers, and we don't limit ourselves with that opportunity.

All right. Very helpful. And then maybe just on kind of the long-term cloud outlook. If we rewind 9 months ago at your Analyst Day, back in November, you talked about kind of this glide path to accelerating organic cloud growth. Obviously, with Cognigy being a big driver of that. Given where numbers have settled out and with some of the changes in buying behavior, are those targets still on the table? Is the time line still the same? Maybe just help us understand kind of your confidence in that reacceleration story back to what you told us 9 months ago.

Yes, sure. Great. I'll let Beth add to anything that I -- from an opening point of view. So when we got together in November last year, I talked a lot about the growth opportunity of both the CX market and the emerging AI opportunity. And I mentioned that we would need to invest in both the native capabilities and all the things that I described about Cognigy being integrated into the CX platform, being able to provide that transformation. We knew that our differentiation was the combined platform, not just having pieces that could compete head-to-head on an isolated case. So that's been a large focus.

And candidly, my main emphasis is being on winning the AI market, winning the CCaaS market, growing our backlog and bookings completing the investments, which were ahead of schedule on that then gives us confidence, and we go into the out years of the midterm guidance with confidence around our cloud revenue and our operating margin. So as of the first half of this year, I feel good about that midterm. What we've got to keep on doing is expand our international, expand with strategic ecosystem, continue to book strongly on both AI and in the CX market and clearly, our opportunity now based on all of the bookings is converted into revenue.

So look, we look at that outlook in a positive way, and we will continue to execute against strategy. I'm feeling good about that.

Betsy, if anything you want to add?

Yes. I think you've done a great job of covering it, Scott. I think one of the things that's important is we've really done well on executing on the strategic priorities that you highlighted really driving the international growth, putting in play the ecosystem, more business with partners and opening that distribution network. So I think we're well positioned. We feel well on track in those medium-term targets we've already executed. And when we see the -- both the backlog that we've had in the first half of this year, combined with some of the largest deals ever that we've seen, both internationally as well as for Cognigy, that gives us really the confidence that we're still on track for that medium-term outlook.

Your next question comes from the line of Samad Samana with Jefferies.

This is Julian, on for Samad. To start, I mean it's great to see the strong results on the product side and the greater-than-expected term renewals in the non-CX business. As we think through the back half as we model product for the rest of the year, how are you thinking about what your expectation as it relates to the on-prem strength?

Yes. Thank you for the question. As you highlighted, I think we had -- as expected, cloud growth in Q2 and really phenomenal growth in the product in the non-CX businesses in the second quarter. It really speaks to the durability of our ongoing business.

When you look at the back half, our strategy remains the same that our expectation is that we continue to drive and our customers, our legacy customers in those non-CX businesses over to the cloud. And that is what we factored into our expectation for the back half. We do have opportunity, and we may potentially see that some of those same financial institutions may opt to actually continue to stay with us durably on a term basis. But as of now our expectation is that we'll continue to see that shift, and that's certainly what we promote to our customers as well as internally to our internal go-to-market teams as well.

Your next question comes from the line of James Fish with Piper Sandler.

Ryan, on for James Fish. So you guys talked about the renewed partnership with RingCentral. How does it impact your UCaaS offering you released and why the decision to renew here?

Well, I think it's -- thanks, James. Look, I think the reality is we've got a wonderful relationship and partnership with Ring, we've had for over a decade. And it's mutually beneficial not for just each other, but also for our customers. And what we realized is back to the earlier question about our strategic partnership is strategic partnerships don't mean exclusivity. So we have many customers that would like a capability that we can provide from NICE, but it's also a recognition that many customers want a world-class UCaaS platform and coexist and buy that in coexistence with their CCaaS or the CX AI platform, and we want to be active in promoting that just as Ring actively promotes and drives the CX capabilities that we have, not only of our CCaaS, but also of Cognigy as well.

So it's a win-win for both organizations, and it's an opportunity for our customers to have better choice, deployment flexibility, and it is accretive to what we can offer to our customers. Hence, we linked into that, and we look forward to continuing to build it out.

A quick follow-up, too. So ARR still growing over 50%. But if we back out Cognigy here, it seems that AI grew sub-30 compared to 40% last quarter. What's going on with that organic AI offering slowing down?

Yes. I think, listen, first of all, you can't really look at organic versus inorganic with respect to Cognigy. At the time we made the acquisition of Cognigy, it meant that we discontinued selling the other comparable solutions we had previously. So you must look at it in consolidation. It doesn't really pertain to look at it in a segmented way at this point.

Your next question comes from the line of Tyler Radke with Citi.

Just going back to some of the comments about sort of the lag of bookings to revenue? And I guess related to the prior question, if I just compare your net new AI ARR, just taking the sequential AI ARR addition, it looks like Q2 was below Q2 of last year. You're calling out record bookings. So I'm curious, is there an offset whether it's churn or consolidation of other existing cloud revenue? Or is there a duration impact? Or is there some timing impact just because it does seem like you called out record strength in bookings. But as we look at that sequential ARR, it's not exactly showing up in terms of net new.

Yes. Thank you for the question, Tyler. And it's spot on to what Scott and I both have been talking about earlier today that related to the conversion of timing. We see the strength in our backlog and you may see variability from quarters in terms of how that shakes out. Again, we expect to see that expansion coming more so you'll see in the forward-looking ARR in the back half.

Your next question comes from the line of Arjun Bhatia with William Blair & Company.

Willow Miller, on for Arjun Bhatia. I appreciate your comments about the targeted renewals and how they were thoughtful and extended to certain marquee customers. But if the strategy plays out how you expect it to, would you consider extending the strategic renewals to customers beyond this first group?

Yes, it's a good question. So as you can appreciate, we look at this really closely. And if you think about the strengths of NICE, many of them are around our product, our history, our capability, but one of our biggest strengths is our customer base and our installed base. So we have a very clear view about our renewals, our outlook not only for 2026, 2027 and even into 2028. We've got a very clear view of what customers, what they're using, where they're at and having proactive conversations about their deployment journeys. So I think what you can interpret is based on the signals and the buying behavior of our customers that we clearly saw in Q1, we're way further in front of being able to engage our customers around how to best deploy AI and leverage that within the CXone environment.

The beauty is now that Cognigy has integrated into CXone completely, they can literally click a button and they can start activating some of those AI capabilities that Cognigy provides, which wasn't available to us, obviously, at the beginning of the year. So I'm not expecting any adverse app impacts in terms of our overall growth or revenue outlook as we look at those renewals. In fact, quite the opposite, as we look at the opportunity with those customers well in advance of renewal events that we can then seamlessly be able to bring in those AI capabilities, do it in an enhanced way and then obviously make it accretive for our growth overall as a company.

Your next question comes from the line of Patrick Walravens Robbins with Citizens.

Great. And congratulations you guys on the biggest deal in your history. So Scott, who -- when you're doing these 8-figure deals, can you just talk to us a little bit about who you're competing against and sort of how that dynamic works? I mean, is it Genesys? Is it Sierra/Decagon does the new agent force contact center product for Salesforce show up? Who do you end up at the end of the day, having to beat out to win these deals?

Yes. It's a good question, Patrick. The answer is probably all of the above. I mean the reality is it is a competitive environment. And let's face it. We are -- we fully acknowledge that all customers have choice of approach. We believe firmly that the system of engagement and the customer engagement platform in a united manner will be the preeminent way large enterprise and medium for that matter, we'll be able to deliver their customer experience. It takes a bit of time because what they're evaluating is not only who is the best vendor or who's the best partner, but how to achieve their business outcomes companies don't want to be integrating different technologies.

So what they're doing is they're looking at AI native solutions, but then they have to figure out how to integrate it and how to maintain that integration -- if they then look at a unified platform like us, then they look at our direct peers and historical CCaaS space and says, who's got the end-to-end capability that provides voice, digital, human, AI agent, all in it completes with and has an innovation road map. So we're clearly in front there. We see that with our win rates, and that's where customers like HMRC who clearly chose to go into our platform going from a legacy on-prem platform that was not NICE.

So it is very competitive in those different scenarios. And the way we feel good about it, Patrick, is this -- if a customer chooses to break it apart and then they're going to choose their CCaaS as distinct from their AI platform as distinct from their workforce management, we stand up really well. But when they look at the combined offer of a unified platform and the benefits of it, we stand apart. That's the way that we go to market and compete on those. But I would highlight NICE Cognigy, I mentioned it earlier, but I just want to reiterate it. On a stand-alone basis, head-to-head against these AI players, it stacks up really well and we compete favorably. So we have confidence that we have different buying behaviors and we're able to compete on those. But clearly, the unified platform is our sweet spot and one that really does drive the large enterprise.

Great. And then if I could do a follow-up for you. Just on the whole bookings versus rev rec, I mean is it -- are you comfortable saying that you're reiterating the $3.5 billion in 2028 because that would kind of answer all the questions.

That's correct, Pat, we are. We are standing with the expectation of the -- to continue to meet all of the guidance on the top line that we've already communicated as well as the other targets that we communicated last November as well, yes.

Your next question comes from the line of Elizabeth Porter with Morgan Stanley.

I had a question just on the cloud AI ARR number, which ticked down a little bit versus Q1. And I appreciate you guys have cited some compression in certain CX components, but clearly highlighting this longer-term opportunity is especially as customers scale with AI. So could you just kind of frame the near-term proportion of cloud ARR that is exposed to some of this compression and maybe some of those milestones that would indicate that NRR has reached a trough before we can get that opportunity to start to re-improve.

Thank you for the question. The cloud NRR and the NRR generally was as anticipated for the quarter, it was really just a modest change from what we saw in the first quarter at 106% NRR. It's really directly tied to what you started your question with, which was the strategic renewal opportunities that we addressed last quarter, and that was expected and really anticipated in what we would have shown here.

Your next question comes from the line of Catherine Trebnick with Rosenblatt Securities.

You mentioned the ACV from the GSI partners with multiple times higher year-over-year. And you featured Capgemini, which I think is a new GSI partner -- and then at NICE International, you had two GSI sponsors, which you hadn't had in the past. So the question is, what are they offering with NICE that can't be replicated from competing platforms. And then is that a durable differentiation? And anything else you can unpack about how these partnerships are really helping you out with a larger opportunity.

Yes, it's a great question. So maybe just a bit of context in history. If you remember, I guess, last year, I spoke a lot about the importance of strategic partnerships and you probably would have noticed they placed an enormous amount of attention on technology partnerships. So whether it be with AWS, with ServiceNow, with Salesforce, with RingCentral and many other technology partners. And I indicated that we were also now really leaning into our GSI partnerships. It takes a bit of time for that to bear fruit. Why? Because we have to invest in a lot of effort. We've got a record number of certified and trained NICE Cognigy and NICE consultants now within our GSI partner ecosystem.

We built a go-to-market platform, which we can now really target and pursue and build out. They see a durable growth opportunity for them because they see the same demand signals as we do. We put in place a new Chief Partner Officer under our COO, Arun, to really drive this engagement. So a lot of work and effort has been building upon this, which has led to the results that you saw in Q2, which was great record wins whether it be at the HMRC with Capgemini, the health care opportunity with Accenture and many others.

So what do we expect from here? The beauty of the GSI ecosystem is once they've got scale of capability and they've got repeatable assets that they build around our technology stack, they will then scale it both from a go-to-market and from an execution. I see multiple advantages, and I'm excited about it, as you can probably hear in my voice. The first is they expand our reach into the market without being dependent on our own go-to-market sellers. So we get a better reach into -- because they have relationships beyond the CX space in all of these enterprise customers. Secondly, they have deep industry expertise that really complement our strong technology stack. So we get win-win. And that's why health care, public sector, insurance, banking, we're able to provide a more nuanced and detailed capability that combines those together. And then last but not least is they help us innovate because what they're able to do is the speed of innovation that we now see with our full deployed engineers combined with our GSI partners is we're able to enter it with rapid prototyping that we can do, we bring that back into product. So they really do give us expansion and scale. We've only scratched the surface. I think you'll continue to see the impact of that ultimately, it's a key driver for us on that long-term growth and the outlook that we provided, which is exciting. Hopefully, that gives some context.

That concludes our question-and-answer session. I will now turn the call back over to Scott Russel for closing remarks.

Thank you, operator. Look, I think as closing, I just want to recap on where we see the quarter and where we see the outlook. At the beginning of the year as was referenced on this call, we talked about investing in international markets. It's a winner. We invested in strategic partnerships -- it's a winner. We invested in an AI capability that is best-in-class. It's a winner. We talked about integrating into a single native platform on CXone. It's a winner. It's ahead of schedule. And we talked about then driving durable growth and then starting to reaccelerate margins as we are able to then capitalize on this opportunity. We're on track. And we feel really good about what we delivered, but more importantly, where we're going. Yes, it's a competitive interesting market, but we're well positioned, and we have a unique strategy compared to others.

So I appreciate the time today and look forward to further engagement. Thanks, everybody.

Ladies and gentlemen, this concludes today's call. Thank you all for joining. You may now disconnect.

Good morning, everyone. I'm Ryan Gilligan, Vice President of Investor Relations at NiCE. Welcome to NiCE's 2026 Investor Day here at NiCE World. Before we begin, I must show you this disclaimer slide. Please note that today's presentation contains forward-looking statements as well as non-GAAP financial measures.

Okay. Now we can start -- we can talk about the agenda. In just a moment, we'll start with our CEO, Scott Russell, Scott will then hand it over to Jeff Comstock, our President of CX Product and Technology. After that, we'll hear from TripAdvisor. Next, Arun Chandra, our COO, will be joined on stage by Accenture. And then finally, Beth Gaspich, our CFO, will wrap up our prepared remarks. Following our presentations, we'll take a 15-minute break. For those of you that are in the room, feel free to grab lunch just outside those doors. And for those of you that are on the webcast, you will have an opportunity to submit questions. We do ask that everyone save their questions until Q&A. And also if you could silence your cell phones, that would be much appreciated.

With that, I will turn it over to Scott Russell.

Good morning, everyone, and welcome to Investor Day. For those of you who are online, I apologize. I'm going to make a few references to what happened in our keynote this morning here at NiCE World. But for those of you who are here with us, thank you for joining us at this event. It's obviously a really important customer event, but also, it's an opportunity for us to share the innovation and the capabilities that not only that we've built and that we've delivered with our customers, but we're also what we're innovating and creating for the next year of CX in AI.

So a few data points that I've just got off stage. So I'm still in the buzz of being in that theater room, but it is a great event. NiCE World, we've got about 20% increase year-on-year. So we continue to get more and more customers. And what's really interesting is the proportion of non-CX customers that are interested in the journey. Even last night, I had connected with 5 different customers that were in the exploratory phase and they didn't know whether they were going to start with their on-prem to CCaas move, whether they're AI move, whether they want to do it all. So the journey was part of the conversation, not just the destination, and often, that's why customers come to an event like this is because they're trying to discover, they've already made the decision to come to NiCE, but how to get there, the journey that they're on, what are the right steps is often. And the most valuable part is talking to other customers because talking to other customers getting insights about how to best work with our organization, but also how to maybe tread the path in a more careful way and a more predictable way than those before them.

And so today, very much is a representation of where we are, but the opportunity of what we're going to be.

So let me start there. I want to start with the market that we're in. And I think this constantly gets analyzed in different forms. You can analyze our market in traditional terms, how much of the on-prem market is out there? What's the CAGR of that market, the total addressable? But you think about a few different scenarios that I would encourage you to consider the market that we are expanding and operating in. The first is, as Phil Heltevig mentioned on stage, and it's the personal agents. Personal agents are expanding this market dramatically, and we're already seeing it. The way that you interact with the brand might have been through our website before, now you're going to interact with an agent and an agent is going to hit a CX platform who has to respond to it. It's going to be AI to AI or AI to human, and it's going to proliferate. I know personally, I have 5 different agents, PA agents, workforce. I do think it's the productivity tools. It's easy to build and deploy. I don't do it much in a professional context yet, but that's coming. But on a personal side, it's already there. And you're seeing companies on the personal compute space are already offering that.

It's also expanding. So what does that mean for us? It's expanding interactions. The metrics that we use to guide our business over decades, the number of human agents that sat in enterprise has actually been quite static for a long period of time. as an increase, but it also hasn't decreased much either. And whether that decrease happens as we all predicted potentially well with the human -- less humans in the contact center, the volume of interactions far outweighs it. It's growing and it's expanding. So that expansion means a proliferation of enterprise AI agents. It means that the digital volume and the interaction that we receive is expanding. And of course, the thing that we know for sure is that the the on-prem base is still far from done. Again, those customers that I spoke to last night of the 5, 3 were still on-prem, on-prem on legacy platforms that are trying to figure out how do I move to not only to the cloud, but to a cloud AI platform that can deliver and enable what they need in the future, not what they did in the past.

So we've got a considerable growing, expanding market. And that's exciting because we're not trying to only take market share. Yes, we've got direct competition in each of the different segments that we operate, but in totality, we've got an ability to be able to grow and expand in a growing and expanding market. It also means that when we take leadership, it allows us to move across. I know many of our investors who have been with us for a period of time think in world of or AI or in CCaaS or in workforce management. That's not the way we view it. We are in enterprise CX. It is a seamless platform and it's interoperable, not because our competition can do that because they can't. They don't have those platforms. They have to compete in the isolated segments they're in through the acquisition of Cognigy through our home built capabilities in workforce management and in the CCaas space, we've already got the ability, and we've already done that integration. So not only is the market large and expanding, it creates a differentiated opportunity for us.

Let me be as bold as I can in this statement. Many companies are evaluating their AI technology in a proof-of-concept pilot. They're in discovery mode. They're trying to figure out if it can work, and if it can work in their environment, but they're very quickly now making decisions that are different, can it work at scale? Can it work with the same operational complexity that the contact centers have to live in, the trust, the security, the scalability, the always on, the accuracy. They are not going to let the AI platform be less accurate, less scalable. It's no good if your first contact is an AI agent, but because 1,000 other customers has hit you at the same time that it doesn't work. That just leads to poor customer experience.

It wasn't the first evaluation criteria when companies were looking at AI, but I can assure you it is now. They're now buying it in enterprise AI. They're thinking about the world of CX with AI infused rather than AI separate, and that's what differentiates us. We've already got the market leadership. We are the market leader in CCaaS. We are the market leader, at least by industry analysts, in AI for the CX space, and we've combined it together for end-to-end orchestration.

And the other point that I would make is there are many AI tools that have got cross-purpose. Many companies are saying, "Oh, I can do different tasks with my AI agents." That is true because you can build it with the same underlying foundational technology. But the building constructs, the scaffolding that you put over the top needs to be specialized. We have specialized on CX. That is the space that we exclusively operate, but CX is not service. CX is all of the engagement with customers, inbound, outbound, proactive, reactive, synchronous, asynchronous, voice, AI, digital, it can cover go step into places where you think about sales and marketing and revenue. There's no limitation within that space because we understand what customers need. We understand their intent. We know how to operate it. We know how to deliver it at scale. And we're infusing the AI capabilities to provide a compounding advantage.

I had a customer yesterday tell me that the idea that an interaction that they had with a human would automatically allow the AI agent to learn from that interaction to make the AI agent even smarter on the next connection, they were blown away. I mean if you think about it, it's fantastic. AI agents learning what the human has done and then figuring out how to do it better in real time. That is orchestrating intelligence. That's what we've got within the platform. So it's not just using the data and the historical data, but it's applying it in real time, and Jeff can talk a little bit more about that.

The other thing that I would highlight, and I guess building upon what I had mentioned before is AI and CX, we believe, is reaching an inflection point. The market is -- we're just scratching the surface of the opportunity. The AI market is huge. You think about the volume of interactions, 3% to 5% of the volume of interactions today are hitting the AI platform. But most of it is pointed at single tasks. And if you had the -- for those in the room, you might have been intrigued by one of the examples by our customer at Fabletics, Jack Roberts. And what Jack spoke about was he spoke about choosing meaningful tasks, items that matter. It is very easy to do simple automation on an AI tool that sits at the front of your CX stack, but it provides very little value. The value comes when you're doing the more complex things. And whether you start simple and then move to the complex or do what Fabletics did and they started with the complex and then they rounded it out with the more simple, the platform is built to provide that value. And when you're going from simple automation to really embedded complex capabilities that can handle the scale, well, you're going to buy differently. You look at the technology differently because it has to work, it has to -- so the historical adoption of patents is full enterprise CX stack, we're already seeing it.

What are our proof points? 100% of our deals in and CCaaS over the last 3 quarters, I think maybe since I've been at least in the last 3 quarters since we acquired Cognigy, 100% of them have included AI. Companies are not buying their on-prem to cloud move without the AI platform. In fact, the other way around. They're starting with the AI capability, and then they're figuring out how the overall CX platform delivers their enduring needs, the human management, the AI agency, human agents and how that operates together. And that's exciting. Why? Because the more complex it gets, the better it is for our competitive differentiation.

What's the choice for a customer? Well, I'm going to have to either use a CCaaS platform and then go an AI platform and maybe multiple AI platforms, and I'm going to have to figure out how to integrate it, and it's got to work at missing-critical scale. When that Lufthansa flight cancellation and you get 20 million interactions within the 1 week, it doesn't work. When you're buying for that scale and you're buying for that interoperability, what we've already built, that delivers the scale that the market needs, and we know it because that's what happens in CCaaS today.

The only difference is, in the CCaaS world, it's only human agents, but it has the same expectations from companies, big brands. They need a platform that will be able to work to that. And so we made a choice. We didn't have to integrate Cognigy into CXone straight away. We could have kept it bolted on, and we would have been able to offer that as a really value-adding offering to the market. We bolted , we integrate it because we knew where the market was going not necessarily how that we're always buying today, but how the market is going to need that capability in the future. And so that's where CX is providing -- in enterprise AI is where CX proves at its scale. We have high volume.

I think everybody would recognize that the CX market is 1 of, I would consider the 2 clearly proven grounds for AI in the enterprise space. Software engineering. There is no doubt companies like ours, we use Claude and other available tools in our engineering, and it helps us drive incredible productivity. The CX space is the other one. Why? It's high volume of data. It has to operate within tremendous complexity in real time, every channel, every department, it's got to be accurate. So whether it be the scenarios like Citi where you've got high stakes complaints that you want accuracy that Mia spoke about this morning. But benches going on to human scenarios, and then she's going to go into different scenarios. You've got -- it's got to always work. It's got to always deliver the accuracy that the customers expect because let's face it, if it's not accurate for a financial institution, that means not only loss of customer, that means potential fines and other things from the regulators.

And then last but not least, it's obviously a high consequence, revenue, loyalty, cost. This isn't a cost play for many businesses now. They look at this platform and say, "Well, if I've got this great interaction, how can I create revenue? How can I drive more value-added offerings onto the same interaction rather than just responding and containing a request."

So it is our view that most AI agents, most point solutions out there only solve part of the problem. We compete on this basis every day, and we are very, very confident with our win rates when we're able to offer our combined NiCE Cognigy CX AI platform. Agents without that full context are conversations, but they're not experiences. They don't have the full context. Agents without that orchestration, they're doing tasks and they're doing very contained tasks, but they're not doing the full business outcome, the full journey. Agents without the governance, and there's a lot of AI platforms out there, if you ask for them about their auditability and their release management and their security framework, things that we take for granted that you must have, they are found wanting. And what it means is it's a risk when it comes to the enterprise AI space.

And last but not least, is I haven't yet met a customer -- sorry, this is not true. I have met a customer who's tried, but not been successful. No customer that I speak to are thinking about no human in the loop. They want human in the loop even if it's simply to guide what the AI agent is doing. You'll see some technology if you get to the show floor for those who are here at NiCE World, you can see how our humans can actually be watching what an AI is doing at the time, and it will actually trigger the AI agent may not be sure. Do I give a credit in this circumstance? It might not be a clear decision 1 way or another. So it sends an alert to a human agent or a supervisor, what do I do in this case? They give the feedback. It learns. Next time, it will make that decision proactively. This is the capability we've already got out of the box that allows a human engagement and an AI engagement all embedded in one flow, one experience. You as a customer won't know it, but it will be a much more seamless experience.

So I guess, end to end, that means that we see ourselves as very different At NiCE, we don't believe that we need to compete head-to-head with an AI player on a stand-alone basis. We can and we do and we win. I need to reiterate, go to any of the Gartner or Forrester industry analysts and look at the #1 conversational AI player with customer service or customer experience. You'll see Cognigy, top right-hand corner. Some of the other point players that you hear and talk about out there, they're not even on the chart. And if they are, they're nowhere near. The richness, the capability of this platform as a stand-alone AI platform in its own right is fantastic, and we try to compete and win on that. But our value is so much broader. We've built an orchestrated platform that no one else can offer. There is simply no one. Others are going to fast follow. There's no doubt about it. We know that others are following our lead with what we've done with Cognigy and integrating it into the full suite, but that takes a lot of work. And we've already got the market leader already in place which means our platform is way richer than what some of those others can potentially offer.

So we're very comfortable that as we go into this AI era, when we're competing with point or fragmented AI platforms that we stand strong, orchestrated outcomes, running AI across the CX operation, every interaction in compounding in its intelligence, whether a human or an AI spoke about it, that is NiCE's advantage. We've got the ability to be able to take all forms of intelligence. The market gets so wound up on artificial intelligence. Yes, it's really important, but it's not the only intelligence that matters.

When you go to a CX site, and you go to a contact center, it's really amazing. You go on the ground and you talk to them and you watch what a human agent does. The amount of decision-making, the complex decision-making they need to make real-time under pressure. The clock is watching, supervisors are watching, leaders are watching and they're making real-time decisions on behalf of their company that has financial consequence, that has brand consequence. This is real, difficult work, and we have the knowledge, that embedded knowledge that is infused in our AI platform that others, they're doing bolt-on tools, they try to copy all the data and they try to figure it out on their own. It's AI on CX not in CX.

So our agentic intelligence, our human intelligence, our operational intelligence, the things that we've had to do for decades to deliver customer service in a human contact in a contact center, we're now applying that in the AI world, and it gives us opportunities to automate where we never could before, but it also gives us the ability to learn from those different so that they provide a compounding advantage on both ways.

That's why AI is so exciting to us. It's not just the unique market opportunity that it presents for NiCE. It presents us an opportunity to differentiate and expand upon what we were already best-in-class at. And it makes that element even stronger. So if you're running a contact center and you're thinking about how to manage the workforce, you're doing what Mia at Citi talked about. You're thinking about how you can improve retention, burn out, challenges around attrition. You're using the data, the knowledge in a way, and then that's also informing the AI agents to perform better as well. These are not disconnected platforms, not with NiCE. If companies choose to go with separate solutions, they're going to have to integrate that together and you know we're near going to get the seamless experience.

So I guess I'm rounding all of this up to say is that we are growing rapidly in an expanding market. Our bookings have been at the record levels for the last 3 quarters. Our backlog is growing, our AI is flying, and that is in a market that is in very early days of what the market's demand on the AI side. But where it goes, which is buying at enterprise scale, in operational complexity, in orchestration, in true orchestration in the contact centers and in the workforce management. That's where the market is going. We've already built it. We are ready and able to then scale that, which is why big organizations such as you might have read about HMRC that announced an 8-digit deal or a 9-digit TCV deal with us a couple of weeks ago, why did they choose NiCE because it's that platform. Everything that I've just spoken about, the CX AI platform operating with over 30,000 agents, operating at scale, that's why they chose NiCE.

So let me move forward quicker. I'll move quickly. We've got an expanded role. We were moving to a bigger category. We're going to bigger buyers. I have been really pleased. It's been interesting the amount of CEO meetings that I've had over the last 12 months has increased because the importance, not only in terms of spend, but in terms of the importance of this platform is to the overall business. We've got an executive engagement track. We had such demand from C-suite customers here at NiCE World, we set up for the first time to have an executive track today purely for that cohort because they're so interested in what we're building and how they can apply it within their organization. And clearly, they're interested in the value that it brings in the ROI.

So hopefully, that gives some context of not only where we are, why we're so excited about the opportunity, but where we're going and what we've built, what we've integrated. The technical integration of Cognigy into CXone was not just a task to be done, it was an embedded platform that we can now go and compete on differentiated terms. And we're already seeing the fruits of that. We're already seeing the benefits with our win rates, with our bookings rates and with our renewals as well. Customers are buying into that vision, and to give a little bit more detail about the day and then go into more details about the technology, I'm going to ask Jeff who's going to talk about the technology platform. Arun and our TripAdvisor team are going to talk about delivering real outcomes in real customer scenarios. Arun, sorry, will cover the scaling outcomes with John from our Accenture team, and then Beth will wrap it up in a monetization of how it all looks from the monetization of the platform.

So with that, Jeff, I'm going to hand over to you.

All right. Good morning, everyone. So I'll walk you through how we orchestrate intelligence across customer experience. I thought I would start with a view of what contact centers basically have today. So before they onboard the CXone, what do they really look like from a conceptual perspective? And here's that view. They have voice. They have the voice channel. They have the all-important voice routing. This is kind of where it all got started. And this is still a critical channel in the contact center. They have all the workforce management, right, managing their human workforce. They have forecasting, scheduling, quality. There's a whole bunch of capabilities and applications in that space. And of course, they have some basic analytics to go manage the voice and the human workflow -- the workforce, right?

As technology has advanced, they add more and more capabilities, right? So on voice, they've added IVRs, digital channels, live chat came out, social messaging channels. They added those. They added sort of the first-generation crappy bots that [indiscernible] had forced upon us, virtual agents. And of course, now today with the emerging very powerful agentic agents. So they've assembled all these capabilities to run a basic customer experience function. But here's the problem with how all that got built out.

Historically, no single vendor had even the majority of these capabilities. So they've had to go add each one of these, they've had to bolt it on ad hoc over many, many years. And that means different vendor solutions, lots of different vendors in this landscape, lots of siloed technologies that they do have to care and feed for and lots of pockets of data, disconnected data that don't talk to each other. And they've got to manage these fragile integrations between these systems, right?

So for these enterprise contact centers, that represents tremendous cost and complexity. They're spending a lot of resources on this and they always have, but that's coming at the cost of focusing and delivering incredible customer experiences. That's what they really want to be focused on. And this is why the platform approach is so valuable. And that, of course, is the path we've taken with CXone, right? CXone spans spans all -- like the big 3 categories of customer engagement. We call it agentic for front end, agentic systems, engagement for all the channels of engagement and then, of course, workforce empowerment, which is managing that human workforce, but also now that AI agent workforce. And CXone is that industrial strength, enterprise-grade platform that can handle those mission-critical high-volume communications. That is CXone. That's our heritage coming from voice.

And that platform powers seamless experiences across all channels of engagement. Yes, voice, but also digital channels and also from self-service to human-assisted service. So all on one platform, it's all in one place, powered by CXone.

And this is really important today that all that data, all those capabilities are in one place in a coherent fashion, and that's critical for agentic AI. That AI needs those capabilities, all that data so we can reason over it and use that data to drive outcomes. And across all 3 areas of customer engagement, we lead. NiCE is in a leadership position in every single category. And you don't have to take our word for it, we've got all the leading analyst firms across the space that give us that external validation as well. And I'll tell you, no other vendor can say this. They just simply don't have all the components, let alone the third-party vendor validation.

So we are leading in the CX platform space, full stop. And we built this platform for adoption flexibility. So as customers start with CXone, what they don't have to do is rip and replace. They have this fragmented landscape. They can start wherever they have the most urgent need. Any one of those product capabilities they can get started with, those components come with a whole host of third-party adopters. So we easily slide into that fragmented landscape and customers can get going. And then from there, they can expand, right? So as they expand, they get 2 big benefits. Number one, of course, they can start retiring all of these different tech stacks, but at the same time, they start getting the platform benefits that we can uniquely deliver, and I'll talk to you about a few of those.

And Arun will talk to you how -- talk you through how we leverage this platform advantage from an architectural perspective in our land and expand delivery motion.

Okay. And in each one of these categories, we also have incredible depth and breadth. This view does not even scratch the surface. And for big enterprises, we truly are a one-stop shop. This is why the HMRCs of the world, the Citis, this is why they choose us. Let's see.

So this is -- and by the way, all these capabilities are sitting on the same CXone platform, that same enterprise-grade, high-volume, mission-critical platform. But it also supports the very long list of security, privacy certifications that the most heavily regulated organizations on planet earth require. We cover that. And of course, the latest addition to this platform is Cognigy, as Scott mentioned.

Cognigy is now native to CXone. In our last Investor Day, I think it was November of last year, shortly after acquisition, I came up here and told you how we were going to go integrate CXone deeply in the platform while retaining the ability for customers to purchase and deploy NiCE Cognigy separately, independently. And I'm happy to stand here and say, we are well ahead of our own ambitious plan there. It is baked in. It is done. It's the foundational conversational AI agentic AI layer for CXone. That means it's 1 application experience, 1 shared data layer, 1 set of communication channels, voice and all the digital capabilities that we have. And coming by the end of the year, we have a few more things to do. We're doing the engineering work and certification work to make Cognigy FedRAMP compliant. We'll have that done by the end of the year. And we have a few more sovereign clouds to deploy. But other than that, it is baked in at the core level.

We've already got lots of innovations I'll talk to you about, and we're just getting started in that direction.

So Cognigy is now native and that means it's already the conversational and agentic AI capability. So from our self-service, on the left-hand side here, you see it is our self-service AI agents for all channels of engagement. For role specific Copilots in our existing products, those are now completely replumbed for -- with Cognigy. That means they even have more tool use, more agentic capabilities, so our existing customers with existing products now have more value, making those products more value for them, even stickier from that perspective.

And -- let's see. Now that it is on the same platform, Cognigy does allow us to do so much more. This is where we can really break out. It allows us to build learning loops within the CXone platform. And we're launching those this week. We talked about it at Scott's session. Hopefully, you can make it to the show floor. We've got lots of examples of where we're building and delivering these learning loops.

I'm going to walk you through an example of what this means. This is one of our broad learning groups. So as we all know, Cognigy, stand-alone product, very successful product. Customers are achieving 60%, 70%, 90% resolution rates depending, of course, on the intent. But what happens to that 20%? It gets escalated to humans, right? But now that we're on the same platform, we can see what's happening with that 20%. What are humans doing? What tools are they using? What sequence are they doing doing? How do they get it resolved? And we have all that multimodal data, the voice stream, we've got the screen recording. We've been in regulated industries forever. We've got all this technology. So we have all this deep data that now we can apply very sophisticated multimodal AI on to get insights in terms of how to go close that final 20%. So basically, it's a goal-seeking loop that is goal seeking to just get more and more automation done past that 80%.

Okay. With every -- so basically, at the end of the day, with every engagement, the system is just getting smarter and smarter. And customers are choosing us for these types of platform advantages. And of course, in just a little bit, you'll hear from our friends at TripAdvisor, and they'll share with you some of the reasons they came over to the platform.

Okay. So that was the platform advantage. Now that Cognigy is native, I'm going to talk to you a little bit about some of the highlights. I'm going to touch on just a few of the innovations we're launching this week just to give you a flavor of where we're at.

So a key theme in addition to agentic AI throughout is how we're advancing the entire platform and all of our applications for the hybrid workforce, humans and AI agents. Agents working alongside human agents, humans supervising fleets of AI agents, and of course, agents assisting humans in the flow of their work. So one of these launches that we have this week is called the engagement -- the agentic engagement plan. So just think of this as an enabling layer that puts AI agents on the same level playing field as humans. And I'll just give you an example to give you a sense of what this enables. But I will tell you, this is a game changer. AI agents are so powerful today, this engagement plan just sort of unleashes that.

Today, when an AI agent has trouble, right? It doesn't have quite the confidence to close the issue, what happens, gets escalated to a human. With this new plan, the AI agent can now just raise his virtual hand and say, "Hey, I don't have quite the confidence to give this -- sort of this return to the customer. I'm not going to go hand it off to the human, I'm going to raise my hand." Human supervisors, just like they do today, they manage in real time the human workforce. And this is what they do. Now they can do that for AI agents. An AI agent has their handheld, they can go -- the human supervisor can go into that conversation, see the whole scenario, the conversation instantly, look at the scenario and say, go ahead and give that return voucher, go ahead and okay it. And then the AI agent can go continue the conversation and close and automate that whole transaction.

So I mean just think about that for a little bit. A human spends 10, 12 seconds reviewing, approving, moves on, helps the next human or AI agent that needs help. The AI agent continues the conversation. And by the way, there's a learning loop. So next time there's a scenario just like that, it knows that it can go ahead and give the return. So this is a good example, I think, of how we're really changing the game in terms of the hybrid workforce, and it is very, very powerful.

The AI-first desktop. We're obviously reimagining what it is for humans to engage with customers. We now have AI infused throughout. It's also that surface area where humans supervise that -- those fleets of AI agents.

So next, workforce empowerment. Across workforce empowerment, we're redefining what it means to manage this workforce with humans working alongside AI agents. So we're extending the operating model from planning, scheduling, quality, cost and performance across the board. There's a lot of capabilities in this space. They're all being updated in a big way to manage that AI and human workforce. And we're delivering very targeted optimization loops there, right? There's a lot of -- for quality and performance of engagements, there's a lot of tools that we've developed over many years. Now we apply that equally across AI engagements as well as human engagement.

And finally, agent experience automation. In this space, think of this as we're just advancing our leadership in the AI agent space, right, across the board. One of them is agentic analytics. So this is where we built a fleet of highly specific domain expert AI that goes in and goes through the entire data set that we have across the platform and it's looking for more opportunities to automate. It's also looking for -- it's also looking at existing automation and how it can improve those automations. Agent Forge, it's already very easy to create AI agents with Cognigy. With Agent Forge, we're making it even easier, of course, from our own platform, but also we can take just about any artifact that you can think of, whether it's a specification, a document of any kind, we can pull that into the platform and generate an AI agent in minutes. A human has -- we basically bootstrap that entire process.

Okay. Let's see. That was a quick round. I'll just maybe touch on one more, Guardian AI. AI agents are proliferating. It's really important for customers to have a control plane in terms of keeping those AI agents on brand, in compliance. And so we have a set of tools for observations and just managing this at massive scale. So Guardian AI is another key development from -- that we're launching this week.

Okay. That was a quick round of highlights. From first engagement to final resolution, this is how we're orchestrating intelligence, and this is how we are expanding our platform advantage. All right. So I'm happy to welcome up from TripAdvisor, John Hanley and Dave Fox.

Thank you for the intro. Well, thank you all for inviting us here today to talk about our journey into the world of AI. I recently joined TripAdvisor around 8 months ago. I am Head of Customer Operations. I'm responsible for defining the strategy. My colleague...

So I'm Dave Fox. I've been at TripAdvisor for rather longer about 8 years now, and they look after telecoms across the TripAdvisor Group. My task is to manage the tools that allow us to talk to each other and our customers.

Thanks, Dave. So when I joined, I totally changed our strategy. We were a human assistance first organization, 100% using, obviously, outsourcing. Hopefully, you all know who TripAdvisor are. It's one of the oldest brands in travel. But the most exciting part of TripAdvisor is via to our experiences. And this is our growth engine. And this is what gives me and customer service is a big issue. How do we service this hugely vast part of growth of our CX with this human assistance team. So it's quite clear to me from day 1 when I joined last year, we need to have AI, not AI necessarily enabling human agents because when customers come to us, I actually proved last year that actually humans are slowing down the conversion rate. It's slowing down the decision making. Why? Well, because we have part of the data, our suppliers are part of the data, our 2 guys have part the data. And [indiscernible] human being, as much as we can give them some amazing turning, they really slowed down that conversation. So we knew we had to go into AI and fast.

So I set a very tough demand of my team, how do we, in 90 days, figure out our strategy, our investment and go live. And of course, everyone said, you're joke in John, you're crazy. This can't be done. Well I think it can be done. And in those probably 2 or 3 months, we saw so many RFPs from other bidders on the world of AI. I mean, every week, I almost got a big coming in. But for me, the problem wasn't about core volume. And I think when I was talking with different suppliers, they didn't understand our strategy. It's customer first. We really care about solving the issue. We want to talk to customers. We don't want to deflect. In my 15-year 25-year history of CS, I have spent so many hours and so much money trying to deflect customers, try to hide the phone number, knowledge bases and chat bots, right? IVRs with 75 options. I think we have 15 actually. I hate it, I despite it. And for me, 15 years ago, I was really passionate about enabling the customer first. So for us, we had to find a technology that enabled this solution and not just affect our customers.

So Dave, you had 90 days to implement. Tell me, how do you do that?

Well, I'll start off by wearing a bit. I must confess. But -- and consider many things, but the answer is always going to be you build from the ground up. If the customers are going to contact you and you want to make it easy, like John described, you need to have a front door through which they can easily walk in and you can help them. So before we started this project, everything would go, as John said, to the human agent, we would say, "Hi, we'd find out what someone wants it." We then have to go and find out. Is that really you because we can't just let anyone change somebody's booking, we're going to find the book a mid, find the detail. And after all that, we can get on with actually trying to fix the issue that they've called us in about. That first little bit, the first 4 boxes on that slide typically takes a couple of minutes, not very long in the scheme of our lifetimes, perhaps. It's an awful long time when you've got someone tied up for it that could be doing something else. And at 2 minutes was the first place we had to look.

So John, if you can just skip on, please? And to do this, we built [indiscernible]. Not my choice of name, it's [indiscernible], I'm growing to it. This is our AI assistant, which helps us to understand, to verify, to retrieve. And eventually, if it can't resolve the thing itself, it can hand off to a human colleague. The idea is to make it seamless. John makes the really important point, we are here to make the customer have a good time not to make them leap through flaming hoops, jump up and down on a Pogo stick and then only then can we help them. It's to make it a nice smooth instance. And the only way we could do that is not to have some bot, which we bought on to the site. We transfer across like you forwarding you call your voice mail, we need those calls to be a voice inside of our architecture and something that becomes part of a seamless journey. [indiscernible].

Yes. And I think just a quick color on there, Dev, I think on the session this morning, which was awesome, by the way, the key word that I heard was we were going to invest in AI, don't do the easy thing, do the right thing. And so many people, even as of last week with St John, [indiscernible] is the easiest thing to do for AI. Absolutely. But you know what, for our customers, we sell the emotional product. When you go on vacation with your family and friends, you don't want to be [indiscernible]. You want to call somebody, okay? So we knew voice was absolutely place to start. And Unfortunately, what Dave told me was, is also the hardest.

Absolutely. And I'll go to my grave same voice is the hardest of the telecoms engineer. I do valuable work, John, take that back to HR, but every -- not only do we have to the calls. And from an engineering perspective and none of you guys need to hear about the engineering of it, it's way more complex, just the simple mouth to wear delay in a global environment, the speed of light gets a bit slow. But also it's a big black hole what we talk classically to customers about because with chats, you have a transcript, with e-mails you've got a mail trial, with calls, there is a conversation which we might record. We might transcribe and someone's got to go through the thing is the traditional way. So there was this huge black hole historically of information, which we couldn't see.

And for us, that was an untapped resource, an untapped opportunity. The guys through the presentation has took loads about the value of insights, the value of context. We need to understand what those conversations are so we can understand where the friction is. Is it a bad process in supporting a customer has got an issue? Is it actually an issue which we could fix by moving the big blue buttons a couple of inches to the right on our website. So it's really important for us to be able to take those contacts to have the insight and then we can start fixing the issue. Can you just step on, please, John?

Yes. And I think 1 thing I had a problem with was it sounds good. And I think the technology is there I thought to myself, but actually, well, our customers accept voice. I'm on vacation, I'm with my family and my friends and sign the to bus doesn't turn up, like am I going to accept some kind of chat kind of talk to me. So the big bet, the big investment wasn't necessarily the risk that we go with because I think we picked someone fantastic. Proof of concept that we did actually was, will, our customers actually voice. That was the unquestioned that we had at the beginning.

Absolutely. So why did we choose NiCE? Now we're a long-standing nice customer. We've been a customer -- 1 customer for many years. He's done a great job for us. So they are always someone who're going to talk about this stuff. But Scott from everything you said you'd be quite pleased that some of my reason in here. But more than anything else, it was the ability to provide everything in a single solution on a global scale for us. The complexity that the guys have been describing to where we've got different sources of data where we've got loads of different tools, we've got a complex agent workspace makes it more and more difficult for me as an engineer to build and manage that thing. Every time someone does a dot change on one of their platforms, I have to go and redo all the integration. That I haven't got time for when this blogs asking me to deploy bots in 90 days.

30 days.

You changed the old post. It's terrible. We wanted something that would give us that scalability, that manageability and let us be future ready. It goes without saying as you've all heard during the day, there's AI capabilities baked into the very heart of what NiCE does. The acquisition of Cognigy, though was a game changer. That gives us the front end, which can be more like the experience we want our customers that particularly on the calls, which, again, I'll say it because I like saying it, voice is more difficult than chat. It's certainly a lot harder to have a persona that gives you a human-like conversation than it is to do something where you're allowed a couple of seconds delighted to think about it.

The fact that it's throughout the platform means things are joined up, and we can have a coherent experience. The final reason we chose NiCE was, as I said, we worked with them a long while, [indiscernible]. We're trust and I see them again, it was mentioned in the keynote as something of an extension of my technical team. I'm sure, John, you see it as an extension of your customer service and operations team. It's something we could feel we could trust. If we're going to do something difficult, we need people that we can rely on to be there with us.

Yes. I mean I do to take you guys he'll tell you the important things about a single platform, but it's true. I mean my demands are fast not because I'm getting older and grayer. It's because we will let to that in the journey like some of CX organizations. But unquestionably, it's not a speed to finish, it's to speed to start. And I think it wasn't the risk about jumping in, it was the long-term part of things. And I think, for me, when I was talking to other organizations, they try to take my strategy and turn it around to fit their product, which is not what I wanted. What I want was a company that could see the strategy of our group and deliver. And NiCE, honestly, was the only organization that got it.

I never talked about cost reduction. It's been the primary focus. It's about solving the issue. So now that we've actually launched [indiscernible], which, by the way, can I just tell you, Igor drinking as guy from the U.K. I don't talk any other [indiscernible]. I actually play Vesper on my phone live. I got to my friend is the call of [indiscernible], they think it is just been awesome, right? We launched in 45 days after we did the contracts, 45 days. It's incredible when I think about it, what we did. Although [indiscernible] Version 1, and now we've internally hired a bunch of people to kind of really grow [indiscernible] into version 2 and version 3. And it's incredible what we can do. This is what excites me. This is why I think I know our partnership is the strongest. It's not about what we've done today, which is build out a reactive inbound customer service. It's the future that I dreamt about 15 years ago. It's about the productive side. How can we figure out customer problems before a customer problem.

I heard the call this morning about the German airline, and it just really excites me because how many people want to go on vacation, jump on a plane, get to destination to find out as a problem. Nobody. Standing there with the family and the kid shouting daddy, mommy, I want -- and I'm in customer services, give an hour, there's a 25-minute weight [indiscernible]. [indiscernible] if we could solve the problem for a problem. A nice really understand that journey that we're on, things like what if we have bad weather, and you can't go on the 2 without day. How about we just rebook it for you for the next year when [indiscernible] it's fantastic rather than funding customer services. So this is the part that we're starting on. This is just a tip of the iceberg.

In fact, if you talk to my account manager from NiCE, I sent 3 e-mails in the key sleek this morning going, call we, call me, call me because there's so much opportunity. So for us, for [indiscernible] and Chip Adviser, yes, it's all about putting the customer first, and this is really exciting. So[indiscernible]. It's been a great partnership, and we're throwing and joining it. Thank you very much.

Thank you, TripAdvisor team. The TripAdvisor narrative really resonated with me, both in my current role at NiCE and my previous role at Disney. Before joining NiCE as COO 6 months ago, I was at Disney for 4 years, transforming the CX function that served over 180 million customers. Using the NiCE platform that Scott and Jeff spoke about, I modernize the end-to-end CX stack from a digital AI front door to CCaaS, to all other aspects of WAM, which allowed us to deliver exceptional Disney-like experiences at the lowest possible cost to serve.

Let me spend a few minutes on how we have a very sharp focus on scaling the outcomes of our customers. To do this, we have built and continue to refine an enterprise-grade methodology to deliver ROI for some of the largest enterprises on the world. We are intensely focused on each stage of the customer journey, not just talking about it, but executing it with rigor and keeping customer success as our North Star. The journey starts with discovery demo and proof-of-concept to define scope and success criteria.

Forward deployed pods of engineers and consultants ensure that value is being delivered rapidly even during the solutioning process. In parallel with solutioning, we align on what a full enterprise-grade deployment will look like, covering customer alignment, configurations, integrations to get the customer into production quickly so that they can get the full value of the platform as soon as possible. As deployment progresses, the focus shifts to business outcomes value realization, ROI tracking and building a success road map to ensure that customers are getting value quickly and have a clear path to continued benefits from the platform.

Next, we work with customers to identify additional use cases, value capture opportunities, which grows the platform adoption for the customer and feeds back into the sales solutioning cycle. This enables the land and expand strategy that Jeff referred to earlier. While many companies describe a very similar cycle, there's nothing unique about that. The differentiator is the intense operational focus that we have at every stage anticipating customer needs in the future and always keeping our North Star as their success, ensuring that they're getting the business outcomes they need.

Next, let me focus on how we are accelerating time to value for our customers. We have built an AI COE that focuses on reusable areas like intent taxonomies, conversational design, hallucination guardrails, fallback protocols, et cetera, all designed to accelerate customer outcomes. We have also built -- we have also prebuilt connectors and APIs to common systems like CRM, workflow automation templates for authentication, routing, escalations, et cetera, and internal AI tooling to speed up every aspect of the customer deployment. These two pillars are now complemented by NICE Labs that was announced earlier today, which will conduct advanced research, rigorous benchmarking and rapid prototyping at the leading edge of agentic customer experience. The third pillar, our partner ecosystem complements, strengthens and expands our ability to accelerate time to value. I will cover more details on the partner ecosystem in the next few slides. These three pillars make up our enterprise-grade deployment strategy to accelerate time to value for our customers, which, in turn, accelerates our revenue recognition.

As you have heard previously from Scott and others, we have been investing in our partner ecosystem, and it's bearing strong results. As part of the investment, I hired a Chief Partner Officer when I joined the company. Our partner strategy has four key areas. We work with all of the major GSIs. We have over 200 certified implementation partners, which also accelerate our deployment capabilities. In technology alliances and ISVs, we have over 180 Dev 1 ISV apps for the platform. And we work with over 400 distribution and reseller partners which gives us tremendous breadth and global reach for our platform.

Just to share a few data points on the depth of these partnerships. We have over 2,300 certified professionals from our partner group on NICE AI and CX solutions. Over 70 new integrations were created in the past 12 months with our technology partners. And finally, 70% of CX1 new enterprise ACV was partner-led. Taken together, these demonstrate the growing power of our enterprise-grade partner ecosystem.

Let me turn to a little bit more detail on the GSI relationships. We are working with all of them and the relationships are becoming stronger with each passing quarter. Why are the top GSIs investing with NICE. One, our fully integrated CX AI platform; two, best-in-class components from agentic AI, orchestration, workforce empowerment, we can start anywhere and customers and partners can scale as needs grow. And third, the opportunity to win 7, 8 and even 9-figure deals. The outcome has been that over the past 12 months, our ACV with GSIs has grown by 3.6x over the previous year. This growth has come from winning marquee customers from a top U.S. bank, perhaps the one we heard about this morning, two of the largest U.S. health care providers, the largest U.S. pharmacy retailer, massive governmental wins such as HMRC in the U.K. and a similar one in Australia. Beyond that, we have won customers together in every major vertical from financial services, insurance, energy, utilities, telecommunications, government, you name it, the entire spectrum.

Next, let me focus on Accenture specifically, who is one of our top GSI partners. As a leading SI, Accenture has a unique point of view into where the enterprise AI CX market is going. They are growing and investing in our partnership for the reasons I already articulated, but also for the ability and opportunity for them to drive large-scale CX transformations for their clients. But rather than me speak to it, let's hear directly from Accenture. Joining me on stage is John Bolds, Accenture's Senior Managing Director for CX Solutions and ecosystem.

Okay. So Welcome, John. Thanks for joining us.

Absolutely.

John, you often and frequently speak with C-suite and CX leaders at the world's largest enterprises. How are they thinking of evolving their CX function? And how has the conversation changed over the past year?

So for years, CX has been a top priority of our clients. Why not as customer experience matters. I'm going to try and say some things today that are somewhat provocative and one click down on the high level. The big point is the amount of investment is amazing. Secondly, the focus is on service. It used to be 1 of it was customer experience, you had marketing digital and so forth. The laser focused on service is amazing. And secondly, think about over the years, that investment was going on to digital. It was drive self-service, drive self-service, better web, better mobile app experience. But now even with all of that, still voice I agree with your TripAdvisor voice is so hard. There's still so much that goes into voice. It's now that investment is into that channel. And with the promise of AI, what they're seeing with conversational, our clients like the objectives or C suites or segments, some of our leading companies, they want 40% to 60% reduction in the cost to serve. But at the same time, they want to see MPS reduce -- increase by 2 to 3x across the board. So that sounds like the Fed's dual mandate high employment, low inflation.

Bingo

Deliver deliver exceptional experiences at the lowest possible cost to serve.

Yes. There's nothing wrong with that. I know people say it's not cost. It's still a big...

It matters.

It matters.

Okay. Moving on to the next one. You have built a dedicated nice practice with hundreds of people who are technically certified on the NICE platform. What prompted you to invest in NICE? And why are you thinking of investing even further?

Yes. Well, sure. Well, because our customers now want an AI-powered contact center. And remember, contact center, a lot of people think it's the same as call center. It's not. There's a reason it's called contact center. It's omnichannel, and they want an AI-powered one. The other thing is you'll hear Julie Sweet, our CEO say quite a bit, our C-suite is going, when do I get the value from AI? I'm not saying for one else get value, when do I get the value, right? And they're seeing, wow, I have an AI power customer service, I can get there. And so that means, and that Number 1 is they want companies who actually get customer service. NiCE does. It's at your core. Secondly, we have that. It's a nice match. Third, they want a platform. They do want a platform, and NiCE has it all. They really do. They now have the CCaaS, the IVR and routing, the workforce management, the intelligence, I mean you saw a Defcomstock slide. It's a perfect blueprint of all the capabilities. NiCE now has them. But what's super cool about NiCE is that you can start anywhere because our clients are in a different part of the journey. They all are. They have different parts of the components, and you have such a huge installed base. So we'll go in there where you have workforce management and make an impact there. We'll go in there. And for instance, in this big FS company, we did the intent analytics, and it led to us driving an entire AI play. And then finally, we're still doing. I love how you guys said it. CCaaS isn't over. There's still massive CCaaS plays to be made. So we can start anywhere and expand from there with outcomes.

And that resonates. I've spoken to dozens and dozens of customers since I joined NiCE, and I think the smartest, the largest enterprises are looking for that entire play versus one or the other, if you would. So that's great.

Let's turn to AI for a moment. I mean, how can we have this conversation or specifically focusing on AI. The market is flooded with point AI solutions, yet Accenture decided to invest meaningfully in Cognigy on the NiCE platform. Why bet on the integrated platform versus one of the point solutions?

Yes. And the reason is because at the end of the day, you point conversational AI solutions are interesting they work, but you have to make it work within the IVR, in the telephony stack, within digital, within all of the different channels. And I think people underplay that. And that's why you're seeing this -- again, I want to give you some provocative points that I found so interesting over my years. This move of having to have people skilled in digital, and all of a sudden, you need to take that digital skills and apply it to the telephony side. And so therefore, we like that Cognigy and then AI has at its core integrated in the platform, how to work holistically within the platform. So let's make it -- also, at the end of the day, the #1 slide my clients use when I work with them is the following. They need to get to that 40% to 60% improvement, and they want to do it. You have to do it across all the layers. Number 1 is where you heard TripAdvisor go, proactive. We've been doing -- we, in fact, had a proactive messaging practice in our firm. We were already, for years, doing multi-day journey management. So take the telco space. When you actually have a problem with your router and you need to schedule appointment and manage that appointment, we would do that all through [indiscernible] journey management. We're actually managing the appointment, checking if they're going to be there, if they are, have they touched the equipment and then when it's done. And that then has been applied to in public service. We then used it in health care. We actually manage someone's appointment and make sure that you check in on them. the reason I spent so much time talking there, I'm more TripAdvisor was. I know I said you guys 4 times, so I was really impressed. That's where we get the most bang for the buck at the top. Then if there's an inbound call, can you then contain it. And so that's where a lot of these solutions are. However, that call, most of the conversations, the harder intents that we're told to start with, they don't usually get fully contained. So when it gets to a human agent, you want a smooth handoff. You want to make sure that, that agent does not start over again [indiscernible] been so frustrating, right? So frustrating. It needs to pick it right up and then help the agent then make that a tradition.

Finally, agent assist. So how do you ensure that, that agent for instance, we're getting so much lift out of doing simple call summary, but more importantly, workflow management after -- like after you've handled a claims conversation is that you actually kick off the forms, kick off the process and make it work. And then you're thinking, well, that's 3 levers. People forget how about running the contact center. There're hundreds and hundreds of people in these contact centers who do quality assurance and the quality assurance on 5% of the calls. You can now automate quality assurance. You can now automate the routing. So that's another lift.

And then finally, how about growth? We're not doing proactive outbound calling or leads that come in, you have a call and to say, I heard your interested in some wealth management products. The voice sounds fine, they take it, and then it kicks off a lead in a sale. So you got to put all that together. And what's great is it's all integrated in one platform.

So said another way, the fact that we've got Cognigy capabilities built across the entire platform that can serve all the use cases you talked about?

It's awesome.

Well, John, we've built a lot of real momentum together. Looking ahead, where do you see the biggest opportunity for a partnership and what excites you?

What excites me is getting the true agentic customer service. How many of you are right now going as your first question, is going to Gemini straight up? You're going there for the answer, and it's good. Well, guess what, we are already seeing Gemini giving the answer, and it needs to hit into your organization to make sure it's giving the right answer. That's where the future is legit going. The other future where it's going is bot to bot. It's absolutely happening. In health care, we already had a situation where you have the providers checking in with the payers whether or not the coverage is there, what's the -- what is covered, what's the different rates you have to charge and so forth. Well, the bots are hammering those calls. If you don't have bots to handle those calls you're getting crushed. So bot to bot is happening. So you have to become agentic. And so I love -- that's where the future is. And what I like is by having this platform, we can get there. And so let's continue to accelerate outcomes with where you have capabilities. The final thing I will say is what you've done to change the partner culture here is phenomenal. You, Scott, see, we worked with Arun and Scott. Everything at the end of the day is personal. We worked with you guys at your prior careers. And you guys know how to scale partnerships. Now the next thing is how do we just accelerate the certification of all of our skills. And if we do that, we're going to help our clients truly get the value out of AI that they want.

Well, that's an important takeaway for our investors. Accenture is choosing to deepen its investment because of the platform is resonating with their clients, the economics are attractive and the outcomes are really strong. John, I want to thank you for taking the time. We are excited about our partnership, and we'll do all things together.

We will. Thank you.

Next, I'm happy to welcome our CFO, Beth.

Thank you, Arun. It's really great to hear the conversation that you just had with John. I think following that, it's that we're in a really exciting time that our ecosystem strategy and the partner acceleration is really expanding. We're accelerating faster. We're extending our reach globally through this connected partner network. And so we're really pleased to hear that directly from John.

So as we move forward, I think throughout the day -- excuse me, I'm clicking a little too fast here. Throughout the day, you've heard one connected story from all of our team. Scott started by outlining why we have a structural advantage at NiCE in a large and growing market. And then you heard from Jeff. And Jeff shared how that advantage is embedded in our CXone platform that orchestrates all of our interactions regardless of whether they're human-led or AI-led across our single platform, which is CXone.

You then heard directly from some of our customers, both earlier today on stage, in the keynote as well as here from TripAdvisors how they're already realizing measurable proven outcomes from our platform. And again, of course, our partner ecosystem is really accelerating that adoption around the world.

So now I want to take all of the things that you've heard today so far in the one connected story and talk about how we're actually monetizing that and driving durable ARR growth at NiCE.

So at NiCE, we've built a monetization framework that captures value from every customer interaction that we have across our orchestration layer regardless of whether that interaction is being driven by a human or if it's being driven by our AI. Today, the large majority, as you see of our revenue is seat-based, and we continue to benefit from ongoing CCaaS migrations that we have in the cloud. But what's really changing is our AI and services layer, as we've been talking to you both throughout today and our recent earnings calls as well. When you look on the first quarter, as an example, you can see that our AI and self-services revenue now contributes 14% of our cloud revenue or $345 million. And that growth was 66% over the same quarter of last year. That 14% is up from 8% of our cloud revenue contribution just 2 years ago, and it shows you how AI is working for us.

As we continue to sell across our customer base and we continue to add new logos, we expect that shift that you're already seeing to continue to drive additional growth in AI and and in our overall cloud growth as a result.

What makes us really differentiated at NiCE, however, is what we've been talking about earlier today is that our customers are making a single platform commitment to us. It is one ARR envelope. And of course, within that, the customers have the ability to flex in between human-led interactions, AI-led interactions and all on our single unified platform of CXone. I think earlier today on the keynote, you heard directly from Citi, which was a great example of how they're using that package and able to flex with our hybrid pricing model between human and agentic agents. So that's really a connected advantage that facilitates our AI adoption across our customer base that all of our customers have that ability to flex between the human-led or the AI-led interactions, and again, all in that single ARR envelope.

One of the strengths of our platform in CX is our ability to consistently increase the customer value over time, and we have a lot of data points that we want to share with you. Historically, when you look at how we've been driving our growth at NiCE, it's a combination of increases in user growth, it's also interaction volumes that continue to expand, it's increasing enterprise -- large enterprise deployments, and finally, broader product adoption. And you heard a lot today from Jeff specifically around our CXone platform, where we have the best depth and breadth of a solution for the CX market. And that's really what allows us to continue to both cross-sell and upsell as a motion into both our existing installed base, but also to offer that into new logos as well.

So when we have customers coming on board in our CXone platform, and with the use of AI, they usually start with a specific use case. You can hear from our customers that they are proving the value and the ROI very quickly. And it's easy for them to then extend into adjacent capabilities that cover all of the breadth of our platform. The additional functionality can be added very easily. I think you heard earlier from the TripAdvisor team specifially that they do not need to rearchitect their environment to add these additional capabilities or Cognigy because everything truly is 1 integrated native platform that we offer. So this dynamic across the platform is particularly powerful when we look at AI adoption, and AI is our growth lever, our #1 growth lever here at NiCE, and it's extremely easy to continue to add that capability into all of our customer base.

So I'm going to now talk more about the platform expansion we're seeing, both AI that predated the acquisition of Cognigy, and then a little more specifically around Cognigy, and what we're seeing there with some of the AI adoption as well.

So when we look at the data points that we have, both in our existing AI customers prior to the acquisition of Cognigy as well as post that, we see clear validation that our AI strategy is working as designed. Today, when you look at an average revenue per a user for an AI customer, you will see that those customers generate approximately 36% higher ARPU than a non-AI customer. And then when you look on an average revenue per customer, or an ARPC of a customer that, again, is an AI user, you will see that their average revenue per customer or the ARPC is 4.5x that of a non-AI customers. These are really great validation points, and it shows you that AI is not just another simple product category here for us at NiCE, it's really a competitive differentiator and is increasing the overall economic value of all of our customer relationships as shown through the higher ARPU as well as the higher revenue per customer that we're achieving through the ongoing deployment of all of our AI capabilities.

So next, we're going to look at some of the data points that we have here at NiCE. This represents a cohort of our customers that adopted AI in 2024. So we see this pattern of expansion over time. And this, of course, was again, prior to the acquisition of Cognigy. So when you look at this cohort of adopters of our AI during the course of 2024, you will see that in a 12-month period alone they added approximately 23% higher or had a 23% higher average ARR relative to when prior to the adoption of AI. So we have some great examples of customers across this full cohort of these adopters in 2024 with evidence of that ARR working and that durable growth happening deployment of our AI. And what's also important in this is to remind you that -- not only are you seeing that growth coming from the AI ARR that's incremental, but we are also maintaining the non-AI revenue layer intact. So of those customers about 7% of the ARR was coming from that AI contribution specifically.

So they're adopting the AI as well as really having the benefits of the strength of the platform of CXone that's fully integrated.

So next, I want to bring us on now to looking at a similar level of information regarding AI and AI adoption, but this becomes more specific to Cognigy. So for Cognigy, what really makes us excited is not just the technology that you've heard a lot about, but also the expansion profile and the opportunity it presents for us here at NiCE. So once Cognigy lands inside a customer, you can see that the adoption is rapidly expanding. And what happens in a deployment is that typically customers start with a single use case, they get that proven value and the ROI that they're looking for very, very quickly. And then, of course, they start expanding. They expand into additional use cases, additional workflows, operationalizing the full journey of the customer. And so that's really a textbook land-and-expand motion that we're seeing. And as you see here, through the 2022 customer cohort data, those customers that had adopted Cognigy in 2022 have a 3x growth in their ARR from the first quarter of 2022 to the first quarter of 2026.

When you also look now at their customer growth, their customers have increased 3x since that same period. And of course, this is Cognigy now looking at prior to the acquisition. Of course, we are continuing to greatly expand that opportunity across the NICE global installed base that we have here.

And finally, the other thing I want to highlight here is the stickiness of the Cognigy solution. Cognigy has a lot of proven use cases. You heard from some of the keynote speakers earlier today. They are at enterprise scale, working with very large, well-known global brand names, and they've had a 100% enterprise logo retention over the last 3 years. So as we bring all of this together, you can see that the opportunity, even prior to the acquisition of Cognigy, was very strong for NiCE with that strength and the ongoing ARR growth. You can see that Cognigy had a similar experience. And now we're bringing that all together, the power of NiCE together with the power of the agentic capabilities that Cognigy brings.

So that stickiness and the land-and-expand motion is exactly why we reached out and proactively worked with a small number of large marquee customer we discussed on our earnings call last month, to accelerate the AI adoption and, in parallel, securing long-term commitments with those customers as well. So we saw a win-win opportunity for us to provide some short-term economic benefit to our customer, and in parallel, again, driving this AI opportunity where we've seen proven results that the ARR growth is strong post deployment.

So now I want to just walk you through 2 of those customers that we were referencing. The first is a Fortune 50 enterprise customer and this customer has an 8-digit ACV. So as you can see in the chart here, while there is an initial impact on ARR that we had discussed last quarter, as you look at the longer term and the expanded ARR, we expect to see a 5% uplift as a start for this customer. And it's through a combination of again, securing the long-term commitment, it's coming from also they have in addition to AI and capturing that opportunity with expansive growth opportunity. Looking forward, they also increased their users in both CCaaS and workforce management. So it's important to say that this particular customer is really looking at securing the relationship with us as well. They're a long-standing customer. And so they're expanding both CCaaS, workforce management and AI, which again is really demonstrating the power of the platform and the integrated relationship that we have.

So the second example is a utilities enterprise customer, which is a 7-digit ACV. And for this customer, you can see that we expect to have a significant uplift to more than double their ARR in the coming quarters. So for this customer, really, our ability to capture the platform economics and combined with the AI innovation that we offer through CXone is what really secured this relationship into a long-term commitment and made them very excited about how they're going to continue to evolve with us adopt more of their AI capabilities in the platform.

So now I'd like to share with you a bit of what we're seeing in our business more recently post acquisition with Cognigy. Here, we can see that in our first quarter bookings from this year, it really demonstrates the enormous opportunity and success we're already seeing in our bookings. We reported a first quarter record of cloud bookings this quarter and the past quarter that just passed. And it's also really highlighting the strength we have in the Cognigy bookings. So importantly, the Cognigy bookings, you can see is broader in terms of the bookings we're achieving with going out into our global installed base with NICE customers. In addition, Cognigy is continuing to sell stand-alone across their customer base and other new logos as well. And I think if you were at the keynote, you heard Phil talking about a little bit of that strategy earlier today on stage as well.

So the acquisition of Cognigy is really providing us with an additional growth layer that we didn't possess before, that provides a true end-to-end CX AI platform. And so today, while our CXone customers represent only a single-digit percent of Cognigy revenue, yet they represented the majority of our Cognigy bookings in Q1. So in other words, the cross-sell motion, it's already landing in our bookings. We're seeing that in our results. It's building that backlog that will convert to revenue, future revenue in coming quarters. And the monetization aspect is still in the very early stages of adoption and scaling.

So the opportunity is immense, as you've seen because we have multiple data points that show post adoption both on the Cognigy side as well as on the NiCE side, great durable growth with our customers.

So I want to conclude and before we break for Q&A to really highlight 3 key takeaways. First is that AI truly is the next evolution of our growth model here at NiCE. Second, we already have clear evidence that we've talked about that AI adoption increases customer value over time through higher ARPU, by greater platform adoption through taking on the more of the capabilities and solutions and the breadth of our CXone offering as well as a proven land-and-expand motion to our large global CXone installed base across the world.

We're also continuing to win large strategic customers. You've heard us earlier today talking about a recent win of HMRC. We're very excited about this recent win. It actually is our third mega large international win. We talked about our international region last -- back at our Capital Markets Day last year about how it's one of our key growth drivers. It is demonstrating that continued success with that win and really demonstrates also the strength that we have at the high end of the market, large enterprise and public sector environments where their expectations are extremely high in terms of the level of collaboration and the strength of the solution that we offer that it will operate at the high expectations that we deliver at.

So that's why, coming in all together, we believe we are uniquely positioned to benefit from both interactions with your human-led or AI-led all through, again, our integrated CXone platform that we orchestrate across the CXone offering.

So that's why we're confident that we'll continue to see durable ARR growth. And looking ahead, we have multiple data points, strong, solid Q1 that we came out of, increasing backlog, 66% growth in our AI revenue of $345 million, and as you can see, great ARR expansion over time with those customers post adoption.

So with that, that's going to -- I'm going to wrap up our -- all of our comments from earlier today from our team. And so I would encourage you all now to take a quick break to grab lunch, which is outside, but we'll continue on Q&A immediately after. So please feel free to grab some lunch, bring it back in and we'll continue. Thank you.

[Break]

Okay. We're going to get started with Q&A. Two mic runners. So if you have a question in the room, please raise your hand, and we'll get you a mic. Okay. We have one here, please. Also, Peter, if you don't mind just saying who you are and where you're from, that would be great.

Peter Blostein, PB Investment Partners out from California. Thank you for the terrific event presentation. And I'd also like to just express appreciation for the management team, all you guys have done on behalf of customers and shareholders with this -- I mean, basically company reset and redirection and acceleration. It's quite impressive. Cognigy partners, management team buyback, all that stuff.

Okay. So what I'd like to ask about is basically the big -- to me and others here, the big disconnect between the first half of the presentation and the financial revenue growth. When we go talk to customers, when we see the quality of the platform, it's phenomenal. The platform of the point solutions, Jeff made a terrific argument for it's going to be recursively self-improving, that's even better that customers don't have. Yet when we look out in the world, great AI products fly off the shelf, Anthrapic adds $1 billion of revenue a day. And yet we're here at mid-single-digit revenue growth and giving pricing concessions to customers who have a 7-digit ACV. Can you help bridge that gap and maybe explain the commercial strategy behind your choices which I'm sure makes sense but aren't apparent to us and certainly not apparent to the stock market. So any insight there would be appreciated. Thanks again.

I'll try to lead in please add in 1 thing to add. I think there's a few things. So first of all, if you remember what Beth had presented before, what we're signing up with our customers. So when we talk about record bookings growth and the backlog that we've generated and the backlog growing, the AI backlog growing in the 80 percentage the cloud backlog growing at 27% on the back of renewals and bookings, that is of a contractual commitment. Most of the AI growth is consumption-based. So if you look at what Cognigy did and all of its expansion, that 3x that Beth mentioned, that's all on top. That's not in what we report. So you've got a growth because -- and the TripAdvisor example is a really good example, and Disney did the same thing [indiscernible] when you were there. But if you take the TripAdvisor example, they started with those first 4 scenarios. That was the first use case, but it wasn't the most value-adding one. It was the one that they needed to get right first. Then they add more and more use cases. And so either they'll do that on a consumption basis, or they will just continue to rebaseline their agreements with a higher commitment.

So first of all, it's exciting because the revenue will come. The second is, well, why is it not with Anthoopic and those examples? In the world of CX, I think you will have heard if you sat here today and you listen to Mia at Citi or Jack with Fabletics or John and the team here with TripAdvisor, CX they have to make sure it works. This isn't just a trial and expand. In the CX space, it has to be operationally resilient. So you take the Citi example of the complaints. They first had to qualify and make sure that the agentic was going to be as accurate as what the human was. That takes time and effort. So there's a lagging effect to that as well. But what we know is once they've implemented, once they've proven the scale, and it expands, the beauty for us is that we're then monetizing the interaction not the agent.

I'm actually most excited about that transition. The economics of a per seat model, all of the advantage ultimately is with the customer. Now we want them to get huge advantage of course. But as the interaction volumes expand, and John mentioned it from Accenture about the bot-to-bot, every time that happens, that's an interaction, that's an experience we're able to then monetize that. So I guess the reason why we're saying we're being -- we're driving our outlook based on the real backlog, the real bookings, the real expansion, but we see so much potential for beyond that because that's what the Cognigy experience has been. Beth, anything...

Very well said. I think maybe just a couple of other things that I would add. I think the acquisition of Cognigy is new. You saw the really strong bookings and the impressive Cognigy contribution to that out of the first quarter, that's not yet in the revenue. And as Scott has highlighted, more and more of our revenue is coming from consumption and the ongoing agentic capabilities that we're adding. Jeff earlier today talked a lot about how easy it is for customers to and add on additional capabilities even more so as we look to the future in AI, yet we are also working with some of the largest enterprises in the world. I would use HMRC as an example. So HMRC is a very recent win for us, really exciting, very large customer, more than $100 million TCV, 8-digit ACV. So really impressive customer when we look on how that will trickle into the revenue, however, you're really looking in the back half of 2027. So it's the technology, yes, the customer can turn it on immediately, but large enterprises like HMRC or Citi you heard from today, they have their own programmatic approaches to how they deploy, what that looks like, and consumption continues to expand post adoption.

Peter, can you wait for the mic?

A brief follow-up is on the slides you presented of the customers resigning with a dip and then a growth with the AI coming in the second year, does that reflect the same dynamic of Cognigy's not really in that little bar on the right-hand side because it's consumption not contractual?

Yes. It's a part of the AI. So that first quarter, they were included because that was the first quarter bookings. The comment I would make about the renewals is -- and it's easy for me to say this, but directionally, I hope everybody probably understands where we're going. When we get them onto the platform, the growth takes care of itself. I need to make sure, we need to make sure that we have our customers on the platform. And by doing so, by sometimes using our commercial leverage, I don't think that's a playbook we will always need to do. We were very targeted, very strategic about it. Most of our customers will naturally go there. I mean we'll obviously, at this event alone, have an incredible number of new leads of existing customers. And so that doesn't require a lot of that commercial leverage. But it's certain places we do, and it was primarily around not about the AI growth. They knew they were going to expend on AI. That was a given. It was more, well, how much do I need to spend on my existing environment? It was really a question, if I wanted a multiyear commitment, what my agent count is going to be in 3 years' time is very different than maybe what the agent count is today. So we basically modeled that and then came to a win-win for both parties.

Okay. We'll take this next question from the webcast. What are the main benefits from a customer's perspective of having Cognigy fully integrated into the platform? And why can't AI native competitors recreate your platform and offer voice?

Hopefully, we've answered that a fair bit. But maybe, Jeff, can I ask you to comment on that one?

Yes, absolutely. I think the first benefit I talked about just in my session here, is a lot of contact centers are spending so much time managing these integrations between systems. We have lots of different systems. They're very fragile in how they connect. Of course, customers adopting our solution, they don't have to do that, right? We -- it's integrated out of the box. I think the second big advantage that we have is because it is one platform, learning loops, the recursive self improvement that I talked about, that's big. That's game-changing capability for our customers, and that is going to compound over time in a very big way. So I think those are 2 big benefits.

I would say one third thing maybe is voice as a channel that we have obviously baked into the platform, and we're proven leaders there. Voice is really, really hard. And you heard [indiscernible] talk about that today as well. Building an operating voice at global scale is tremendously difficult. And it is going to continue to be a critical channel. So I think that's another thing that we bring to the -- in terms of the value proposition with all the digital channels, that's really hard for others to just add, right?

So I think that's to consider.

And if I could just add 1 thing. I mean the rollout of voice, I mean you see voice coming back. I mean, you think of the AI world, think about how you interact with your business applications in your desktop, your business environment, it's going to change. It's going to be voice and it's going to be a voice AI agent that you're going to be interoperate. We're leading the way. Cognigy team, Jeff's team are leading the way, speeches, Techspeech, how does it work now speech technology. So our knowledge in voice more broadly is becoming a real thought leadership in this as well.

Anyone in the room? Right here.

Clarke Wright with D.A. Davidson. One of the initial pieces that you referenced early these data points was around 50% of the overall customer contact center seats are still on on-premise infrastructure. we'll love to understand the AI strategy that these customers have that you're engaging with today versus the on-cloud providers or at least where they're at today, as well.

This is -- I'll probably answer it and please chime in anyone. I'll try to simplify. Every one of those stand-alone AI cases that we solve with Cognigy are either an on-prem CCaaS customer or a cloud CCaaS. But when they're on-prem, they are choosing to do an AI step first before they then do the CCaS rollout. And I think you heard John and others talk about a multistep. Customers are in different parts of their journey. Some have already done a CCaaS move into the cloud. But they've got some other capabilities they haven't done their AI piece, and others are already starting on the AI side first and then moving maybe to the ACD or the contact center. Basically, our strategy now is now that we've got the one platform, we didn't really talk about it, but what Jeff's done is build a modular architecture. All of those boxes he describes is a deployment option. You can switch it on. And so what we're finding with customers who are in that on-prem world know that they want to move, want to benefit. They're taking modular pieces and they'll take some of the -- what we traditionally would have said in CCaas or in workforce management, they're taking pieces there and automation of AI agents, and they're doing that on the first deployment.

So we're seeing really different rollout schemes compared to what they were before. And that's where Aruns' team working with our GSI partners become so important. So it's no longer, I've got it on-prem, I've got a maintenance window, I've got to flip. Yes, but that's not the only driving factor they -- and that's why 100% of our CCaaS deals, our 7-digit deals have AI included because they usually stop there.

Awesome. And just a follow-up on the deployment time lines. Is -- are you seeing those get consolidated as a result of a need to to see an ROI on AI? Or is that -- I mean, the on-prem to cloud was a multiyear transition. So I'm just trying to understand how we should frame this layering on that next step?

I'll let you add to it but let me just maybe start by saying, again, one of the reasons why this architecture is so important is it modular. It is so much harder to do deployments when you've got fragmented solutions within your own stack. That's why we didn't do Cognigy as a bolt-on. It had to be integrated because then you can switch on rather than reimplement because you're not reimplementing different technology. So the benefits of that from a rollout haven't -- we haven't got that because we've only just completed the integration of Cognigy into the core of CXone, but we do expect that to come. But do you want to comment on the...

Yes. I mean, I think it depends on the use case. So if you as a customer who's trying to do a proof of concept or wants to build a single agent for a single simpler use case, a matter of weeks. Somebody who wants to do a really complicated use case, could be a bit longer. But if you're looking at trying to deploy the workforce management solution or the other parts of the portfolio, integrate that into your back-end systems, that obviously becomes a multistep process, if you would, very much like I did in my previous role.

But I guess just remember the question, how do we think about it? AI deployments are faster and they're more agile, and they will become more and more so as time goes on with this integrated platform compared to what you saw in the CCaaS where it was a pretty significant shift in particularly given complexities of voice.

Okay. We'll take this next one from the webcast. Can you talk about the switching cost from a customer's perspective once Cognigy is deployed?

the switching cost to move away from cognitive?

Yes.

Well, I guess the first comment I would make is we haven't seen it. And I don't say that with arrogance and I'd just say that with reality.

100% at the enterprise leve.

100% at the enterprise level. I think I think there's 2 things that I would say about the switching for -- in the AI space. Once you've established the platform, and I think it just reinforces why we're so focused on the platform. Once you've established it, it works. The AI agent is not the hard part, it's the operating intelligence and the plumbing that sits underneath it to make the AI agent great. And so we've been really focused on helping Cognigy get a richer data context, a richer orchestration even with its existing customers benefiting from CXone from NiCE and then for all of our new customers, getting that out of the box.

So I do -- I expect we've not seen any retention risk of those customers. And it's not so much about switching costs. It can move to another AI agent. But if you're going to move to another AI agent who doesn't have that operational context, doesn't have the richness of data, doesn't know how to work with the humans that are in the contact center, doesn't know how to do a combined workforce, why would you? So it's a great product in itself and it stands tall by itself, but now is an integrated suite even stronger.

Can I add something?

Please

So I think the added thing I would say is that if it's a stand-alone agent for a simple use case, which is not connected to your systems of record or your back-end systems, it's a much easier thing to do. But the real value from these agents comes when you actually like the Lufthansa example or the Fabletics, you connect your agent to your back-end systems, and that's where the real ROI comes from to be able to resolve real issues and drive containment and better experiences. Once you start building those integrations, the switching cost becomes much harder.

I've got to say, 12 months ago, what you heard from Fabletics today and going after the moments that matter, that was not the way customers were thinking about AI that we're going for the simple repeatable tasks. Now they're thinking, okay, this can do some really interesting complex things. The Lufthansa example, the Alianz example, there's so many examples where we've got -- and I think that then drives that stickiness that we're expecting from the platform as well. So it gives us confidence that once they're using it in that way, switch out is very unlikely.

Anyone in the room? Let's go right here, please.

I'm [indiscernible] here for [indiscernible] on William Blair. Scott, at the end of the keynote, you had mentioned many customers already have access to AI features, and you encourage them to better utilize them. So I'm curious to hear how prevalent is this underutilization and what NiCE is doing to help support adoption?

Yes. You can probably, by my noting you probably sensing a little bit of my frustration. We have got an incredible installed base that are already using CXone. And because it's got CXone has now got Cognigy native, we've now got this inherent capability that is available that can be switched on. Now yes, if you think about augmentation, so agent augmentation, Copilot, there's still configuration and work to be done, but it is not -- we don't need to go through contracting. We don't need to -- it is simply being able to switch on a service and being able to expand those use cases. And so we're trying to make it simpler both commercially, but also from a deployment point of view and being able to do that more easily. So auto summary, like automated summary is such a simple, easy thing that we can roll out and deploy on voice calls, on digital chats and on AI agents that we're able to roll out. So it's now -- it's been more a case of us showcasing and unlocking that in making that visible rather than any resistance from the customer.

There's no resistance from that side. But we also need to remember that we don't want them to be thinking about another tool to do chat. And another tool to do summaries, we've already got it out of the box. So that's the reason why I highlighted it. And we're very excited about the land and expand opportunity that, that brings.

I've got to say again, what Jeff and the team have done for us allows that to be a switch on rather than a deployment. It's such a critical task that maybe I didn't represent as well as we could have when we talked at Capital Markets Day. This isn't just about the integration of an acquisition into our tech stack. It is about the underlying foundation that allows us to create that value model for our customers, but also for us. So it's a really important work that we've been doing over the last 6 to 9 months.

Can I just add a little bit of a customer kind of view as well, and, Arun, feel free to jump in here. I think one of the things you probably heard in the keynote is how customers have highlighted that our approach in working with our customers is really understanding their pain points. It's not about trying to push our solution on to them. It's really trying to understand what we can do to help them on the ground deliver their best customer experience to their own end customers. And I think that last night, I had dinner with a few customers as well, several of us did. And I was really excited to hear how they talked about how we are collaborative. We don't just go in and sell. We're collaborative. We continue to maintain that relationship. And I think that's also what blossoms the ongoing relationship and adoption post deployment.

I mean I lived it for 4 years, so I know.

Did I see a hand on this side of the room before? Okay. We'll take this next question from the webcast. Can you talk to your planned usage of forward-deployed pods? Is this a shift in strategy? And is it scalable?

Do you want to come on that?

Yes, I can do that. So it is not a shift in strategy. It's a complement to what we have already been doing. So we basically have enterprise grade deployments, as I spoke about. We have a full deployment life cycle that we discussed. This is an additional tool that we have complemented by the nice labs that we had -- we announced this morning. The intent is to basically how do we quickly deliver value to the customer. So this is a huge complementary solution. It is not a shift in strategy. And what we are doing is we're making sure that the AI COE that we've built, our forward deployed engineers are working synergistically, anything that we learn from the FDEs is fed back into the AI COE to ensure that we're building it into a repeatable framework unlike many of the point, AI solutions were essentially relying on scaling their FDES, which is not an economically sustainable model.

Peter?

So something that just clicked for me listening actually after thinking about this quite a bit, is that this business is transitioning from CCaas, right, enterprise -- a SaaS model to a platform. And platform -- building a platform can be a very, very valuable enterprise, but it involves decisions that might be different than those decisions you make as an enterprise SaaS company. Can you talk -- Scott, you're nodding, and I'd like to ask about your experience at SAP, and Jeff, your insights from Microsoft building platforms. How is that different than building SaaS? And which KPIs -- we should probably look at different things as you think about building a platform and what should those be, customer count, Cognigy sign-ups, what have you? Because you said, look, what's important is to get on the platform revenue growth takes care of itself. The stock market doesn't get that. And so I'm trying to understand, look inside your brand is what you see because you see something different and exciting.

So I'll start. And Jeff, you can comment on the technology side and your background as well. So the platform strategy is so crucial to the way forward. And let me just take a few of the indicators of why we believe that to be so. CCaas was built primarily from a human to enterprise on a one way. It was an inbound and it was a time-bound exercise. So it had limitations about my time and the enterprise's ability to absorb it. That's why you could never see the contact center phone number, they would never look to find it because they were capacity bound. And as human, we didn't want to be sitting on the phone waiting the whole day. So it was built on that construct.

The world going forward is going to be an unlimited interaction model. There is literally no limits because your time and the organization's time are no longer the constraints. Now to deal with that scale, you have to have a platform that handles scale. In my background, you're right, at SAP, we dealt with the most mission-critical environments, and we were very clear when I was there that these business applications that were sitting on top, the orchestration, the data layer, the foundational intelligence was built that everybody leveraged. And that means that when you thought about a customer context or sort of supplier context, you could think of it in all of the different suite of applications. So for us, in the CX space, what does that mean for us? We're not limited to service. It's really important right now. But with proactive, you get to be able to do sales, marketing, outreach. You can do revenue generation, service volume increases, we can switch between AI and human. It's really going to be a design toggle for companies to say, "Look, we've got this really critical moment that we want more humans in the loop and we want them to be interacting because it's a really critical exercise." We're going to turn that up and do less of our AI agents. This is a typical business day we'll do more on the AI side. So it gives you that operational flexibility.

And for me, ultimately, as the CEO of this company, it gives us much higher predictable revenue growth. I don't want to be only worried about the CCaas to on-prem migrations, I'm looking for platform expansion, how the market consumes and we clip the ticket every time and be a valuable addition. So when we think about our revenue model going forward, I'm not thinking about only the bookings and the backlog, I'm thinking about the market expansion and how their platform can be the monetizing angle to it. Jeff, do you want to add anything?

You covered a lot, but, yes, I would just say, if you're fortunate enough to have enough scope to really go after a platform approach, which we obviously do, there's both internal or obviously an external benefits. The external, Scott touched on a lot of them. For customers, it's just start wherever you have the most urgent need, expand from there, and there's just a whole bunch of stuff the platform takes care of, fully integrated, we get some -- like even in the past, there's some form of learning loops, leveraging the data, leveraging the knowledge of that stack, lots of customer benefits there. But one thing we shouldn't overlook is the internal benefits of running a platform play. And especially with NiCE, our heritage again is voice. I can't emphasize enough. Voice is really, really hard, mission-critical, massive scale. And we take all that heritage and now we apply it, we can just make that same investment, but then we get all these returns across all these other workloads. And by the way, they become industrial strength, mission-critical because that's just what we do. And all of it is sitting on that same platform.

So I love where we have come from, from that voice heritage and everything we're doing now sits on that. And so we get tremendous leverage from the engineering, the operations across that entire portfolio. And as Scott said, it's expanding, and so it's gotten great...

And I sure have added 1 last thing it's a conscious decision. When we acquired Cognigy, we could have easily just said, let's add more function and feature in Cognigy, let it run, we could have, but we decided to integrate it because the return is not necessarily today, it's what we are able to get into the future. It was the opportunity that we felt differentiated us and gave us a winning advantage. So that was the other thing about conscious.

And if I could just add we did talk about this. We weren't going to -- if I could just add 1 thing, we didn't talk about it today. We believe that, in the future, the volume coming into contact centers is going to increase exponentially. We're all going to have AI agents going out. We're not going to call up 1800, whatever it is, we're just going to tell our agent go handle this, go find this product, go return go figure it out for me. And if some event happens globally, guess what, millions and millions of AI agents are going to go pound on these brand websites and all these engagement, whether it's voice or digital and all that. And so that platform approach for customers coming on, whether it's Cognigy, anywhere on CXone, they're going to be ready for that, especially as they get that front door in place and all that mission-critical platform is going to support that.

So I think that's really important. And I think customers are just starting to think about it. But getting that digital front door in place with someone like NiCE who can handle just incredible mission-critical volume is going to be important in the next generation that we're heading into any day. I don't know if it's 6 months, 9 months, but those personal agents are coming and when they're good enough, it's going to happen really quickly.

We have time for 1 more question. There.

I'm Kincaid from Citizens. I work in your Pat Walravens. I'm really, really excited by this idea of recruitingly self-improving your guys' systems and using your data from a human to improve the agents. This is something I'm a data scientist, my bachelor is in it. So I really, really like this. My concern is that that's something that I've seen the big labs targeting as well. This seems to be their strategy of how they want to continue to improve their systems. How do you retain engineering talent when you're targeting the same type of problem that they are and they have such a large gravitational force behind them?

So I guess there's a couple of things. First of all, specialization matters. They might be doing that at a general level, but there's a reason why there's a whole lot of AI companies in the CX space that are dedicated because those companies, when you get to the granular needs of what happens inside of a customer interaction and the complexity and the knowledge framework and the security and all of those other things and the operational systems, it takes penetration. It's why, for example, I've made the decision that we don't go into HR flows. Our platform, Cognigy could easily do help desks and -- can you easily do that, the core platform, but once you get into the specifics, it becomes a lot more granular. So first and foremost, we're targeting -- the depth of the problem we're targeting is different and it's unique and it's focused.

Having said that, capturing engineering talent, I think capturing talent is matched to the story and the vision that you're driving. So we have engineers who love the world of customer experience. They love the idea of creating a platform that makes your life better. I had this analogy. My first job was a paperboy, and I loved it because every morning, I got up and through papers and somebody had a great day if it was on the front doorstep. In the world of customer experience, our engineers, and I'm telling you, they love this. They love the fact that their technology has made millions of people's day better. So I think when you're capturing because you can be an engineering, you can do all sorts of interesting things. We try to connect it to our vision. We are always in the war for talent. I would not lie to say that we're not always looking for the retention and the expansion, but that's where great engineering leaders like Jeff makes such a difference because you want to work on interesting things. You want to be able to build our products. And I've got to tell you where we are as pervasive a user of the AI technology, the front-end models, as any software company on the planet, and we're getting the benefits...

And Cognigy, our entire IT help us actually does run on Cognigy just internal internally. The fact that it can run, but we chose not to put it externally out there.

We've not been challenged on the war for talent. But I also think we've been looking for scale. So we're not -- the opportunity with all the AI tools has allowed us to get expansion and efficiency and innovation without necessarily continuing to add a lot more people and our operating margins reflect that as well.

Very good. Well, look, I -- first of all, for those of you who are in the room, I hope you found it interesting. Hopefully, we've been able to unlock a little bit for you about why we're so excited about the opportunity where we're at on that journey but also the validation from the customers. For those of you who can, we're going to join you in the show floor. For those who have joined us online, thank you for joining and listening in. We're in a great place. We're in a great market. I think you've heard from both myself, but our customers and analysts, the amount of investment coming into this space is incredible and we're the leading player. So we're looking forward to capitalizing on it and making sure we deliver durable shareholder returns and great value for our investors. Thank you so much. Appreciate it.

Welcome to the NiCE conference call discussing first quarter 2026 results, and thank you all for holding. [Operator Instructions] As a reminder, this conference is being recorded May 6, 2026. I would now like to turn this call over to Mr. Ryan Gilligan, Vice President of Investor Relations at NiCE. Please go ahead.

Thank you, operator. With me on today's call are Scott Russell, Chief Executive Officer; and Beth Gaspich, Chief Financial Officer. Before we start, I would like to point out that some of the statements made on this call will constitute forward-looking statements. In accordance with the safe harbor provisions of the Private Securities Litigation Reform Act of 1995, please be advised that the company's actual results could differ materially from these forward-looking statements.

Additional information regarding the factors that could cause actual results or performance of the company to differ materially is contained in the section entitled Risk Factors in Item 3 of the company's 2025 annual report on Form 20-F as filed with the Securities and Exchange Commission on February 26, 2026. During today's call, we will present a more detailed discussion of first quarter 2026 results and the company's guidance for the second quarter and full year 2026. You can find our press release as well as PDFs of our financial results on NiCE's Investor Relations website.

Following our comments, there will be an opportunity for questions. Let me remind you that unless otherwise noted on this call, we will be commenting on our adjusted results of operations, which differ in certain respects from generally accepted accounting principles as reflected mainly in accounting for share-based compensation, amortization of acquired intangible assets, acquisition-related expenses, gains on intercompany foreign currency transactions, amortization of deferred financing costs, amortization of discount on debt, the tax effect of the non-GAAP adjustments and the tax rate impact resulting from the non-U.S. intercompany transaction.

The differences between the non-GAAP adjusted results and the equivalent GAAP figures are detailed in today's press release. The information and some of our comments discussed on this call may contain forward-looking statements that are subject to risks, uncertainties and assumptions. I will now turn the call over to Scott.

Thank you, Ryan, and good morning, everyone. What an exciting and dynamic market that we're operating in. Our team is moving with speed and purpose to seize the CX AI opportunity, and that is evident in our Q1 results. We are taking bold and decisive actions to create durable long-term growth in the CX AI market.

In Q1, we delivered total revenue of $769 million and non-GAAP EPS of $2.64, both above the high end of our guidance ranges and cloud revenue growth of 14.6% year-over-year. As the only player in the CX market with a full -- fully AI-native platform that operates seamlessly across digital, voice and AI at enterprise scale, we are delivering real transformative outcomes for our customers. And you can see that clearly in our Q1 performance.

We delivered a record first quarter for new cloud ACV bookings, both including and excluding Cognigy, reflecting growing demand across our platform and driving accelerated cloud backlog growth of 27%, including Cognigy; and 24%, excluding it. In AI, we are seeing continued strong adoption and monetization with AI ARR increasing 66% year-over-year and now representing 14% of cloud revenue. And once again, 100% of our CXone enterprise deals included our AI solutions.

We're also seeing this reflected across our customer base. As customers renew and expand on our platform, they are increasingly leaning into our AI capabilities to drive measurable outcomes and deliver immediate customer savings. This is contributing to a strong AI bookings with AI backlog growth of 78% year-over-year and AI pipeline growth that is accelerating even faster.

International was another area of strength with revenue growth of 30% as we continue to win and scale large enterprise deployments across our international markets. And that momentum is also evident in our partner ecosystem with our GSI partners helping us secure multiple large multimillion-dollar ACV deals in Q1.

Let me now turn to how we are creating value with our AI solutions. As basic automation becomes increasingly commoditized, enterprises are prioritizing platforms that can orchestrate end-to-end customer journeys and deliver consistent, high-quality customer experiences. Early adopters of NiCE Cognigy's Agentic AI solutions are reporting approximately 20% improvements in CSAT, over 80% containment rates for Tier 1 inquiries and double-digit reductions in cost per contact.

One example of the tangible value we are creating is with Openreach, the largest wholesale broadband network in the U.K. Openreach deployed proactive AI agents from NiCE Cognigy to redesign customer engagement across 15 million customer journeys. Following deployment, our proactive AI agents helped drive a 1/3 reduction in missed appointments and inbound contact volume. This also drove a significant improvement in customer experience with Openreach's Trustpilot rating rising from a score of 2 out of 5 to 4.7 based on hundreds of thousands of customer reviews. Ultimately, our deployment delivered tens of millions of pounds in revenue and operating expense benefits to Openreach.

Lufthansa is another great example. Flight disruptions driven by labor strikes drove a surge in customer interactions. Over a 7-day period, NiCE Cognigy handled nearly 2 million interactions, completed rebookings and refunds end-end, providing food and train vouchers, hotel accommodation information and more while significantly reducing contact center workload. This translated into hundreds of thousands of euros in direct cost savings, along with over 1,000 additional hours of avoided manual handling at a critical moment for Lufthansa. This is not a pilot, and it isn't a proof of concept. This is production-grade, Agentic AI, delivering outcomes at a scale no other player in this market can match.

Eight months after closing the Cognigy acquisition, integration is ahead of schedule. And importantly, we have moved beyond foundational work into real platform execution. Cognigy is now tightly integrated into CXone, allowing us to sell, deploy and scale Cognigy as part of a unified CXone platform offering. This progress is showing up in how our platform operates. NiCE Cognigy AI agents are now powering both proactive engagement and real-time agent assistance, extending across outbound outreach, copilot and end-to-end workflow automation. What that means for our customers is simple, a unified AI layer that can orchestrate interactions and workflows across the customer journey at enterprise scale.

Importantly, the progress we're making on integration is already accelerating innovation and nowhere is more evident than in automated Insights, a capability made possible by bringing NiCE Cognigy together with CXone. Automated Insights analyzes structured and unstructured data across our voice, digital, self-service and workflows to identify where AI can drive greatest business impact. It quantifies the ROI upfront and automatically generates production-ready NiCE Cognigy AI agents within the same platform. Our closed-loop approach from discovery to deployment to optimization is already resonating with customers, and our solution was recognized as the best innovation for customer experience at Enterprise Connect.

And that's just one example. This quarter, we introduced a set of capabilities that further differentiate us in the market, including advanced testing to optimize AI performance before deployment; expanded multimodal and proactive engagement across voice, digital and human interactions; and deeper MCP integration that allows our platform to operate seamlessly within broader enterprise AI environments. These capabilities and more are why NiCE Cognigy is consistently ranked as a market leader by industry analysts.

Last month, Forrester named NiCE Cognigy as a leader in the Forrester Wave for conversational AI platforms for customer service, 1 of only 3 vendors to earn that designation and with the highest combined score across current offerings and strategy of all vendors evaluated and the only vendor to stand out on customer feedback relative to peers. In a market where there is no shortage of bold claims about AI leadership, it is worth noting that independent analyst validation tells a more precise story. But the most important validation, as always, comes from our customers, and it's reflected in several key deals during the quarter.

We closed a 7-figure ACV deal with a leading U.S. healthcare services company and a long-time CXone customer. They expanded their CXone deployment to transform customer and partner engagement by adding NiCE Cognigy for Agentic AI automation and Copilot for real-time agent guidance. We won with our connected end-to-end AI platform, bringing together Agentic AI agent assistance and analytics with a clear ROI narrative and a proven ability to scale in highly complex regulated environments.

We also closed a 7-figure ACV win in the U.K.'s leading roadside assistance provider. The customer selected CXone, including Cognigy, as an AI-powered engagement hub, leveraging Agentic AI, Copilot and analytics to enable a universal agent model, automate complex customer journeys and consolidate multiple point solutions into a single platform. Taken together, these wins demonstrate the incremental value created by bringing Cognigy together with CXone, enabling NiCE Cognigy to win larger, more strategic enterprise deals, including in head-to-head evaluation of both traditional vendors and AI point solutions.

Separately, our core CCaaS business -- in our core CCaaS business, we closed a competitive 7-figure ACV enterprise win for CXone with a global leading healthcare and life sciences company as they consolidate vendors and modernize their contact center environment. NiCE was selected to replace a large enterprise CRM-based contact center solution and unify multiple platforms into a single cloud foundation, reflecting the shift towards customer engagement platform as the center of gravity while addressing immediate operational needs and creating a strong platform for future expansion into digital analytics and AI-driven capabilities.

I also want to take a brief moment to talk about how AI is changing how NiCE operates. We are rapidly deploying AI to simplify our tech stack, accelerate product development and drive productivity across our workforce. Within our product and technology organization alone, projects are being completed in a fraction of their original times. In a recent example, we used AI to modernize hundreds of administrative pages to ensure our product meets enterprise accessibility standards, reducing 18 weeks of engineering work to just 6 weeks. This is just one example of the types of gains we are being delivered across our teams, and they are already translating into faster, more efficient ways of building and delivering our platform.

AI is a clear tailwind for NiCE. What's often missed in the discussion around AI is the volume of interactions are rapidly expanding. Today, time is the single biggest constraint limiting how often a consumer engages with a brand. As personal AI removes that friction, engagement will further increase and NiCE sits directly in the flow of those interactions. We are the digital front door. Most enterprise software companies monetize internal users and some monetize only the AI flows. We monetize all consumer interactions with the brand, be it voice, digital or AI, and that digital front door has no ceiling.

As AI adoption evolves, voice will remain a critical channel, which means capturing the CX AI opportunity requires a platform that can seamlessly operate across voice, digital and AI at enterprise scale. And that's exactly what NiCE delivers and something no other provider in the CX market offers today. That advantage is amplified by our large and expanding installed base, which allows us to bring Agentic AI to the thousands of customers already running on CXone and accelerate adoption at scale. We are taking decisive actions now to seize on that opportunity.

What makes our position durable is the combination of scale, data and a deep domain expertise. Specialization matters. With decades of experience and tens of billions of interactions flowing through our platform, we understand customer intent, workflows and outcomes at a level that allows us to deliver production-grade AI agents with the right controls, context and operational reliability already built in. These capabilities are essential for large enterprises where customer experience is mission-critical and requires consistent performance, trusted data handling and alignment with complex operational and regulatory requirements. This is the NiCE moat. And we look forward to bringing it to life for you at our Investor Day at NiCE World on June 9 in Orlando. We hope you'll join us.

Before passing it over to Beth, let me briefly address our broader portfolio. We spend a lot of time talking about our CX business, but it's important to remember, we also have 2 other great businesses in financial crime and compliance and public safety, both of which provide mission-critical solutions and have strong market positions. As I've shared, we regularly review our portfolio to ensure we are maximizing value for our shareholders. We've been working with advisers over the past several months to run a process for our non-CX assets. I want to emphasize that this is an exploration. No decisions have been made, and we continue to see value in these businesses. With that, I'll now turn the call over to Beth.

Thank you, Scott. I'm pleased to report our Q1 results highlighted by strong 10% revenue growth, healthy profitability and growing backlog. Our first quarter execution reflects alignment with our strategy to drive durable long-term growth through disciplined investment. Total revenue for the first quarter was $769 million and exceeded the high end of our guidance range. Foreign exchange contributed approximately 1% to year-over-year growth this quarter. We're pleased with the execution across the business, including our international regions, which continue to demonstrate strong underlying demand as we expand our global footprint.

Starting with revenue by business line. Cloud revenue totaled $603 million, representing 79% of total revenue and demonstrating healthy 14.6% year-over-year growth or approximately 12%, excluding Cognigy. This performance reflects continued strong adoption of CXone and ongoing momentum in AI-driven use cases across both Cognigy and our organic AI portfolio. Within cloud, CX AI and self-service ARR reached $345 million, representing 66% growth year-over-year and now accounting for 14% of cloud revenue. Importantly, AI already represents a larger share of our cloud backlog, approximately 18%, indicating that AI demand and future monetization are running ahead of what is reflected in the current revenue as those commitments convert over time.

Cloud net revenue retention was 107%, reflecting continued expansion within our installed base and remaining healthy overall. We are seeing some near-term pressure on NRR as we continue to transition our portfolio towards AI-driven capabilities, which can result in compression in certain CX components. Importantly, our focus remains on driving durable long-term growth. Our cloud and AI-specific bookings and backlog remain strong and growing, supported by momentum that we're seeing from new logos and expanding AI adoption, and we expect this to translate into improved expansion and NRR over time.

Notably, in Q1, 100% of our CXone enterprise customer deals included our AI solutions. We continue to make steady progress upmarket with average deal sizes increasing double digits year-over-year. This reflects both the scale and enterprise readiness of our platform as well as the breadth of our AI-driven portfolio, which enables broader initial adoption and creates meaningful cross-sell and expansion opportunities over time.

Moving to our premise-based revenues. Services revenue, which represented 16% of total revenue, declined 12% year-over-year, reflecting the ongoing migration of our on-premise installed base to cloud, which naturally reduces the service activity associated with legacy deployments, while product revenue representing the remaining 5% of total revenue increased 23% year-over-year, driven by strength in our financial crime and compliance business. From a geographic perspective, the Americas region, which represented 81% of total revenue, grew 6% year-over-year with healthy CX Cloud growth. Coming off the record Q1 cloud bookings, we see significant cross-sell opportunity ahead to expand AI adoption across our large U.S. customer base where Cognigy penetration remains early.

International was a standout area of performance this quarter with strong growth across both EMEA and APAC. EMEA revenue, representing 13% of total revenue grew 34% year-over-year or 26% on a constant currency basis, while APAC revenue representing 6% of total revenue, grew 23% year-over-year or 19% on a constant currency basis. This performance was driven by continued strength in our cloud business, which is now the majority of revenue in both regions, with international cloud revenue growing over 50% year-over-year on a constant currency basis. This reflects strong adoption of our cloud platform and underpenetrated international markets and reinforces our confidence that international expansion will remain a durable and meaningful growth driver for NiCE.

Turning to our business segments. Customer Engagement revenue was $636 million, representing 83% of total revenue and increased 7% year-over-year, driven by double-digit cloud revenue growth that more than offset reductions in on-premise product and services revenue. Financial crime and compliance revenue totaled $133 million, representing 17% of total revenue and increased 23% year-over-year. Our FCC segment had a standout quarter with premise-based term renewals, demonstrating the long-standing and high retention record with top-tier financial institutions across the globe. This premise business drove strong product revenue alongside continued healthy cloud revenue growth.

Next, on profitability. Gross margin for the quarter was 68.4% as anticipated. This reflects the planned investment impact of what we outlined at our November Capital Markets Day last year as we scale our global cloud infrastructure and support increased AI workloads that are deliberate, time-bound and expected to drive margin expansion in the second half of 2026 and beyond. Operating income was $200 million, resulting in an operating margin of 26%. As planned, targeted operating expense investments stepped up in the quarter with higher R&D and sales and marketing spend to support our growth initiatives across go-to-market and AI innovation.

At NiCE, we have repeatedly demonstrated our ability to drive healthy operating leverage. Today, we are driving healthy ROI from our internal AI deployments, and these efficiencies partly offset the increased investments we made stepping into the year. We expect these AI benefits to continue and build throughout the year. Earnings per share for the first quarter were $2.64, coming in well above the high end of our guidance range, largely driven by better-than-expected operating margin.

Each quarter, we provide a reconciliation from our non-GAAP to our GAAP results. This quarter, I would like to highlight that our non-GAAP results exclude a discrete nonrecurring tax charge. Our non-GAAP effective tax rate remains consistent with our expectations previously shared for 2026 and looking ahead. Cash flow from operations in the first quarter was $179 million, and free cash flow was $149 million. Cash flow generation compared to the first quarter of 2025 was impacted by a timing difference in bonus payments, which were paid in March this year versus early April last year. The remaining differences were related to planned increased investments, including Cognigy. We now expect free cash flow margin to be at the higher end of the 18% to 19% range we provided at Capital Markets Day.

We ended the quarter with $304 million in cash and short-term investments. We remain committed to prudent capital allocation, balancing investment in our growth initiatives with consistent returns to shareholders. Reflecting our confidence in the strength of our business and long-term opportunity, we executed significant share repurchases during Q1, repurchasing a record $253 million of shares, representing 3.5% of our market capitalization. Shares outstanding at the end of March were approximately 58.5 million shares, a decline of 5% year-over-year. We exited the first quarter with $745 million of authorized buyback, and we remain committed to our share repurchases exceeding 50% of our free cash flow this year.

Turning to guidance. For the full year 2026, we are reiterating our total revenue guidance and raising our EPS guidance to reflect higher operating margins. Full year 2026 total revenue guidance is expected to be in a range of $3.170 billion to $3.190 billion, which represents an increase of 8% at the midpoint. We now expect 2026 cloud revenue growth to be in the range of 13% to 15%. Full year diluted -- or fully diluted earnings per share are now expected to be in the range of $10.98 to $11.18.

For the second quarter of 2026, we expect total revenue to be in the range of $761 million to $771 million, representing 5.5% year-over-year growth at the midpoint. We expect second quarter fully diluted earnings per share to be in the range of $2.60 to $2.70. As Scott mentioned, we are seeing strong interest from existing customers in our AI offerings with a clear focus on the outcomes and savings we can deliver. Importantly, ARPU remains stable. Average revenue per customer continues to increase and our bookings, backlog and pipeline remains strong.

In Q1, we proactively worked with a small number of existing marquee customers by taking renewal-specific commercial actions to accelerate AI expansion and secure long-term commitments. Those decisions create some phasing effects in how revenue is recognized with a more pronounced impact expected in Q2. As a result, we expect Q2 cloud revenue growth to be slightly below our full year range, followed by an increase in Q3. We now expect operating margins for the full year 2026 to be at the higher end of the 25% to 26% margin range. Based on our forward indicators, we remain confident in our midterm guidance we shared at Capital Markets Day.

With an increasing global presence and expanding penetration of Agentic AI to our extensive large enterprise customer base, we remain excited for the year ahead. Together with our NiCE Cognigy offering, our seamless CXone customer experience platform is unparalleled. We expect to continue to drive healthy top line growth with intentional investment while remaining disciplined in how we manage the business, which is evident in our healthy free cash flow generation, industry-leading stock-based compensation expense ratio and our strong share repurchase activity. Our ongoing review of our portfolio is another example of that discipline. This combination of growth investment and financial discipline positions NiCE for sustained long-term value creation.

With that, I'll turn the call back to the operator for questions. Operator?

[Operator Instructions]

Your first question comes from the line of Patrick Walravens with Citizens.

Congratulations on the quarter. This is Kincaid, on for Pat. I saw earlier this week that Sierra raised $950 million for their AI agents. I was curious, what does that mean for NiCE?

I'll answer that. Great question. So I guess it does a couple of things. First of all, it validates that we are in an incredible market. If you think about the world of AI, there is no better example of how AI can create durable value for customers than in the CX market. The use cases, what I talked about with Openreach and Lufthansa, what -- wins that we talked about in the quarter and our customer base, we see what I suspect our point solution competitors do, which is that there is an incredible demand opportunity that will deliver durable value for customers and companies on the AI side.

But here's the thing that I think maybe that people are not putting enough emphasis on. Creating automated agents for simple flows, it is easy, simple to do. And frankly, that's not what enterprises need at scale. The volume of interactions that are happening that are being managed by AI is actually still relatively low. It's still single digit. But as those interactions deal with more complex scenario, more complex needs that require the security, the observability, the guardrails, the ability to be able to interoperate with other ways of interacting with their customers, that's where an enterprise platform that handles all of the engagement rather than just the AI becomes critical.

And so what we see is large companies are clearly looking at AI to drive benefits, but they're wanting a platform that gives them the end-to-end solution rather than the AI only. But we've pivoted hard as the AI leader. We've got validation from analysts. We've got validation from customers. And I guess the best validation is that our pipeline, our backlog, our bookings are growing at record levels in the AI space. So we're winning and we will be the CX AI winner.

Your next question comes from the line of Siti Panigrahi with Mizuho.

Nice start to the quarter. Basically, Q1 revenue top and bottom line was pretty strong. A question we're getting on your Q2 revenue guidance and also your cloud revenue now widened to 13% to 15% from 14.5% to 15%. Beth, you talked about some of the renewal action by customer. But could you drill into the other factors or even drill into that, what drove this kind of guidance, Q2 step down to 5% from 9% plus?

Yes. So maybe let me start with that, Beth, and then you can add some context to it, if you don't mind. I fully understand. As I mentioned, we are in this dynamic market. Our business decision-making is always about durable long-term growth in the CX AI market is the CX AI winner. So the variability in the cloud growth is very much a function of decisive commercial actions to drive future AI growth.

Maybe let me add on to this, give a bit of context. We always talk about the AI market, but what NiCE has is an asset that our AI point competitors do not have, a significant installed base of customers that we've got a long-term relationship with. And so what we're seeing, particularly with large marquee customers that have got upcoming renewal events with us is that these customers are moving quickly to adopt AI, but they're also very focused on the outcomes and the savings that can be achieved. These customers are leaning in with us on AI. They're saying, "Hey, you're our partner. We want to expand with you on AI."

But in that context, we're making deliberate commercial decisions to lock in that AI business rather than let it go to a broader market evaluation. This gives us a number of benefits. It shortens the AI sales cycle. It leads to more AI revenues on a faster time line, and it obviously has shown up in our backlog that we've reflected. But what it also then highlights is some near-term variability on existing products and timing differences between the AI bookings that convert to revenue. But our view on this is this is the right trade. We are managing the business for long-term growth.

Maybe if I can, and I'm sorry to give a long-winded answer, but it's important. Let me give you an example to bring this to life. There was a customer that came to us that had a large financial services customer, where we secured a broader commitment to deploy Cognigy for automation. We added an additional year on the total term and to get the deal done faster, we provided attractive pricing on some of our existing CX products. The AI deployment will begin contributing to revenue later on in the year and more significantly in 2027, but the discount is felt right away.

So as a result, there's a near-term impact on ARR, but a clear visibility to growth above the pre-renewal ARR as the AI bookings convert to revenue. And as Beth indicated, this creates a phasing impact. So I guess you can see that our strategy is working in the indicators we shared, backlog up by -- AI backlog up by 78%, pipeline growing even faster, cloud backlog growing at record levels, record bookings levels. It's because we're taking these decisive actions to win in the AI market that drives and the expansion opportunity once we're in there as the AI platform are tremendous. Beth, do you want to just add anything in this context?

Yes, I think you've covered it quite well, Scott. I think the only thing that I would add on to that is that it's a dynamic market. And when we provided our expected cloud revenue growth at the start of this year, last quarter, we didn't contemplate this action that we ultimately took. I think that when we got into the quarter, we said this is an option for us to really lock in these long-term durable commitments that are going to be with us to drive that accelerated AI growth for years ahead. And so that was important. These were extremely important large marquee customers. And so it was something that we proactively stepped into. So that's the only other thing that I would add beyond what Scott has already shared. Thank you.

Okay. And as a follow-up, I think Cognigy, you talked about integration is ahead of the plan. And this quarter also seems like that it was 240 bps growth. What kind of trends are you seeing in Cognigy customer base? And do you still expect that 200 bps contribution from Cognigy for this year?

Yes. Thank you for the question. It's a great one. And the answer is yes. We do expect to see that 200 bps plus as a contribution to the cloud revenue growth this year. We're really excited about Cognigy. I think Scott talked earlier about how it's -- we're moving very rapidly in terms of the integration into the CXone platform. The pipeline is tremendous and growing. I think if you look across the globe, we have such an opportunity to continue to cross-sell Cognigy into our expansive installed base at NiCE across the globe. We're very excited. Our teams are very excited.

And again, it goes back to what Scott and I both have been talking about, we're here for the long run. We're focused on that long-term growth, and Cognigy is really the -- one of the highest key drivers of that growth looking forward.

Your next question comes from the line of Samad Samana with Jefferies.

Maybe first, Beth, I want to keep pulling the string on the contracts with the large customers and maybe the effect of that. I guess, how should we think about the deflationary effect there? And I guess, as you think forward in the updated guidance, was that largely a reduction as a result of additional contracts that will come up for renewal that will be potentially deflationary? I mean just help us understand, right, because part of the context and the e-mails that we're getting from investors is thinking through the guidance given last fall and then this being a new outcome? Or was this already previously contemplated? And then I have a follow-up question.

Yes. Thanks, Samad, for the question. As I highlighted to Citi, I said, no, this wasn't contemplated. Obviously, we went into the year and felt really excited, and we remain that excited. We had a great backlog growth. We saw the pipeline, the bookings. Following that, in Q1, we've had record bookings. I think what has changed is that action was not contemplated at the time we shared our earnings or our expectations last quarter.

So as we stepped into this quarter, as we've said, there are a few customers that we felt were really critical to driving that AI growth and commitment. That's part of the health of our business at NiCE and part of our core strength is the strength of our recurring revenue and those long-term durable commitments. And so that was really the focus.

Yes. Maybe if I can just add to it before any follow-up, Samad, because it's obviously a good question. I would -- I want to be really -- I guess, clear about our thoughtfulness on this. We're playing offense. We're not trying to defend current contracts and current renewals. We're playing offense. We're in the AI market for CX. Companies are making AI decisions now. They are making them right now.

And when they're making those decisions, they're not only considering what's the best AI platform, but it's very clear that they're trying to figure out, "Well, how do I get bankable savings as I'm making long-term commitments." We are in a prime position. So we seize the moment, which is really clear and obvious to us now that these companies are renewing big commitments with us. They rely on us for mission-critical platform, but they're also now making long-term commitments on AI that will scale and grow that has -- that is durable.

And so whilst it has -- it's allowed for a wider range on our full year cloud outlook because of some of the timing effects of the savings given versus when the AI revenue comes, it doesn't change our long term. Our cloud guidance is not -- there's no reduction. In fact, we see it as an acceleration there. So from an outlook -- on a mid-range outlook, we feel really confident that these pivots give us the advantage to be able to further accelerate AI.

And I just would highlight again, it's something that we have that no AI competition can compete with. Big companies, big agreements that are going to scale with us, we're seizing the advantages and the assets we have. And so the anticipation is we're going to be really thoughtful and focused on this to be able to make sure we get great outcomes.

The last benefit for what it's worth, it's actually accelerating sales cycles. So our deal cycles are getting faster because let's face it, we're bringing forward deals that may have gone into a competitive evaluation later on in the year, and we're bringing them forward. We always knew there was an opportunity there. So it's really thoughtful, really focused, and that's the reason for the variance and the broadening of the range.

Understood. And then maybe just as a follow-up, I know that you all mentioned the investments and what we saw in the quarter. But just can you dig a little deeper in, is the sales hiring and the acceleration there? Is headcount where you expect it to be at this point in the year? And based on sales cycles accelerating and maybe the success that you're having, is that the right level? Or how should we think about maybe any changes to what the shape of that accelerated investment will look like going forward?

Yes. I guess there's a couple of things. I'll let you just talk about on the financial side a bit, but let me just give you a color on what we're actually seeing. So there's a couple of things. First of all, we've definitely been active in acquiring talent and bringing sales expertise into the organization that have got the AI knowledge and the skills, but it's obviously complementary. What we're also doing is putting an enormous effort on the enablement of our existing sales force that have got great CX domain knowledge with the AI capabilities. And now with the integrated platform, we're in a really good place.

So I think from my point of view, this is more about productivity and driving expansion rather than necessarily more headcount. I think you'll find that from a sales coverage, we're in a really good place. And that obviously then is reflected in our outlook from an operating margin point of view. We're managing it really well. But Beth, did you want to add?

Yes, sure. I would just talk about -- if you think about kind of the quarterly trend that we expect for sales and marketing during the course of this year, the E/R ratio for Q1 is a little bit higher than what you should anticipate for the rest of the year. And that's really representative of a lot of the go-to-market kickoff activities we have and really the focus around kicking off the year strong, which has really driven those record bookings that we talked about. So you will see that Q1 is a bit higher, and you'll see that on an overall basis, the sales and marketing trend for the year will be a bit lower than what you had in Q1. So you'll see that playing out during the course of this year.

Your next question comes from the line of Arjun Bhatia with William Blair & Company.

Perfect. Scott, I wanted to go back to the comment you made on financial crimes and public safety. I understand it's completely sort of exploratory at this point. But what are you sort of looking for in this initial assessment? And if you were to sort of maybe go down the path of divesting these businesses, is this just operational focus and sort of maybe retrenchment on CX? Or how do you think about the decision maybe ahead of you for those businesses?

Yes. Look, thanks for the question. Look, I've obviously said as much as I think we can share at this time. As I mentioned, we're in an exploratory process, and we have been for several months. But I want to be really clear, we are focused on long-term durable growth and maximizing shareholder value. And so that guides our thoughtfulness on the portfolio, our decision-making about how we undertake that. And that's why we've got an exploratory process.

Okay. Fair enough. And then on going back to the sort of the AI contracting dynamics, is it fair to sort of describe this as you're sort of trading maybe near term, I don't want to say legacy, but traditional CX revenue for future AI revenue. And like I'm just curious how you see these customer ramps on AI playing out? Like are these multiyear commitments? And I know we've touched on this a little bit, but would love some more color there.

Yes. No, it's a great question. And I think you've actually described it really well. We are making a short-term trade-off for a long-term success. What was really obvious to us, and it probably -- the market is moving so quickly. So companies are moving so fast in their own evaluations of their AI projects and where do they put those resources and their spend and how do they do that.

And so when they're making their renewal decisions and when they came to us, we always were aware that we were looking to be able to expand. We had sales cycles already in place. What was clear though is that we were able to see long-term expanded outcome where we were able to get long-term agreements where we were the embedded AI platform. But as a part of that, we were then trading off a little bit on some of their existing products. For example, call recording, which they still use, but that might be just -- we might discount it a little bit further because we're able to then provide some immediate savings, but the benefit is we get a lock in AI.

And when you're talking about large marquee companies, the upside for us as AI expands, as interaction volume expands, as automation expands, if we're the underlying platform in a noncompetitive scenario, you can clearly see how exciting we feel about that. So the way I look at it is, "Okay, we've built incredible backlog already as a result of taking these decisive actions," But the upside on top of the backlog, the backlog is what they can see about, what they're going to roll out with AI. It's not the best case scenario. We continue to build upon that, and that's the beauty as interaction volumes on AI expand, then the revenue opportunity for us does so as well. So I think you've described it very well, and it was thoughtful. It was decisive, and we will leverage that muscle really strongly as the year progresses.

Your next question comes from the line of Rishi Jaluria with RBC.

Nice to see the momentum with AI. Maybe I want to start on that thread. So it sounds like you're seeing continued strength in underlying bookings with AI as being part of it. And Scott, you talked a little bit about the beginning that it's kind of a baseline and there's potentially upside from there. Can you maybe walk us through kind of the puts and takes of AI going into backlog. Backlog -- what does that time line from backlog to translate into revenue look like? And maybe more importantly, as the mix shift goes maybe from kind of traditional seat-based to more consumptive, understanding you've always had some level of consumption in the model to begin with, what does that do to your overall visibility as you kind of think out 4 quarters?

And then what kind of tools in your arsenal do you have to help your customers maintain some level of predictability, so they're not kind of waking up and facing some level of sticker shock as we're seeing with a lot of AI solutions in the valley today where people end up with a bill that is meaningfully higher than what they thought because of token usage. Maybe help us understand all those pieces, and then I've got a quick follow-up.

Thanks for the question, Rishi. That was quite a long one. So I'll do my best, and then you'll have to let me know if I didn't cover everything. I think -- let's start with the AI backlog. We've highlighted that as a percent of the backlog, it's growing, and it's part of our key driver with the AI being attached to everything we do.

When we think about the time line that it takes to AI from AI and once the contract is signed until it actually goes into our revenue recognition, from a product standpoint, our product is ready to go. We can turn it over to our customers. We've seen with Cognigy and NiCE Cognigy, Agentic AI, they can deliver this very easily to the customers and put it into the revenue stream.

When we look at customers, of course, we all live in a world of reality as well. So despite the solution being available to immediately turn up, in practice, customers often want to really work with us and look for our services and our expertise to understand how they'll get the best ROI. So you do have an impact from that as well. I think what's important, and I've highlighted it in the past as well, is that when you think about the AI backlog, typically, when a customer goes live, what you'll see is that the commitment that they have signed up for and similar to these long-term commitments that we've just talked about with the Q1 marquee customers, that commitment is what will initially start going into the revenue stream.

And then as the customers continue to adopt and have further consumption, then that consumption or usage is on top of their commitments. Many of our customers and even more so with the recent acquisition of Cognigy AI are in their very initial stages of adoption. And that, again, is another reason why we are factoring and focused on the long-term durable growth. We're in the early stages of really driving this AI expansion.

Yes. Maybe I'll just add a couple of comments that is the deployment, what actually happens to customers. The rollout of agents is simple. Cognigy at a click of a button will generate production-ready AI agents. That's not the difficulty.

What happens, though, is that the customers before they're prepared to deploy, they need to make sure the data is corrected. It's appropriate guardrails. They test the security. Is the observability correct? Does it have the auditability? Things that are a part of our platform, which I will highlight our AI point solution competitors may not fare so well in all of these inherent capabilities that we do, but they are really important because you can't have errors when you're dealing with customer service. You can't respond to the customer in an incorrect way. It's got to be -- the quality levels have got to be high. So that's where there's an amount of work on the initial deployment, which obviously has a period of time before that turns to revenue.

I want to then add though, most customers have very targeted use cases that they're signing up to that is a part of our AI backlog. But the expansion opportunity is tremendous because you'll start with simple automation cases and then you'll start doing on more customer flows. And then you'll add in automated outcomes. And then you'll add in Copilot to help your human workforce. And then you'll add in proactive AI so you can do outreach to your customers. And so what we see is a baseline, and we're already doing outcome-based pricing with certain customers because we are very flexible in our pricing models to be able to deliver the ROI.

And the beauty is we have got a quantified ROI model based on our data. We know what the benefits will be. We've proven it. And that allows us to go in with high confidence about the benefits case that customers are looking for. Because to your point, if they're going to spend more in this area, they want to be able to have the corresponding benefits. And so quantification of that becomes really critical, and that's what we step up to.

Got it. That's very helpful and very thorough. Maybe just a quick follow-up. As we think about some of the headline success we see from some companies in and around the ecosystem, I know we've had conversations around partnering with the ecosystem and implementation providers. But maybe can you help us understand, is there an opportunity for greater technology partnerships or at least integration? Because ultimately, whichever way the customer kind of chooses should be able to meet them where they are. Maybe can you help us understand, is that something that can maybe open up a few more doors rather than being kind of an all-in, all-out type of situation?

Yes, it's a great point. And the answer is yes. So our technology team led by Jeff Comstock have been really proactive in expanding our technology partnerships. We announced a further expansion of what we're doing with ServiceNow. We've got obviously working with all of the AI players around how we develop and embed their models. And remember, we're all beneficiaries of the LLM, but what really is important for companies like ours is the scaffolding you build around it. So it's production grade ready in customer service, auditability, observability, all of the security and things that don't come with your LLM, but do come with our assets, that's what customers are wanting already in place, and that really plays to our strength.

So that gives us a few opportunities. One, further expanding collaboration and partnerships with the large AI players and with large, let me call it, agentic platforms that are being rolled out in enterprises. And I mentioned that we've rolled out an MCP integration layer already for broader expansion. So that's a good example.

But the other one that I want to just highlight is all of these point AI solutions, guess what? They need our data. They cannot operate successfully without the data that NiCE has. The difference is we've already got the proprietary models, the insights, the value. We've already got that packaged into our agents that they don't. So we're able to give a more comprehensive outcome for our AI solutions rather than just picking up that data and then using it from their case.

So -- but even with that, we partner and are able to collaborate with any of those players as well. So we definitely see ourselves at the center of the system of engagement, the ecosystem that interoperates with it. We operate in an environment where point solutions will be out there. We're very comfortable with that. But when companies want an end-to-end platform, we feel really, really good about our competitive position.

Your next question comes from the line of James Reynolds with Morgan Stanley.

This is Jamie, on for Elizabeth Porter. Great to see another strong quarter of growth internationally. So just would be curious how we should be thinking about the durability of that growth in 2026? And just if there's any sort of macro-related callouts to be aware of?

Great question. It's exciting. I guess I feel really proud of the international team. I mentioned when I joined and took over at the beginning of last year, my background has significant experience in working in all international markets, and I felt it was a really clear opportunity for NiCE to be able to seize upon it. But the reality is the team were already there. They were running fast, and we needed to give them the right support.

So the growth profile, pipeline growth across our international markets is really strong. It's growing even faster than what you've seen in terms of the growth rates. Our bookings performance is at the record levels. I feel really positive about the opportunity to be able to do the combination of enterprise-wide CCaaS transformation combined with AI. It happens every single time with our big marquee prospects in the international markets. And because we're so committed to those markets, those customers have a high confidence that we've got local capability to be able to deliver at scale and serve their needs. So you can rightly expect that our focus on international is a durable growth driver for the company.

And I would just add to that, Scott. I think I highlighted earlier that our international cloud revenue is already growing at 50% year-over-year on a constant currency basis. And we're really continuing to be very excited of the opportunity there. The international arena generally is still underpenetrated. So there's a huge runway of opportunity that we're really attacking, and we're very excited, as Scott highlighted.

Your next question comes from the line of James Fish with Piper Sandler.

It seems like product continues to stabilize and you guys called out really good term renewals. Is it that customers are still wanting to stay on-prem for the longer duration and those conversions aren't going to happen? Or are they just not sure what to do with cloud and AI still? Was there a net pull-in of demand just given concerns around supply chain and kind of getting their back-end hardware with your software? And just for modeling purposes, what was the percentage of revenue from recurring this quarter?

Yes. So James, let me take the question. Let me start by the first part, which is where we see that. First, I'll say that where we don't see that product is CX. CX today is highly cloud-driven. We've kind of made that transition long ago. Where we do see the term renewals coming into play is typically in our financial crime and compliance business, where we have long-standing some of the largest global financial institutions across the globe, obviously. And so a lot of those customers have been with us for many, many years.

When we go into those renewal cycles, sometimes just for the ease of ongoing continuity of the customer, they want to do a term renewal in the near term. But the feedback that we have from our go-to-market teams is consistent that there's a clear intent by all of those financial institutions to shift into our cloud offerings. And so really, it's just a matter of timing. Again, the feedback that we hear is that generally, even as they're doing a renewal, they're talking about how they plan to shift to the cloud in the near-term upcoming renewals. And our recurring is around 90%. So it demonstrates that even in a quarter where you have such strength in the product, it demonstrates both the strength of the overall business as well as just the stickiness and the health of the financial crime and compliance business as well.

Got it. And if I could follow up. Obviously, this point has been kind of belabored a little bit. But is the impact simply a shift more towards interaction-based pricing rather than seat-based pricing? What are you guys seeing with that? Or is it that you guys did offer kind of steeper discounts with larger minimum, longer-term durations? And really, Scott, for you, the crux of my question is, why do you guys feel the need to kind of do this now if you guys have that kind of best AI portfolio with the end-to-end and go into that base early?

Yes. Great question. Maybe let me answer the last part first because it probably is the most important one. It's not about me. It's about taking advantage of a competitive strength. We've got a great installed base, existing commitments with durable long-term relationships. And we're seizing the moment and the opportunity with their move to AI.

Now relationships, as you know, require the opportunity to be able to have a win-win. And what these customers are looking for is, "Well, okay, I'll lean in with you on that long term. We could have made the decision. You know what, we'll hold up and we'll just -- we'll protect our short-term cloud revenue." I'm not interested in that. I'm interested in the long-term durable growth for NiCE that our shareholders, our partners and our customers and our employees will be beneficiaries of. And that means we saw the opportunity to seize the moment, and it's very thoughtful, targeted.

So it's not about need, it's about decisive action that is to our competitive advantage. And frankly, it allows us then to be able not only with these marquee customers able to then implement and deploy in the future, the AI capability, they become the bellwether for all large enterprises of how they're deploying AI in the CX environment at scale with NiCE. So there are other benefits beyond the pure financial side over the long term. It becomes leadership across major industries and major companies. And there was a no-brainer in terms of a trade-off.

Your next question comes from the line of Thomas Blakey with Cantor.

Great. Just a couple of quick ones there over time. But just maybe touch on that process mining. That's what I'm calling it anyway, but this ability to kind of search for efficiencies and create them and -- create some agentic workflows around that and deploy them and what that could do in terms of monetizing these record bookings and backlog, Scott.

And maybe, Beth, if I'm hearing correctly and listening to all the questions here at the end here, you guys have been -- you have the ability and the flexibility to be opportunistic and go after these very large deals that companies are committing a lot of capital and a lot of brand in some cases, to the level of expanding AI to digital CX. If I'm characterizing that, maybe you could just give an affirmative there, but like what does that mean for calendar '27 as we go out? You guys are obviously talking about some pricing actions here, but still solidly talking about margins here in the second half of '26, and that's got to portend for a great '27? So a couple of questions there. Congratulations on the quarter.

Yes. Thanks a lot, Thomas. Listen, I'm going to kind of kick it off, and then I'll hand it back over to Scott. I think one of the things I think was really critical that you touched on is that large enterprise, they want to make that spend happen now. They've allocated budget. It's in the current year. They are really looking to drive the benefits they can get from AI, and we are extremely well positioned and really unparalleled in our capabilities, not just with AI, but the end-to-end platform we have with customer experience.

So it reinforces again our -- all of our comments today and how we are seizing that opportunity. The spend is happening now. We are looking to capitalize on that, and that will drive the durable growth as we step into 2027. We're already demonstrating the muscle we have and our operating leverage through stepping out with the high end of the range on the operating margin in Q1, and we expect that trend to continue. So I think that it's clear that we are seizing that dedicated spend you're seeing across multiple organizations at this time in the market. And Scott, I'll hand it to you now.

Yes. I just would reiterate again, all of the forward indicators that when you think about the future and as you think about the future of our business, our cloud backlog, our cloud bookings, our AI backlog, the pipeline, all of those forward indicators are trending upwards at really high levels. So it gives not only us, but also, I guess, a level of confidence for our shareholders, a level of confidence that the durable growth that we keep talking about, it's real and tangible, and we can see it.

I just want to pick up on your first question about, well, what do we see and what are the value with the AI? Probably the best way to describe it is one of the things that we've talked about quite often is the value of our data and why that data will be such an important asset when you think about winning in the AI world. What we've now done between our data and Cognigy is have a platform, automated insights that is able to use the data in a production context that gives ROI clarity and production-grade AI agents with a click of a button, which means for businesses, if you think about that for a customer, you're not going into some discovery mode to try to figure out, "Oh, what's the benefit that I'm going to get here? What is the outcomes that I'm achieving and how will the AI agents work?"

We've already got a proven use case that we are prepared to stand behind on outcome-based models to be able to give a quantifiable outcome with the best of both: the best data, the most -- the largest data, but also then the AI agent, the agentic capability to be able to deploy it at production-grade standards. So that's a great example of what we're seeing because I think what you'll find in the market is simply deploying a simple agent for simple use cases. Yes, that's easy. Anybody can really do that. When you get to really having production-grade enterprise grade, that's where NiCE steps in, and that's where we shine brightest. And we're excited about how that market will continue to evolve and our capability stands up to it.

Your next question comes from the line of Michael Funk with Bank of America.

I wanted to come back to what was [ anticipated, unanticipated ] in the conversations with customers this quarter and in some of the early renewals that you talked about. So clearly, some shift in power to the buyers. You mentioned that some components under pressure. I think call recording was one that you mentioned. Can you walk through what other components that might be under pressure on these early renewals, percentage of the CX revenue base? And if those conversations were reverse inquiry or if you were surprised by the power shifting to the buyer?

Yes. Again, maybe I'll just -- I have to sort of highlight this again because I understand the question. We took an offensive -- we're in the game of offense here. So it's not so much about, hey, buying power. There's no -- we're not under any pressure in terms of any specific products. Our ARPU is strong. We continue to see strong demand of our cloud products across our portfolio.

What we really did was we took a decisive action with those marquee customers, which was obviously predominantly after when we reported Q4, to be able to then seize the opportunity that is in front of us. And we not only saw it in Q4, but we're projecting that out through the year and making sure that we seize upon this.

I think what you are seeing, though, is that in the conversations we're having with these customers, they want bankable savings. They've got their own business challenges, and they want the value -- the durable value of AI to be delivered. And what we can do is we can trade into that in a positive win-win way where we can say, "All right, we can lean in, provide some discount, provide some value in the short term, but with a long-term commitment with us, not only in AI, but also in our cloud backlog as well that's really strong." So this is very much an affirmative action rather than one where we're trying to respond to any pressure from the customer base.

And sorry, just a question on the percent of CX revenue from components that are at risk in your view. You mentioned call recording. I am sure there may be some others that are lightly used or might be replaced by AI. Can you comment on that?

The answer is a very, very small percentage of our -- and even in the example of call recording, by the way, it's a great product. It's not under pressure. But clearly, it was just an example I gave of a customer that looked at that and said, "Oh, we want to be able to -- we've got a reduced usage or -- because we're going to AI, because we're going to use your copilot, because we're going to use your automated insights, because we're going to use your auto summary capability," that then allows them to be able to get even more value, but slight compression. So a very small portion of our products under pressure that I would categorize in that way.

Yes. And I would just add to that in terms of kind of putting it into financial perspective, I highlighted earlier, when you think about our CX business, most of that business has already long, well migrated to the cloud. So there's very little sort of what I would say, some of those lines that you've talked about, which were more on-premise oriented. So really, that exposure is quite small.

That concludes our question-and-answer session. I will now turn the call back over to Scott Russell for closing remarks.

Yes. Thank you, operator. Look, first of all, thank you, everyone, for the questions today. I just want to reiterate again, we are -- it's exciting. We're in the game of offense. We're in a great market, and we're seizing that opportunity. Our business fundamentals, our financial strength, our forward outlook, the indicators that drive our durable growth are all trending really, really positively and in the right direction. And we will be the winners in the CX AI market, and we're proving it every single week. So I look forward to sharing more details for those who are able to join us on June 9 at NiCE World in Orlando.

Ladies and gentlemen, this concludes today's call. Thank you all for joining. You may now disconnect.

Great. Well, let's get started. Good morning, everyone. Thank you for joining us here at the Morgan Stanley TMT Conference. My name is Jamie Reynolds, and I'm here on behalf of Elizabeth Porter. We're very pleased to have with us here today, NiCE's CEO, Scott Russell.

But before we begin, some important disclosures. For important disclosures, please see the Morgan Stanley research disclosure website at www.morganstanley/researchdisclosures.com (sic) [ www.morganstanley.com/researchdisclosures. ] If you have any questions, please direct them to your Morgan Stanley sales representative. With that, let's get started.

Scott, obviously, great to have you back here at TMT with us. Maybe to start off, investor sentiment on the CCaaS space has been challenged for some time now, despite positive commentary towards the AI opportunity from NiCE, your peers in the space as well as consistent optimism in our conversations with channel partners. Where do you feel like that disconnect lies? And what's the path to closing that chasm?

Yes, there's definitely a disconnect. There's no doubt about that. Well, so first of all, I understand the discussion. I guess investors are underwriting AI as a disruption, we are clearly indicating that it's a tailwind. There's no doubt. Why the disconnect? I think it's partly because there is a lack of understanding of what the future revenue models are compared to what they were in the past and trying to figure that out. So let me try to explain that a little bit in NiCE's terms.

Historically, we're a company that, yes, we have generated our revenue primarily through the number of seats. Those seats were people sitting in the contact center that were receiving interactions from consumers. Our revenue model in the future is interactions, and that interaction volume is growing and growing rapidly. So first of all, the number of seats are not declining, but even when they do, the number of interactions continues to grow.

Just conceptualize it for a second. Right now, we live in a world, the single biggest constraint that a human has when it contacts a brand and the biggest single constraint the brand has when it interacts with a human is time. Time is the biggest inhibitor. Your willingness to contact the company is limited by your availability, your own capacity. And a brand's limitation is purely how many agents it's got, how many calls it can receive or how many interactions and the productivity of the contact center.

If you fast forward the way the world is going to roll out, you're not going to be limited by your time anymore. You wake up in the morning and say, "Hey, personal AI, contact my bank and increase the credit limit by -- because I'm going to go on holidays with my family next month. Hey, personal AI, can you change my seat on my flight, I've got a business trip tomorrow and I want you to change my seat. Hey, personal AI, contact my utility, I noticed there was a line item on the bill that I don't believe is accurate. Hey, personal AI, I ordered some shoes last week, they're the wrong size, can you get them picked up and returned and then get the new ones."

You will no longer be limited by time. But what will happen is the interaction volume between you and your brand will increase. So you're going to have -- and then likewise, for the brand side, their ability to be able to absorb that is not possible in a capacity-constrained contact center. They need the AI platform to be able to then deliver to that.

So I think the fundamental assumptions about the disruption of existing revenue streams, while I understand the high-level thesis in the past, when you think about it in the world of customer experience, volume of interactions, complexity of interactions, speed of interactions and the ability to have interoperable interactions. You will not accept being handed one query by an AI agent and then your call shut off, you want to go to the right human that has the right knowledge, that is at the right time to be able to deliver the right outcome for you. That is what customer experience expects.

And in an AI world, we are just scratching the surface. Most use cases that you will see that we deliver and our competitors deliver in the AI market is pretty simple use cases for the large majority. It's why of the total interaction volume, only 2% to 3% are handled by AI. We've gone for the low-hanging fruit. And that's why the capacity of contact centers hasn't gone down because all it really has done is freed up capacity to do more value-adding activities that otherwise led you sitting on a phone waiting for an hour. Now you're waiting for 45 minutes. Maybe you're waiting for 30 minutes. Ultimately, you'll get to a point that you won't wait anymore then you'll start to see that -- and in between time, the revenue shift is obviously to our advantage.

So look, I'm realistic about it because the way that we are winning in this market has changed materially, and our revenue models have changed materially, but it's a tailwind not a headwind. And our Q4 results and what we showed in our backlog, what we showed in our uplift, in what we have guided on 2026 and beyond, clearly indicates the market moving as a tailwind with AI and not a headwind.

Got it. And so just to follow up a little bit more on that. Where do you think the argument is most flawed today, either in terms of the number of agents that potentially get cut or who ends up benefiting? And why do you believe NiCE is best positioned relative to competitors, whether it be AI-native start-ups or larger hyperscale and application software peers?

Yes. So where I think it's flawed is that if you look at it simplistically on a seat basis, our competitive moat, most SaaS companies monetize internal users of their software in an enterprise workflow. We monetize based on consumers interacting with the brand. We are the digital front door. That digital front door and the ability to monetize that digital front door has no limitation.

So whether it's done by seats, whether it's done by an AI agent, whether it's an intermix of both, higher -- able to win, the more the consumers interact with brands and interoperate with brands and deliver outcomes with brands, then we are able to be -- so our -- we don't have the disruption of seats and the revenue models of seats the way maybe some other SaaS companies have.

And I think the early hypothesis of CX is everybody understood, "Oh, gee, AI could make it easier." Yes, it could, but it's still not going to displace all of the -- because no AI company has said 100% replacement of humans in terms of customer experience. So you still need humans, all the complex stuff that you want and a lot of companies will keep that. So the competitive moat around that.

The differentiation for NiCE is very simple. Up until September 8, when we closed Cognigy, none of the CCaaS players could offer the market a best-in-class AI platform to deliver their AI experience needs. We all, at that time, leveraged third-party solutions that are out there in the market, some of the -- those competitors, those AI natives that are out there, none of them -- and to this day, we are the only ones that now have a best-in-class AI platform with NiCE Cognigy, a best-in-class CCaaS platform with our CXone platform. And as I quickly integrate and build a single unified stack, I am the only company that has the combined platform to do both, which means I can compete and we compete and win really well on a head-to-head basis on an AI-only where we're not involved with that customer, no CCaaS at all.

We are winning in that market because it's growing, and you're seeing all of those AI start-ups in that space. It's why they're all flocking to it because it's a great market. Demand signals are high, buying indications are high. So we win there. But when the company wants to do real complex orchestration between humans and AI, and I use this example because it's real. What contact centers do today, what you probably don't realize, but it's built-in within our core platform is when you contact that agent, not only are we figuring out what you want, "Hey, I want to get my -- I'm disputing this line item of a bill." They're actually judging your tone, your speed of voice, what time of day, how many times you've called before, what is your purchase history, all of that data.

And then what they do right now in the contact center is they hand you to a specific person. The technical integration to hand off from an AI agent to a human, anybody can do that. The logic to be able to route and switch to the right person at the right time, you don't even realize this, the amount of time a supervisor listens to your call with a human agent and then routes you to somebody else, it happens a lot. Why? Because they're worried about the call quality. They're worried about the resolution, a specialized knowledge and skill that is required.

That embedded complexity and knowledge in enterprise CX, we are the best at it. We do that better than anybody. And then I infuse that with the AI world, I've got something that no one else -- the native AI players can't do it. The current CCaaS players can't do it. We have the embedded capability, and we're looking to exploit it. And I guess I would refer again to our bookings, the growth and what we're seeing is a clear proof point that we're winning and being able to gain advantage out of it.

Got it. And so then are you actually seeing these AI-native start-ups show up in enterprise evaluations today? And to what extent is the message that you just outlined really resonating with the enterprise customers?

Yes. I've got to say, when I decided to make the acquisition of Cognigy earlier last year, the speed of the change, I wish I was -- I could lay claim that I was that prophetic. I knew the change was coming, but it was even faster than I had anticipated. I knew we needed that AI capability.

I am not seeing -- so first of all, am I seeing the AI-native players? Yes, I do. They are definitely -- mainly their value proposition is targeted use cases. They'll go into an enterprise, and they'll say, we -- let us build this use case using fully deployed engineers, let us build it, don't have to pay anything, we'll fund it. And then when we prove that use case, that scenario, password reset, customer account creation, certain scenarios that have got a high volume, low complexity, and they come in and they do that. And they're good at it. Cognigy does the same thing.

Are they being used to go and do the majority of enterprise engagement with all of the inherent complexity that a current contact center does? No, they do not. Do they want to? Yes. But that is a journey. It's why only 2% to 3% of the interactions are being handled by AI versus the what we all hope.

And here's the trick that the enterprises are trying to figure out. They're doing these POCs and these pilots with AI companies, including us. Cognigy does a number of pilots with our own customers, but also with our net new customers. We often go in there and say, "We've done this. We've proven it." I'll go to an airline and say, "This is what we did at Lufthansa. Let us do the same thing." But what they're trying to then figure out is, "All right, how -- what's my roadmap of doing this at scale? How is it going to interoperate with my current CCaaS platform? How am I going to make that a consistent experience? So that has not started. It's all been on top. It's an incremental investment. But we're moving into when they're going to make enterprise technology decisions. And that's why the move of Cognigy with NiCE was so important because I've got a single platform that compete on that basis versus single players on either.

The last thing that I would say is I think companies -- customers are no longer willing to just accept that they're going to have to go and build the agents. What are we doing with Cognigy? We're using those 20 billion interaction data and then generating, with a click of the button, AI agents. That's part of the integration. Because I don't believe the advantage is going to be my AI is better than yours. It's democratized. Everyone's got access to it. I can use the same agentic reasoning models as good, if not better than anybody else. It is not a competitive advantage. What is a competitive advantage is your specialized knowledge that you can put into an enterprise context at scale.

So if you're a bank and you've got 100 different interaction types and you've got 0.5 billion of interactions that you do a year, we are able to, out of the box, click of the button, generate the 50 AI agents and how they will interoperate with your human agents, and I will natively have that in a single platform. An AI player can't do that and a CCaaS player can't do that. And I think that's what enterprises will need as they continue to expand in the use of AI in the context of their CX platform.

Okay. And then to put some numbers around the market opportunity. You've articulated a vision where the CX TAM expands from $31 billion in 2025 to $72 billion by 2028 as AI enables expansion into front-office, mid-office and back-office workflows. What gives you the confidence in NiCE's ability to capture these adjacent markets where you haven't historically participated? And to what extent are customers coming to you today to address some of these workflows?

Yes. So the most logical and easy one, and I think everybody understands the opportunity of a reduced number of people in the contact center and the reduction of that labor spend getting reinvested, more than 50% getting reinvested back into your technology stack. That is a big part of the wider TAM.

Most of our customers today, for example, they ask us what's the ROI? Can I reduce my number of seats? So what we've seen is we haven't seen the reduction, but we've modeled the reduction from an ROI and the total addressable revenue spend goes up because any reduction of seats gets invested in more use cases that you deliver on your AI platform.

The second, and I think the more complex battle is in the battle of orchestration. Our view of orchestration and what I mean by orchestration, I'll give you a simple use case with, you're a great customer of Disney. You call up about your streaming and you've got a family subscription and the quality of the service is not very good, and you want to be able to complain about that service and say you want your service canceled or you've got a change. There is a series of tasks and workflows.

The human agent or the AI agent that interacts with you is not allowed to make the decision whether to cancel that. It goes through a workflow in through the organization. They will then maybe introduce a human to -- hey, look, can we understand your concern, madam or sir, how about I offer you something new and unique. And unique to be able to retain that customer. So there's a series of complex workflows that involve different stakeholders inside the enterprise that's not just done at the front office.

Whose agent does that work is the battle yet to be won. My honest view is it is going to be a combination of our AI agents interoperating with other AI agents that are done by either enterprise LLMs or by enterprise SaaS players or by hyperscalers or a mix thereof. We've already got proven use cases. In the Disney scenario, we work really well with Salesforce. They use their platform in terms of the internal workflows, but they use NiCE as the digital front door. I could give you other examples as well. But that is where I think the market will go.

And our belief is when that enterprise workflow of AI agents is to ultimately fulfill a customer requirement, we are the most likely builder of that workflow, and that's where the addressable market continues to expand because right now, we monetize only the human that receives the phone call. All of the tasks that happen in the back office, we've not had any role in. The human who is running on our platform does, but we've had no monetization of it. Now through the creation of AI agents that perform those tasks -- and I think we will go to the mid-complexity and task closed to the front office, but I think there will be an ongoing battle in that space.

And then when we think about the core, you've spoken to only about 40% of enterprise contact centers have made the shift to the cloud. We still have 60% to go. But within that remaining 60%, are these customers getting easier or harder to move? And then is AI accelerating their decision to migrate? And are you seeing incremental competitive displacement as part of that motion?

So two or three things to comment. First of all, the customers that have yet moved, a lot of them are international. It's still in the U.S. as well. It's still the U.S. market. It's certainly a significant market. But a lot of them are international. Many of them are in highly regulated industries that have certain constraints and guardrails around the complexity. So they're not willing to just flip over. They're very thoughtful in their consideration.

What is very clear is every single one of them have in the top 2, often top 3 or top 4 criteria is the AI capability. They are not prepared to move without a knowledge about what the AI role is in their customer experience. That is why 100% of our 7-digit deals have got an AI embedded because they're looking at us and saying, "Well, if I'm going to move to your core CCaaS platform, I want to leverage the core AI capabilities that you offer out of the box." If we didn't have that, candidly, what happened to us previously before we acquired Cognigy is we still would have won and tried to compete on the CCaaS, but somebody else would have won the AI and competed on the AI piece. They're combining it together.

So I don't think it is getting more complex. I actually think it's getting sharper on the ROI expectations. I've got -- and it's not only new. I would highlight this. I am competing for customers that have already made a decision to move to a CCaaS. They haven't yet migrated because it's a multiyear journey. It's complicated, and I'm going in there with my Cognigy platform and saying, how about we pause that. We go in with our AI capability, and then we'll come back on what CCaaS you need left. So I'm trying to use it -- disrupt maybe existing company's ability to be able to do core CCaaS migrations where we haven't been the winner. And I can do that because we've got the core capability now.

Got it. And then as we think about the near-term demand backdrop, I think on the last call, you mentioned customers are becoming more astute about the ROI expectations for AI. Are you seeing any pushback on AI pricing or any elongation of sales cycles as customers try to validate the returns before committing?

I find this remarkable. I guess I've been in and around the enterprise technology space for a long period of time. My experience is enterprise software buyers are very astute. They know what they want. They know the ROI. In the AI world, there's been an enormous amount of pilots and POCs, an enormous amount. Now it's partly because the AI start-ups are coming in and we're offering -- and they're trying to figure out what the ROI actually is.

So 2025 was an interesting year. They clearly saw the benefits around augmentation copilot. So where you've got an AI assistant working with a human agent in a CX scenario, and we were able to prove that. As the year progressed, Cognigy, but also its direct competitors got more and more data about how does that reduce handling time, how does that reduce containment rate, what are the use cases that work, what are the use cases that are more complicated and don't. And they're getting smarter about looking at that -- the sharpness of the ROI and the benefits.

What I find -- so it is definitely -- I think we will move more away from let's pilot, does the technology work. We're beyond that. They know that these platforms work. I do believe, however, what will be interesting is how you're going to commercially put your value prop there. For my company, I do not want to be dependent only on the revenue of seats. So if it's an existing customer, and I know that I can automate savings and that will drive efficiency in their contact center, I will offer it in a single platform. For a noncustomer, I will then be able to offer the AI that -- and I've got proven ability with data that I know that I can reduce Genesys or Five9's or Amazon's seats in their own contact center.

So I think it will move from -- I wouldn't call it outcome-based pricing. Last time I checked enterprises were pretty smart, benefiting for the savings that they're getting from their use of technology themselves. They don't necessarily want to hand that always back to their partners. But I definitely see ROI-based value propositions being the core way of being able to compete and win.

Super helpful. And so then shifting the discussion back to Cognigy, obviously, a very complementary asset. But can you update us on the progress of that integration? What's been done already? And what are some of the major milestones you're tracking towards in 2026?

Yes. Let me start by saying up until us acquiring Cognigy, we were working with Cognigy and every other native AI player in the market, and we had done for a period of time because no AI player can deliver their CX requirements without the contact center data. Let me say that again. No AI player, no AI player can deliver the needs of the use cases without the contact center data. So every one of those players that you talked about before are an existing partner. They need the NiCE data or the other CCaaS vendor data. So we already had a prebuilt integration with Cognigy. It works seamlessly, no problems.

What we have done initially was we have hardened and made more robust the orchestration of the data flows between Cognigy and the CXone platform. We are in the process right now of embedding all of the data that we had in CXone, which is our contact center, natively into Cognigy. So what it will mean is Cognigy, you will be able to not create AI agents, it will generate AI agents based on the data that you've got with all of the guardrails and context that you have.

What we will have by the -- and that will be ready by midyear. By the end of the year, we will be complete orchestrated into a single platform where all of your data layer, your orchestration layer, interoperability between human and AI agents. I'll give you a quick example. We've got contact centers. Some contact centers have 20,000 humans sitting in the contact center. You're then going to have maybe 100 or 200 AI agents. Has anybody trained the contact center humans how to work with the AI agents? How it's going to interoperate? When do they hand off? What's the knowledge they use? All the rules of engagement around that.

We've got a great history around workforce management. How do you manage the workforce of humans in CX? We're now embedding a single platform that manages your AI agents and your human agents into a single stack, so we can -- you can -- when you supervise and manage your combined workforce of AI and human, you can do it in a single platform. That will be complete by the end of the year.

So all of the integration, the main -- the road map is on track, in fact, arguably slightly ahead. So we're tracking very well for our -- for that work to be done, which is critical, by the way, because it is competitively differentiated. No one else can offer it. And we have to do that at speed, which is why I had the targeted investments that I announced at Capital Markets Day that are largely first half, largely first half. So most of those investments you will see in the first half of the year as we get to the second half of the year, we will be -- start to be able to accelerate margin improvement.

Excellent. And so then on the go-to-market side, since you joined, NiCE has made substantial progress towards expanding its partnership ecosystem. I guess how should we think about the timeline for these partnerships to more meaningfully begin contributing to improved growth?

Yes. I think there's two parts of partnerships that I would call out. There is perception and reality. Let me cover the reality first. The reality is most of those partnerships require technical, deep orchestration between our platform and theirs. So with AWS, the orchestration with Bedrock; with Salesforce, our orchestration with the Agentforce platform and prebuilt scenarios; same with ServiceNow and with Snowflake. That work is largely -- we will complete most of that early to mid this year, which means then in terms of combined offering.

But when you're buying in the enterprise segment, they're not buying the product as it is today. They're buying the product that is going to be built out. So from a demand signaling and a go-to-market and an engagement model, we've seen material improvement around the way we're collaborating with each of those parties and with SIs, which I think we were not focused on to the extent that we should have been.

So we're now -- we're already seeing the traction where customers will say, "Well, how are you working, interoperating with AWS or with Salesforce or with other key players?" And we are able to show clear proof, combined messaging from both parties, go-to-market plays around the joint value proposition. Too much gets made of the competitive overlap, and nowhere near enough gets recognized of the competitive synergies that you get. Yes, we will compete for parts of the portfolio. We've been doing that in enterprise software for decades and mature companies know that you can partner and compete at the same time.

Got it. And so then on the Q4 call and earlier in the discussion, you talked about record bookings performance in the fourth quarter. Even excluding Cognigy, you disclosed a significant increase in your cloud backlog, growing 25% year-over-year or 22% excluding Cognigy. Can you just unpack a little bit more of what's driving that strength and acceleration that you saw relative to 3Q?

Yes. So four things, and you could easily note that those four things will be the key go-to-market drivers for 2026. Number one, we were able to win as a stand-alone AI platform where we were not involved or even offered to participate with Cognigy stand-alone. Cognigy is a great product, proven capability, win and compete in a market that has a high demand signal, high profile. So we won in Q4. We've got -- and the pipeline generation is tremendous and being able to capture that.

Number two, we already saw a large number of existing NiCE customers that have said, "We're going to make an AI decision. We trust you, we will work with you and then we will build that out." So we're winning inside of our installed base. I've got to tell you, I am frenetically pursuing that because we've got hometown advantage, and we need to make sure we capitalize on it, especially as NiCE is serving arguably the most complex, largest companies on the planet in their CX needs.

The third is we had an improved win rate of our CCaaS jump balls. You asked the question earlier, Jamie, around how that's working. So when we've been competing with that CCaaS move on-prem, whether it's an Avaya or Cisco or Genesys on-prem, whatever, and they're moving to the cloud, because of our AI capabilities, we've been able to improve our win rates on those jump balls. I expect that to continue through '26 as well. And then last but not least is our international business continues to make great strides. We continue to have more wins, which arguably is in the CCaaS side.

So between those four, that led to significant bookings in Q3, significant bookings in Q4, record in Q4. Our backlog is at record levels. You saw in Q3, our backlog was at 15%. Our backlog in Q4 was at 25%. I think the forward indicators are really strong.

The only other comment I would make is backlog is great, bookings are great. It's amazing when you generate that much demand, you've then got to be able to execute it into live customers to ultimately generate revenue. You could appreciate that I'm putting a lot of emphasis on that because companies -- enterprises don't have patience at the best of times. But in AI, they definitely don't have patience. They want to be able to see the results and roll them out quickly. So it's created a good problem for our business.

Got it. And so then to just follow up on international a little bit more, obviously, a standout year in 2025, growing 16% for the year and accelerating to 29% growth in the fourth quarter. How much of that comes from the sovereign cloud investments you've made over the past year or so? And what does the international pipeline look like as we head into 2026?

Yes. Sovereign cloud, look, I have to credit the prior management. There was a lot of emphasis around building infrastructure, CapEx and OpEx deployments that had -- that didn't have a fast return, I guess you could argue. You could look at more broadly the AI market and what's happening. We sort of did it within our microcosm with our sovereign clouds.

So when you look at the U.K. wins such as the DWP or the Australian wins at the Services Australia, some other wins with key utility providers in Germany and in Europe, wins in Africa, where we have -- with financial, highly regulated customers all of them were on the basis of those sovereign cloud investments, our ability to operate domestically.

And let's face it, geopolitical uncertainty has meant that further localization of your data, your providers, your services in those markets is key. I wouldn't call it -- it's not only because of the sovereign clouds because we've deployed and invested in capability more broadly in the public market as well, not just in sovereign regulated environments, but they are a key prerequisite for us to be able to win, and we're now seizing on the opportunity.

Got it. And so you spoke to this a little bit earlier. But at the Analyst Day, you outlined the $160 million of incremental investments for 2026 across three buckets, cloud and AI delivery, research and development and go-to-market. Now that we're a few months into the year, which of those investments are already in motion? And what are the leading indicators we should be watching to assess whether or not they're working?

Yes. So first of all, I probably should have in Capital Markets Day explained this in a little bit more detail. But Cognigy, right now, it will be margin accretive within 18 months. But right now, it's margin dilutive, structural effect of bringing that into the business. Now you didn't see that in Q4, but in Q4, we have a seasonal uplift in terms of our product and other revenues. But in a full year basis, there is obviously just a structural dilution, which is a key part of why you're seeing that with some of the dilutive effect.

The second then is what I described earlier, the faster I can integrate and have a single platform that covers my AI and my CX and all into a single platform, the faster I -- my ability to differentiate against either AI-native players or CCaaS players through a single platform. So that is a key part.

And Cognigy's ability, I mentioned sales and marketing, they're a great company, great business, but they only had 300 approximate employees. So the sales and marketing coverage to be able to get as many at-bats on the AI native play around the world and particularly in North America, I needed more capacity to be able to go win and compete because the market is frenetic right now. That is largely, largely first half.

So what you will see when you think about is that the investments, very sharp, very targeted that will largely be delivered in the first half. And so you'll see from a margin point of view as we go throughout the year that the margin will start improving in the second half, and then that will obviously -- that trend line continues in 2027 and beyond. I'm very confident of our ability to be able to hit the margin guidance and be able to show the improvement of margins as we head into '27 and '28 as we guided in Capital Markets Day with those investments.

Last thing I'll say is we made a significant investment on behalf of our shareholders and in part -- on behalf of our investors of Cognigy. We then made it through our use of capital. We then made the organic investment through the use of our OpEx. We've got to give return on that investment to our shareholders, and I'm committed to doing so and doing so quickly.

Excellent. We are out of time. Scott, thank you so much for joining us this year. And to the audience, thank you for joining the session.

Thank you, Jamie. Thanks, everybody. Appreciate it.

Welcome to the NiCE conference call discussing fourth quarter 2025 results, and thank you all for holding. [Operator Instructions] As a reminder, this conference is being recorded February 19, 2026. I would now like to turn this call over to Mr. Ryan Gilligan, VP, Investor Relations at NiCE. Please go ahead.

Thank you, operator. With me on Today's call are Scott Russell, Chief Executive Officer; and Beth Gaspich, Chief Financial Officer. Before we start, I would like to point out that some of the statements made on this call will constitute forward-looking statements. In accordance with the safe harbor provisions of the Private Securities Litigation Reform Act of 1995, please be advised that the company's actual results could differ materially from these forward-looking statements.

Additional information regarding the factors that could cause actual results or performance of the company to differ materially is contained in the section entitled Risk Factors in Item 3 of the company's 2024 annual report on Form 20-F as filed with the Securities and Exchange Commission on March 19, 2025.

During today's call, we will present a more detailed discussion of fourth quarter and full year 2025 results and the company's guidance for first quarter and full year 2026. You can find our press release as well as PDFs of our financial results on NiCE's Investor Relations website.

Following our comments, there will be an opportunity for questions. Let me remind you that unless otherwise noted on this call, we will be commenting on our adjusted results of operations, which differ in certain respects from generally accepted accounting principles as reflected mainly in accounting for share-based compensation, amortization of acquired intangible assets, acquisition-related expenses, amortization of discount on debt and loss from extinguishment of debt and the tax effect of the non-GAAP adjustments. The differences between the non-GAAP adjusted results and the equivalent GAAP figures are detailed in today's press release. The information and some of our comments discussed on this call may contain forward-looking statements that are subject to risks, uncertainties and assumptions.

I will now turn the call over to Scott.

Thank you, Ryan, and good morning, everyone. I am incredibly proud of what our team accomplished in 2025. We achieved our financial guidance each quarter and for the full year, delivered total revenue growth of 8%, cloud revenue growth of 13% and non-GAAP EPS of $12.30, all at the high end of our guidance range.

Since I joined, we sharpened our focus on execution and speed. We leaned into the AI-first platform-led strategy and doubled down on international expansion and strategic partnerships. Our 2025 results reflect strong execution against that strategy. In 2025, we extended our CX AI market leadership with AI ARR increasing 66% to $328 million, representing 13% of cloud revenue. We set records for acquiring new AI logos, growing 300% year-over-year and closed a record number of seven-figure ACV deals for CXone with 100% including AI. We further strengthened our competitive position with the acquisition of Cognigy, the enterprise leader in agentic AI, making NiCE the only player in the CX market with a fully AI native CX platform.

In our international markets, 2025 was a breakthrough year. We landed our largest international deal ever and ultimately grew international revenue by 16% with growth accelerating to 29% in the fourth quarter. We also expanded our strategic partner ecosystem through deals with ServiceNow, AWS, Snowflake, Salesforce, Deloitte Digital, PwC and RingCentral as well as several other international SI partners. Our partners continue to be an incredibly valuable and exciting part of our growing contribution, and we expect these partnerships to bring even more in the coming years.

Coming out of Q4 with a strong booking momentum and retention, we are entering 2026 on track to reaccelerate cloud revenue growth, which Beth will, of course, cover in more detail shortly. None of this would be possible without a healthy core CCaaS business. We have the leading platform in a growing and healthy market. Seats and interactions on CXone continued to grow in 2025. And importantly, only about 40% of contact centers have migrated to CCaaS today, leaving a large and durable on-premise to cloud migration opportunity ahead. We are delivering real transformative value to our customers, and this is translating into strong performance in our core CCaaS business.

In Q4, cloud revenue grew 14% year-over-year and excluding NiCE Cognigy, grew 12%. Q4 was a record quarter for new cloud ACV bookings, including and excluding Cognigy, driving cloud backlog growth to 25%, including Cognigy and 22% excluding it. Our win rates continue to improve against key CX competitors as customers increasingly favor holistic end-to-end CX platforms over fragmented point solutions. This is reflected in several key deals during the quarter, including a large enterprise win with a leading North American financial services firm. They selected NiCE in a competitive displacement of a legacy on-prem environment and will adopt NiCE's AI-powered CXone platform, including NiCE Cognigy to increase service automation, reduce low-value interactions and deliver more personalized client experiences. Additionally, we won a seven-figure ACV deal with a leading financial services group in EMEA, which selected NICE CXone to replace a legacy on-premise ACD and consolidate multiple platforms into a unified AI-ready CX foundation.

With a strong core, we are positioned to capitalize on the significant CX AI opportunity in front of us. AI is expanding NiCE's CX market opportunity beyond the contact center, creating new use cases that are still early in adoption and driving faster expansion as customers scale AI across their organizations. NiCE Cognigy NICE strengthens that position. NiCE Cognigy is ranked #1 by industry analysts and was recently recognized as the only conversational AI platform to receive the customer choice distinction in the latest Gartner Peer Insights Voice of the Customer Report. That customer validation extends across our core platform as well with CXone also now recognized as the only CCaaS platform to receive the customer choice distinction. Combining the market leaders in CCaaS and agentic AI for CX into the only AI native CX platform that can operate seamlessly across voice, digital and AI at enterprise scale allows NiCE to be uniquely positioned to seize the significant CX AI opportunity ahead.

Our platform owns the point of engagement and is built on the industry's largest CX data foundation. With decades of CX experience and a platform that supports 20 billion interactions annually, NiCE understands customer experience better than anyone, and this leadership is showing in the results. 2026 is the year that NiCE Cognigy begins to act as a force multiplier. We recently launched Cognigy Simulator, an AI performance lab that allows for faster, scalable and more reliable testing of AI agents. And soon, we will expand NiCE Copilot capabilities with Task Assist for agents powered by NiCE Cognigy.

Later this year, we will complete the integration of NiCE Cognigy into a single fully native CXone platform, delivering a seamless AI native experience at enterprise scale. As we enter 2026, I am very excited about the significant pipeline growth from our NiCE installed base that we -- and we expect that pipeline to grow as we further integrate NiCE Cognigy into CXone.

While we're incredibly excited about what the future holds for our seamlessly integrated capabilities, NiCE Cognigy is seeing strong momentum today. More broadly, we continue to see strong AI-driven enterprise software demand with customers prioritizing investments that deliver clear ROI and measurable outcomes. In Q4, seven-digit ACV wins included a leading North American consumer services company that expanded its relationship with NiCE by adding Cognigy for self-service to its existing CXone platform. This expansion will replace an AI solution from a CRM provider, providing -- delivering a compounding benefits of a unified platform with improved orchestration, deeper insights and more seamless experiences across channels.

In another large enterprise win, a leading North American energy company and an existing CXone customer expanded its relationship with NiCE to accelerate AI-driven customer engagement. By adopting Cognigy for self-service and Copilot to support agents on more complex interactions, the customer aims to improve containment and call handle times while scaling efficiently during periods of elevated demand.

The market is still in the early stages of AI adoption, yet it's already driving our growth. But as you heard me say in the Capital Markets Day, we need to make strategic, targeted and time-bound investments in 2026 to seize this opportunity. These investments will focus on innovation, including integrating NiCE Cognigy and advancing our agentic AI capabilities, while also expanding our go-to-market and delivery capabilities, so we're able to execute on the significant growth catalysts we see in 2026 and beyond. These catalysts, including driving AI-first growth across every customer touch point, automating end-to-end customer journeys with AI -- agentic AI on our platform, capitalizing on the CCaaS cloud migration, accelerating our international expansion and partner ecosystem and expanding beyond the contact center.

Before handing it over to Beth, I want to emphasize two points. First, 2026 is all about speed, and we're moving quickly to seize the opportunity in front of us. And secondly, my conviction today is stronger than when I joined that AI is a clear tailwind for NiCE. Let me be really clear here. NiCE is an AI company. Enterprise CX AI requires deep domain expertise, unified data, orchestration and governance at scale, and that is what we do. We have the technology, the data, the domain expertise and the customer base to win, and we will seize this opportunity.

With that, I'll now hand the call over to Beth.

Thank you, Scott. I'm pleased to close out 2025 by sharing our strong fourth quarter and full year results, which reflect continued disciplined execution across our business. Our fourth quarter performance has further strengthened our confidence in the recent financial targets we shared at our Capital Markets Day in November 2025. Later in my remarks, I will share our first quarter and full year guidance for 2026, which reflects the healthy momentum we experienced exiting 2025. 2025 was a transformative year for NiCE with Scott and our NiCErs across the globe laying the groundwork for accelerating top line growth in the years ahead.

Before I dive further into the fourth quarter 2025 results, there are several financial accomplishments from last year that I would like to highlight. First, our full year 2025 results were impressive and came in at the high end of our previously communicated guidance ranges. Full year total revenue was $2.945 billion, representing 8% year-over-year growth. Full year cloud revenue grew 13% year-over-year and 12% excluding Cognigy. 2025 reflected consistent execution in our core cloud business with 12% cloud revenue growth delivered each quarter, excluding Cognigy. Operating margin tracked as expected, while free cash flow margin of 21% exceeded our guidance, reflecting disciplined execution while absorbing Cognigy starting in early September.

Second, we completed the acquisition of Cognigy, which was financed entirely with cash on hand, supported by our strong balance sheet and robust organic operating cash flow. Third, we fully repaid $460 million of outstanding debt. Our balance sheet is now debt-free, providing us with significant financial flexibility to invest prudently in our business and return capital to shareholders. And fourth, we continue to return significant capital to our shareholders through our share repurchase program, underscoring our confidence in the durability of our cash flow generation and long-term value creation. In 2025, we repurchased $489 million of our shares, representing 32% growth year-over-year and 79% of free cash flow generation, ending the year with approximately 60.4 million shares outstanding.

Shifting to fourth quarter financial results. Total revenue was $786 million, representing 9% year-over-year growth. Cloud revenue totaled $608 million, growing 14% year-over-year and represented 77% of total revenue, continuing the steady mix shift toward our cloud-first model. Excluding Cognigy, cloud revenue increased 12% year-over-year. Cloud growth in the quarter was driven primarily by continued momentum in our CX AI offerings with AI ARR of $328 million, up 66% year-over-year as customers increasingly adopt our AI-powered automation across both self-service and human-assisted workflows.

Cloud growth also benefited from ongoing CCaaS migrations and a very strong international performance, including a modest incremental contribution for an earlier-than-expected go-live of a large international enterprise deployment originally planned for 2026 as well as a small foreign exchange tailwind of approximately 50 basis points in the quarter.

As we've noticed previously, while AI is already a meaningful contributor to growth, we remain early in fully monetizing its long-term potential. That context is important as we continue to invest in this opportunity today while building operating leverage over time as our AI revenue compounds. Our cloud net revenue retention for the trailing 12 months was 109%, remaining healthy and stable with the prior quarter, reflecting continued customer retention and expansion activity.

Turning to our business segments. Customer Engagement revenue was $658 million in Q4, representing 84% of total revenue and growing 10% year-over-year, driven by double-digit cloud revenue expansion across all geographic regions with strong performance internationally, reflecting increased enterprise adoption of CXone and growing demand for our AI-powered CX solutions. Financial Crime and Compliance revenue totaled $128 million, growing 2% year-over-year and represented 16% of total revenue. Actimize is the clear market leader and is benefiting from the positive momentum we are experiencing in shifting this segment to a higher recurring business with healthy cloud revenue growth.

From a geographic perspective, the Americas region represented 82% of total revenue, growing 5% year-over-year, and this performance was supported by double-digit cloud revenue growth in the region alongside the continued evolution of our revenue mix from on-premise related revenue towards cloud-based solutions. EMEA revenue, which represented 13% of total revenue, grew 38% year-over-year or 32% on a constant currency basis, and APAC revenue representing 5% of total revenue grew 11% year-over-year, consistent on a constant currency basis. This strong growth is reflective of continued healthy demand in international markets, one of our key growth drivers. International revenue is now majority cloud, while cloud adoption internationally remains underpenetrated, supporting a significant growth runway in 2026 and beyond.

Turning to profitability. Our total gross margin for the fourth quarter was 69.3%, consistent with our expectations. Our gross margin reflects our continued investments in scaling our global cloud infrastructure and supporting increased AI workloads, particularly as usage expands across regions and use cases. Operating income for the quarter was $301 million, resulting in an operating margin of 31%. Earnings per share for the quarter were $3.24, a 7% increase compared to last year. Cash flow from operations in Q4 was $180 million, underscoring the strength of our operating model and our ability to fund growth internally. Free cash flow was $156 million in Q4, and we ended the year with $417 million in cash and short-term investments. Our strong free cash flow and balance sheet are key strategic assets that provide us flexibility to invest in innovation, support strategic initiatives and continue returning capital to shareholders over time. We remain committed to disciplined and thoughtful capital allocation.

To further enhance our financial flexibility, yesterday, we entered into a new $300 million revolving credit facility, which provides additional liquidity and optionality while maintaining our strong balance sheet. In addition, we are announcing that our Board has authorized a new $600 million share repurchase program, reinforcing our confidence in the durability of our cash flow generation and our disciplined approach to capital allocation. This brings our total remaining share repurchase authorization to approximately $1 billion.

Before closing with guidance, I do want to spend a few minutes on how we are thinking about 2026, specifically around the cadence of investments and how that should translate into margins throughout the year. At our Capital Markets Day, we shared a midterm framework for growth, margins and cash generation. Today, we are confirming that framework with additional clarity on timing and cadence. 2026 will be a year of deliberate targeted investment to support our next phase of growth to capitalize on the immense CX AI opportunity. These investments are focused on three primary areas: cost of goods sold, R&D, and sales and marketing. As we've shared, near-term margin performance expectations reflect intentional investment choices. These investments are designed to optimize our AI market-leading position, drive durable growth, expand our competitive differentiation and position the business for long-term operating leverage.

While we plan to increase organic investments during 2026, our margins remain industry-leading, outperforming our market peers even with the addition of the focused spend, and we expect to build on this strength with steady margin expansion in 2027. In tandem with investing for growth acceleration, we are investing in AI internally to enhance productivity and execution across the organization. Within our go-to-market operations, we are applying AI to accelerate customer quoting and surface key signals from customer interactions, enabling faster deal execution, improved forecast accuracy and reduced deal risk.

Beyond go-to-market, we're using AI to improve internal operations, including applying AI to HR knowledge and deploying Cognigy within our internal help desk to resolve IT queries more quickly and with a more human-like experience. These are just a few examples where we're already leveraging AI internally to deliver long-term operational efficiencies.

In 2026, we expect the pace of incremental margin investment to be highest in the first half of the year as we execute against our growth priorities, including integrating Cognigy and scaling its operations with operating margins improving in the second half. This positions us to exit 2026 near the upper end of our 25% to 26% operating margin range and sets the stage for margin expansion in 2027 and beyond, driven by the benefits of our 2026 investments, including stronger cloud revenue growth, continued scaling of our AI business and the increasingly accretive contribution from Cognigy. Cognigy remains on track to be accretive within 18 months of the acquisition close.

Now I'll close with our total revenue and non-GAAP EPS guidance for the full year and first quarter of 2026. Full year 2026 total revenue is expected to be in a range of $3.170 billion to $3.190 billion, which represents an increase of 8% at the midpoint. We expect cloud revenue growth in 2026 to be in the range of 14.5% to 15% with Cognigy expected to contribute approximately 200 basis points.

Turning to financial income. It's important to note that our cash and short-term investment balance was reduced by approximately $1.2 billion in 2025 as we financed the Cognigy acquisition and fully repaid our outstanding debt, which will naturally impact financial income in 2026. We expect our effective tax rate throughout 2026 to be in the range of 20.5% to 21% due to tax law changes in certain jurisdictions that became effective at the start of this year. Full year 2026 fully diluted earnings per share is expected to be in a range of $10.85 to $11.05. For the first quarter of '26, we expect total revenue to be in the range of $755 million to $765 million, representing an 8.5% year-over-year growth at the midpoint. We expect the first quarter 2026 fully diluted earnings per share to be in a range of $2.45 to $2.55.

In summary, we exited 2025 from a position of strength. anchored by a stabilized and growing cloud business, a differentiated customer experience platform with embedded agentic AI and a strong balance sheet that supports investment and continued capital returns to our shareholders. Our large and expanding installed base reflected in healthy cloud net revenue retention, continued growth in cloud backlog from both customer expansion and new large enterprise wins and an increasing number of enterprise go-lives gives us confidence in the durability of our growth as we enter 2026.

Our 2026 guidance reflects our excitement about the market opportunity ahead and our confidence in our ability to accelerate top line growth through our market leadership and unmatched assets.

Together with Scott, we would like to thank all our dedicated teams across NiCE for their disciplined execution and focus throughout the past year, which drove our strong financial performance. We remain confident in our strategy, our execution and our ability to deliver durable shareholder value over the long term.

With that, I'll turn the call back to the operator for questions. Operator?

[Operator Instructions] Your first question comes from the line of Rishi Jaluria with RBC.

This is Rishi Jaluria. Nice to see solid execution to close out the year. Maybe two questions, if I may. First, look, looking at the market, it's pretty clear that the market is scared of AI disrupting and displacing your business. Clearly, that's spread to all of software and is something that we've all been dealing with really in a big way over the past couple of months. You made it clear over the past couple of years and at Analyst Day and now today that you're viewing AI as a real tailwind for NiCE and something that could pick up accelerating momentum in kind of the coming years.

Can you maybe help us understand where is the disconnect? Where do you think that the market is wrong? And kind of where is your opportunity to kind of disprove those bear cases and kind of prove yourselves as an AI beneficiary? And then I've got a quick follow-up.

Sure. Thanks, Rish. So let me try to take that. So there is clearly a disconnect between the fears in the market and the reality of what we're seeing in the business. So let me try to break it down, if I can. First of all, there's a concern about competition from new AI point solution. And the reality is this, the CX AI market is expanding rapidly. And it's large enough actually to support multiple approaches. But our growth -- the growth of our business is not coming at the expense of those competitors. Actually, it's a beneficiary. If you look at NiCE's business, 13% of our cloud revenue is AI. We've already proven that we've embedded it into our core platform. We're able to deliver durable value to our customers. And why is that?

Well, CX is complex, and we are domain experts in CX. You look at what is required from our customers, it requires orchestration, really rich and unified data governance. It requires deep domain expertise across the customer journey. And so whilst point solutions and some AI solutions can address use cases and narrow use cases, they don't actually fulfill the full customer journey. They're -- in fact, in some ways, they're actually complicating or creating more complexity. So a unified platform that is able to deliver across voice, digital and AI is what the market needs and expects. And that's where a combined platform that we offer, which is unique in that we've got the best-in-class in both cases helps us.

And that -- and I guess, ultimately, we're showing that in the numbers. The growth rates, I indicated at Capital Markets Day, if you remember, Rish, that we expected our cloud growth in 2026 to be between 13% to 15%. We're already indicating at the high end of 14.5% to 15%. That's on the back of customer demand, real backlog that's growing at 25%, real pipeline that we're converting into ultimately revenue for NiCE, but ultimately, it's value for our customers. So I'm confident that our growth indicators reflect the tailwind that AI brings, and I'm sure the market ultimately will see NiCE in a favorable way.

All right. That's super helpful. And maybe just a follow-up on that. In kind of the AI native space, we've obviously seen a lot of funding for voice AI start-ups. And it feels like maybe piggyback on that earlier point of conversation, the market is kind of viewed it as -- at least the stock market is viewed it as kind of an either/or. But it really feels like there might be opportunities for even partnerships and integrations and kind of focusing on customer success. Can you maybe talk about your opportunities? I know, Scott, you talked a lot about increasing partner ecosystem traction, et cetera, but maybe an opportunity to even just have deeper integrations and partnerships with some of these AI natives just to kind of leave the choice up to the customers even if it may sound potentially competitive. Because at the end of the day, they do need the pipes that you have, they do need the call routing piece. Maybe help us understand what could that kind of ISV or AI partnership look like?

Yes. It's a great question, Rish. I'll probably break it into two parts. The first is we're an open platform. We've made a very conscious decision to be a platform that allows the customers to utilize their data because it's their data that all of the billions of interactions that sits on our platform and being able to leverage it across not only the NiCE CXone, but an open stack that supports the use of other tools. And that's why the partnerships with Salesforce, with AWS, with ServiceNow and many others are essential to it. And we're -- at the enterprise, you're dealing with a complex technology landscape, and so we're able to use that to our advantage.

But let me just zero in on the AI side. One of the questions that we often get is, hey, these new frontier models and what does it mean? And is that going to be a disruption to us? And actually, it's a benefit. It's actually a significant positive because if you look at it, the labs, these frontier models, they are tremendous advancements in agentic capability. But we leverage those models. We have partnerships with those AI players that we can use those models in our stack, but then we've built a purpose-built AI around customer engagement data. And so we differentiate by our specialization. Those models are really powerful, but then we process it on those billions of interactions, the specific learning loops, the optimization. So the specialization around the customer intent resolution, the compliance-heavy workflows, the guardrails that enterprise have, the real-time voice orchestration.

So the reality is it's not replacing, it's enabling a more powerful and differentiated outcome with the combination of what we bring and what they bring to give a better outcome for our customers. So it's not replacement. It's actually expansion and extension from what we've already done, and it gives us more opportunity to deliver ROI. Again, that's why we're seeing the backlog and the bookings growth that we're getting because the customers are voting by their choice of NiCE, and we're benefiting that in our revenue outlook.

Your next question comes from the line of Samad Samana with Jefferies.

Great to see the solid 4Q results. Maybe first, just one on the guidance. I think we're all happy to see the upward revision to the 2026 cloud revenue growth forecast. I was curious, Beth or Scott, if you guys could break down what led to the upward revision? Is it the core organic cloud revenue? Is it Cognigy doing better than expected? Because if we assume Cognigy is at 200 basis points of revenue growth contribution, that kind of implies an acceleration for the organic business. Just help us unpack that. And then I have one follow-up.

Yes. Thanks for the question, Samad. And I'll take that, and Scott, feel free to chime here. I think generally, as a starting point, we feel confident that both will contribute to that mix and give us that confidence as we step into 2026. Scott has already highlighted the strength of the backlog. We had a record in terms of new cloud ACV bookings in the fourth quarter that led to that strength of the 25% growth in our cloud backlog looking ahead. So that's a mix of both the strength of that AI force that we see, inclusive of both our own homegrown AI and of course, amplified by the addition of Cognigy. So when we look both at the core, which you've seen was consistent at a 12% growth throughout each and every quarter this year, we feel confident that there is opportunity to accelerate growth both in that core as well as continue to drive that growth through Cognigy, which had very strong fourth quarter showing as well. So it comes from a combination of both those places.

Great. And then, Scott, a follow-up for you. And I know that this topic came up at the Capital Markets Day as well. I think it's appreciated by investors that the company is putting the foot on the gas with AI being this massive opportunity, right? You guys are literally putting your money where your mouth is. I'm curious maybe as you think about deploying new investments and how that's going inside the organization? And are you starting to see a shift inside of the sales organization, whether it's win rates, whether it's productivity as maybe the accelerated investments drive enthusiasm in the organization as well?

Yes. It's good question. So first of all, there is, I guess, a positive energy and momentum that we're seeing in the business. And that's obviously on the back of the bookings and the backlog generated in Q4, the momentum that we've been able to generate, but also the pipeline and what we see. What was interesting is the Cognigy business continues to grow remarkably on a stand-alone basis, just acquisition of new market where NiCE has no footprint at all and our ability to be able to go and compete and win in that new marketplace where they don't have a need for a CCaaS, but they really want an AI CX platform as a leadership, that's given a real positive energy inside of our sales organization, combined with the obvious opportunity that we see with existing installed base, the large customer base that we have and our ability to be able to serve that.

So I think first on the positive momentum, fantastic. The other point, and Beth touched on this in her opening comments, we're embracing the use of AI inside of our business as much as we expect our customers to. We're living and breathing that reality. So for our sales teams, being able to use it to be able to get better understanding of customer signals, intent, our ability to automate quoting and being able to do fast turnaround for business for our customers when we're competing, these were deployed and we're up and running. So I think our go-to-market are also seeing higher productivity that allows them to get more at bats to be able to get more customers engaged and ultimately improve our win rates. So you need to do both. You need to have a great capability that you take in a market, but you've got to walk the talk, and we're definitely doing that.

Your next question comes from the line of Arjun Bhatia with William Blair & Company.

Scott, maybe one for you to start out with. Obviously, it's good to see the continued traction in your AI and self-service ARR. I imagine the distribution of customers in that group of those that are advanced versus those that are still starting is quite wide. But when you're looking at your more sort of advanced customers, what are you seeing in terms of seat dynamics there? Has that changed at all over the past couple of quarters? Or is this still like something that's being contemplated for years or quarters in the future in terms of what they do with their seat counts and agent counts?

Yes. It's a great question, Arjun. So I think there's a couple of things to maybe highlight here. As I mentioned in my opening comments, our core CX CCaaS platform is really strong. And to Beth's earlier comment, we see reacceleration in our outlook for '26 and beyond. Why is that? Well, I guess I'll best answer it by discussions that I've been having. This week, I had a number of meetings with customers, CEO, CTO and we were just talking about their CX environment and their existing use of their contact center. And right now, they both had indicated that their contact centers are capacity constrained. They're not overstaffed. And so they plan to use AI to actually free up their agents for higher value engagement, proactive outreach, more revenue generation or more value orientated. So rather than elimination of roles, they're using it as an efficiency driver so their people can be driving more value-added activities. And so they had no plans, no plans to reduce agents in the short to midterm.

Now that's not to say that as we continue to build out our platform that we don't see the opportunity to be able to reduce the human capacity as the AI picks up. But we -- that's why in these complex environments because remember, CX is tough. you've got to have accuracy of data at high volume, the guardrails, the domain expertise and ultimately, it's got to fulfill a great consumer experience for the brand. And so what they don't want is a point solution that gives them a bit of automation, but then increases the complexity when it has to interoperate with their AI agents. And I think we've really seized upon this. What we see at the top end is that customers value a unified customer engagement platform. We call it the front door.

So whether it's voice, whether it's digital, whether it's AI or what is most likely to be a combination of all three at the same time, real time at enterprises at the top end, they need a platform that can give that in a scalable, reliable way. And obviously, we differentiate on that basis. So it's interesting about the, I guess, the perceived concerns that you're going to see this erosion of the seats. We -- the data does not support that assertion, but we're growing on both levers, and we continue to expect to do so.

All right. Perfect. Yes, that's super helpful color. And then Beth, I had one for you. Just in terms of the investments that you're making, I think I fully appreciate, right, it's the right time to sort of lean in given the precipice of the tech change here. But how are you just monitoring that you're making the sort of the right investments and you're allocating capital appropriately? Like what are the ROI signals you're looking for? Or is it just continued sort of revenue reacceleration here?

Yes. Thank you. We're very excited about the opportunity ahead of us, and we absolutely believe this is the appropriate time to lean in. We really have at NiCE a fence investment approach where we are very closely monitoring a very tightly the exact areas that we plan to invest, which we've talked a lot about. It's around the go-to-market. It's bringing in more integration of Cognigy into the platform, agentic capabilities as well as using additional AI technologies internally, accelerating our delivery time line, all of those areas are very intentional, and we are very much closely monitoring that the dollars are being spent in the right places. In parallel, as a general muscle that we have in NiCE, we are constantly also driving initiatives that drive long-term operating leverage. Scott talked about the use of AI. There are other initiatives as well that we're always putting in place.

So we're also monitoring the effectiveness and seeing that we get the ROI from those initiatives and investments through key specific metrics. And when you add all of those together, ultimately, the big test is that we see that we are delivering on the growth that we've signed up for on the top line. And so those are a combination of all of the things we monitor very, very closely to ensure we're on track and that we're getting the ROI from those investments.

Your next question comes from the line of Tyler Radke with Citi.

This is Kyle on for Tyler. It was great to see the significant acceleration in international revenue. And I'd be curious to hear how you'd expect that trend to continue into FY '26? And what -- maybe any color on what would be embedded in the total revenue guidance on a constant currency basis?

So let me cover the international expansion. So first of all, I need to highlight. I've inherited a beneficiary from a significant investment that had been made in our international expansion. So the footprint of our data centers, the sovereign cloud, the capacity in key markets in U.K., Europe, in parts of Asia. So what we saw in '25 was a real breakthrough in terms of -- obviously, our bookings and the backlog, we saw in Q4 a significant acceleration of our revenue that you saw in those results. And so for '26 and beyond, what we see is expansion opportunity. And if I give you a couple of data points to color. First is the CCaaS shift in the international markets is not as progressed as what it is in North America. So there are more opportunities with our platform to be able to win the on-prem to cloud migration, leveraging those investments, leveraging our momentum.

The second is they're doing it with AI from the get-go. They're not doing this in a two-part move or sequential. They're doing it at the same time. So the unified platform where we can embed Cognigy and our AI agentic capabilities in that -- in those deals gives us competitive edge, but it also allows us to be able to accelerate revenue because the AI adoption time frames are faster, whilst often the CCaaS migration is a complex onetime undertaking.

And then the last, what I would say is those international markets are benefiting from our investments in the ecosystem. Practically, all of our go-to-market in international is through our partners. And so the strategic ecosystem is part of the reason why our international expansion is performing strongly because we've really made sure our go-to-market motions with both SI partners, resellers, technology partners internationally be the core vehicle that we use. And that gives us reach that goes beyond the 4 walls of the NiCE capability. We really do leverage their breadth and strength in those international markets. So it is -- you can expect to see continued momentum in that area.

And then I would just quickly, Kyle, address on the currency side. I think, first of all, I'll start with the overall outlook for NiCE in totality. I think it's important to highlight that in total, NiCE is still predominantly concentrated in terms of mix out of the Americas, which is mostly USD denominated. So 82%, for example, of our revenue in the fourth quarter was coming from the Americas, mostly USD. Any impact that we may see within the international business, which is thriving and growing for us, has been considered and is factored in. We're always looking at the environment generally on a macro for exchange rates and other factors as well that is inclusive in the expectations that we're looking at. Again, you may see that more noticeable as you've seen in the fourth quarter in terms of the impact on the international markets, but not any expectation that is not already baked into our expectation for the full year.

Understood. And then regarding the Better Together story with NiCE and Cognigy, the ability to win more deals as a combined CCaaS and AI domain expert. How did the joint go-to-market motion play out in 4Q? I know it's early, but also how to think about the Cognigy opportunities from current CXone customers versus sales to customers on competitor CCaaS platforms as well?

Let me take that one. So I was really pleased. I've got to say that despite it being -- with Cognigy coming into the NiCE family at the -- in September, coming into our busiest and most hectic quarter of the year, it was remarkable to see two things. One, Cognigy and our ability to win and grow as a stand-alone AI market-leading platform, it was fantastic. But then secondly, our -- I've got to give it to our -- the NiCE go-to-market team, we were able to quickly pivot. And so the fourth quarter performance also on a Better Together where we were able to embed it into our big wins and the strong performance we had in fourth quarter, Cognigy was well and truly a part of that, which is why, by the way, 100% of our seven-digit deals included AI and that pretty much nearly all of them was inclusive of Cognigy.

So the early collaboration was really strong. What we're really now focused on is how do we then capitalize and expanding on that rapidly in '26. So we're very early days in the AI expansion. We see obviously new competitors with AI point solutions. We've got a differentiated offer. So really, we're doubling down on the Better Together, unified platform, but also winning and competing in the AI-only market where the situation exists and being able to win and win well. So competitive win rates were good. I feel very good about the fast integration, and it's a credit to Phil Heltewig and the Cognigy team and the way they've really embraced and coming to the NiCE team and led the way.

Your next question comes from the line of Siti Panigrahi with Mizuho.

Great. If I look at your cloud backlog that excluding Cognigy, it's organic cloud backlog, now 22% growth, that is quite a step-up from 13% in Q3. So a few things, like what's the composition like for that step-up? And you guys earlier talked about it takes longer to convert to recognized revenue. So how should we think about the lag from the backlog to cloud revenue growth over the next 2, 3 years? -- 2-3 quarters?

Yes. Thanks, Siti, for the question. I would start and just say that when you think about the 25% growth we had in the backlog, you highlighted the 22% growth that we had, excluding Cognigy. When you think about how that will play out in the coming years and months, essentially, the substantial majority of that will actually be recognized in the next 24 months. It is not, however, linear. Of course, it is dependent upon various go-lives that happen throughout that period. So the expectation and as we continue to shift that from the backlog over into recognized revenue, you should see that gradual expansion playing out in the cloud revenue growth over that period.

Okay. And then on the Cognigy side, Beth, you talked about before exiting Q4, $85 million ARR. Is that still -- does that still holds good based on what you're guiding for the year?

It is. We had a very nice performance of Cognigy since the start of the acquisition and the close. So yes, very much on track and looking forward and excited about our ongoing opportunity during the course of '26.

Your next question comes from the line of Jamie Reynolds with Morgan Stanley.

This is Jamie on for Elizabeth. And congrats on the strong quarter. It's just the first question. It'd be great to just unpack a little bit more about how that displacement with the CRM vendor materialized. What capabilities did NiCE bring where that vendor fell short?

Yes. I'll answer this one, Jamie. So there's a couple of factors here. First of all, customers -- the customer that we're referring to had a need of an integrated customer engagement platform. What they didn't want is one platform to handle the AI piece, another platform to handle digital and another platform to handle voice because what it did was it created friction in their engagement, and it was actually impacting a positive customer experience. What they wanted was the data, the operational flows, the process to be orchestrated end-to-end. So it was more about clear conscious strategy for customers. And we're seeing this more and more where they're distinguishing a customer engagement platform, the front door to the enterprise by their customers in a unified single approach rather than fragmented through differing technologies.

Now that's not to say that they don't need and orchestrate with the CRM because you still want your sales data, your commerce data, your other information, your customer data that you've got there. But when it comes to the interaction and understanding the customers' intent and then having a simple way of being able to orchestrate between a human agent, an AI agent, synchronous, asynchronous, inbound and outbound, they wanted it on a single stack. And obviously, we see the benefits of that. Ultimately, they chose it because it will deliver better ROI, better customer experience. And it was one customer example. We've got many others that are doing the same journey.

Got it. That's helpful. And then just as a quick follow-up, it'd be great to get any color on how the performance among the more seasonal customers kind of trended in the fourth quarter relative to your expectations?

Yes, thanks. When we looked at the seasonality, we had highlighted that we had a strong bar to climb when compared to the fourth quarter of 2024, but we were quite pleased with the seasonality that we experienced in the fourth quarter this year. I did highlight a couple of things in my formal remarks around we had about a 50 basis point tailwind coming into the cloud revenue in the fourth quarter coming from foreign exchange that was included there. We also ended up having a go-live of a very large international deal earlier than anticipated that came into that. So those also kind of triggered some health in the quarter. But generally, we were pleased with the seasonality that we saw, which was healthy for our fourth quarter across our diversified vertical customer base.

Your next question comes from the line of Michael Funk with Bank of America.

So Scott, earlier you mentioned -- I think you mentioned that only 40% of enterprise have moved from on-prem into the cloud. So I'd love to hear more color around the pace of that migration and then net new versus migration internally and the increase that you see in TCV when customers do migrate internally?

Yes. So as I mentioned, there's a significant market in front of us. Now the international side, Michael, is particularly strong because they've not progressed in the migration compared to the Americas. So just from a geographic standpoint, we see real momentum on the international side and obviously, we're benefiting from it. I think what -- if I take a step back, what's happening in the market is customers were previously forced to choose, do they do the on-prem, the cloud migration? Do they do an AI move? They had to distinguish between their methods. Now we give them the choice to do that as well. But what we've now seen and the results are undeniable around all of our big wins, all of our CCaaS moves are embedding AI in. So what we're seeing now is they're using AI to be able to drive the automation capability, give them fast return, early deployment while they're still doing their CCaaS shift, and that is able to help make sure that they've got early return on investment. It gives us a competitive differentiation because we unify the journey of not just the on-prem to cloud and the AI, but it's combined together.

So it actually has given us a really significant differentiation compared to where we were a year ago, where we were obviously able to still capitalize on that. The last comment I would make is the routes that customers are choosing will -- that they will -- migration paths will continue to be a key part of the differentiator. What customers aren't prepared to do on the CCaaS migration is long time to transition. So the other thing that we've really focused on is reducing the time to turn up or the time to value. We improved our delivery time frames by 20% during 2025. I mentioned that, that was a focus area at the beginning of last year. And I think the more we're able to show that we can do a time-bound, efficient migration while capitalizing on the AI capability, we're going to be able to seize an acceleration of those CCaaS moves as the customers evaluate the use of this technology in their landscape.

Maybe one more, if I could, quickly. Financial crime and compliance business, love to hear your thoughts on the operating and strategic benefits of owning that business versus maybe some strategic alternatives?

Yes. It's such a great business. What makes me smile is it continues to be seen and perceived and understood as the market leader. We serve the most sophisticated financial institutions with a level of trust that, honestly, it is a joy. I meet with banking executives and our clients. And the first thing they tell me is, we trust Actimize, we rely upon it. We need your help to continue to support our ability to fight financial crime, fraud and compliance factors. So from a brand point of view and from a trust point of view of that segment, which is also a big segment inside of our CX business, it really does enhance our -- the trust position that we have as a company. So great business, strong performance, really profitable. And yes, we're proud for it to be a part of the NiCE family.

Your next question comes from the line of Thomas Blakey with Cantor Fitzgerald.

Maybe just first one, Scott, I just wanted to talk about these increased win rates that you're talking about and obviously evidenced by the increase in backlog. If you could maybe -- in answering another way about the increased win rates on pricing and any levers you might have there with regard to your to Cognigy or other kind of consumption-based AI levers that you have here in the market, that would be helpful?

Yes. I'll try to answer it simply. We're definitely seeing customers being more astute in their expectations of ROI and that leads to more quantifiable outcome. Now they're not buying outcome-based pricing, but they're negotiating an understanding proven ROI that we're able to deliver. One of the advantages we obviously have is that we understand their volumes, their interactions on their existing seats, how efficient their platform is. We use data to inform them about what the automation that AI can do to improve upon that and then how that then delivers measurable return and we put that into our offers.

So look, we've seen our pricing continue to be effective in terms of profitable business for NiCE, but also as a differentiator. But we're watching it closely. I think the market in AI will continue to be scrutinized, the promise versus the reality. It's easy to come in with an AI solution and say, we'll build you a bunch of AI agents. But if it doesn't deliver the real value, they go to vendors and partners that have proven to deliver that before. And we leverage that. There is no doubt that we're using our historical strength and benefits to our advantage. And if that means updating our pricing models, we'll do so.

Yes. No, that's helpful. And you're definitely balancing that well in terms of the backlog growth. Maybe for Beth, you've broken out in the past the consumption-based AI ARR. I don't know if it's something you'd want to help with here. And just understanding the increase in backlog and the jump in AI ARR in total, I wanted to know if consumption is driving that. And when we can kind of expect as folks are finding value here, looking to expand AI in terms of the CX role internally, NRR to start maybe expanding? Is that more of a '26 or more of a kind of an out-year kind of environment when you kind of look at your contracts and backlog wins, that would be helpful?

Yes, sure. So I think I would start with where Scott just led to, which is we have a flexible pricing model that allows that fluidity, and we're driving more and more increasingly towards interaction and consumption-based pricing, which is demonstrated in our overall AI ARR growth, where we're leaning in more and more towards pricing, which is coming from that increasing and ongoing expansion of interactions that we see. With respect to our backlog, we actually -- it demonstrates we have even further upside. When we look at our backlog, we're actually only including there our minimum contractual commitments. So our pricing model and the way we commercialize with our customers generally is on a subscription basis over a multiyear period. So that's what's being reflected in our model. We're still in very early stages of deployment with a lot of those enterprise customers. So as we continue to see those interactions increasing, that's further upside that we have even beyond what's already captured in our backlog.

Your final question comes from the line of Patrick Walravens with Citizens.

Great. Let me add my congratulations. I was wondering if you could give us an update on your two $100 million deals. I think you had one that was in APAC and one that was in EMEA. And Beth, maybe you commented on that when you talked about something that went live. So what's the state of those two now? And then are there anything else -- are there any more this big that are in the pipeline?

Yes. So I'll take the first part, which is -- thanks for the question. Those -- both of those deals that were internationally driven are actually within our recognized revenue. They've both gone live. We're very excited about them. We're delivering to the customers. I would also add that there are additional opportunities. Those customers are continuing to look to do more with us. So we're off in a great start of those relationships, and we'll have more to come. But yes, they are already live and contributing to our revenue.

Yes. And in terms of the outlook, look, I guess you're getting a sense on this call, both with our backlog, but our optimism. There is some big opportunities that are in front of us. It's highly competitive out there, but I think we're proving that we've got a differentiated ability to win those. And so I look forward to being able to share more significant wins going forward, both internationally, but also in North America.

That concludes our question-and-answer session. I will now turn the call back over to Scott for closing remarks.

Look, I just wanted to, first of all, thank everybody for the engagements, not only today, but throughout '25. It was a year of clear transition, but we're really excited about what we delivered, but also about the future in front of us. And in particular, I just wanted to thank all the NiCE employees, the NiCE is all around the world, our partners and our customers that contributed towards this. We've got exciting times ahead. It is an exciting market, but we've got the momentum to be able to seize upon it, which we will do. So I appreciate the time, everyone, today.

Ladies and gentlemen, this concludes today's call. Thank you all for joining. You may now disconnect.

All right. Welcome, everybody, as we close out the NASDAQ Conference. I'm delighted to have NICE here and have Beth Gaspich, CFO of NICE. I am filling back in as Meta Marshall previously covered communication software. So very familiar with Beth and the story.

Yes. Thank you. Thank you for having us. We appreciate it. Nice to see you again.

Great. Thanks for having you back at NASDAQ. We all appreciate it. Investor sentiment on CCaaS has been a little bit challenged despite kind of positive commentary towards the AI opportunity from NICE, your peers in the space as well as kind of consistent optimism in our channel techs. Just where do you feel like that disconnect lies? And is there a path to kind of closing that?

Yes, it's a great question I would say by probably the primary misconception is to really understand that AI is a tailwind and a key growth driver for NICE. As we've looked at our performance year-to-date, we've seen our AI revenue that's embedded in our cloud platform, scoring at more than 40%. It's a key driver for us in enabling in the customer experience platform that we deliver really end-to-end capabilities to optimize the customer experience, the customer journey, doing it in a cost-effective manner for customers. And so first, that expertise that we have in AI, then further amplified and accelerated through the recent acquisition that we did of Cognigy, which is another leader in the market in agentic AI, coupled with NICE as a leader in CCaaS really brings the strength of all of that together.

So the combination of that, along with our expertise specific to CX is really critical for our ongoing success and the confidence we have in our growth. There are a lot of options today in terms of AI capabilities. But what we do is very specific to our customer experience domain, and we have the full CX stack end to end and how we engage with the customer and being in that space or the single pane of glass for the consumer with our customers.

Got it. So I mean you talked about a big disconnect in just how much you're kind of capitalizing on AI, which I think is one misconception that people have. But another one is just, okay, what if agents get caught? Just where do you -- why do you ultimately believe that NICE is best positioned kind of relative to competitors and versus kind of other peers coming into the space when it comes to kind of addressing some of these kind of arguments and opportunities?

Yes. So it comes from a couple of different places. One is we have a fundamental strength in our core CCaaS business. If you've been following us this year, we have outperformed our guidance each and every quarter with an expectation of a 12% growth quarter after quarter and our cloud revenue coming from the core of our AI as the key growth driver. And as we look specifically on Q3, we see that our year-over-year cloud backlog has actually increased to 13% year-over-year growth. So it gives us that confidence looking ahead of that continued growth. And that's, again, even prior to the acquisition of Cognigy, which will add further amplification and acceleration to the combination of AI with the strength of our overall platform.

Okay. Yes. So that acceleration is really -- is important to kind of point out. On that point, you spoke to kind of win rates against CX competitors increasing within Q3. Can you just walk us through, are there -- you've obviously had new management over the last year. Just what are some of the drivers of that improvement? And how can we think about the sustainability of that?

So we're very excited about the recent expansion we've seen in increased win rates as well as strong bookings out of the third quarter and just positivity looking forward with our backlog and other general indicators. With Scott Russell, our new CEO, coming on board this year, he brings an enormous amount of wealth of expertise. He was part of SAP, helping to drive the transformation from on-premise to the cloud, growing from about EUR 8 billion in cloud revenue to, I believe, about EUR 17 billion. And so he has done that transformation.

And as we look at the opportunity ahead of us for NICE, we see that our area in CCaaS is still highly underpenetrated in the cloud. So today, there is about an estimate of only about 40% penetration of organizations that have yet already shifted over to the cloud and our operating customer experience in the cloud. So there's still a huge runway that is ahead of us.

And Scott brings that expertise to NICE. Some of the key areas that he brings great experience, first of all, is that migration from premise to the cloud, also really building strong ecosystems and strategic partnerships. And so we're excited around all of the strategic partnerships we've already announced this year. That includes Salesforce, ServiceNow, Snowflake, AWS, RingCentral. So we're either introducing new partnerships and/or expanding the ones that we have. So the combination of all of those things, along with really the real-time capabilities we have in our platform that are unmatched and unparalleled in the market, are a combination of why we believe we're seeing this increase in expanded win, the things and actions that we've already taken to date, and they're being demonstrated in the results.

Okay. Got it. At your recent Investor Day or Capital Markets Day, you outlined the plan to kind of double the cloud revenue over the next 4 years, reaching 17% to 19% cloud revenue growth by 2028. Can you just walk us through kind of the assumptions underpinning that confidence? You spoke to some of what you've just seen, but what are the markers that kind of gave you that confidence in that?

Yes. So there's multiple key drivers and growth catalysts that are underpinning that confidence. I would start off with AI being a growth driver. We had AI that has been part of our strength and our platform for many years at NICE. So we have AI capabilities that are both augmenting agents in the contact center as well as AI agents as well. Earlier, you also mentioned the pricing model. And so our pricing model also accommodates that ongoing shift that we'll see and the interchangeability between human agents and AI-based agents. So that's a huge benefit that we have. Similarly, that exists also with the ability for us to handle both voice as well as digital channels through those capabilities.

So those are huge advantages in terms of AI and the way we interact and interchangeability between human and AI agents. The second thing that I would highlight is just the depth of our offering. If you look at any leading analyst report, for example, Gartner, we are in the top right quadrant. And that's because we are really successful in the large enterprise. It is not easy to be able to service the large enterprise. We have years of experience doing so. And part of that is due to the depth and breadth of the platform that we have through CXone. So that allows us to go in and cross-sell and upsell to these customers. So you have the combination of AI as a catalyst, you have our ongoing cross-sell and upsell, and you have the fact that the ecosystem generally is only about 40% migrated to the cloud.

So all of the migrations that have yet to happen are generally in the large enterprise where we thrive and have a great deal of experience, and all of that is incremental for us in terms of revenue because this is routing in the cloud. So we're taking market share from those premise players as we do that. The final thing that I would highlight in terms of one of the other catalysts is our international momentum. We have focused a lot over the past few years of investing heavily internationally, really driving our go-to-market as well as our infrastructure and introducing sovereign clouds. It's another competitive advantage and differentiation we have at NICE.

There are very few companies that can deliver at the scale that we are for very large multinational and government agencies that can provide the level of data residency, security that's required and really getting those customers and organizations comfortable from a compliance and regulatory perspective. So we have all of that to offer as well.

Okay. And what you just said about international might kind of answer part of the next question. But you also kind of spoke to operating margins kind of taking a step back in 2026 before kind of recovering. Can you just kind of break down some of those investments that you're making and explain why you think now is kind of the right time to make those investments?

Yes. So a combination of our position as a market leader, the strength of our real-time CX specific platform, our AI capabilities and coupled with Scott coming on board with his immense experience, we just feel like this is really the opportune time. 60% of the market has yet to shift to the cloud. The strength that we have and the combination, both in CX expertise, servicing the client, driving optimal customer journeys, coupled with that AI and experience means that we really see now is the time to make those investments to set us up for long-term sustained growth and long-term shareholder value as well.

Okay. I mean do you want to maybe outline what some of those kind of key investments are?

Yes, of course. So during the course of our recent Capital Markets Day, we shared that we expect to spend about an additional $160 million during the course of 2026. And that we'll continue to make incremental spend over the course of '26, '27 and '28, with the broadest spend in incremental amount being in 2026. So it's really divided in 3 different areas, there's in our cost of delivery that we're providing in terms of the cloud platform itself, our R&D area as well as go-to-market.

When I dive a little into -- further into each of those, in the cost of delivery, first of all, I talked about the success we've seen in international momentum. So we're making certain investments there around sovereign cloud, building infrastructure. We're also looking to accelerate time to value for customers, meaning that we are using further implementation partners as well as part of our delivery model to drive that accelerated value for customers and providing our solutions very quickly into their operations.

We also have what we refer to as AI centers of excellence, creating repeatable frameworks for customers as we deliver to the very high end of the market. So those are just a few of the investments we're making around the cost of delivery. If we break it down then and look at the R&D area, the R&D area is predominantly embedding Cognigy fully into our CX platform as well as adding additional AI capabilities that are necessary in the large enterprise, but also to allow us to further scale into new TAM.

So adding AI capabilities, for example, and other functionality that are extending us further into mid- and back office workflow as well. And then finally, on the go-to-market, I talked earlier about strategic partnerships. So we are looking to utilize those strategic partnerships and actually invest there to ensure strong positive execution, sales enablement, and using AI tools in our sales organization as well, as well as ongoing hiring of our sales force into the further momentum we see coming.

Okay. You just spoke to -- at your Analyst Day, you spoke to kind of the TAM expanding to $31 billion to $72 billion. Some of that was from this mid- and back office that you just spoke kind of making investments in. Just why do you think that, that could be such a good opportunity for you guys?

It's a great opportunity, and we see that TAM expansion because we're so well positioned within CX. I mentioned that we are a market leader today and have a strong portion of the market share of that TAM opportunity as one of the leaders. As we look ahead in terms of that TAM opportunity and how we fit into the broader TAM, there are 2 areas that are a natural extension for NICE as we execute on our strategy looking forward. The first is looking at extending beyond the front office to mid- and back office. NICE is -- and our CXone platform is both an orchestration layer and interaction layer. We are the sole primary point of contact between our enterprise customers and their consumers or citizens in the case of governments. So we are looking to further that relationship and moving into the mid- and back office through the capabilities we have with workflow automation and further agentic AI capabilities that we are going to even further amplify from the recent acquisition of Cognigy.

So agentic AI capabilities shift beyond conversational layers and allow a more complex execution of specific tasks. So an example would be there, if you are reaching out to your insurance broker and looking for a new insurance policy, today, we can help you provide knowledge management, address questions, put you in contact to resolve any issues you have. As we look forward, that's going to continue to move forward. For example, if you want a new policy, we will be able to, through our orchestration layer, fully fulfill that as one interaction with the consumer. So it's a natural extension for us from beyond the front office shifting into the mid- and back office. That's one area of TAM expansion.

The second area of TAM expansion is that, to date, the CCaaS platform that we offer at NICE has been predominantly inbound focused, meaning that consumers are reaching into organizations to problem solve, to ask questions, to gain education for a variety of reasons. And we have an enormous amount of experience and vast amounts of data that help resolve quickly those types of inbound requests. But we also now have more and more assets from recent acquisitions we have done with Cognigy, but other assets we have acquired over the last few years, which are outbound oriented, and they are more proactive in nature rather than reactive. So this also opens up a great TAM opportunity for us.

And where you see that as an example, is, for example, today, if you are a customer and you are reaching out to inquire with your airline about flight information, we have proactive capabilities that if we see that you have been looking online potentially to upgrade, we can use our same software and our same platform from an outbound basis to actually offer you, listen, we would like to upgrade you at a reduced cost, as an example. So that would be an opportunity that brings us more into the top line growth for our customers, where, up until now, it's been more focused on cost effectiveness, cost efficiency. So that's still an enormous amount of our business, but we have other opportunities extending that I've just talked about.

Okay, kind of leveraging a lot of that LiveVox...

That's right.

Okay. Maybe turning to Cognigy, the conversational AI space is crowded and is expanding, but Cognigy has been a leader within that space. What made Cognigy the best fit for you guys relative to your road map versus maybe some of the other players within this space?

It starts with the strength of the technology itself and ability to scale. More than 50% of our cloud revenue today comes from large enterprise, which we define as $1 million plus ARR. And it is not easy to operate in large enterprise. It means that you need to be able to design and deliver software that can really scale and handle an enormous amount of interactions, both for us, both voice as well as going through digital channels. And so we have an active M&A team that's always looking at the market, understanding the different capabilities that exist in the market. And we identified and had a relationship with several different players, but we saw the strength of what Cognigy was doing in the market as well as a proven ability to provide and deploy solutions in large enterprise.

So Cognigy today has a number of marquee, well-known global organizations. Lufthansa is a great example of a very large, well-known company, where they have great success deploying their solutions in a very efficient and easy way. And so for us, that ability to demonstrate they are effective, can deploy and the scale at the same level that we can at NICE and bringing 2 market leaders together just made perfect sense and further enhancing the AI capabilities that we had already embedded into our platform.

Okay. So kind of a perfect match from an end market and technology standpoint. Just how do you go about kind of cross-selling to each other's bases?

So Cognigy has been, to date, predominantly focused internationally and have just more recently started selling into the Americas. And I would say the reverse is true for NICE, where we have great success in the Americas, and we've started to see really nice momentum internationally over the last couple of years. So it's natural that we have a great opportunity without a lot of overlap of customers for us to cross-sell CXone into their installed base, for Cognigy to obviously sell into our existing installed base.

So both directions of cross-selling as well as Cognigy will continue to sell on a stand-alone basis as well. So for organizations that may even not be ready to move to the cloud, we will be selling the Cognigy agentic AI capabilities to those organizations, which may even be on top of premise players that eventually we will look to, again, accelerate that migration over to our CXone platform.

Yes. Got it. On -- AI and self-service ARR reached $268 million in Q3, grew 49% year-over-year or 43% excluding Cognigy. Given AI now represents about 12% of cloud revenue, what's the path to reaching 30% of cloud revenue by 2028? Is that just all of the things you just laid out are executed on? Just how did you think about what cloud penetration do we need to get to, to kind of get to those numbers?

So we have a very stringent financial model that we do internally at NICE, where we look at how we expect to cross-sell into the different regions and to the different installed bases as well as bringing in new logos as well. All those go into that, along with just looking at the success and momentum we have seen both stand-alone at NICE, where those 40%-plus rates are coming even pre-Cognigy. We also see the momentum that Cognigy has been driving on a stand-alone basis. And at the time of the close of the acquisition, we announced that we expect Cognigy on their own to exit 2026 with $85 million of ARR, and we're well on track for that. So I think the combination of the momentum we're seeing and the pipeline, of course, along with proven opportunities that we've closed throughout the course of this year, where nearly all of our large enterprise deals include part of our AI offering on our platform.

Okay. And then just how does kind of increasing consumption model revenue or kind of consumption revenue impact kind of your visibility of the business?

So AI interaction volume drives AI revenue growth over time. So as customers continue to expand their usage and the consumption above the commitments that they have with us, that continues to drive further growth above the committed revenue. So I mentioned the backlog of the 13%, excluding Cognigy at the end of Q3 that would indicate a potential for accelerated growth in the core of our cloud. And that, of course, is what's on the RPO where the remaining performance obligations that are committed. So on top of that, there's also the potential for incremental consumption-based usage over that and beyond that.

Okay. You mentioned previously that NICE had made substantial progress in kind of expanding its partnership ecosystem. Just how should we think about kind of the time line of these becoming more meaningful, or just kind of how they contribute to growth? Is this mostly lead gen? Just like how are you thinking about partnerships contributing to the growth algorithm?

So we've signed a significant number of partnerships this year, either new or expanded, and Scott has been a large part of building that ecosystem. When we think about the impact of that, some of those partnerships have already been in place today. And in most of those players, we have both a tight technical integration and partnership as well as often a selling and either referral or reseller model as well. So when you think about what the impact is, some of that will come sooner than later. I would say the area where we would expect to see the more near-term impact starting to show up is, for example, in our relationship with AWS, where we're selling through the AWS marketplace.

So it's an area of opportunity to broaden the go-to-market distribution through using that marketplace more than we have in the past. That is something that you can see start coming in more in the near term in the earlier part of 2026. But most of those partnerships take time to train their sales force and educate them around sales enablement, educate them also as well as kind of the newer capabilities around AI and what we have for agentic AI. So you should expect that, that looks more towards the back half of 2026, really into 2027, and we're creating those partnerships for really driving long-term sustained top line growth.

Okay. And then maybe just as a final question for me. We get a question a lot around, you have this strong competitive positioning, profitable FCC business, financial crimes and compliance business. We often hear just like why is this asset still core to NICE? And just how should we think of that as a part of NICE's story, particularly just given what you're seeing in the contact center market?

Yes. So I think we're proud of the success we have across both of our business segments, CX as well as FCC. Clearly, at this point, CX represents about 85% of our total revenue. So it certainly gets more airtime and we spend more time talking about it. But we continue to be very excited and pleased with the performance of the FCC business. It's a great business, is profitable, has many long-term global FIs that have been customers that continue to come back and buy with us year after year. And it has its own leadership and management team that largely operates independently on a day-to-day basis.

So it's a business we continue to be very excited about in addition to CX. I think with respect to the overall portfolio of NICE, this year is no different than any year that we always look at the portfolio of assets in the business segments that we are investing as an organization. And as part of our annual strategy process, look at what is the best way to ultimately drive long-term shareholder value. And of course, that's part of the consideration that we go through annually.

Got it. All right. Well, Beth, thanks so much for being here today. It was great talking to you.

Yes, thank you for having me. Thank you.

All right. Welcome to day 2 of the UBS Tech Conference. My name is Seth Gilbert. I'm one of the SMID software analysts, SMID-cap software analysts here at UBS. And today, we're joined by Beth Gaspich the CFO of NiCE. So thank you so much for being here.

Yes. Thanks, Seth, for having us.

Amazing. You have a relatively new CEO -- we'll just jump right into it.

Sure.

You have a relatively new CEO, Scott Russell. Can you talk about some of the strategic priorities and maybe how they've changed under his leadership?

Yes, absolutely. So we were very excited this year at the start, out of the gate of 2025 to have Scott Russell join us from SAP. Scott was a key driver at SAP and really driving the transformation in that area of cloud, so migrating from premise to cloud. Ultimately growing from about EUR 8 billion to over EUR 17 billion for SAP. So he has great experience on continuing to drive and capitalize on the opportunity of organizations that are moving from premise to the cloud. So it's a great opportunity to have him bring in his expertise to help us really capitalize on the next transformation at NiCE.

Got it. You recently hosted a Capital Markets Day as well. One of the main takeaways I think we had was you're well positioned to win in the CX AI market and about accelerating growth. It's another key takeaway. I guess what gives you the conviction that you'll be able to hit the revenue targets? And maybe you can discuss any recent acquisitions like Cognigy that might have played into that?

Yes, it's a great question. I think we're very excited. Scott came on board because he saw the opportunity in front of us at NiCE and the strength of the assets that we have. So he has really brought on some strategic priorities that will continue to allow us to drive that growth and continue to accelerate growth in the future.

I think I would start with we have a great skill set of AI. It's core to what we do at NiCE and embedded in our core offering. We have recently, as you highlighted, further amplified the strength of that technology through the acquisition of Cognigy, which is a conversational and agentic AI, a leader in the space in customer experience. So when we bring together both the opportunity in front of us with the ongoing migration of organizations and large enterprise from being on-prem over to the cloud, where today, there's still about 60% of enterprises have not yet made that shift, combined with the strength of our AI capabilities, it presents a tremendous opportunity looking ahead.

Now as you start to actually unpack that in terms of what gives us confidence, I think, first of all, we see strength in our core business. Throughout this year, we've consistently achieved our expectations on our cloud growth. We have seen 12% routinely cloud growth of our core business throughout the course of this year. And most recently, at our Capital Markets Day, we disclosed our cloud backlog, which there, we see a 15% growth year-over-year. That's inclusive of the acquisition of Cognigy. We also see 13% growth in the cloud, excluding Cognigy.

So when you look at the indication of the strength of the recent bookings, our strong win rates and other strong indicators, we see that there are clear signs of potential accelerated growth, both in our core business even prior to the acquisition of Cognigy. So the combination of the two really give us this conviction looking forward and the strength of the underlying metrics in our business and also what we've seen from Cognigy, both through pre-acquisition and of course, post-acquisition and the strength of the business that they're driving as well.

Got it. Another key takeaway at the Capital Markets Day, you're doing some substantial investments in 2026 related to cloud and AI to accelerate revenue. And I just wanted to know if we could touch on this a little bit. Can you provide a little bit more detail into some of these areas? Maybe you can touch on when you expect margins to recover and how much of the margin compression might be due to M&A?

Yes. I would start with the backdrop that we have financial excellence at NiCE. If you look on the strength of our overall performance, we're about a $3 billion total revenue company, driving healthy 70% or so gross margins, 30%-plus operating margins. So that's really the core of where we start with our business. And I talked about the opportunity ahead of us, and those are also some of the reasons that Scott Russell decided to join NiCE is looking at the opportunity ahead of us with the ongoing migration of premise to the cloud, but also the opportunity that agentic AI creates for us in terms of how we deliver that into the customer-experience market.

So what we looked at is really with the indicators of the recent accelerated growth in the core business indicators as well as the acquisition of Cognigy, we really wanted to capitalize on the opportunity now and into 2026 to invest further to drive long-term sustained top line growth.

And when you look at those investments, we've estimated to be about $160 million of investments that will be incremental during the course of 2026. And it breaks down really in, I would say, three buckets. There is a bucket of CX and AI and cloud delivery. There is a bucket of go-to-market, and there is a bucket that is related to our product road map. When you look at the different components of how you unpack that, first of all, I would highlight that most of this investment of the $160 million is unrelated to Cognigy and the acquisition. There is a modest level of investment there as well. However, most of this is really core to our existing business and continuing to drive growth there.

So when you start to get into more of the details of what's included in that $160 million, on the cost of cloud, what you'll see is a combination of both continued investments in areas such as sovereign cloud. We offer our software and our AI cloud platforms into large enterprise. We have, in the last couple of years, had wonderful momentum internationally, seeing strong growth. And part of the area that we're investing there is continued investment in sovereign cloud, meaning that we are actually deploying our CXone cloud platform in regional areas to address data residency, to also ensure we have proper feet on the ground in those areas to support those sovereign clouds as well as important infrastructure that's underlying those clouds as well.

So that's an example of some of the areas we're investing in, in cost of goods sold. Also, we're further investing in our third-party partners that we use for deploying our solutions as well. So that's kind of giving flavor around some of the cost of sales.

When you move on into the R&D, we are continuing to invest in our product road map and our CXone offering predominantly. We are -- today have more than 50% of our revenue that is with large enterprise customers. And so for those customers, we are continuing to add capabilities that will further provide additional functionality to those customers, and that's part of the product road map investment that will be consistent with the overall offering of our CX platform and inclusive of our AI capabilities.

And then finally, on the go-to-market side, for the go-to-market aspect, it's a combination of both people, bringing in additional subject matter experts around all of the different offering that we provide. It is also really capitalizing on a lot of the strategic partnerships that we have signed earlier this year.

So with the strategic partnerships, we have either added new partnerships or strengthened existing partnerships throughout the course of this year with AWS, Salesforce, ServiceNow, Snowflake. And with those key partnerships, we are further broadening our go-to-market capabilities. Often, that will also include expanding further on portals or marketplaces with some of those organizations. So that is also built into the go-to-market. And then finally, we are also investing in internal AI tools for our sales organization as well. So that's just an area of kind of some further granularity around the spend planned for next year.

Got it. Super helpful. I want to switch to the competitive landscape a little bit. There's all these flashy headlines for AI-native companies nowadays. You have competitors like Zoom, Salesforce Agentforce and Amazon. They've been ramping as they've been in the market for a little bit longer with their respective products. Has this changed in your view, the competitive landscape at all? Are you seeing some of those maybe AI-native competitors coming up? Or are you playing in a little bit of a different market?

So first, I would share, from our standpoint, we view it as validation that we are in a great space, that customer experience is an area where others are investing and are interested in. And it means that it's an exciting opportunity, which is exactly why we're looking to capitalize on this opportunity now with the strength of our portfolio.

What sets us apart at NiCE is really the power of the platform. Our platform is fully integrating omnichannel routing, analytics, workforce engagement and agentic capabilities that we offer. So it's unique in the sense that it's an interaction layer and orchestration layer that really can't be matched or paralleled by other offerings that are out in the marketplace.

And of course, this is also further complemented by the strong set of proprietary data models that we have that are specific for CX and customer experience and that actually can be used to complement our AI capabilities and drive better outcomes for our customers, both in terms of average handling time as well as the end consumer sentiment. So we're packaging all of that together in a platform that is really unparalleled, and it's one of the reasons why we continue to be a leader in our space in customer experience.

Got it. Maybe one more on the competitive landscape. You're also partners with companies like Salesforce and Amazon. So I'd be curious to know a little bit about the push and pull of those relationships. Are these partnerships creating value for you today?

So we operate in a space where there is a considerable amount of coopetition, which is normal in enterprise software. And it's yet another indication of validation that these players in the market that are partnering with us and other players as well really are looking to take advantage of the opportunity that exists in these markets. I mentioned several of the partners where we have relationships and expanded relationships. So for many years, we have been highly integrated with Salesforce and other CRMs in terms of the offering, which provides a better experience both for the employees that are using those -- the platform as well as the experience that the consumer receives.

So there's a coopetition in terms of the nature of how we interact with the partners. So it's beneficial and ultimately a win-win both for them and us by providing the seamless integration to our customers. And in many cases, most of these partners are both integration partners that we integrate the solutions and applications with. And in most cases, they are also resellers or referral partners. And at NiCE, during the course of this year, 73% of our CXone new bookings have been partner-led.

So they're also really critical as we look forward to the next step of our continued growth and accelerated top line expectation by having that extended relationship, both from the technical integration aspect, but also the reseller and referral relationships that we have as well.

Got it. One more on partnerships as well. We have Vlad Shmunis from RingCentral on stage yesterday. They also have a pretty substantial partnership with NiCE, and they just renewed it as well. But they also have their own solution. So I'd be curious to know how that partnership continues to evolve and how you see that relationship moving forward.

Yes. So we have been partnering with RingCentral for many years, and we're very happy that we just recently, as you highlighted, renewed that relationship with Ring.

I think when you think about RingCentral where they operate and where we operate at NiCE, it's very distinct, that the offering that RingCentral has is appropriate for the lower end of the market. In terms of really more of the SMB space. But they partner with NiCE specifically because as they move upmarket and into the large enterprise, they need a player and an offering that can support the complexity and the ability to scale in the very large enterprise. And so that's where we fit in and why they come to us to have a strong relationship with, to really enter and have ability to step into the high end of the market where we really thrive at NiCE.

Got it. Makes sense. AI is growing. We've seen that from at least one of your competitors, Five9, who we also have on stage. And in 3Q, Five9 came in a bit light on the non-AI subscription revenue growth. Can we spend a moment talking about AI versus non-AI? Is AI leading to a decline in seats at all? And how are you thinking about the split here? Both are important, but I'd be curious to get your thoughts.

So in our business, the key driver of our business is our CXone platform. There are components and solutions as part of the platform that are AI specific. And then there is the core of the business, which is more of omnichannel routing and WM and analytics. So what we see in the core of the business is that the largest growth driver, not surprisingly, is our AI growth. And we've continued to report on that through the course of this year with strong growth recently in Q3, 43% year-over-year growth in our AI and self-service capabilities of our CXone platform. So we see that as a strong growth driver. And the other aspects of our business, we continue to see nice growth there as well. But really, the key driver is the overall AI component of the offering.

So as we look forward, one of the pieces of information that we're looking at that gives us confidence is both that core -- steady growth that we're seeing in the core of the business and the non-AI aspects and then, of course, accelerated and being amplified further by the AI acceleration and trend that we're seeing there. And at NiCE, our pricing model is designed in a way that as AI interactions accelerate and continue to expand, our AI revenue accompanies that. And so that gives us confidence, again, in terms of the go-forward aspect with what we're seeing in AI but also coupled with the strong kind of steady growth in the foundational layer of the platform.

And I'm glad you brought up pricing because it's something that we hear from investors and from our channel checks as well. I think there's periods of time where you're able to take price and there's periods of time where we hear from the channel that pricing is moving down. So I'd be curious to get your thoughts on where we are in pricing today? Has it been moving up, down, left, right?

And then also with AI, it's maybe a little bit of a new area of budget for some folks, some of your customers and some of your customers might be willing to spend and others may be not as willing to spend. So I guess a two-parter. One is where are we kind of in the current pricing environment? And how is AI impacting the pricing environment?

Yes, it's a great question. I think I would step back first and just highlight a little bit of the structure and how we enter into commercial agreements with customers. We sell CXone across all aspects of the market in terms of the size of customer, SMB on up to very large enterprise. However, really where we thrive and where we see the greatest opportunity ahead is in the large enterprise. And I highlight that when you think about the commercial structure, typically, what you see is those large enterprises are entering into a committed spend with us over a multiyear period. And so then you apply the pricing model with inside of that.

And how the pricing model works is it's really two-pronged. So we have a hybrid approach. One prong is based on users or seats and the other is based on sessions or interactions. And so for those customers, those customers can either buy the human-led agent seats under the agent-based pricing and for more of the AI capabilities that are AI agents, for those, they tend to be interaction-based pricing. And then, of course, there is sometimes offerings that we provide, such as a copilot where we are actually augmenting the human agent in the contact center that will have a component of both users and sessions.

So our pricing model has really been in place for some time that allows for the shift that we've been seeing to ever-increasing volumes of more and more agentless interactions or AI-based interaction volumes. So that is what we're seeing as a trend. I think when you think about the non-AI-based pricing or the user pricing, it's more or less remained stable in terms of the overall price that you would think on a per user basis for the platform.

Got it. And then as you continue to move further upmarket with some of these larger deals and these larger deals start to ramp, can you talk about how that will change the revenue mix and maybe even the margin mix at NiCE? And then maybe as a follow-up, can you talk about some of the puts and takes associated with this mix shift towards larger customers?

Absolutely. At our most recent Capital Markets Day, I actually shared some data around the stickiness of our customers, that our customers continue to come back and we will cross-sell and upsell into the customers with a multitude of solutions that we have on our platform. At the high end of the market, there is a high level of complexity that's required around customer experience. And that entails having all of these different capabilities that are needed to deliver upon that. So that is all embedded in the offering that we're providing.

Got it. And then maybe switching over to the international side. In terms of international expansion, can you talk a little bit about the sovereign clouds and how you guys differentiate there?

Yes. With respect to our international momentum, we have seen some really great growth in the past couple of years. And in fact, we have signed two $100 million TCV deals out of our international region over the past couple of years. So we're seeing really strong momentum selling our cloud and AI platform there.

As a result of that, we have continued to invest in sovereign cloud environments. And sovereign cloud is where we're deploying our CXone platform into regions to have data residency that will also include a high level of data security and compliance that's required in these different regions. So it's an area where we are distinct in terms of the ability to offer these sovereign cloud environments. And it's given a great competitive advantage for those organizations, especially large enterprise and governmental agencies that are looking for the level of scalability and confidence in our security and compliance capabilities to the size and scale that we can deliver at NiCE.

So it's an area where we're continuing to invest in. I highlighted earlier as one of the areas that we are investing -- continuing to invest in during the course of 2026 to continue to capitalize on the opportunity because as we look at the international markets, they're still highly underpenetrated in terms of the opportunity to shift customers onto the cloud and further that through the AI offering as well.

Got it. And how does this set you apart from your competition, if at all? Are there some of your competitors where you might compete with upmarket that offer more of the sovereign clouds as much as you guys do? Or is it a big point of differentiation for you when you go into these meetings with customers?

It's highlighted point of differentiation. And NiCE is very distinct in our ability to be able to offer this level of sovereign deployment in country, especially at the size and scale that is required for the large organizations that we're dealing with. And of course, these customers can continue to buy more and more of the offering as we continue to offer more AI capabilities that also allow them to continue to shift from the higher cost of human labor over to using our AI capabilities. So it's a great ROI for our customers, and it drives incremental revenue for us.

Got it. Maybe we'll shift over a little bit to capital allocation. And I'd be curious to know what you're thinking about share repurchases and also maybe you can touch on furthering M&A as a tool in the toolkit.

Sure. When we think about our capital allocation strategy, there's essentially three pillars. One is which -- continued prioritization of investment. So that's investment both back into our business organically and that we've talked a little bit about. It's also ongoing investment that may be through M&A. The second pillar would be share buybacks that we continue having a program. And then the third is just the strength of our overall financial foundation as a company, but the robust balance sheet that we have and the significant amount of cash flow we generate.

So let me talk a little bit more about each one. When we think about investment, if we look at what's expected in 2026, we expect most of that prioritized investment to be the $160 million that we talked about of incremental spend back into the business. We just recently concluded the acquisition of Cognigy, and that's where most of our focus is expected to be during the course of the coming 12 to 18 months is continuing to drive momentum in that business and prioritize the integration that we're looking forward to the accelerated growth that will come from that acquisition. So that's with respect to acquisitions.

In addition to that, we do leave ourselves open to potentially doing more tuck-in-type acquisitions. And so that is something that as we look at what our customers are looking for in terms of additional capabilities into the platform that we leave ourselves open for additional acquisitions.

The second pillar I mentioned was the share buyback. So earlier this year, we mentioned a $500 million share buyback. We have already increased through the end of Q3, an 18% increase in our share buyback on a year-to-date basis. It continues to be a priority for us in terms of the buyback. And we're in a beneficial position that we generate a significant amount of healthy cash flow at NiCE. In fact, we generated almost $700 million over the last 12 months. So that allows us to continue to utilize that $500 million buyback program that we have in place.

And then finally, the health of our balance sheet. And with our balance sheet, our balance sheet currently is debt free. We just paid off some of the debt on our balance sheet at the end of the third quarter. So we also remain open to taking on additional financing, really up to the level about 1x EBITDA in terms of potential financing that we might consider taking as well. So those are kind of the three pillars and kind of adding some additional color around capital allocation.

Got it. Well, thank you so much. I think that's all the time we have for today. But thank you for joining us, and thanks for being here.

Yes. Thank you for having us. Appreciate it. Thank you.

Good morning. We're going to get started. Hi, everyone. I'm Ryan Gilligan, Vice President of Investor Relations here at NICE, and we are thrilled to welcome you to our 2025 Capital Markets Day. Before we begin, I need to quickly show you this disclaimer slide. There we go. Just a quick note that the presentation does contain non-GAAP figures.

Okay. Now we can talk about the great day that we have planned for you all. So in just a moment, we're going to pass it over to Scott Russell, our CEO, who's going to lay out his vision and our opportunity. Scott will then turn it over to Jeff Comstock, our new President of CX, Product and Technology. After a quick break, we'll go to Phil Heltewig, our Chief AI Officer and the General Manager of NICE Cognigy.

And then we're very fortunate to have Nick Allgaier from Lufthansa join us. He is going to share his perspective as a customer. And then we'll go to Niraj Verma, who's our Vice President of Customer Service Automation. And then lastly, we'll wrap with Beth Gaspich, our CFO, who will provide a financial overview. After that, we'll take another quick break. At that point, those of you that are in the room can step outside just there and grab lunch and bring it back into the room. And those of you that are on the webcast, you'll have an opportunity to type in questions. And we do ask that everybody save their questions for this formal Q&A session. So with that, I will turn it over to Scott Russell.

Good morning, everybody. Hopefully, you've enjoyed breakfast. Thank you for being here. Thank you to those who are online. It's very much appreciated that you've joined us for the next few hours as we go through an update for our investors and the financial community in the capital markets session.

First of all, I do want to just recognize and welcome Ryan. He obviously has only just joined us. We put him under fire. He joined about a week before our first earnings and Capital Markets Day. He is now an expert on the company. But very, very happy to have Ryan join us and lead our Investor Relations as a part of our leadership team.

Before I jump into the agenda, I did want to just recognize you might have seen a PR this morning. We've announced this morning a new COO, Arun Chandra, who has joined us, who is joining us on 1st of December. Arun comes from one of our customers, Walt Disney Corporation. But before that, he was an executive that worked with Meta, at HPE as running all of their operations. He also was the CEO of 2 -- 3 tech companies.

But he comes to us very much as a partner to Jeff Comstock around to make sure that we deliver value and we as a company are an AI company the way we run and then how do we deliver the value for our customers. So very excited for Arun to join as a part of our core leadership team combined with Ryan and Jeff and others who have joined us recently.

Okay. So today, I'm going to cover and if I can ask one thing, it will be to remember these 3 things. There are 3 things that we're going to go through the entire day that hopefully will resonate with you and recognize. First of all, we operate in a great market. And I'm going to talk about why it's a great market because I think that sometimes gets questioned. Why is the market that we're in a good one? Why would that be a positive? But I'm going to go into a bit of detail about the trends that are in our favor in the customer experience market.

Secondly, we will clearly highlight why we are perfectly positioned to capitalize on that market opportunity. We will not only talk about the AI trends, and we'll go -- you'll obviously hear a lot about AI today, but we'll talk about we as a company, whether it be our financial position, whether it be because of our -- the acquisition of Cognigy with the AI capability, but also just the broader portfolio that we have as an organization and how that best sets us up to be able to meet the market needs, which is a great growing market.

And then last but not least, is clearly highlighting and articulating how that drives accelerated growth, accelerated shareholder value via some focused investments, and we're going to go into the details of that. Beth will speak in a lot of detail about what those growth drivers are, what the outlook looks like, what the growth looks like. We will be sharing midterm guidance for you and indicators of what those variables are. And then we'll obviously answer your questions later on in the day.

So great market opportunity, which I will primarily cover, why we're perfectly positioned, and you're going to hear from the speakers, Jeff, Phil, Niraj, talking about our technology capability and why we believe that we're best positioned and then how that translates into accelerated growth, accelerated shareholder value and via some focused investments.

So before I do that, let me just give -- for those of you who are not deeply knowledgeable about NICE and who we are and what we do, let me just recap. And I get asked this question a lot this year. For those of you who don't know, I'm in my 11th month. I feel like I've been here for 11 years. I feel like I've been in this organization for a long period of time, and that's in a good way, by the way.

I feel like I'm -- this organization was built for me and I was built for NICE. But I get asked the question, why did I join? Well, I wanted to join a leader. I wanted to join a leader in their respective market. But I also wanted to join a company with the appetite to drive the vision and the willingness to seize the opportunity that AI brings to its respective market. Leadership in its current space, but the appetite and the capability and the drive to be able to go and utilize because AI allows technology and humans to converge better than any other. And I've been in the technology industry for over 30 years.

We are the #1 company in customer experience, and we'll talk more about that. 27,000 customers around the world, leveraging our capabilities, 10,000 NICE’s in different parts of the planet, serving our customers. The majority of the top banks, the majority of the Fortune 500 or Fortune 100 and Fortune 500 leverage our company every day. And while today is going to be particularly geared to CX, it's a worthwhile reminder that we are not only leaders in customer experience, we're also leaders in financial crime and compliance, protecting $5 trillion a day of transactions that happen through our Actimize our financial fraud and compliance portfolio.

We have 30 million pieces of evidence supporting first response also for those who are in need with 911 recording and being able to support in the public safety and justice business. So we are a market leader in our own right, and we are well set up. As I say, we lead the market today as an organization. And clearly, we do so in a very financially responsible and attractive way.

So the massive CX opportunity. Why do we believe this is such a great market? Well, I think in the hype of AI, a few things get lost. Every customer we speak to starts with this. They start with what is the business value for their company. Now it could be triggered by problems or issues. But fundamentally, companies or brands that invest in customer experience outperform their peers. You can do any research you want. We obviously have done research from different categories. So whether it be about increasing your top line, whether it be about reducing your cost, whether it be able to get operational improvement, whether it be about delivering a higher customer sat.

Businesses invest in CX, not because of AI, they invest in CX because it delivers business returns, period. And that is still true today. I'll talk about AI in a moment, but companies that invest in CX perform better than their peers. And it's proven and they're able to showcase that. For example, just a simple example, if you take Bose, they're a great company, you might use their technology in your car or in your home. They leveraged CXone, they consolidated all on our platform. They increased their customer sat by 30%. They reduced their operating cost and their core volumes by nearly 20% and they increased their CSAT, so they're happier customers by over 20%. So they were able to achieve through focusing investments on their CX platform, they are able to get a better top line.

They doubled their sales during the holiday season as a result of having a better customer experience. Increased customer sat, reduced cost, better returns and better revenue. So I say this because sometimes we can get caught into the hype of what AI means in this market. Companies are investing in CX and they will continue to do so because it's good business. It is good for their business to do so. And it's a market that is naturally growing. We sit here today, call volumes, digital interactions, AI interactions are naturally growing.

Consumers are interacting with their brands more than ever, and it will just continue to rise. So just as a natural market where businesses are investing, they're seeing more and more volumes coming through. And our data reinforces that, not only because we're acquiring, winning new customers, so our volumes, but if you take NICE in the last months, in the last 9 months, our AI volumes have grown by 65%.

Our digital volumes have grown in the mid-40s and good old voice has grown in the mid-20s. So not only are we winning in the AI market, it's not at the expense of others because the whole volume of interactions between consumers and brands are increasing. And here's the thing. This -- that number doesn't include some of the things that you're now seeing in the market. And you'll hear a little bit, and I know Nick will talk about the Lufthansa example, where, by the way, they were able to automate, I think, 16 million-plus interactions on their Cognigy platform.

But this doesn't even include where you think about how consumers are going to interact more with their CX platform rather than websites or apps because they're just going to chat. They're just going to converse. They're going to interact on a conversational platform that will increase the amount of volume that goes through their CX platform. That doesn't even include here, machine-to-machine, where you tell your agent on your phone, hey, I want to call my bank. I want to be able to increase my credit limit.

And at the same time, can you contact my airline because I want to rebook the flight with my family. All of those interactions, the volume of interactions are often limited by the time and capacity we have as consumers and as humans, a lot of those constraints go away. That's not built in here. This is just pure volume of interactions that naturally is happening between consumers and their brands. But if that market was great, well, it just got a whole lot better. It got a whole lot better. This is a massive market. The AI potential, the transformation that it brings, the opportunity it brings in CX has got a whole lot better.

Why do I say that? Well, first of all, you're going to hear a lot today about fully autonomous resolution. So I think we've all had the experience when we've called in or we've chatted to our brand of choice, and they use words like this. Look, let me just put you on hold for a few moments, if I can, please. And then you don't know what's happening.

But right now, that agent is pivoting and they're going and chatting and interacting and conversing with different parts of their organization to resolve your request. And it might happen multiple times because they might have to operate with multiple individuals in the organization. So unless it's a knowledge-based request such as a password reset or checking a balance initially on those easy automated plays, then the ability for organizations up until the use of AI was pretty limited. You are still response -- you still needed a human in the loop. Well, we can do that automated with AI. And we can do it again and again and again at scale.

As I say before, the Lufthansa example is a great one, but it's not the only one, and I'll talk a little bit about our customer references. The second is our journeys are customer-driven. Most enterprises, when they talk about AI, they're talking about how they can replace what humans do in the enterprise. Our focus is the customer's journey. It is very different lens on how you use AI to deliver an outcome. When you're trying to use AI to complete a task that an otherwise an internal employee would do, yes, sure, that's useful. And we do that as well for the front office. We'll get to that.

But our emphasis is the customer journey. So you do get full resolution in an automated way. And all of the interaction needs, whether you ask for it as consumers or whether the brand wants to contact you to be able to fulfill an outcome, it can all be done automated, autonomously on the platform. So that going from reactive to proactive, using the data, the intelligence and being able to drive a proactive model rather than a reactive one, which has historically been in the world of CX.

I want to highlight the seamless human and AI experiences. Every company, even if they want to go to a full automated model, will not do it in one go. And I would contend that there are many businesses, and I'll highlight this, that don't want to go to a fully automated model. They want you to contact and talk to somebody at the other end. Why? A ability to upsell and cross-sell, ability to be able to provide different levels of service.

There are some businesses, particularly in life sciences and health care, that they want the first interaction with AI, understanding intent, understanding your needs, but they will intentionally take you to a human agent because your needs give them an opportunity to perform a task for you as a consumer better than what an AI would be because they want that human touch.

But even then, -- even then AI will play an active role because we will be supporting, assisting using the same models, the same data to be able to converse with that consumer through the human agent. So AI is a tailwind for NICE for this market. I'm talking about the market. It is a tailwind. There is no doubt. The market is great with CX, interaction volumes continue to rise, and we have got a market shift where the value proposition back to the core business drivers and the opportunities that AI brings are continuing to expand our opportunity, and I'll talk about that in total addressable market terms as well.

So it not only gives us the ability to automate automated self-service, but we also have the ability to do assisted service with humans in the contact center as well. But here's the thing. While we are incredibly bullish and we are, we are incredibly bullish about the opportunity that AI brings to be able to automate low-complexity transactions. And there is -- you can debate what low complexity looks like, but there is a large volume of interactions that are happening with contact centers today that can be easily automated on the NICE Cognigy platform today.

Today, you can do that, and you can do it in a really scalable way. But we also recognize to my earlier comment that some of the high-complexity transactions, the things that are really difficult0020to be able to serve and deliver or as I say, where they are intentionally wanting a human in the loop, there is still a lot of intact serve. So this isn't a market where it will replace all of the human work.

And even if it ultimately gets there, the period of transition is a long one and one where to deliver the full CX needs, you need both, and you know where I'm going with this. But as I highlighted before, even in that human in the loop, those interactions will still be AI assisted. We do not see a world where AI does not play a role in the customer experience market. So either fully autonomous self-service or human and AI working interoperably or human engaged service where your customer service representative is interacting, but it is assisted by the AI platform. This is a market that is fantastic.

Great business value, great business value, interactions volumes continuing to grow. Clearly, a market where AI is giving a significant shift and boost and a tailwind and an opportunity for us. And then ultimately, it is a market where it is not one or the other, human engagement in the contact center, AI, automation and assistance in that platform, end-to-end, it is a growing market from both perspectives.

So why are we positioned to win? What is the strengths of NICE to be able to capitalize on this? Let's just start with our current momentum. These are numbers today. 20 billion-plus interactions, 20 billion interactions across all of the major industries, AI interactions, human interactions, combination thereof that are coming into our platform every single day around the world. I mentioned the growth of voice. I find it remarkable because humans still like to talk and chat and sometimes they want to talk to somebody whether it be an AI agent, but we had over 1 billion minutes of voice, [indiscernible] voice in September, over 1 billion minutes.

So there is a lot. And that is with average handling time and call times continuing to reduce because businesses are better and better. They're getting the AI assistance to be able to make calls shorter, faster, better containment. We are a company that has had 40 years of experience in this market. We understand customer experience better than anyone. We understand the intents, the needs, the contextual, the behavioral. We understand the skills that are required. We know what a good interaction looks like and what it doesn't. All of that knowledge, all of that experience, all of that logic, all of that capability is core to the platform that drives all those interactions, drives those engagements and helps businesses deliver on the business promise that I mentioned at the beginning.

But we're not just getting started in AI today. And you saw the numbers in Q3 that we reported last week, 49% growth in our AI ARR and self-service. Effectively, we are growing, and there's over 6 billion augmented interactions on that platform. So the ones that are coming in, there is a significant number that are already AI assisted or AI delivered in a self-service way or in an assisted way.

And clearly, the traffic growth continues to rise and grow. As you could appreciate, for us to be able to continue to grow the revenue line, we've got to have the volume that is growing, and then we're able to monetize that volume. What's interesting about the AI, the traffic growth is this. One interaction can lead to many, many AI sessions.

Just think of the flow. You first call in, you have an interaction, you've got a need, maybe you've got a -- well, an example that Niraj is going to talk about later is a dispute on a credit card, you call in and you're interacted by an AI bot. That is trying to determine, number one, what is your intent? What are you there to solve? Number two.

And usually, it will already have the prebuilt logic about who you are, how you like to interact, not only the language, the style, the behavior, the sentiment that you have and be able to change based on the tone and your interaction. But then that first session says, look, we need another bot that needs -- is specialized in dispute. And so it will go into details, and it will another AI agent that will be triggered.

That AI agent then says, look, this requires someone -- this is a complex one. We now need to get a human to be able to step in. So they hand over to a human agent. A human agent then has a copilot where they're interacting and there's another session. That Copilot then gives assistance to the human agent about how to resolve the task and then it gets handed back to an AI agent.

So one interaction, which historically you would have seen in our commercial models, and Beth will talk about commercial and pricing, that would have been a user-based human where we had seat-based pricing. But in the AI world, it's not one-to-one replacement because we're able to increase the volume of interactions and not only those interactions increasing, the number of sessions and AI services that we can run can then be multifold.

And that's what's driving a lot of that traffic growth above what you're already seeing in the momentum in the transition to self-service. And that clearly translates to a financial model that is strong. Not only is the AI growing at 49%, we're nearly at $3 billion in 2025. We updated our full year guidance and increased our outlook for 2025. But even more importantly, we're a cash -- free cash flow, we're a cash generation machine.

So our ability to be able to generate real value for our customers is also translated into a financial performance where not only we're growing our top line, but we're then generating true value for the company that we can then transfer to our shareholders. But we don't believe ourselves only. The market also recognizes us. There's not many times where a vendor can get up and say they are the #1, undisputed #1 according to all of the industry analysts.

This isn't our data. This is theirs. Cognigy was ranked #1 for conversational AI for CX. The NICE business was ranked both highest in vision, but also highest in ability to execute in the Gartner Magic Quadrant for Contact Center as a Service.

Clearly proven leader is the #1, ability to execute and vision. We're the #1 in intelligent self-service. We're the #1 in intelligent contact centers. You can see the list. And all of these analysts spend their time and effort, and I know you interact with many of them. Their job is to analyze the industry and who is best placed to be able to serve this market, deliver on those outcomes and advising companies who to go to. What does that mean?

We get a lot of inbound demand from our customers that has already been prequalified, validated by these industry analysts. These industry analysts are constantly assessing the movement and the change and the role AI plays -- and so they are very deep in our industry and the knowledge on what we serve, but also what we need to be to continue to be the best.

And if they weren't proof enough, I guess you can just look at the world's leading brands that have chosen us. Every one of these companies, and there's 27,000, I couldn't put 27,000 names up on the slide. 27,000 companies that have chosen NICE as their brand of choice -- their CX platform of choice. Every one of these has a business story of value.

So whether it be an espresso that implemented our platform and they were able to increase automated payment completions, automated payment completions by nearly 30%. Every one of these scenarios, and I'm so pleased Nick is here to talk about the Lufthansa story, but there are so many stories. Every one of them driving business value, every one of them are clearly looking for the outcome, the benefits and the results and every one of them improve the capability of our platform because we're able to then serve more needs, more data, more capability that we can then reinvest back into an AI-led platform.

So how do we do it? How are we the market leader, validated by the industry analysts, validated by the customer market and in total revenue terms, we are the market leader as well. Well, we are the only company that has a purpose-built platform for CX. And you're going to hear this a lot from us today. What do I mean by purpose built?

Well, number one, it is a platform that is only focused on CX. There are many other technology companies that want to cover tasks, workflows, cases, processes. They want to cover all of your different organizational things. They're trying to be experts at everything that happens in the enterprise. In my view, that's not possible. If you want to go deep and you want to be rich and you want to have a great customer experience, you've got to have the logic, the knowledge, the capability that is purpose-built. NICE Cognigy was purpose-built for using AI in customer experience.

Now you can use AI for all sorts of purposes. You can use it in your supply chain. You can use it in HR. You can use it in your finance, you can do it in your operations, and you can do self-service in those scenarios. They built it specifically for CX. And of course, NICE in our history, whether it be in workforce management, whether it be in the contact center, the Contact Center as a Service, our whole company was geared around CX.

So we're the only organization that has the full suite of capabilities. The AI platform is native. I'll come to this later, but let me just say this. The other contact center as a service players do not have an AI native platform of their own. They have to use somebody else's and embed it into their platform. They don't have their own. We do. The advantage that, that brings us to win in this market is immense.

And Jeff and Phil and Niraj are going to showcase how that will play out, why a combined platform where you've got native capability all in the one stack matters. But it's also a platform that has all of that data, that 20 billion interactions per year, that's all [indiscernible] it's repeatable value. Every interaction adds to it. We get more context. We get more knowledge. We get more insights. We can build AI CX-specific models that is solving for those scenarios, and it's transferable. We can do it by industry.

We can do it by horizontal. We've got the ability to use that interaction data, that leading volume to our advantage to ultimately deliver a better experience for customers. It also is a platform that allows for that end-to-end journey, so we can get better resolution. And what I mean by that is we own the point of engagement. So when it comes in, whether it's a chat, whether it's an e-mail, whether it's a text, whether it's a call, whether it comes from an AI ChatGPT or whatever platform they're coming in, once it hits the enterprise, we are the platform of engagement. We are the customer engagement platform. It's a moat.

It goes into there. Why does it go into that platform? Where there are rules, guardrails, knowledge, systems to interact with. You're not going to let your consumer interact and have a poor experience. So not only does it need to be responsive and scalable and knowledgeable, but it needs to operate within the framework that the enterprise has set. And that's not a static requirement.

Businesses are constantly evolving what they want their customers to see, what services they want to render, how they're going to deliver against that. So that platform becomes the gateway of value for a company. Now historically, in the contact center, a lot of those calls were simply contained. Anyone can create a bot that says, hi, Scott, how are you? What's your request? I say, look, I want to dispute something that's on my credit card. And they say, fantastic. I've got that for you. I will get a service representative to contact you shortly, finish. That's not resolution.

That's simply containing that first request and then you sit there as a consumer waiting for that call to come back, that interaction to come back. With our platform, we take the call, we interact, we're able to resolve it real time, including performing tasks in the mid and the back office through AI agents, and we're able to deliver end-to-end resolutions. So we own the point of engagement, but we also then turn that intelligence, that knowledge we have with customers, and we turn it into autonomous interactions -- autonomous actions.

I can't tell you how important that is. Contact centers were often built because they had certain levels of constraints, how many humans, how many people could be staffed and they were never staffed for peak volumes. So when an event occurs, you can't possibly, which means you then they also manage the handling time. How long are people waiting and interacting on that call, and they're constantly trying to reduce it.

But they're also then measuring that first contact resolution. So can they resolve it now with knowledge ways that the agents can. But there's no -- if you're a large organization and you have got tens of thousands of different types of intents coming into your business, I don't care how smart the customer service representative is, they're not going to be able to be specialized. So you needed specialization in your contact center.

All of that knowledge and how that gets delivered, that is now being embedded and used from an AI purposes in our platform. We use that same data, that same knowledge, what a human agent does, how they interact, what those and then we look to do it in an autonomous way. So every channel, every journey, every interaction, AI in the loop, human in the loop, it does not matter. It all goes into that one platform, and we're able to then learn and use that for our customers' benefit in either a human way or an AI way.

And it's built on the industry's largest CX data foundation that the market has. And then clearly, we can then do autonomous delivery and being able to get a better outcome, higher resolution rates, reduced cost to operate, improved customer service through CSAT. So that platform then gives ongoing value, whether it be in assisted or an autonomous way.

And this -- and I think you've heard us talk about this before, but this is why when we talk about the mid and the back office and the role we play, this is what we mean. Our platform, a contact center by its very nature, the platform was built to serve that first contact. It was the first brand guardians to be able to take that inbound digital, that chat, e-mail, text, call and being able to find a way to resolve it usually through knowledge or specialized tasks.

But if they weren't able to resolve it, that they would then contain it, so then there was a follow-up activity afterwards. Well, with AI and the build of AI agents, our platform able to build AI agents that can solve the tasks that you need as a consumer, and we can do it real time. So no, I'm not trying to pivot our company to be a mid- and back-office player. We're not going to be an ERP. We're not going to be any sort of back-office enterprise HR finance systems, but we will build and deploy AI agents that will perform the tasks that they do in the mid and the back office for customer journeys.

Remember, we're purpose-built for a customer journey, which means I'm not interested in trying to replace what a billing clerk does. What I am interested in is that there is a task to be able to approve a bill to -- a charge on that bill back to Niraj's example later, I want to be able to automate that task. We can do it from our platform. You know why? Because we interact with every business system that is out there, every CRM, every ERP, every back-office banking system, insurance systems, every back of airline systems.

All of them have already got the prebuilt interactions. We've already got that connective tissue. We simply leverage that to be able to create AI agents to be able to solve the consumer journey. And I highlight this because AI can be used for many reasons. But just because you've got an efficient back office doesn't mean you've got a great customer experience.

In fact, I would argue there are a lot of businesses that might experience that pain because they're looking at how do they reduce the cost of somebody in finance or in payable or in credit or in claims rather than thinking about what's the customer's experience and how do I make it better? And how do I use AI to fulfill against that? So again, we are purpose-built for CX. But what it does mean is it gives us adjacencies, and Beth is going to talk about those adjacencies. We've lived and breathed in the world of customer service for a long period of time.

We'll continue to do so. But we were largely contained to the front office. To deliver customer service, we're able to now move into the mid and back office to complete resolution, fulfillment of customer needs on this platform. But we're also then able to move into sales, into marketing. Organizational internal boundaries are being blurred. Why did you have a specialized sales outbound team that was different than your customer service inbound team? It was largely the skills and the capability and the needs that you had to serve to. It was based on the human constraint.

But if you think about it, if you're interacting, which is why, by the way, many, many customers still like to have human assisted in customer experiences, if you've called in about your pharmaceutical, you're making sure that your drugs that you need for your life needs and the delivery of that is on time, that if you're interacting, hey, there's also some herbal remedies or other products that you can take, you can proactively do an -- you can assist them, you'll be able to upsell on the same platform.

So customer experience is not customer service. We say it intentionally. It is customer experience, fulfilling all of the needs of service, but then the opportunity to go beyond that into sales, marketing, commerce from a customer journey perspective.

The last thing I'll say about this is it will increase our market immeasurably. So in ‘20 -- interactions for those who joined me, you would have seen that our total addressable market is about $31 billion in the market that we operate today. We estimate based on the opportunity that AI brings both agentically and conversationally, but also the expansion of the CCaaS market, this market continues to grow.

I'll come to our growth drivers in a moment. And the ability to go into the mid and back office, we will more than double our total addressable market within the next 3 years. This is a great market of which we are well positioned to capitalize on. And if we do our job well, we are able to then grow. And last but not least, if you weren't convinced up until now, we did some research or more importantly, BCG did some research -- and they were able to assess and they went to NICE customers, non-NICE customers. They went to a broad section of different customers.

And it was a really interesting bit of feedback around how companies are thinking about who they will buy their AI platform from in the context of customer experience. This isn't who will I use for AI. It is who will I use for AI in customer experience? So let me just go one by one, if you don't mind. 40% of the respondents said that they would buy it by AI from their CCaaS provider if that CCaaS provider has a world-class AI platform. Why?

Well, it makes sense if you think about it. Why would a company that's already invested all of that capability and logic into their CCaaS platform? If it's got an AI native capability, one of the first things you'll do is you'll do human-assisted. When we first launched our AI capabilities, you could appreciate the majority of our early AI platform was assisted. It was Copilot.

Because you're trying to make your human agent, which was under a lot of pressure, high turnover, really difficult skills to be able to recruit and then retain, high-pressure environment, inbound, unhappy customers, we're trying to make it easier for them, better for them. So we're improving the productivity.

So real-time assistance, contextual assistance using that data on the Contact Center as a Service platform. But then it expanded into auto summary and insights from the different calls. It changed how quality management was done. So instead of getting a call recording and having to decipher and a supervisor, you would then be able to do real-time insights that made it easier for managers and supervisors to be able to assist and train their agents.

But then naturally, as you could appreciate, our autopilot then become more -- because we already understand what the interactions are. We already understand as a contact center platform, what can be automated. Again, we've got great data, and we can already tell them using automated insights, hey, these interactions are purpose-built for self-service. And so of course, that self-service autonomous play became part of that CCaaS platform. So no wonder, 40% of the respondents said that they will buy their AI from their CCaaS vendor. Now NICE, up until the 9th of September, that was where we got our growth from.

Did companies come to us when we weren't their CCaaS provider? No. And by the way, they didn't go to any of the other CCaaS vendors either. Because if you don't have an inherent AI platform to be able to deliver to it, then why would you go to your CCaaS vendor? It's got to be -- and what the market has now decided is you can't just have average capability. It's got to be great. It's one of the reasons why Cognigy was so important because we understood what their needs were. We didn't want to OEM a third-party product.

We wanted to have our native capability to be able to serve those customers, those installed base customers the best possible way. And that meant we needed a significantly improved AI platform to do it. NICE Cognigy delivers against that. The second most -- the second highest amount of choice was to go to a CX or so an AI-specific vendor. NICE Cognigy is one of those. And you know about the other ones. There's a ton of capital going into these companies in the market.

You know them, Kore AI, PolyAI, Yellow AI, Sierra, Deca, -- all of these companies are built where a business says I want to go to an AI-specific player to do my AI service for my -- in the context of customer experience. Well, now we have got market leader in Cognigy with both conversational and agentic AI to go compete with that market. And it doesn't matter. It does not matter that we're the contact center or not.

In fact, I'll tell you this. We are going to aggressively go after every, every, every company. We're going to be explicit to go after everyone that uses another CCaaS platform because what a great opportunity for us with the richness of knowledge that we have to be able to have an embedded -- Cognigy is fantastic as it is. It's going to get a whole lot better on our platform, but we are not going to say to those customers, you must use our CCaaS.

We are simply going to go to those customers and say, use our AI platform that is a market leader in its own right. And by the way, the journey will likely get you there in consolidation because we will then have the ability to show a better together story versus not. So the first, the highest places where companies will go for their CX AI needs is the CCaaS vendor and a purpose-built player. We are now able to natively capture that.

And you can see there that, yes, this market does sometimes go to a hyperscaler. Now what they usually do there is they'll do that because they're trying to build themselves and they want the inherent use of the underlying technology. And yes, they'll sometimes go to their CRM player. But here's the thing. We get the feedback. Why would you go to a company that is focused around the internal employee and usage of a CRM platform when the whole goal is customer experience from a customer journey. That's what we do. That's what we've always done.

And so a platform that delivers great customer journeys is very different than a CRM platform that is about the business value that you can get from your internal business outbound to customers, very, very different. And to give you a simple example is Sony. So Sony hit all of these identified measures. They had a challenge. They were a company that has got a lot of different sub-brands, as you know, whether it be the TVs, different devices, PlayStation, et cetera, et cetera. And they had a whole lot of inbound where it was not easy for consumers to be able to be navigated to get the right response at the right time, the right service. So the first thing they did was they consolidated all of that customer experience on to CXone and put it all onto the platform.

Once they were on the platform, what they then did is they used all the data, which was primarily human-assisted interactions. So you would call or chat or whatever with Sony. And we used the data and we identified the top self-service scenarios. And then we purpose-built it on the platform so that they were able to create all of those self-service scenarios natively and then could interoperate with the humans that were assisting.

And so what did they deliver? They delivered an increase in customer sat. They delivered a reduction in cost because they were able to contain more of those interactions via self-service and autonomous channels. And they were able to increase their revenues because they were able to get better feedback, better responsiveness that was then able to get better performance from the top line because they were able to get more upsell through the same mechanism on that platform. Increased revenue, reduced cost, better customer sat. So again, I'll just repeat why we are poised to win.

We are the only player in the CX market that is an AI-native CX platform. CCaaS players don't have it. I'll say that again. CCaaS players don't have it. We are the only ones that do. We're also the platform that owns the engagement. CRMs don't own the point of engagement. It has to get into the enterprise before they can do anything with it. So our platform, that first point of engagement is what we're able to contain no matter how and when those interactions, 24/7, 365, never down, being able to make sure we deliver against that promise. We have the CX domain expertise. Hyperscalers don't have that.

Hyperscalers do not have CX domain expertise. They've got great technology. And same with the LLMs, by the way, the big AI players. We leverage those. We use the generative AI models. We love the large language models, and we're very agnostic about which ones we can use. But they don't have the -- they don't understand the guardrails, the rules, the knowledge, the insights, the small models, by the way, to make it cost effective as well. You don't want to be going always to your large language models when you don't need to, but we're able to deliver upon that natively out of our platform.

And the human and AI engagement is going to be an interoperable one for many, many years to come. It's not going to be AI only or human only. It will be both. Well, that's native in our platform. So those AI domain players that used to be nice Cognigy and is now part of us, they could only do the AI piece. They can't do all of the other voice and all of the other channels and all the other interactions that requires human in the loop.

And enterprises, especially large enterprises, must have the ability to do both. They want the ability to do both. They need the ability to do both. And so the native platform that brings that all together is something only we can offer. I can tell you all of those 7-figure deals that we present each quarter and it keeps on growing. Quite often, it's just a consolidation of fragmented stack. They've used different technologies for different pieces, and they consolidate on the platform.

Now that we've got an AI native platform, our ability to do that is better than ever. So we feel that we are in a great market, and we are really well positioned to win. So what does that mean for growth? Well, let me start by saying we have a number of growth catalysts, things that we see here and now that will drive our midterm growth.

Let me quickly go one by one. The first is AI growth across every touch point. So clearly, yes, our NICE Cognigy platform will be taken to every installed base customer we have. You can be assured of that. Every one of those customers has AI needs. Some of them might have already implemented something basic, something advanced doesn't matter. We are going to make sure that we leverage not only that 40% preference, but all preferences because we've got a full platform and we're going to take it into that market, and it is a large market.

But we're also going to make sure NICE Cognigy is a winner in the AI CX stand-alone market as customers decide that's the way they want to go. It is a market leader already, and we will continue to make sure it is. But we will also -- number two, we will automate our agentic AI on our platform. So our NICE Cognigy platform and the Agentic capabilities, combined with the CX platform combined together into one offering a compelling offering using the data, the knowledge, the insights that becomes better together, we will then be able to provide better automation, better offering, something unique that the market hasn't -- isn't able to do, and we're going to do so quickly.

And Jeff will talk a bit about what our focus areas are from an engineering point of view to capitalize on that opportunity. The third growth catalyst is the one that you all know very well, and that is continuing the CCaaS jumps. Our win rates are improving. They're getting better. We see that. We see our win rates, but it's also the market continues to move across.

So this is a good market. About 40% has moved. You can debate about the stats on that, but about 40% of the market has moved to a contact center in the cloud. So there is a significant amount of jump balls that we are competing for and win. And let me assure you, when we go for those CCaaS moves, we're going to be using our AI capability as a differentiator from what we've already got.

We've already got the market-leading platform. It just got a whole lot better. I think you can see and my emphasis on international and partnerships is a key growth driver. International expansion is tracking really well. I've got to acknowledge that the company had invested heavily and continues to do so in sovereign clouds and capacity around the world, U.K., Europe, Asia, -- we're able to then get greater expansion with our market-leading platform.

And because international hasn't moved as quickly to the cloud as what it has in the U.S., the opportunity for us to be able to go straight to that combined platform has become even more compelling. And we're seeing that such as what you saw with DWP that originally chose purely on the CCaaS platform and then quickly said, look, we'll use all the AI capabilities that you have got at NICE to be able to then extend and then transform even faster in delivering to the U.K. citizens.

And then last but not least, as a growth driver is going beyond the contact center. I mentioned going into the mid and back office and doing more customer resolution and automation from our platform rather than purely the front office. And I also talked about going beyond customer service into sales, marketing and other areas. That growth driver, what you're going to hear is not really -- this is more an engineering growth catalyst that will drive into a sale. So it's not really a significant number in the midterm guidance that you're going to hear. But clearly, we see a tremendous opportunity, particularly with agentic AI to be able to grow that with this platform.

So we're on the road to doubling our cloud revenue. You can see the numbers that we're going to go from $2.2 billion to $3.5 billion by 2028. We're on the road to $4 billion plus, and that road is based on those growth drivers, based on a great market and based on our ability to compete and win. But there are a few things that we need to continue to invest upon. And Beth will go into more details about the financial outlook, including 2026.

So first of all, we need to continue to innovate. This isn't a market where you can sit still. As great as our capability is, this is a fast-moving market. There is a lot of investment coming in. So we've got to accelerate our innovation, whether it be about consolidating and bringing the Cognigy platform and the CXone platform together to become a better stack, a more complete stack to be able to offer to our customers, whether it be about innovating in orchestration or automating resolution with the Agentic capabilities, there is a lot of innovation needs that Jeff and the team will drive in the coming years.

The second is to be able to seize on that growth catalyst about international, we've got to continue to increase coverage, capability, assets, service to be able to serve that market. It's not a case of just asking if we're going to open new capabilities in new countries, we've got to have a localized capability to be able to support that. It also means recruiting and enabling supporting partners who are going to be able to serve and be able to help us serve locally in those markets. And then last but not least is you could appreciate the operation and the delivery foundations. So whether it be about reducing the time to deploy, we've made significant improvement in our deployment time frames of AI.

It was initially quite a long period of time. We've been able to reduce that, and we continue to invest in the capabilities to be able to serve and get deployments faster, more valuable, more capable in a shorter period of time. So it isn't that we're just doubling our revenue without investment, we will be investing and those investments will be able to deliver significant growth and shareholder return.

So let me recap again. Number one, great market. Number two, we're in a really great position. And number three, that will deliver growth. And I know that the expectations or there will be a lot of interest in what that top line and margin and what that looks like. The growth is real. I think you saw in the sentiment that I talked about in the earnings call, I was very clear we needed to see the proof, the data and the plan that we've built to achieve this is rock solid. We've looked at all of the things that could happen that could potentially derail or impact that.

Does the AI movement happen as quickly? Have we got the ability to deliver? What if the competitors step into different spaces and move into us? We've looked at all of those angles. This is a bottom-up rock-solid plan that we are executing on. I'm not giving a guidance from the midterm that has speculation. It is based on real data, real understanding of the market, real pipeline, real customer feedback, real analyst feedback, real knowledge of who our competition and the evolving competitive landscape.

We believe that we will achieve that midterm outlook and top line growth and double our revenue over the next 4 years based on all of those variables. We are ready to run. And really, it's just about execution against the plan from now on. So what we want to be able to do is be able to share with you on a quarterly basis. And you saw, for example, in Q3, we shared our cloud backlog.

Our cloud backlog growing at 15%. So we clearly are seeing both pipeline and the underlying proof points of a future revenue that we get that is growing and is going all in the right direction based on executing against this plan. Hopefully, that makes sense. Hopefully, the context of who we are as a company, the market that we operate in and the top line growth that we are expecting to achieve is very clear.

For the rest of today, what we want to do is quantify it. We want to take you through the real technology stack, what it really looks like. We then want to go through the financial models and what it really looks like. And then obviously, at the end of today, we will come back and answer your questions where we'll have the whole group, all the presenters up on stage to be able to answer questions that you have.

And with that, I'm now going to welcome on the stage. He's been with us for 6 weeks, but it feels like 6 months. Probably not as much as mine, but Jeff Comstock. Jeff joins us from Microsoft. For those who have not had the chance to meet Jeff. He was the leader of all of their CX portfolio, their CRM, their CX, his company. He led the build-out of a contact center platform ground up. He obviously led the CRM portfolio for Dynamics. So he understands this space exceptionally well. We're very lucky to have him, and he will be able to share with you the outlook and where we're going from a product and technology direction. Jeff Comstock. Thank you.

Okay. Good morning. It's great to be here with you. Great intro. Scott, I appreciate that. So you've got a lot of context on what I've done before joining NICE. I was with Microsoft for 25 years. And for many of those years, like Scott mentioned, I was building CX-related products. And I got the opportunity to scale those products through the last few platform shifts that we've seen in the industry.

And what became really clear to me at the very beginning of this platform shift, which is agentic AI, is that things are going to be different. CX is going to fundamentally change and how CX is delivered is going to fundamentally change. And NICE is incredibly well positioned in the face of this change. So in this session today, I want to go through just a few things. One is what are the trends that we're seeing in the marketplace already underway and how is NICE positioned with those trends and in that context. And then I'll cover our product investment areas like Scott mentioned, right?

So how are we going to leverage that position of strength and our unique CX assets to lead and win in the Agentic era. After my session, hopefully, that will be super clear. So let's start with the trends that we're seeing. I don't think I need to convince anyone in this room that consumer AI has gone mainstream, right? There's over 800 million users of ChatGPT alone, hundreds of millions of users of other tools like Gemini, Claude. What that means for CX is consumer expectations have skyrocketed, right? And as we know, unfortunately, most enterprises aren't meeting that expectation.

And the gap between expectation and what enterprises are able to deliver is widening by the day. So this is obviously a key impetus behind our acquisition of Cognigy, our market leader in agentic AI and conversational AI. And you're going to see that in action when Phil comes up and demos the product. It's really helping our customers close that gap and then some in terms of those expectations.

Second, the AI that augments the workforce in the flow of their work has really gone from market buzz to strong customer demand. And of course, NICE is really well positioned here with specialized copilots out of the box. So we're seeing a surge in usage, a surge in revenue from that. In Beth session, you're going to see how that shows up in our revenues.

The third big trend is platform consolidation. in the CX space, it's highly fragmented, like Scott mentioned. It has been for many years. And unfortunately, enterprises have just had to a la carte, pull together these best-of-breed capabilities, integrate them together in a very fragile way just to support a basic CX function. But now we're seeing a real big push by customers to accelerate that consolidation. And why is that?

Because customers even realize that to get the most out of AI, they need to consolidate and simplify their data estate. This is where NICE is really well positioned with the CXone platform. It's arguably the broadest and deepest CX platform on the market. And as Scott mentioned, we're seeing customers as they come on board to CXone, they're consolidating a number of other solutions on to CXone. Now story and that value proposition is just going to get that much better as we bring Cognigy on and we expand those platform capabilities.

Next is the fact that agentic AI is really enabling us to leverage that point of customer engagement that Scott talked about and automate more of the tasks and jobs that need to be done to deliver incredible customer experiences across the enterprise. So we can automate those tasks, we can orchestrate across the enterprise in a way that just really wasn't feasible before agentic AI.

So this is a huge focus area for us. There's a lot of strong customer demand. At the end of the day, they want more automation. They want better customer experiences, and we're going to have a really big opportunity to expand our value proposition to our customers.

And lastly, we're seeing a really strong demand for proactive experiences. Scott gave a really good example in his walk-through, right? The best consumer experience, if something is going to go wrong, for example, is for the brand to notify you that something went wrong and here's what they're doing to resolve it, right? That's just a better customer experience. We've got great solutions at NICE for proactive engagement, and we're seeing a surge in usage there.

I'll also say this proactive engagement capability is going to play another strong role as we build out our agentic AI orchestration capabilities, right? Because the direction we're going is supporting more holistic customer journeys, and that's going to involve proactive engagement, reactive engagement. And so we have all the component parts to that. So we are really well positioned from a platform perspective. We have a platform advantage. Now I want to focus on how are we going to expand that? How are we going to leverage that advantage and differentiate even further.

And to do that, I want to show you the most common point of fragmentation in the enterprise. This is essentially every single enterprise contact center on Planet Earth, right? They have one system, one stack for human-assisted service. This is the land of CCaaS, right? This is where NICE has been a market leader for a long time and continues to lead the market. And then this is a simplistic view. Most enterprises have a collection of capabilities, digital channels, bots, virtual assistants, right?

And this has long been a real big challenge for enterprises, fragile integrations. Each stack is operating on an incomplete data set. But these challenges magnify as organizations try to advance with AI, right? So as they're going on that AI transformation journey, this becomes even more of a problem. As they go to automate, they've got to automate it in 2 different stacks in 2 different ways. That automation drifts over time. So even though we're seeing from customers a really strong motivation to transform with AX, with AI, it's fragmentations like this that are standing in the way.

So how are we going to help in this particular situation and others and further differentiate our platform in the process. Well, we're going to do that by bringing Cognigy onto the CXone platform natively. And that is going to have game-changing implications for our customers because now they'll have best-of-breed capability for self-service with Cognigy, best-of-breed capability for human-assisted engagement and market-leading agentic AI capability. But that's not where it stops, right? When we bring it on natively, what that means is we now have one data layer for customer engagement.

And think about that data set, right? That's every single intent, every customer need, all the steps that have been performed, whether by automation or through human-assisted engagement and then the outcome that was achieved. across the entire enterprise, across all interactions across all channels. And I will tell you that is by far the most valuable data in CX. This is the most valuable data, right? We will have it in our data layer. We'll apply our unique set of CX-specific purpose-built AI to drive insights, right?

How do we get better outcomes, including cross-sell, upsell, like Scott mentioned, right? And then we'll take those insights, and we will feed a common AI stack that is supporting both self-service and human-assisted service, right? So we're learning from all engagements, whether it's automation or human-assisted service, everything we learn feeds the AI stack that then improves both self-service and human-assisted service. So this creates a very powerful compounding AI learning loop that quite literally with every interaction, it gets smarter, automates more as it goes, right?

So this is our platform advantage taken to the next level. No other vendor has the best-of-breed capabilities for one, as Scott mentioned, let alone all integrated into one platform, powering this AI learning loop. That's what we're building. That's where we're going. So I've talked about this platform advantage that we already have. So let me just briefly review the CXone platform today.

So it is composed of 3 distinct product areas. On the left-hand side, and I'm talking about that white arc across the top, is automated experiences, right? So this is where self-service is. This is where we just upgraded in a big way to best-of-breed capabilities with Cognigy. Then we have orchestration of workflows. This is classic CCaaS, orchestrating customer engagements across all channels of engagement.

And then on the right-hand side, the augmented workforce, another area NICE has led for many years in the WEM, WFM space. All of these product areas sit on the same stack, right? They're powered by the same customer engagement data, the same purpose-built AI models, but they're independently adoptable. We can sell them independently. They can be adopted independently.

But as customers adopt more, they get compounding value as a suite. And this is very important because, again, as Scott mentioned, this is a very fragmented market. Customers want to consolidate, but we've got to meet them where they're at. They will start where they have the most urgent need and they'll expand from that. And we've got the CXone platform is a distinct advantage that we already have and that we'll be building on. So in terms of that fragmentation, meeting customers where they're at, the NICE team has done an incredible job over the years, building adapters so we can land in any environment in the enterprise. Highly fragmented. Customers don't need to do a rip and replace.

On the left-hand side, we have a ton of adapters where we can link right into the channels that they already have, right? Even other CCaaS and ACD systems. On the right-hand side, we have hundreds of adapters and connectors to CRMs, other mid-office, back office systems. And this helps us bring in context from the enterprise. This will also be a key facilitator for us as we expand beyond the contact center and orchestrate workflows across the enterprise.

All right. So let me kind of close here on our investment themes, our investment areas. First, no surprise, I've talked about it is accelerate Cognigy. And our focus there is very specifically to accelerate Cognitive stand-alone value. right? So Phil and the team have done an incredible job getting Cognigy to a leadership position in conversational AI, self-service and agentic AI.

We're just going to pour a whole bunch of fuel on that, accelerate that road map and extend that leadership position in the market stand-alone. The second vector of investment around Cognigy, as I mentioned, is to bring it on to the platform natively. I've already touched on how that is going to take the CXone platform, take it to a whole another level, incredible platform benefits. But that's also going to accrue benefit back to Cognigy stand-alone because as it operates on the CXone platform, we can easily bring in market-leading capability like proactive engagement that I mentioned earlier.

All of a sudden, Cognigy will have a world-class knowledge management system and expert because we can just bring that along for the ride. And all the AI models that we have that are CX specific also goes right into Cognigy. So in multiple ways, we are going to accelerate Cognigy stand-alone. It's a key land and expand for us. This is an area where a lot of customers want to start their AI transformation journey, and we're going to be there for them.

The second place we're going to focus is extending our enterprise leadership from a platform perspective. So we partner with some of the biggest, most complex brands on Planet Earth. And we treat these customers as design partners. So they want -- they need further feature functionality. We build that for them, but we build those at the product level. So other customers can benefit. The second place in the platform we're investing heavily is to ensure that our platform has plan at scale, resiliency, availability and performance.

As Scott mentioned, we're getting tons more interactions on the platform as we bring Cognigy natively on to the platform, that's going to drive more interactions. And of course, we're planning to execute many more agentic journeys on the platform. So we're getting ahead of that, getting ready for that surge of volume.

And then the last place, the third sort of big investment area is this notion of orchestration. So we have a number of capabilities in the platform we're going to leverage there. As you can guess, Cognigy, again, is going to play a role from an agentic capability. And then we're making net new investments to enable these types of orchestrations. So in a little bit, Niraj is going to come up and really bring this to life for you and what that looks like when we're orchestrating more holistic customer journeys across the enterprise. So we'll get more into that.

So I'll just close with this. Agentic AI, it is going to fundamentally change CX, and NICE is incredibly well positioned. We have the specific and unique CX assets, and we have the plan to not only lead but to win in this new era. So with that, I believe we have a break coming up 20 minutes, 15 minutes. So we'll be back in 15 minutes, and then Phil will come up and demo Cognigy live for you. All right. Thank you.

[Break]

All right. Welcome back, everyone, and thanks for coming today to listen to us. Really good to listen to Scott and Jeff about where the future is taking us and the market opportunity. And I'm here today to give you a bit more of a look at Cognigy and what we're doing at NICE Cognigy and the future that we're seeing as in the better together story of NICE and Cognigy together.

Now for those of you who don't know so much about Cognigy, we thought we put a quick slide up to give you an overview of who is this company that NICE acquired. Now we were founded in 2016 in the beautiful city of Dusseldorf in Germany. And we have since emerged as a market leader in what used to be called conversational AI now is called agentic AI for customer experience.

We are processing by now, so this was in 2024, but by now, we are processing billions of user interactions every year. We have the highest recommendation rate in the industry, as you can see on Gartner Peer Insights, we're servicing brands all around the world. I think it's around 1,000 brands that we are servicing. And we're also praised essentially by any analyst in the market.

We're a Gartner Magic Quadrant leader. We are a Forrester leader, we're an IDC leader, we're an ISG leader, et cetera, et cetera. And we're very proud that we have attained this position as a small start-up from Germany growing into this market leader globally. Now to give you a bit of background where we came from. This is getting a little bit technical, but we emerged in an era of the so-called NLP frameworks.

NLP frameworks back in the day 2015 were coding frameworks that analyzed user inputs and attached a label, a so-called intent to them, right? So a customer would come in and say, I want a refund for my ticket. The NLP framework would then detect, okay, refund request and then would give you that result and then you had to write code to do something with that, okay? So what do I do next?

We saw a gap in the market where we saw that large enterprises don't actually want to write code to then determine what to do, but we want to have a graphical tool set, what is now called a low-code tool set to define the process that would happen afterwards. This is what would then be called a conversational AI platform, and that is what Cognigy built and emerged as a leader in. Over time then, of course, with the emergence of large language models, we first enhanced the conversational AI platform with large language model capabilities such as generating these NLP models with large language models, testing, et cetera, et cetera.

And then last year, we created what is called the AI agent orchestration platform. So an LLM native platform inside of Cognigy that makes use of all the enterprise features that we already had and still incorporated large language models. And by the way, any large language model, not one specific model to enable our enterprises to make use of this amazing technology. And the next step for that is NICE Cognigy, and that's what we're going to be talking about here today.

The platform is a holistic platform that allows you to design, run and optimize AI agents at scale for large enterprises. We have various components, various subproducts like AI copilots to help human agents with Agentic-driven experiences, knowledge, process knowledge, et cetera, in real time during calls and chats.

We have a live agent product, which is a digital channel product. We have the AI agent platform that we're going to look at more today, voice gateway to connect the Cognigy AI agents to any ACD on the market. So this means whether it is CXone, whether it is Genesys, whether it is Avaya, whether it's 8x8, we can work on top of all of those ACDs and CCaaS players.

And then we have a very advanced insights product as well, which is specific for insights for agentic AI for customer experience. Now very important, Cognigy is not just an agentic AI product, but it combines agentic AI with logic guardrails and prebuilt system integrations that we have built out over the years because hallucinations remain a fundamental challenge in the agentic AI world.

But by embedding it into a structured workflow, as you will see in Cognigy, we actually get a handle on that, plus AI agents must be deeply aligned with the company's logic, data flows and value creation. And agentic AI can't really do anything unless it is connected to back-end systems, to booking systems like in the Lufthansa case, 2 CRMs, 2 ERPs, et cetera.

These AI agents need access to these systems, to the data in these systems, to the APIs in these systems in real time in order to be able to help a customer. Now I can tell you a lot about the platform, but we thought you're seeing slides every day, you're seeing videos every day on the Internet. Why don't we do something different and just show it to you live. And that's what we're going to do now. If we could please switch to the laptop view. There we go. This is essentially how you set up an AI agent in Cognigy.

You can see. You can pick an avatar, you can define a name, you can define a description, et cetera, et cetera, the style of this AI agents and so on. This is what we call the persona of an AI agent. You can have one person for all things AI agent does. You can have multiple personas where you say, okay, let me hand this over to another AI agent and this agent might have a different person or not.

What we do is we assign this AI agent a job. Okay? So this AI agent, Jennifer has a job here. She's a virtual expert and she has a job description and specific instructions and knowledge for this job that she needs to be able to do. We're also giving this AI agent so-called tools. In this case, here, an authentication tool to authenticate a customer, make payment tool and an update account tool.

So these are the things that this specific AI agent can do, and it's all done in this low-code platform so that enterprises can build these AI agents themselves. Now Cognigy's AI agents are multimodal AI agents. That means we can interact with them both in chat and also in voice. This is a chat interaction here in what we call the interaction panel. It could also be on SMS. It could be on WhatsApp. It could be on our website widget. And we can just have a chat with it.

So here we say, so the agent says, hello, Phil, thank you for reaching out. My name is Jennifer. I'm a virtual service expert with Nexor. How can I help you? I could say I want to make a payment. And then she says, got it, Phil, I can help you with that. First, we need to authenticate you. Shall I go and send you the verification pin? And so I can just have this chat with this AI agent.

But in Cognigy, you cannot just set up the AI agent like this, and then it's kind of a black box and you don't really know what's going on, but you can actually look under the hood. And that's what we see here. We can take AI agents. So in this case, Jennifer and embed her in a structured workflow. So we can do things before data hits the AI agent. And these things are required in an enterprise context.

You filter out PII data, you make specific settings, et cetera. And we can also see the processes that happen if Jennifer wants to do a specific thing. So for example, here, we have authenticate. So when Jennifer wants to authenticate a customer, she will say something specific and she will say exactly that. So that is important because LLMs, you can't force them to say something in an exact way. But here in Cognigy, you can, then she will send out an SMS via Twilio and continue with the flow or with the payments.

In this case here, we have integrated with Stripe. And you can see we can do that in a very low-code way in a very easy way. Now as I said, these AI agents work in both chat and voice. So what we're going to do now is we're going to call this AI agent, and we're going to use something in Cognigy, we call Live Follow mode. I've now activated the Live Follow mode for this phone number that I'm going to use, and we can see what is happening in real time. So let's kick that off.

[Presentation]

All right. So what we saw here, we saw a real-time interaction with one of Cognigy's AI agents. This is not a pre-rendered video. This is exactly the type of experience that our customers can create with Cognigy. You could see you can use this low-code interface for debugging purposes, but this voice experience, the very natural voice, the very fast responses whilst interacting with back-end systems is not fake. This is reality.

And this is what we have deployed at scale for hundreds of thousands of brands out there already, and we are going to have Lufthansa talk about that in a second. If we could please switch back to the slides. Great. Now what we saw was the Cognigy interface, right, the Cognigy AI studio that we can use that our customers use, that enterprises use to build out these types of experiences.

But what I also want to share with you is another experience, which is a front-end experience. This is the type of experience that can be created with the Cognigy platform. Earlier in the demo, we saw a chat, and we saw a phone call that was made using a regular phone through the phone network, so connected to a CCaaS and then against the Cognigy AI agents.

Now what we're seeing here is the next level of experience. It is a proactive outreach by an AI agent that knows that this customer has to renew their mobile phone plan. This customer is then sent a widget and using this widget can then using what is called WebRTC communicate with the AI agent in real time. So here the widget comes in via SMS, they click the URL, they go in and then a voice conversation starts afterwards. So let's take a look at that.

[Presentation]

I know everyone wants to erupt and cheers because this is exactly the type of customer experience that we would all like to have, right? Because it really is. And what we are seeing here is not the future. This is reality right now. This is not a video that was produced by our marketing team in some video cutting. This is reality. This is a straight-off recording of a phone. Our customers can and are producing those types of experiences at this point in time.

But there is something very, very important that I want to share with you. everyone can do a great demo these days. We have LLM technologies. We have speech-to-text technologies and text-to-speech technologies like ElevenLabs. We have the OpenAI LLMs. Everyone who can code a little bit of JavaScript can put a cool demo together and blow you away with the demo.

But for the types of customers we are dealing with enterprise customers, this is not near enough. There's a lot of stuff happening under the waterline that is even more important. And without these kinds of things, our customers could not even think about going live. There's omnichannel routing. We are supporting more than 30 different channels in the platform, whether it's voice channels through the contact center, whether it's voice channels on WebRTC, whether it's web chat, whether it's WhatsApp, whether it's WeChat, whether it's LINE Messenger for the Asian markets or Kakao Messenger in Korea.

We are supporting a large number of channels. And you don't have to build this experience for each channel. You build it once and then you deploy it on a channel and it immediately works. And you saw that earlier, proof in point, I chatted with the AI agent and then I called the AI agent and the experience was equal. Plus, there's agentic orchestration.

We have the tool usage, the planning and reasoning baked directly into the platform. We did not tell the AI agent, okay, now you use the authenticate tool. Now you do this, right? We just provide the tools and the reasoning capabilities of the LLM take care of the rest. We can build end-to-end workflows where we have a visual flow builder that you saw. We can have guardrails where we can make sure that the AIs actually stay on track we can have fallbacks because sometimes LLM APIs are flaky, right?

Maybe sometimes the response time of a certain API goes up and then the LLMs don't respond in 200 milliseconds anymore, but they respond in 3 seconds. That is too long for a voice interaction. We measure these kinds of things in Cognigy, and it can then fall back to another LLM that is faster to maintain a very good customer experience.

We have more than 100 different system integrations with CRM systems, ERP systems, et cetera, so that our customers don't have to build them, plus the contact center integrations. Cognigy is integrated into the NICE CXone platform and will be even tighter integrated in the near future, but we also remain a stand-alone platform, and I can't stress that enough.

A large number of our customers at NICE Cognigy are using a very wide variety of CCaaS systems, right, be it a Genesys, be it an Avaya, we work just as nicely based on those contact centers through our integrations, both on chat and on voice. We have the handover to life agent. We didn't see that in the demos here, but the AI agents, if they get stuck, can also say, "Hey, I think I want to loop a human in, either by communicating with a human in the background and then providing this information to the customer or by handing the full conversation to a human agent because human agents are not going away.

And when it's handed over to a human agent, we can use embedded agent assist. And then we have all these boring things that are still extremely important for large enterprises, versioning, auditing, who did what in the platform, role-based access control, data residency controls with sovereign clouds around the world. GDPR, observability, et cetera, et cetera.

So it's much more important to have a holistic platform rather than just a prompt wrapper that allows you to show a nice demo, but in an enterprise scenario, you will not be able to go live with that. So to summarize all of that, how do we differentiate as Cognigy? We allow for hybrid AI agents. That means AI agents that are both agentic and based on traditional conversational AI, so more deterministic, especially important in regulated industries.

We have AI operations and orchestration, the fallbacks, the observability, the orchestration of different AI models, native contact center connectivity to pretty much any contact center out there. Multimodal experiences like we saw in the second demo. We can have chat experience, we can have voice experiences, we can have voice experience with multimodal widgets and graphical interfaces, which we believe, and by the way, many of the analysts believe to be the future of customer service and customer experience interaction and of course, all the enterprise readiness with our certifications, security compliance, data privacy compliance, et cetera.

And that really led to us being loved by many of the largest brands in the world. If you look at Gartner Peer Insights, we have the highest ratings in the world and the most ratings in the world compared to the likes of Kore AI, Emilia, Sierra and many others. And we picked out 3 quotes here that make me as the founder of Cognigy, specifically proud. While others do the slides, Cognigy does the work, surpassing expectations and agent AI boost teams with easy use.

And the other thing that is important when you want to make a customer successful. So on the one hand, you have the product that needs to be outstanding. But on the other side, you have the company, Cognigy, that makes you successful, right? And this is something that we also, I think, share in vision with NICE.

We don't just provide the technology. We provide the experience and the knowledge in the industry that makes our customers successful. So our secret to -- or one of our secrets to the success of our customers is our customer obsession. We work very closely with our customers. But in the end, we are delivering real impact. We could have an amazing product. We could have amazing customer obsession. If we don't deliver impact, it's worth nothing. But we are delivering real impact. Core containment, depending on the use case, between 60% and 90%.

Core containment means that the call does not have to reach a human agent anymore afterwards. If it reaches a human agent, average handling time reduction of 25% or more through the AI capabilities first that come before the interaction with the human and then how we are supporting the human agent during the conversation with the customer. And it's truly a win-win-win situation, CSAT improvement.

Customers love it. Nick is going to talk about that in a second. Customers like being helped by the AI agents because they're being helped quicker. They don't have to wait on the phone lines to get done what they want to get done. So we are seeing also a CSAT improvement here. And I could tell you about this all day long, but you might think, yes, of course, Phil is a fan of Cognigy, and I am. But there are also other fans of Cognigy. So I thought I would like to bring on stage here, Nick Alger from Lufthansa. Please everyone give a hand to Nick. And he will tell you firsthand about his experience with Cognigy. Thank you.

Good morning, everyone, and thanks for having me. My name is Nick. I've been with Lufthansa Group since 2014 and my teams and I, we are in charge of the conversational AI developments for our B2C space. So if you ask me one of the most exciting spaces to be around.

Today, I would like to show 3 things. First, I would like to show how we are leveraging conversational AI to address real operational challenges at scale. Next, I would like to show how conversational AI has become really mission-critical asset for us. And third, I would like to point out how our partnership with now NICE Cognigy is of strategic importance to us as we move into the next era of customer interaction.

But first, let me fill in on who we actually are at Lufthansa Group. We're around about 100,000 employees, and our mission is to connect people, cultures and economies. We do that around about 3,000 times a day on one of our flights. So we bring our guests to more than 300 destinations across 12 airline brands, with more than 700 planes. And all of that summed up in the year brings us to 130 million passengers, bringing us revenue of round about EUR 38 billion. That scale is great until it's not. And why is that? Our business is not a linear business. Our business is pretty peak heavy. So let me take you on a little trip with a bit of a twist of a perspective because many people might not have looked at this challenge from that angle. So it's July. A beautiful summer day. You're at the airport, mid-90s degrees outside. And the airport is full of people. So you see that a couple about to go on their honeymoon cruise. You see that family about to depart on their beach holiday. And you see the grandparents excited to meet their grandchildren. But then at the back of the skies, you see dark clouds. And you can hear roaring thunder coming in, and you see the [ first ] lightning. There is a thunderstorm right above the airport. So what is happening? Unfortunately, due to the thunderstorm, the first flight is not about to go out. The flight from Frankfurt to Paris in this example, can leave. What does that mean in turn? If the flight to Paris is not leaving, it can also not bring passengers back from Paris to Frankfurt. Unfortunately, the thunderstorm is sticking around for longer than expected. So also your third flight and fourth flight of the day leaving for Zurich is delayed. And unfortunately, due to the delays throughout the day, also the last -- the fifth and the sixth flight, they're not going to make it on time. So lots of passengers will have to contact us that day. And that is not because they love to do so, but because they will have to. If you run the numbers here real quick, and this simplified example, we're talking 0.5 million passengers in a day easily. For our passengers for our guests, this is a massive inconvenience that situation. For us, that means suddenly 0.5 million of our passengers need answers. They need support. And that support can look very different. Some people might just need a new flight. Others might want to get their money back because there is no point in taking that trip anymore. Others might have missed their connecting flights. So they need a hotel, they need food. They need compensation. So it's a wide range of customer intent and requests that we'll have to serve on that day. And let me assure you, such peaks, no matter how big the human workforce, there is no chance to handle that peak, that spike in demand reliably at scale. So this was a summer day. So now imagine a full pandemic is about to hit you. And we're not talking on airport closed for a day but we're talking a country shutting down. We're talking an entire fleet of 700 planes on the ground for days and weeks and your passenger is reaching out to you. And that's exactly the situation that we were in. That was the reality that we were facing and that made us start looking into conversation at AI before it became so fashionable. So we realized if the future for us continue to be so peak driven. Our customer support model, how it was no longer had a real future. So we saw this would not be a simple task, but we realize there's 4 key areas that we had to focus on. The first one is we needed to automate whatever we could. So we had to reduce the manual -- the manual contact volume. Second, for what's left, we have to prioritize. If your flight is leaving in an hour, you should be first in line because you have no time to wait. If you're contacting us for a seat reservation for your next trip 2 weeks out, you'll probably be okay waiting for a couple of minutes. Next, what we still need to handle manually, we have to look at efficiency drivers here and improve the time spent on each case. And lastly, we want to gather insights into the first 3 areas and see what is working, what's not working and how can we get a continuous improvement cycle going. So we saw 2 things here. The first is there would be a wide range of use cases that we'd have to look at, starting from simple FAQs ranging to complex end-to-end re-bookings, deeply integrated into our legacy systems, our booking system and other legacy. And also, the more we lean into automation, the more important the scale would become. Now if you start implementing automation on several channels, that wave of contact is going to hit you on all the channels at once. So scale really becomes important. So the question for us was now who would be the right partner to pick in that endeavor. So we sat down with our experts, and we're imagining what platform would work best for us. So we came up with all sorts of requirements. First, the first attempt 150 requirements. Then we cut it down to a short list of 30 requirements. And I would like to point out 5 in particular that we then decided to focus on. First, we wanted to have an agnostic modular platform. We wanted to have the opportunity to replace certain components with others if we saw the need for it. We wanted to have a platform that not just our technical experts, our developers could use, but also the business experts could contribute to creating the experience. As you saw earlier, we needed a platform that could handle the scale required, and we wanted something where we could create the experience once and then implement it for all of our airlines, otherwise we'd have to create one bot for each airline in each language. If you're serving 4, 5 airlines in 6 different languages, you could imagine the work that would go into creating each of the experience separately.

And lastly, as I pointed out, we wanted to get analytical insights into what works, what doesn't work and what needs improvement. So we screened the market. We started with hyperscalers, and we saw that wouldn't work for us. Very technical solutions is what we saw, but we realize we need to keep looking.

The second area was CCaaS providers. And I believe it's fair to say, have -- we found something that worked for us. I would not be standing here today.

The third area was specialized AI, conversational AI vendors, and there we were on to something. So we did an RFP. We looked around and then out of that RFP, Cognigy came out as a winner. The first reason was Cognigy provided a platform that matched best with our requirements. But then we also saw that the team of Cognigy, they understood what challenge we were facing, they did not just understand the challenge. But together, we've been working on that challenge. And they have supported us in tackling that challenge since then. Say, this was the world before identic AI. So if you were to look into platforms now, you might have different arguments. So I'd like to have a look at the differences of the world before Agentic AI. So if you were look into platforms now, you might have different arguments. So I'd like to have to look at the differences of before Agentic AI and Agentic AI and point out what I would still say is important to look at.

First, how do these systems work. In a deterministic conversational AI system, you tell the system what to do. In an Agentic AI system, you tell a system what to do, but also you have to cater for what not to do. And the problem here is there is an infinite number of options for the what not to do. So the decision-making on the left-hand side, it's pretty clear. It's if, than, else. On the other side, the Agentic system has much more autonomous decision-making power and ways to decide, leading to outcomes on the one hand, deterministic, so consistent and reliable. On the other hand, probabilistic outcomes. So the decision-making was autonomous, but the outcomes can be inconsistent. The flip side of it is the deterministic hand -- a deterministic system can feel rather clunky, it can feel rigid and scripted while in Agentic system, there the conversation can flow much more natural. It can feel much more flexible and smooth. So if we were to look at platform selection again, I would say to those [ 30 ] criteria. I would add 2 more as very important. The first one is as a business, I would like to have full transparency over what's happening underneath the hood. And I want to be in a position to control where I want to use what. If this process is important to me, I want to have consistent outcomes. So 3 points that I would like to point out here. The first one is, if you ask me is, sorry, I can't answer that, can be better than a rogue AI agent. And sorry, I can't answer that. It's very different to sorry, I don't understand. I think the times of sorry, I don't understand, they're over. They are no longer accepted by the customer. But I can understand what you mean, but for whatever reason, decide that I don't want my AI system to answer that. That could be because it's a very sensitive topic or because I'm not confident enough that the AI system has all the relevant information at hand to autonomously answer that question.

Think back to that couple about to go on their honeymoon cruise. If their flight was canceled and they missed their cruise and now they ask for a refund, imagine how they would feel if we hallucinated their refund, gave them the wrong amount of money and would give them the wrong timing of when they would receive the refund. I'm not sure that would fly with us again if this is something that we mess up back -- big time. So for us, it's important to be able to blend these 2 things. We would like to have the control of certain things and have a deterministic system where needed in place, but complement that with an Agentic AI experience where it's meaningful.

Fast forward to 2025. Where do we stand now? Actually, Conversational has become the most popular channel throughout Lufthansa Group. Those experiences are the #1 contact channel for us now. We are integrated in chat, voice and agent assist. And we're making use of generative AI in more than 50% of our conversations. Actually in voice, we're beyond 90% of conversational AIUs and we're in the process of rolling out more and more Agentic AI use cases. This year, we will probably end up with around about 12 million conversations being facilitated through the Cognigy platform. And we have had record days like the ones that I pointed out earlier, where we had around about 400,000 sessions in a day and more than 10,000 concurrent conversations with our customers.

Now we see that millions of customers, customer contacts get prioritized. So it is now a reality that if you call us and we can identify you and your flight is leaving in an hour from now, you will be first in line, and we will tell you that you're first in line because your flight is leaving soon. We see shortened AHT across both chat and call and we're saving a good amount of money every single year.

So where do we go from here. What we want to create is Lufthansa Group's digital go-to person. And I think it goes along towards what Scott is saying that companies are now not looking at ways to reduce customer contacts, but we want to find better ways to serve our customers. We want to embed our conversational experiences across different points of the customer journey. And overall, we want to create the best conversational experiences in the tourism industry. For us, that means practically, we will embed our conversational experiences in more channels.

So you will be able to find us hopefully soon, then also in messaging apps, more touch points on our website. Wherever you're going to call us, et cetera. Then I also strongly believe that channels will blend. And Phil also showed that earlier. I believe as multimodal experiences are starting to mature now, customers will think less in this is chat, this is voice, this is call, but we'll see those experiences blend and customers will want to interact however, how natural it now feels in that very moment. And that can mean you might call us for a seat reservation, but why not select this seat on your phone? Because whenever you've seen a seat map, it's much easier to pick where you want to sit than having an agent walk you through your options or think talking to the website and telling the website what you need to find out and then the UI will serve you in a dynamic fashion.

And lastly, this is not where our collaboration with NICE Cognigy will stop. Aviation will always face volatility and unpredictability, but dealing with that volatility and managing that volatility, this is really where customer value is created and where competitive advantage lies. So for us, AI is more than NICE to have, how we handle volatility creates true customer value. So AI enables us to manage unpredictability, to scale reliably and to improve customer experience in a time where expectations have never been higher. And with our partners like NICE Cognigy, we're not just waiting for this to happen, but we're actively creating the next generation of our digital customer experience, one that weather storms even in the most literal sense. Thank you very much.

Thank you, Nick, for this amazing presentation. I think what this presentation really shows is that what we can create with our type of technology a true win-win-win situations. Now what do I mean by that? Because usually, it's win-win, but here it's a triple win. Firstly, the enterprises deploying our technology are winning because they are saving, as we could see in this example, multimillions of dollars every year whilst creating superior customer experiences. And that is the second win. Okay?

The customers of our customers are also experiencing the benefits at scale because if such a storm hits and 500,000 people have to call the contact center, they're going to be waiting for hours on the phone lines before anyone can help them unless they have deployed AI agents. And then the third party to win is us because we are the software provider, and we are generating revenues in that way. And I hope what you can also take away from this experience, this is not just about putting an IVR phone bot in.

Yes, we can do that, too, and we are doing that. It's not just about putting a chat bot on the website. It is really about revolutionizing the customer experiences that can be created and not limiting the customers. With Cognigy, if a new LLM comes out tomorrow, you can embed that in your customer experience flow. It's an orchestration platform that allows you to be open, new voice models are coming out.

New speech detection models are coming out, et cetera, et cetera, you can use all of that. You can use different models in different markets around the world. And what all of this means is that our customers can grow together with us. They can power all of their customer experience, whether it be customer service, whether it be marketing or sales in one platform, and that platform is NICE Cognigy.

Now we've spoken a lot about Cognigy and what we've done in the past and the position to which we've gotten. But of course, the really big news is that NICE has acquired us because otherwise, we wouldn't be standing here on stage today. And the analysts around the world, industry analysts really welcome this. Many of those have said that an acquisition like this would happen. And some of them called it the biggest news in the CX industry of 2025. An industry leader as a NICE coming together with an Agentic AI and Conversational AI leader as Cognigy, it's really the perfect union.

Now one thing to highlight again, and I know I've mentioned a couple of times, whilst we will be integrated, and I'm going to be speaking about that a little bit more in a second, we'll also remain available as a stand-alone platform. Now bringing those 2 together, what is that better together story. Why is it so unique? Why does it bring such tremendous value? So on the one hand, we have Cognigy, which is agenetic AI and orchestration of AI agents at scale. We bring a world-leading platform with all the systems integrations et cetera. But what does it mean financially? What does it mean GTM wise? It means that now NICE cannot just sell AI solutions to their existing customer base, but the whole CX market. We have a stand-alone solution that can be adopted by anyone in the market, no matter whether they're using CXone or not. On the other hand, we have NICE, which is, of course, vastly larger than Cognigy, has a much bigger scale, the global GTM teams in place all around the world. I have already visited our teams in Singapore, in Australia, all around Europe. So massive scale compared to what Cognigy has, 27,000 customers that NICE Cognigy can now be sold into. So a massive upsell opportunity on that end. But those are the GTM portions. But in addition, there is this amazing fit that is the product fit. So again, we have Cognigy with the AI agents, you can build, deploy, operate and optimize, and then we have the CXone Empower platform with all of their capabilities. And we worked on this slide a lot and we try to do it justice of how amazing this integration is, but we couldn't really because it is much bigger than this. But if we wanted to show you how good this integration really is, we would need a slide that's 10x the size. And what do I mean by that? At Cognigy, we had all these plans when we were still stand-alone. What are we going to build in the future? We knew it would be about orchestrating customer experiences across the lifetime of a customer, not just singular interactions. It would be about not just handling inbound, but also outbound so that we can expand into the sales arena. It would be about intent mining, taking customer call records or transcript and mining them for what do customers actually want and then building AI agents based on that. It would be about analyzing transcripts after the fact. So really in-depth agenetic analytics. And then when NICE approached us to acquire us, we saw that all of that was already there. the world's leading outbound dialer, the world's leading intent mining. All of these components are already in the CXone Empower platform, and we are integrating with those now in Cognigy. And we are going to create the leading CX AI platform on the market, and we are very well progressed in that journey already, and we can't wait to show you what's going to happen here over the next couple of years. I really believe that with those 2 companies coming together, we possess a strength that no one else in the industry has no matter how big the competitor is. All of them have some components of this, but really bringing it all together in one is extremely unique and is extremely exciting for us here at NICE and NICE Cognigy specifically.

Now I would like you to introduce you to 1 of my colleagues here at NICE. Neeraj, who is going to show you a little bit about that future, about the progress that we have already made in integrating those 2 platforms, and I couldn't be more excited than to hand over to Neeraj. Thank you very much.

Thanks, Phil. I was going to use my Starbucks name. I'd like Nick better than years. Never no one pronounces as the same. Okay. So let's talk about what it takes to achieve consumer intent resolution right? When we talk about intent, it's a really interesting story. And this is going to get deep and technical. This is what the consumer expects. When they call a business in, they expect they have a problem, they have a need. They expect that they're talking to a front office agent or a chatbot, and their problems are resolved in real time. The reality is slightly different.

The reality is that it's a -- we call this intent resolution journey. And this journey goes across, and Scott's mentioned it, it goes across front, back and mid-office workers. So it's really disparate labor forces that exist in most organizations. When you think about these disparate labor forces, oftentimes, you've got back office workers that work completely different hours than front office agents that are 24/7. You get this asynchrony and resolution.

The customer calls into the front office, they handle all the conversations. Well, someone in the back office might be fulfilling a request to actually complete the customers need, which creates once again, this necessity for a case management system to manage this asynchronous behavior. It creates a really frustrating experience, right? Everybody is called in and they've -- I know you call in a business about a problem, and they give you a case number and maybe they'll follow up with you later.

This is the reality of intent resolution in a lot of organizations today. But when you think about the unique advantage that NICE has, we are the customer engagement platform. And that doesn't mean we just sit at the intents generation, right? We're not sitting at when the initiation of the intent happens. We sit across from the initiation of the intent all the way down to the fulfillment and resolution of that intent across all of these disparate workers.

And it's really important. We always talk about this concept of our data layer and this data lake that where all these conversations we're mining, all these screen recordings we're mining. But the reality and the moat that we've created is, we have a really, really interesting operational view of how an intent is resolved in every organization in the entire world.

We understand exactly what each of these workers are doing, how they're doing it, what applications they're using, what tools they're using and how long it takes. It's really, really important. It creates a really big moat for us. AI agents are, you can -- just like Phil said, you can create an AI agent for anything using OpenAI. But the reality of AI agents that actually solve customer service problems is super complex and our data allows us to get there really fast.

Now I just talked about us gathering data points, right? Now we know what every single worker across the entire enterprise is doing to resolve consumer problem. We're gathering tasks. We're gathering what tools they're using. We know the channels and we know the integrations. So what does that look like to you? What is an AI agent, right? AI agent is just a description of a job. What job are they performing? What tasks are they doing? And what tools are they going to be using to complete those tasks. We have all of this data on the platform.

So now we can translate the human workers across not only the front office, right? This is what everybody thinks about when they think about automation, automating the front office, customer chat bots. But the reality is that we can expand our TAM and market all the way down into the full intent resolution journey. It's really, really important. Automating back office, knowing what those workers are doing is going to be the future of customer service.

Now what happens when you do that? The reality is that as a customer engagement platform, we operate on top of all ecosystems, right? Everybody thinks about CRMs or case management systems as being the customer management platform, but really intent resolution sits across all of those ecosystems and platforms. And as a customer engagement platform, we understand the entire journey. And once we add AI agents into this journey using Cognigy, it creates this intent resolution journey that's in real time, it's hyper-personalized and allows us as NICE to really expand what we're doing today in the front office all the way down to journey resolution.

So we'll see a quick demo. Let's talk about what this demo is going to be. You're going to see a consumer. We're going to join a call. We're going to join a conversation with a consumer and a business. And this consumer is chatting with an agent or a front office agent about a credit card dispute, right? They've seen something on their bill and they're going to chat to an agent. You're going to see this customer is not -- or this prospect is not on CXone today.

So you're going to see what their agents are doing today to handle these types of conversations. So you could see as the conversation goes on, this human agents got SOP pulled up. They've got billing systems. They've got CRM systems. It's a pretty complex process, right? In general, agents have something like 8 to 12 applications open at any given time. It's really, really complex. And this is the world today, right? Everybody thinks it's super streamlined. 1 application to handle, everything CRM. No. The reality of customer service is this. It's a really, really complex process.

Now if you looked at the SOP of this particular agent, right, the procedures that they're using to solve this consumer intent, their entire job is to talk to the consumer, takes a couple of notes, create a case and then say, we'll follow up with you later. The conversation ends right here, and it's super frustrating, right, non-real-time resolution for the customer. Okay.

Now several days later, right, that same case goes to a back office worker. This is really important. A back office worker. It's got a case management, ticket management system up. They've got a lot of tasks. Some are CX related, some are not. And this disparity in what they're doing is a big problem, right? They're going up, opening the ticket. They're helping us resolve it, done.

Now if you really think about this journey, and by the way, when we think about the moat that we have today, just last week, I had my team pull up 1.8 million of these journeys across the top 10 banks in the U.S. This journey on average today across those banks takes 3 to 5 days to resolve. It's a big problem. This is not fake data. This is not made up. We understand these journeys really well. It's a 3- to 5-day journey across the front, all the way down to the back office. Now let's talk about how NICE solves this problem. We're going to join a CX Orchestrator right? Their entire job is to look at customer journeys, solutions to consumer problems from a journey perspective. This Orchestrator is an AI-powered tool that's looking at the conversation that you just had and thousands of other conversations. Putting together these disparate pieces in what we call, once again, the intent resolution journey. Of course, there's a lot of front office journeys that we're already automating, things like FAQs and just like Scott said, password resets, there's a ton of these, easy, easy to create agents were already doing that today. But a lot of journeys that are -- they cost a lot of money. They cost a lot of frustration from a customer perspective are journeys that go across the front back and mid-office. Now this Orchestrator, as he's analyzing these conversations, right? It's using AI agents to do analysis on screen recordings and SOPs to see what tools and integrations our agents and our workers are using to resolve this issue. I can see that the dispute charge is being highlighted by the Orchestrator. Let's drill into dispute charge. This is really interesting. This is the journey that we just noticed. The really disparate journey, right, you've got a Tier 1 agent that's using all these tools. And then you've got a case being created by that agent and then you've got back office workers executing those cases. The reality is all the data that we've gathered allows us to orchestrate and put this journey together, put together a picture of what's happening in the world today. And if you notice on the right side, we've got very specific descriptions of exactly what these agents and workers are doing to resolve the problem, right? We've been able to take conversations and screen recordings and tasks and integrations, convert them into descriptions of what an AI agent should be doing, which allows us to really quickly take the next step. So it's recommending that, hey, I can analyze these screen recordings. I can analyze these SOPs that are already within CXone expert and empower agents in all of our call recordings and it's going to recommend something really interesting. You can see that it's taking this really synchronous journey across all of these workers and recommending that we create AI agents to replace the tasks that these workers are doing. It's really, really interesting. We have the descriptions. We understand what these agents are now doing in the front office and the workers are doing in the back office. We can use those tasks and descriptions and data that's coming from the front office and the back office to create AI agents to replace the humans and the human-driven tasks in the front office and the back office with AI agents created in Cognigy. This is really a data-driven AI approach. Creating AI agent is just like I've said, it's super easy, right, type in a couple of descriptions. But the reality of creating AI agents to solve customer service is really complex. It's this journey and being able to translate that into AI agents that drive value across the entire NICE platform is really difficult. Now I'll highlight and hover over a couple of these agents, and you'll see the tools kind of blink through right? This is what's happening. These agents are using these tools and they're assigned these tools, and they're working together using the agent to agent platform. Now let's click on SAM here. As soon as I click on SAM, it's recommending that I create a dispute intake agent, and this is directly within the Cognigy platform. I've taken the description, the system-generated description based on all the recordings from all the conversations and screen recordings that we have from the front office. We've created this agent automatically within Cognigy, using the right tools that are already available in the enterprise platform. But the reality is that having this enterprise platform that we have within CXone Empower, we have every integration that you can imagine. So as the agent, the human agent is opening up applications. We can monitor what they're doing, translate that to what an AI agent should be doing and create the AI agent in Cognigy. And this is the power of the platform combined with Cognigy.

Now let's go ahead and deploy these agents. This is how easy deploying an agent on the CXone platform is. We understand the channels already. We understand what the journey looks like. Now we're going to deploy this AI agent across our platform. And you're going to see a conversation, right? Let's talk about the original disjointed asynchronous conversation we saw that was super frustrating for our customers. Let's see that being replicated within the platform with AI agents. You'll see the nice reasoning capability of our agents right here and how our primary AI agent, SAM, is utilizing other AI agents across the enterprise in order to complete his tasks.

[Presentation]

Wow, what a great experience, right? The reality of the world is orchestrating these types of experience takes an enterprise platform and creating these types of agents isn't a single prompt. It's a data-driven approach that takes the entire customer intended resolution journey, convert it to AI agents and turns 3 to 5 days into 1 to 2 minutes, right? That's the reality of the world that we're living in today. CXone is in the ideal position. You cannot expect case management CRO system -- CRM systems to understand these journeys. They do not lie at the heart of the initiation of the intent all the way down to the resolution. It's really, really important. Having this data is what gives NICE the advantage.

Now we've been managing human-to-human interactions for 40 years. We understand how human agents work operate, how they resolve issues, how they're optimized. I mean, it's really, really interesting. We've got 40 years of data on this. Converting that and using that expertise to manage AI agents is just the obvious next step. I mean it's really, really obvious. And here, you see a unified agent management platform that manages intent resolution AI agents and humans working together, right? You've got AI agents that are reaching out to humans for help. And you've got entire fleets of agents that are not generic out of the box agents. They're working together to resolve intent journeys, all the way across the front to back office. And you could see how much -- how many operational dollars you're saving, how many agents you have deployed. It's really, really important. And some of the reality of having all this data is optimizing AI agents and testing and evaluating AI agents is really difficult. It's actually an open research topic. Are you going to use goal-based evaluations? Are you going to write all the goals yourselves? Having this 40 years of data on what great conversations look like, what resolution looks like allows us to create AI agents that actually resolve customer issues and not have to create them manually, right? I think in this sort of near-term future, you're going to see there's going to be a lot of adoption in AI agents, but creating those agents is difficult and being able to automatically create some gives us a huge head start.

So once again, the unmatched domain expertise that we have in resolving intent is really the key here. You cannot expect other organizations that don't live and breathe customer intent resolution to understand how AI agents to solve problems. And you see this across the market today. Our platform is purpose-built. We have tens of thousands of integrations across the platform. Hundreds and millions of journeys flow across the platform every month. We understand these systems really, really well. We have thousands of AI models that understand what good conversations look like and what resolutions look like. It's unmatched expertise and our sort of transformative approach going from conversations and journeys to creating AI agents to solve those journeys automatically is truly unique in the market.

And with that, I'd like to introduce Beth. Everybody knows her.

Thank you, Neeraj. And just in case everyone doesn't know me, I'm Beth Gaspich, I'm the CFO at NICE, and I'm pleased to be here with all of you today. I'm going to close out our prepared remarks. And I want to assure you as well that I'm the last speaker before you and lunch in case you're hungry.

So I hope you've heard throughout all of our speakers and presenters today, just how excited we are about the future of NICE with our CX AI platform and what it means in the next wave of transformation in the CX and customer experience era. Every time I see the demos from Phil and Neeraj earlier, it reminds me of just how I'm increasingly impressed with the opportunity we have in front of us. This is -- it's important to highlight that is real technology. NICE Cognigy is deployed in large enterprise customers, global marquee brands like Lufthansa Group that you heard about from Nick. So it's really exciting. So what I want to do is start back with where Scott began and started earlier today talking about the massive opportunity that exists in the AI market and how we are going to capitalize on that with our leadership and the strength of our assets.

After that, you've heard from our product leaders, starting with Jeff. You heard from Nick, you heard from Neeraj, you also heard from a customer that our innovation together with Cognigy is perfectly positioning us to win in the CX AI era. So now in the next several slides, what I want to do is share with you how we are also perfectly positioned to win from a financial perspective and capitalize on this massive opportunity.

So I want to start with talking about building on our profitable foundation. NICE has a proven track record of strong financial performance. You can see that since 2020, our revenue has increased at a compounded growth rate of 13% and we exceeded $2.7 billion in our total revenue last year in 2024. If you look on our profitability and our operating income, you'll see that we're growing even faster at a 16% compounded growth rate over that same period. And importantly to highlight the great track record of our operating margins throughout that time, exceeding a 31% operating margin last year. This healthy financial profile really demonstrates the great best-in-class operating leverage we have at NICE, but as well as a testament to the scalability of our CXone cloud platform and the ongoing financial strength and discipline we have at NICE.

Further looking at the strength of our financial foundation and the health we have at NICE, free cash flow, it's one of our greatest strengths, you can see over the same 5 period that I talked about previously, we had a 15% growth annually in our free cash flow, and we generated more than $700 million in 2024. Throughout those 5 years, we have consistently shown and delivered on very healthy, best-in-class, very strong cash generation from our operations. And of course, it's important to highlight that, of course, during this time, this has allowed us to make strong, bold strategic investments like the one that we just did of Cognigy.

In the third quarter, we spent about almost $1 billion acquiring Cognigy. In the same quarter, we continued the strength of our buyback program. And in parallel, we paid $460 million of debt, ending the quarter with no debt on our balance sheet. And we did all of this through this strong free cash flow generation and exited the quarter still with nearly $0.5 billion in cash. So our strong cash flow generation really sets us up well to step into and capitalize on this next opportunity in front of us. And really, it demonstrates both the financial resilience and agility we have in our business.

Next, I want to share with you a little bit about how year-to-date we have consistently delivered on our revenue and profitability targets. You'll see that through the first 3 quarters of this year, in total revenue, cloud revenue and EPS, we have exceeded the midpoint of our guidance consistently across all 3 each and every quarter. And the other important area to highlight here is the stabilization of our cloud revenue. And you see that 12% plus growth in the first 2 quarters, of course, coming -- excluding Cognigy, and achieving that 12% in Q3 also excluding Cognigy, with a 13% growth overall in the third quarter, inclusive of Cognigy in our cloud. This growth that we're seeing and the impressive results that we're putting on the board here are really being driven by the success we're seeing in AI. Our capital allocation approach as well uniquely sets us apart at NICE. So I talked about the significant amount of free cash flow that we generate and the strength of our cash and our balance sheet altogether. It's important that we always continue to deploy our capital in a disciplined way. We've done that historically, and that is our plan looking forward as well. We're going to continue to propel the business forward and we're also planning to deliver significant shareholder value. Our approach is really 3-pronged. So it's focused on these 3 different pillars, and I want to talk a little bit about each one. The first is strategic and disciplined investment, and we prioritize investing organically. The areas that we're focused on and we'll talk more about organically are around, of course, driving our product innovation, both fueling Cognigy as well as our other AI product road map.

The second is around increasing go-to-market efficiency, which, again, I'll talk more around the strategic partnerships and how that's positively impacting that growth and expansion, and of course, AI and cloud delivery. All of our organic investment is also allowing us with that free cash flow to continue to look at acquisitions as well. With respect to acquisitions, typically, what we're looking at is technology tuck-ins. So we look for tuck-ins that fit and complement naturally our CXone AI platform. So while we are primarily focused on these types of tuck-ins, we also remain open to larger acquisitions as well as long as they're meeting our strict criteria, both financially and strategically, they continue to drive us on that road map and the overall CX AI strategy.

Finally, the expanding share buyback program, you've seen that we've increased our buyback throughout the course of this year. At the end of the third quarter, we had increased our buyback by 18% on a year-to-date basis. And we have a tremendous yield of a buyback yield of greater than 5% over the last 12 months. So we continue to prioritize in addition to the spend we're doing organically as well as for acquisitions in our buyback program.

Finally, our rock-solid balance sheet is something we're highly proud of at NICE. We continue to fund all of these capabilities that I've highlighted as well as those share repurchases. We announced a $500 million buyback program earlier this year, and we're also continuing to make that a mainstay of our program.

So these 3 pillars and the strength that we have in our capital allocation with great ample flexibility to fund on growing top line growth as well as drive increasing shareholder value and returns.

We've built NICE both on resilience and flexibility. And we have an incredibly strong financial foundation that is going to allow us to continue to accelerate this top line growth. Our plan is to accelerate that top line growth and shareholder value by making some targeted and strategic investments in the coming year. These investments are going to be highly aligned with the growth catalyst that Scott talked about earlier today, and then I'll share a little more about to ensure we win with precision and purpose. So these are the 5 growth catalysts that Scott highlighted earlier today. What I'm planning to do is actually show you some financial metrics and data behind each of these that demonstrate the grow -- great positive momentum we're already seeing in each of these growth catalysts. So all of these 5 growth catalysts, of course, are overlaid by the incredible cross-sell and upsell motions that we have at NICE. And so we have multiple different levers that we are using to accelerate top line growth. And it's important to highlight as well that this cross-sell and upsell motion, we now have even a greater customer opportunity by also cross-selling into that Cognigy installed base as well.

Growing demand for our AI is our #1 driver of our top line growth at NICE. We're seeing rapid adoption of AI across all facets of our business. And you can see we expect Cognigy to further accelerate that growth. Customers are choosing NICE because they look for us to lead their AI transformations. They see the positive impact that we have on the customer experience, that we understand the customer journey. And you can see and -- financially quantifiable metrics and outputs like you saw from Phil earlier today, that this is real, customers can measure the positive impact in ROI that they see from our technology.

So our customers are choosing our CXone platform. And this is allowing them to augment their workforce, allows them to orchestrate workflows and of course, to automate with AI and our Cognigy and AI as well as our organic NICE AI as well to automate those experiences using AI. Here, I want to share a little bit of in numbers how we see the acceleration of AI in our business. So from the start of this year, we began sharing with you our AI ARR growth on a quarterly basis. You can see throughout the course of this year, our growth is getting stronger and stronger. And this is even before the acquisition of Cognigy. So in the third quarter of this year, just a few days ago, we shared that our year-over-year growth in our AI revenue grew 43% and that further increased to 49% when you add Cognigy in that picture. And we remain confident that our CX AI ARR is expected to grow more than 2x by the end of 2026 as we exit the year. We're on a great path. You can see that based on the growth. We see that in places such as our pipeline, the RFPs that are coming in. The recent bookings where Scott shared that we had AI in every single 7-figure ACV deal. So we see it in the numbers. And of course, we expect further growth acceleration from all of our AI offering beyond 2026.

Earlier, Scott also mentioned that I would talk to you a little bit about the pricing model. From -- over the last several years, our pricing model has continued to evolve, and it has continued to evolve to really ensure we are monetizing the opportunities and this continued shift towards AI. So I'm showing you here a very simple look of what our pricing model is composed of. There's primarily 2 key levers. They are users on the platform and sessions, which you can consider as interactions. So we are monetizing across both of those. So regardless if you are a user, human-led on the platform or if it's sessions, the pricing model will monetize and accelerate the growth from both of those. What we've seen over the last year is the growth in the sessions is greatly outpacing the number of users. That means that the AI that's coming through and the shift to AI and automation, we see that in the volumes, which I'll share a little more with you. So as customer automation is increasing, we're seeing the positive impact of that. And you saw that in the prior slide with the increasing growth in our AI revenue that we're generating.

Finally, regardless of the mix, whether a customer is using our copilot to augment their users, and drive a better user experience or if they're fully Agentic and using AI for automation only, our model is designed to accommodate and drive growth in any of these levers or a combination of them as well. So here, you see more evidence that our pricing model is working is exactly as we designed it. We're seeing that the growth acceleration that Scott talked about, which has been phenomenal growth in the agent and agentless automated AI is really taking off. So the volume interactions that are AI-driven is really accelerating. And you can see that there is a parallel growth as well in our AI revenue. So the pricing model is working exactly as defined that as automation and AI use increases, we're seeing that direct parallel correlation into our AI revenue.

So now I want to shift away from talking around the pricing model and talk more about what we're seeing from customers. You heard earlier from Nick from Lufthansa Group, but I'm going to share 2 other real customer success stories with you. The first customer success story is a Fortune 500 Media and Entertainment customer, and this customer started their journey with NICE back in 2023. This customer initially adopted our core CCaaS offering. So that included also digital channels. And as they stepped into using our CXone platform, they created a really strong operational foundation for them with the customer experience. But in 2024, you'll see that they came back and purchased additional AI capabilities. At that time, they purchased both our autopilot capabilities as well as knowledge management and that allowed them to automate their front-office interactions, but also guide their agents in real time. And you see that increase in revenue that we received as a result of that additional adoption during the course of 2024. But they've had a great experience. This customer continues to come back to us. And most recently, they have further that by now also deploying a lot of our CX AI models. Earlier today, Phil talked about the strength of the data as well as Jeff, that we have at NICE. For decades, we have been delivering intent-based outcomes to our customers. So we have proprietary data that allows us to drive the best resolution for our customers. So our customer and this success story came back, took on that additional CX AI models in addition. And you can see the great trajectory of growth we've seen over this period. that in '20 -- between 2024 and 2025, the AI growth in the recurring revenue for NICE was 71% year-over-year. And the growth in the overall revenue and spend at NICE increased 45% year-over-year to $9 million. So you can see that we -- it's a great growth that we're seeing in the overall AI. And what's important to highlight about this story is the transition and the transformation the customer is going through. You'll notice that the seat count initially increased in 2024, but then as they adopted more of the AIs and they become further embedded in their environment, you can see that they actually successfully reduce the number of human agents in 2025. So they were able to do this. They have reduced costs. We've delivered a strong ROI. And of course, it's a win-win for us at NICE as we've seen this great accelerated recurring revenue growth.

So I'm going to share with you a second customer success story as well. So this is a very similar pattern, where initially this very well-known Fortune 500 U.S. utility company came to NICE in 2023 and initially also purchased our core CXone offering. That customer very quickly came back and added more of our capabilities due to the depth and breadth of our platform. They quickly added virtual agents. They added predictive analytics, and they also added automated self-service. What you've seen in this customer is that they have been able to maintain a steady level of agents. In their normal environment and in their business, they would have continued to add more and more human agents, but with the adoption of our CXone platform and our AI capabilities, they have used our AI and Agentic AI capabilities to be able to maintain that steady number of seats. And they've done that with feedback to us that they've improved their customer experience because they're getting a much faster resolution and they're much happier in terms of the interaction with the agents, which are now being guided in real time.

So once again, you can see our economics worked perfectly as designed. You'll see that on the AI ARR, we've seen a 40% increase year-over-year. And in the total spend, we've seen a 26% year-over-year increase. And again, this is just in the last 12 months. And this is just the beginning for us.

We're seeing many, many customers that are on this path initially adopting the core CCaaS capabilities, then starting to get more and more familiar in adopting our other AI solutions that are allowing them to really drive ROI and further our ARR spend with NICE.

So the other growth catalyst, the second growth catalyst is about the migration of the CX customers from on-prem over to the cloud. And Scott talked about that this morning that the estimate is that there are 15 million human agents on a global basis. But it's still expected that there's only about 40% penetration of those customers moving that have already moved from on-prem into the cloud. So this leaves a massive number of 9 million seats that are still available and that we will use to continue to cross-sell and upsell and bring in those new logos onto our platform over the next several years. So there's a great runway ahead that this will continue to inject growth into our cloud. And this is an area where at NICE, we shine. I've shown you some of the strength that we've had in those customer success stories. But you can see we have an increasing number of 1 million plus ARR cloud customers. We operate in the large enterprise, more and more. We are bringing on further large global brands. So this will continue to be a tremendous growth catalyst looking forward for NICE. And today, these 444 customers already represent more than 50% of our cloud revenue.

The next growth catalyst. You've heard us talk about quite a few quarters over the past year. We've seen enormous success in our international business. We've won some great deals, both large deals over $100 million in TCV, but many other smaller deals where we continue to gain momentum and grab further market share. You can see this reflected in the 36% compounded growth we've seen from the third quarter of 2020 and our international revenue and the contribution from the cloud is now 57% of our total international revenue. So more and more of this business is coming in the cloud internationally. This momentum reflects the opportunity that we have as well. When I shared of the 9 million seats that are still yet untapped to move to the cloud, the biggest areas of opportunity there both are in the large enterprise and as well as the opportunity for us internationally.

The next growth catalyst is accelerating our ecosystem. This year, we have both added many new strategic partnerships. We have also expanded a lot of key partners that we work with at NICE. You can see that 73% of our new large enterprise CXone ACV year-to-date at NICE was led by our partners. We're seeing really great success. And through our integration with AWS, Salesforce, Snowflake and ServiceNow, we're expanding our reach. We're accelerating our time to value, and we're driving strong customer success together. This will continue to be a great growth catalyst as we continue to strengthen these partners and use this opportunity to tap into further market share across the globe.

Finally, when I turn to our last growth catalyst, we want to talk about expanding beyond the contact center. First, I'll start with where we work today. And today, automating customer service is orchestrating workflows, which is really our bread and butter at NICE. And this perfectly was demonstrated by the demos that you saw earlier from Phil. So regardless of whether it's human-led or fully automated, automating customer service is the core of what we do.

So fulfilling customer service intent is really the next frontier for us at NICE. We have spent years mastering interactions in the front office between our customers and consumers. And this was demonstrated in the example that you saw earlier today from Neeraj, and it shows really just a glimpse of what's possible and how we're continuing to extend the customer journey. And then finally, when we look beyond the customer service, this is the TAM that today is sitting in front of us, but we have an immense opportunity for new incremental revenue. And this new incremental revenue is not included in any of the financial models that I will share with you. So this is an opportunity that exists going beyond customer service. This is areas where you've heard Phil talk, for example, around proactive outbound capabilities and allowing customers to do more selling to their customers.

So this is really just an area that is the tip of the iceberg that we haven't yet even really started to tap into, but the combination of all of these different areas provide us with incredible confidence and excitement about the future as we start here in the core of our growth where we're already seeing great indications of that accelerated growth, moving into the mid and back office where we can naturally extend the orchestration of workflows and then, of course, the further capabilities outside of the customer service arena.

I talked earlier about our cross-sell capabilities. This slide really shares just the strength of what we do at NICE, but it also demonstrates the intense depth and breadth that we have in our platform, which is now even further enriched with the addition of Cognigy. You can see that our customers routinely come back and buy more and more from us at NICE. And we're seeing that our CXone customers are increasingly adopting multiple solutions. So the deepening adoption we have of all of these solutions and our advanced AI capabilities in our platform is one of the reasons that we feel highly confident about the growth path and the acceleration that we expect to see looking forward and also will provide long-term, durable growth given the stickiness of how deep we are actually embedded within those enterprise customers.

So to summarize for the growth catalyst, you can see we're actually executing on multiple levers. There are multiple growth catalysts that we have in our business, and we have many ways to win. We are seeing momentum across all of those, and we will continue to fuel them, which is what I'm going to talk about a little bit more now.

So with the strength of our financial foundation, the healthy free cash flow generation we have and this immense opportunity that's in front of us with the wave of CX transformation, we are extremely well positioned with our AI and our CX AI platform, we plan to make some strategic targeted investments.

So here is what it looks like for 2026. In 2026, we plan to spend an incremental $160 million to seize the opportunity that's ahead of us now. You've heard about how excited we are, how confident we are that at NICE, we have the assets, we have the market leadership, and we have the financial foundation to fuel and win that opportunity. So the time is upon us, and we expect to seize it by really making these strategic, targeted investments. These investments are designed to unlock that accelerated future revenue growth.

So I want to walk through each of these a bit. The first is the investments around cloud and AI delivery. And the second is around R&D, where we've grouped these together, where we plan to spend about $95 million incremental spend in 2026. And then also in the go-to-market area, where we plan to spend an incremental $65 million in 2026.

So let me talk a little more specifically about where that spend will be going. In 2026, under the cloud and AI delivery, we are going to continue to fuel the delivery of the cloud by optimizing compute, which is needed for the very large enterprise customers where we operate, also to expand our regional infrastructure and resource capacity. I showed earlier that we've had great growth internationally, and we're seeing continuous momentum with a market that's still largely underpenetrated. We've invested in the past couple of years for sovereign cloud. We will continue to do so that and further fuel it from here. And then finally, we will also build AI centers of excellence that will help us drive that important time to value for our customers. And this is all part of the delivery.

Then when we look on the R&D front, for R&D, we purchased Cognigy. We're very excited about what agentic AI means to the inclusion of our platform as well as on a stand-alone basis, and we plan to fuel it further. So we are going to continue to invest in Cognigy as well as our AI roadmap for our other AI capabilities at NICE.

Then finally, on the go-to-market expansion, I've talked a lot about the success we've had this year with the partners that we've either brought on board or that are new for NICE. We will continue to focus on those and use that go-to-market to further enhance and increase our global reach.

And then finally, the last thing on the go-to-market is around the AI-first sales strategy. We are going to bring in tools and more focus on subject matter experts as part of our go-to-market that will also allow us to seize this opportunity. So this is all incremental revenue spend on top of what you would typically see for us. And in a few minutes, I'm going to show you how that all comes together.

First, I want to share what the impact will look like on our gross margin. So in 2025, you see where we plan to exit 2025. And the expected and estimated impact in 2026 is about a 200 basis point impact on our gross margin. It's important to highlight that, once again, these investments are strategic, they're deliberate, they're intentional, but they're also time-bound. So while we will make these significant investments in '26, we will also continue to invest in the course of 2027, but you'll see those margins start to recover in 2027. And then you'll see in 2028 that we're returning back to our expansion path.

So this is going to shift a little way from the internal investments that we plan to make. And I want to focus here around the operational rigor at NICE. One of the areas that we pride ourselves on at NICE is the rigor that we have in driving operating leverage. Today, we are already using AI tools internally at NICE across all of the different domains that you see here. And we've deployed them in highly measurable ways.

So what's important to highlight is that we are going to maintain that continued strong rigor in our business, that operational excellence that we've been known for. So while we're making those strategic investments, we are also putting in more and more AI embedded capabilities within our company to drive ongoing operating leverage long term.

Next, I'm going to move to our operating expenses, where you'll see that we have increased go-to-market and R&D investment to accelerate our top line growth.

First, I want to highlight, it's important to note that the percentage of revenue that we're showing here for OpEx is actually inclusive of R&D capitalization. We wanted to show you the full spend that we have on the R&D front, but that should be taken into consideration that the portion that you see on top of these bars is what we're capitalizing and putting back on the balance sheet, but this represents the full spend we have.

So the plan that I talked about where we're planning to target these deliberate investments, are showing up here. So you can see that a big area of expansion and these deliberate investments, first is in our sales and marketing, where we expect our expense ratio to move from 20% to 22% in 2026 and to continue to invest, and that sales and marketing ratio will increase to 24% by 2028. For R&D, you can also see this combined spend of about 15% of our total revenue estimated for this year, and that we will continue to further fuel that over the next few years as well.

So these investments are going to allow us to really seize the opportunity to make these intentional investments to be able to drive that growth momentum we see in the top line and to really capitalize on the opportunity both with Cognigy, but more broadly, the CX AI transformation that is happening.

So now, I want to bring everything together financially and what you should expect. We expect revenue growth to grow from high single digits, which is what we expect this year and the 7% to 8% total revenue growth that I mentioned just a few days ago as we reported our third quarter earnings. And we expect to see that growth acceleration continuing to extend first into 2026, where that range is now moving from 7% to 9% in 2026 and to further accelerate to an estimated double-digit growth in 2028 between 12% and 14% on our total revenue. This will all be driven by all of those growth catalysts that I talked to you about earlier.

The cloud revenue growth is going to be driven by those cloud -- those different catalysts that I mentioned and of course, with AI being the #1 key driver of that growth. Our expectation for cloud revenue growth is a range of 12% to 13% for this year in 2025. And we just increased our cloud revenue expectation coming out of third quarter. I want to reiterate that expectation is that we have maintained an expectation of a 12% cloud revenue this year, exclusive of Cognigy and incremental growth as well coming in the Cognigy acquisition that we just recently closed.

Moving into 2026, we expect Cognigy to add about 150 to 250 basis points of incremental growth in our cloud. And during that time, we have seen already the stabilization of our existing cloud revenue, where we also see many indicators of accelerated growth. With an expected outcome by 2028, we will see a 17% to 19% expectation in our cloud revenue growth. So the investments that I highlighted earlier are intentional, and we feel that we want to move now to take time during this wave of transformation to really capture this growth and fuel it here at NICE.

So now beyond the top line, I also want to share with you what it means for our margins. So the margin profile with this incremental investment injection, we'll expect to see a shift from where we expect to outcome during the course of 2025 with operating margin this year of about 31%, a free cash flow margin estimated to be about 19% to 20%. So we expect that additional investment to result in a 25% to 26% operating margin during the course of 2026 and an 18% to 19% impact on the free cash flow. Again, you'll see that return to profitable growth and the operating leverage in our margin coming out in 2028. And that will happen gradually throughout the course of 2027 as we step into 2028.

Earlier today, I mentioned the strength of our financial foundation and our healthy free cash flow generation. So throughout this time, while we make these incremental investments to drive acceleration in our top line, we also plan to continue to return to our shareholders through our buybacks at least 50% or greater of our annual free cash flow. So in any scenario, we are going to maintain a balanced approach where it matters, keeping a disciplined yield return profile that we expect to yield significant shareholder value as we capitalize on this opportunity and drive this accelerated growth.

The cloud backlog is something that we just shared for the first time in the last quarter and a few days ago. And we've seen that the cloud backlog increased 15% year-over-year. Excluding Cognigy, that same cloud backlog grew 13% year-over-year. The expected duration on that is approximately 24 months, and that gives us really great confidence of this acceleration of our underlying business. And we're -- of course, that will be amplified further by the addition of Cognigy.

AI is driving the next phase of our cloud revenue growth. This year, of the $2.2 billion cloud revenue that we expect to achieve for 2025, AI represents approximately 12% of that. We expect as with AI as our #1 growth driver that AI will expand to approximately 30% of our cloud revenue in 2028, and we expect to achieve a $1 billion AI revenue in 2028. $1 billion of AI revenue over such a short period is, of course, a major milestone, both for NICE, but frankly, the industry as well. So we're extremely excited about this path and the indicators of growth that we see that we plan to capitalize on and further fuel.

So before I wrap up today, I do want to summarize and share what our value creation playbook looks like at NICE. It's composed of these 4 different areas of focus. The first is our cloud revenue growth, where we continue to be laser-focused on that acceleration. And we are perfectly positioned to win in this CX AI market opportunity. Our assets and our short-term investments that we plan to make will allow us to get to this 17% to 19% growth by 2028.

The second focus area is our operating margin. So I've shown you our great track record that we have at NICE of driving great profitability, and we have the operational rigor that we will use to continue to drive that leverage in our model and deliver on this expectation with a return to margin expansion in 2027 and rising margins in '28 and beyond.

The third is the health of our free cash flow. With more than $700 million in free cash flow that we generated in 2024, we run a very healthy and profitable business. We have tremendous retention rates from our customers. You can see just how sticky our customers are. As you saw how many different solutions as part of our CXone platform our customers are using that are very embedded in their day-to-day and their mission-critical customer-facing opportunities with those consumers.

For free cash flow, you can see we expect the margins to be 20% to 21% in 2028. And then finally, capital return, where I've mentioned that throughout this period on an annual basis, we expect to deliver at least 50% of our free cash flow back to our shareholders through our share buyback, where we have a $500 million share buyback program in place for us to utilize.

So bringing this all together, we have the perfect playbook, the financial foundation. We are positioned to excel and win in this next era. Together with Cognigy, we couldn't be more excited here at NICE to drive forward and be the market leader in this enormous transformation that is happening in customer experience, ultimately, leading with strength, investing with purpose and delivering value.

So thank you. That concludes my remarks. We are going to now break for lunch, and then we will come back for Q&A. Thank you.

[Break]

Okay. So before we kick off, maybe I thought I would just say a few words because you've seen the whole morning in the presentation. You've seen, I guess, the overall vision that we have, the product capabilities, the financial outlook. So I just want to set the tone and set the scene.

We are in growth mode. Now I sort of opened that up this morning, but when you're in growth mode. When you've got a market that is -- has got a growth opportunity, we are unapologetically driving long-term growth. The vision for this company is clear, long-term profitable growth, but the time is now. This isn't a market where I can sit there and say, oh, let's acquire Cognigy and let it run as it is and try to capitalize. We're going to double down. So a lot of the investment that you saw is on the back of seizing the market opportunity. A lot of it is related to making the acquisition of Cognigy and the AI capability live, real winning for this company over the long term. We are clearly pivoting ourselves in a growth mode of this business. And so it is about the long term. We're driving that long-term growth.

When it looks at the investment and Beth has had the opportunity to present it, but it's not a long window of time where we're that additional $160 million, that is not -- we're not going to go continually in that -- going down the margin. We're going to lift the margin back up, and it's going to be scalable, profitable growth as we continue to expand, but we need to seize the opportunity now.

This isn't a company where I can say, let's just try to continue at the same margins and expect the growth profile. There is a lot of companies investing in the AI market in this space. We have an opportunity to lead and dominate this market, but we need to move. So that's the reason why you saw the implications on 2026, but I hope you would have confidence that through that, we're able to then drive long-term growth because I would remind you, even without those investments, we're already back to organic growth of our core, accelerating that growth. So we're reaccelerating our core growth. Then you add the Cognigy and the AI impact, and then that growth becomes more long-term sustainable.

So I wanted to highlight that because I didn't have the opportunity in the beginning. You can see the product capabilities where we want to go. You can also see what we're trying to drive in terms of that high-growth balanced business. And the last that I will say is you will see the margin profile is a very favorably comparison to most of our peers, and we will drive that margin growth as well as the top line growth in a more balanced way.

So hopefully, that answers, I guess, a couple of questions that I had immediately after the session. Happy to answer any more in that regard. And I'm not sure who's controlling the...

If everyone could just raise their hands, we'll call on you and we'll get you a mic. So why don't we start with Tyler?

Maybe a multipart on the big highlight, obviously, investing for growth. So Scott, you came in earlier this year, I guess, it feels like, as you said, longer than the year. NICE, as a company, has historically been a very financially disciplined company, right? Beth showed the chart of kind of consistent expanding operating income. We've seen really good EPS, growth CAGR. Like what specifically were the biggest areas that you kind of came in and said, gosh, like we're massively underinvested here. And I guess for Beth, I mean, as I look at the free cash flow margins, last year, I think you did about 27% free cash flow margin. Even at...

26%, but close enough.

Yes. The mid-20s. Like even as I look to 2028, it doesn't look like free cash flow margins are getting back to that. So just help us understand the free cash flow dynamics there, too.

So I'll answer the first one on the investment and what was missing or it's probably not about missing, but it's more about emphasis and capitalizing on the opportunity.

So 3 parts. The first is clearly a native AI capability. So if you look underneath our platform, we worked with a lot of partners that we needed their AI platform embedded and underneath to be able to deliver to an AI experience. The market is pivoting. I've presented the numbers. If anywhere between 30% and 80% of the volume of interactions can be delivered in an AI-native way as this context as the center of engagement, the customer engagement platform, we have to own it. We have to be at the center of it. That is a core part of what we offer. That's not something. So that was a core capability and Cognigy was the perfect mix. And I would highlight Cognigy. If you heard, Nick, scale, it's a platform. You don't need forward deployed engineers. We don't use those terms because it's already built. So an analyst, you could sit on there, create agents, low-code platform is a great platform view. So AI is one.

The second is international markets is not just about sovereign clouds, but it's also about feet-on-the-street partner ecosystem, our own teams of sales covering those markets. And that market is not well penetrated from a CCaaS to the cloud. So we've got to move faster and more aggressively to be able to seize on that opportunity. We were already doing it, but you don't want little increments. You got to go and both because once they've moved to their CCaaS cloud platform, it's pretty hard to change.

And then the third thing that I would say is the underlying core AI platform when you combine this together in CCaaS platform, we believe it needs the opportunity to accelerate that, that Jeffrey is going to drive, that native AI CX platform and the way the market is going to require that -- requires that as well. So winning the AI, including in a market where we have 0 participation that drives tremendous growth; International markets, given the size and scale of the coverage; and then last but not least is a core stack that we're able to then expand into those adjacent markets. So core platform going into the front, middle and back office, fulfilling journeys, going into sales, going into marketing, those expanded areas.

I think the way I would best describe it, Tyler, is we are really driving to capitalize on the market opportunity, but I can't sit and wait. If we sit and try to hold on and then manage it, we didn't buy Cognigy to run it as it is. We bought Cognigy to be able to really double down our investment in it to continue with leadership so we can -- because the market will move, it won't wait for us. In fact, we will lead the way, and it will actually cause our competitors to have real challenges because we'll be able to dominate where we currently don't participate. Beth, do you want to answer that?

Yes, sure. Let me take the free cash flow. So as you can see, I mean, we consistently generate significant healthy amounts of free cash flow. When you look on the free cash flow we generated in 2026, relative to what we're seeing this year, first of all, I would say last year, we generated more than $700 million in free cash flow. On a year-to-date basis, over the last 12 months at the end of Q3, we had almost generated another $700 million. So continuing to generate profitable cash that we invest into the business.

When you look on the free cash flow margin as a percent of revenue in last year relative to what we expect in the current year 2025, there's 2 key factors, which are different year-over-year. One, of course, is Cognigy and the impact of that from the date of close through the end of the year. At the time that we announced the close of Cognigy, we mentioned that we do expect that it will be dilutive in the near term. Over the first 18 months is the estimation based on our financial models that by the time you get to around the 18-month mark from the date of close, you'll see a return to accretion from -- coming from Cognigy, both in EPS and cash flow, by the way. So that's one of the factors you see in the current year.

The second item that you see in the free cash flow impact this year is a nonrecurring onetime item. If you look back on the second quarter, we had an issue of a tax matter that settles. That was a onetime nonrecurring item in the second quarter. Those kind of items are -- you can't anticipate the timing of the close, but that happened during the course of Q2. It was actually quite a favorable outcome. And you can see that because if you look at our effective tax rate during Q2, it wasn't changed, so we had more than adequately reserved for an expected outcome there. However, it did impact the free cash flow impact this year. So if you normalize those 2 impacts, Cognigy, together with that onetime nonrecurring item, you'd see a similar margin to what you saw last year.

I think, more importantly, as we look forward, we're all very excited and sitting here about the opportunity that's ahead of us. And so we want to fuel it. And so I've talked about the investments that we plan to make to seize the opportunity. And when you look at the expected free cash flow margin even during the course of this fueling where we're fueling the roadmap of Cognigy and our AI roadmap and everything we're going to do to capitalize and seize this opportunity, it's an important part that we feel is highly necessary to drive that accelerated top line growth and durable sustained growth over the long term.

Yes, over there. If you don't mind, state your name and your firm, please.

All right. Wonderful. Rishi Jaluria, RBC. I really appreciate all the details and greater transparency. Definitely something I think a lot of us will go back and really appreciate as we rebuild our models. Maybe 2 questions. Scott, I didn't -- obviously, I can understand why today is very CX-focused, but I'd have to imagine there's probably a lot of excitement around the FCC business as well, especially if we think about the -- maybe I don't want to call it opportunity, but the risk that AI agents create more fraud, more complexity in the financial systems, which probably creates an opportunity for you, and maybe even leveraging AI within the FCC platform to make it easier for firms like ours to stop fraud and really get just more insight into what's going on. So I would love to hear a little bit more of your thought process there.

And then one that would be, I think, both for Beth and Scott is just around the gross margins. Totally appreciate that you're bringing down gross margins in the near term. It makes sense. Totally get that. It seems like you have confidence in that bouncing back pretty quickly in 2028, in spite of the fact that your AI mix shift is going to go up pretty dramatically, right? And obviously, cost of inferencing might be coming down a little bit here and there, but maybe walk us through what gives you confidence in gross margins rebounding back, especially as those that AI mix continues to go up and up and up, and we're going to keep having more complex models that just add more drags. So maybe walk us through that.

Yes. Great questions. So you're right. We put a great emphasis on CX today. I mentioned the FCC or the Actimize as most people know it, and the public safety business at the beginning. And, obviously, the CX business, more than 85% of our revenues, is the primary, and we are very focused on capitalizing that opportunity.

Having said that, we are the market leader when it comes to financial crime and compliance. We have a great track record. And the beauty of that business, as you described, is AI from a machine learning point of view is entrenched and deep and really domain specific. It's actually very strong with -- in a highly regulated way.

Businesses are clearly the bank, the financial institutions are working with us in using the generative models, but there are 2 factors that continue to be -- to play a role. I think in the usability of what we're seeing in that space is, companies where you've got your investigators are using AI to be able -- the generative AI platform and more on the investigation and streamlining and shortening cases and the investigation.

But explainability matters. I use -- I like the example that Nick used in the CXone going from deterministic versus probabilistic. You can't use probabilistic when you're talking about fraud. It has to be something that's explainable. So what we see is the continued investment of that platform. So it's a great growth opportunity. As you know about the Actimize business, it has not -- it's got a lot of runway in terms of the on-prem customer base and moving over to our cloud. So it's a real growth driver. So it's a great business in its own right and opportunity there. And Beth, if you.

Yes. For the gross margin, I would highlight a few things. I think, first of all, it's important to highlight that we are in the early adoption stage for many of our customers, both as you think about a lot of the very large international customers we've added over the last 12 to 18 months as well as many of the AI customers that they're in the early phases of adoption. So we've already embedded a lot of those fixed costs without giving the benefit of the ongoing ramp that we'll see in the cloud, that's going to be further accelerated that growth trajectory as we see ongoing adoption of AI, and we showed you a lot of that in the interaction volumes today.

So we see the signs out there that give us the confidence that we've made these investments, but on the other side of that, you're going to see the cloud growth accelerating and driving accretion to the margin. Similarly, on AI specifically, we see that our AI solutions and Cognigy are going to be accretive to our gross margin.

We've done a lot of the AI development of our AI internally over the years. So in some -- to some extent, it's some cost. Of course, we continue to invest, but a lot of the AI is our own technology, the AI proprietary Enlighten models as an example, a lot of the AI other solutions that we've built.

So today, we integrate with a lot of the LLMs, but the LLMs are agnostic. So it also gives us the flexibility that if we find that we're partnering with a third-party vendor that is more expensive, then we have the option too to switch. We're not wedded to any particular vendor. So I think the combination of those things, the top line where we have early days in terms of the cloud revenue contribution, together with the accretive nature of what we offer and the meaning and value that it brings to customers from these AI capabilities and more agentic AI, while they're getting a strong ROI. So they're willing to spend more with us to save significantly more on their end.

Question down here in the second row, please.

Sorry for being inconveniently placed. Samad Samana from Jefferies. So just if I think about the disclosures around where AI revenue is in terms of cloud today, just back-of-the-envelope math, I apologize, I'm doing this in a notebook. It's about $260 million of AI revenue that goes to $1 billion in 2028. Can you help us, maybe understand how much of that is NICE pre-Cognigy? How much of that is Cognigy given that you gave us the $85 million end mark for '26? I know, again, I'm not trying to make you do back-of-the-envelope math without a pen and paper up there, but just help us think about those building blocks. And I have one follow-up.

Yes. I would start by saying that the Cognigy contribution, we expect it to add about 150 to 250 basis points of contribution to our cloud revenue each year on an annual basis. So that's the contribution from Cognigy. We broke it down this year as well in 2025. It was about a 50 bp impact positively to our cloud growth in Q3. We expect it to be about 150 bps to our Q4. That's for 2025. And then as I said, extending the 150 to 250 as you look forward to next year. So we expect it to continue to amplify our growth. And this, of course, is already on the stabilization of the cloud you've seen on the core CCaaS side.

Yes. What I would just add a couple of things, if I can. So Cognigy, it's pretty hard by the end of next year, it's going to be pretty hard to distinguish. There is no other AI platform. It is the Cognigy platform embedded on the CXone stack. So there's no separate. We're using the agentic capabilities, the conversational capabilities. The models, the Enlighten models, the CX data, all those things, obviously, leveraging on the CX platform, but it is one AI platform.

But what I would say is if you think about, where our growth to get to that $1 billion, it will be CX customers, CCaaS customers of NICE, where we cross-sell Cognigy capabilities at scale. We will win stand-alone with Cognigy as a stand-alone player where we do not get reached today. That is all incremental. And then we're able to go into the mid and the back office and do more things with our customers' AI capabilities beyond pure conversation, more use cases, more scenarios. So those 3 under the AI banner are the growth drivers. So it's an accelerating.

So as you can see, our total growth rate going up to the 17%, 19% in the cloud, but the AI growth rate, obviously, way more than that. But you don't really distinguish post -- once we've gone through the acquisition and the integration, and we're investing a lot of short-term impact on that margin is very much around the acquisition of Cognigy and seizing on the opportunity in front of us. But once you get through that, it is NICE's CX.

One follow-up. Everybody describes AI as a gold rush. So I think that NICE is showing their actions are behind it, right, whether it's the acquisition of Cognigy, now accelerating investments for next year. Just maybe help us think through though, what are the guardrails that you put around in terms of seeing. Should we accelerate even the investments you announced today based on what maybe the proof points of success are? Would you overshoot it and/or on the other side of that, what are the guardrails on the other side? So just help us think about your framework around, this is the anchor point going forward.

Yes. So first and foremost, being -- it's easier to chase the puck. So if you noticed in the short-term guardrails, we presented 5 growth catalysts. 4 of those are very clearly associated to the midterm guidance that we gave. AI everywhere, automating AI creation, CX market jump balls, international and strategic partnerships. So you are clear and using those and having multi pivots, whereas I would argue 2 years ago, it was the CCaaS move that was our primary growth driver. So we've clearly put more arrows in than we can fire.

The contact center, beyond the contact center is really exciting. And what Neeraj presented, the opportunity for us there is immense. That is more about an engineering roadmap, but we're not getting ahead of ourselves around trying to chase those end-to-end scenarios because there is a big CX in customer service and automating that without needing to go too broad or too wide.

So one of the guardrails is be clear and sharp in our purpose and being maniacally focused on that. So as these new things come up, we're able to then absorb. So as the market, this will continue to evolve, we focus on those CX journeys, which means those adjacencies will be very purposeful in investment and very purposeful in outcome that we expect to deliver.

And then the other one is on that international expansion, as much as I'm very excited about, we're not going to go into every country in every geography where we don't need to, where it has a high cost to serve. So we're really targeted about which markets. So obviously, with Cognigy, Beth really talked about it today, but we get a tremendous uplift from the go-to-market that they have with their European presence, their relationship and their knowledge.

If you go into Germany, when they think about an AI market-leading company, Cognigy is at the top of the list. It's -- and so we're able to use that in the European market and be able to expand there. Same when we go into Asia, it won't be to every single country. We're not going to 50. It will be really purposeful on the big markets.

So I guess what I'm highlighting is our growth is really purposeful and targeted. Our innovation is really purposeful and targeted. And so we are delivering value that we can resonate as a market leader, as a CX market leader rather than being an AI player that can do a lot of different things.

My analogy is many AI players are trying to be an inch deep and a mile wide. We are deep in the CX market. I believe you will find. In the different domains, you will get leaders in each of those domains, whether it be in HR or finance or supply chain or procurement, there will be leaders that will go deep in those domains, we will be deep in the AI CX market.

Question down here, please.

Great. Elizabeth Elliott Porter from Morgan Stanley. So first question, just on the hybrid pricing model strategy. The growth in sessions outpacing users makes a lot of sense. We're seeing AI drive a ton of acceleration, more interactions. And so 2 questions. One is, are there any implications for the revenue visibility as customers shift more towards pricing per session rather than pricing per user?

And then second, one of the pushbacks that we often hear from customers is as we price by session, by interaction, costs can quickly get out of control. So is there anything that you guys are doing in terms of guardrails or holding customers' hands in order to help manage the transition between users and sessions?

Yes. It's an evolving one. So first of all, we wanted to present on the pricing because it is a changing buying mix. When you do those 7-digit ACV deals, the proportion that is under the AI that is session-based or interaction-based versus seats. So customers are being very purposeful about buying where they're ultimately able -- if they're going to get efficiency, productivity, maybe even seat reduction, they're reinvesting back into the AI. Again, with Cognigy, we are able to win in both scenarios.

So the perfect one is you keep or you keep on increasing seats, interaction volumes increase, and you have the AI sessions or not. But we've proven and we know with customers such as the media company that even when seats reduce, i.e., so we can see that reduction, the AI sessions more than compensate because you're able to do more of those service requests, you're able to have more of that, so you're able to then drive that certain mix.

And I expect that mix shift will continue where customers will initially look to use productivity and keeping their seat count similar. That's what we've seen so far. But ultimately, once automation really kicks in, the seats will reduce, but they will correspondingly increase their AI side.

So now the second part of your question is about the value, and maybe those -- we're able to -- one of the reasons while you use a CX-specific platform, you can go do -- you can go to an AI and LLM, start doing this natively yourself and realize your compute is out of control. So Phil presented and Jeff presented observability, analytics, insights about what the ROI is, what your cost to serve, and also what the return is. So we're able to give them that observability in the context of CX, and so they can thoughtfully manage that without blowing out their costs. It's one of the reasons why you will come to a vendor like us.

Last but not least is I will say this, we are very optimistic about value pricing models. It's early days. But because we've got the data about where you get value, and for example, on proactive, we know we've got examples with customers where they will pay a significant amount of more per session on some of the outbound scenarios because of the value drivers that it will bring. So they'll spend a lot more on those and then they get the return on it because it's increasing top line, not just reducing cost.

So that gives us future opportunity to be able to use pricing power, using our knowledge about the value drivers and being able to step up to that. This market, most customers ask us for a value driver proposition, but they don't necessarily want to pay for it or price it in. They want to monitor it under a consistent pricing model, but that could evolve over time.

Let's go over here, please.

Tom Blakey from Cantor. Thank you, by the way, for a great presentation and lots of data here to digest. Maybe a multiparter, but I'd like to hear from maybe Scott, Beth and the panel.

The platform consolidation examples that I think the gentleman here at the end gave was great in terms of that credit card fraud example. You're turning 3- to 5-day resolutions into minutes, but there was a lot of different software packages that had to be touched there. So along the theme of platform consolidation, is there enough investment here with this quick hit, if you will, investing in calendar '26, where margins start expanding again to maybe shift in terms of your competitive landscape more on the workflow side and those adjacent market side. I'd like to hear from everybody about are you now competing against ServiceNow and Microsoft? And is there enough investment here that Beth's outlined very articulately to compete at that level going forward?

Maybe I'll just kick us off. I think our focus initially is going to be just that CX workflow perspective. So helping customers from that point of customer engagement, and automating the tasks and orchestrating across the enterprise. So it isn't about taking out those applications, it's about orchestrating on top, right? So that's how we're going to start. That's where customers want us to focus. And then we'll just see how it plays out, right? Does it mean those other systems just have less value to those customers? Do they replace them? We'll see how it works out, but we're going to be very CX driven in that regard, if that makes sense.

Yes. What I would add to it, though, and I guess this is very important because it's very purposeful from our point of view. Those systems in the mid and the back office are largely built around human usage internally. So whether it be use of cases, processes, transactions, it has a flow of activity that is driven by what a user or a department or an area does. We are very purposeful around a customer journey.

Now that doesn't mean that they -- the Lufthansa example, they were really clear about what journeys, what scenarios, what use cases, and what it took to fulfill those to achieve the outcome. You extrapolate that out and what the platform is able to do. We can be super sharp on building out those journeys, those AI agents on our platform that interact with those platforms. And it may mean that you don't need to raise a case, or you don't need to initiate that task because it's automatically happening from our platform.

I say that because it is an evolving mix. As Jeff mentioned, and you know this better than anyone with your background at Microsoft is other vendors have got their own focus around whether it be CRM or finance or billing or those different platforms, they're looking at it from the internal usage. Our focus is from a customer journey. That will distinguish. And when that all comes together, I suspect what you'll see is our focus around strategic partnerships, for example, how we're building collaboration with ServiceNow because if you are going to build in internal workflows that can be used for customer service, we'll use it.

So we want to help customers capitalize on that back-office investment and being able to seize upon that, but we'll do it from a customer journey context, not from an internal workflow or ticketing context. Hopefully, that makes sense.

Let's go here, please.

Alexa Rocha from Guggenheim. I know you started to disclose AI ARR earlier this year. But if you could just provide a little more color on what actually makes that up? I know it obviously has to do with AI solutions, but I'm just curious if there's like a list of products. Just trying to better understand how do you define AI ARR?

So AI ARR, we're very specific. It, ultimately, is a set of SKUs that are AI products either through a direct interaction or a product that is used as a facilitation of that interaction for customers. So very specific, very clear and transparent and tangible that we can then track the growth. And so as we're tracking the volume of usage, whether it be an autonomous one or it's an AI agent that orchestrates that journey or it's an AI product, for example, Copilot that is helping assist, any of those are our AI products. So it really does cover automation, orchestration and assistant augmentation that covers that portfolio.

And I would just further clarify that it is CX only, the AI that we report and it's advanced AI as well. So we have some kind of early machine learning-based AI that is in CX that we exclude from that. So it's what we characterize as more automation-based AI.

Okay. We'll take this next question from the webcast. The question is on expanding the contact center, can you do this alone? Or do you need to make any acquisitions in this space?

So sorry, what was expanding the contact center?

Beyond the contact center.

Beyond the contact center. I sort of come back to the point -- the question that was asked around where we were going to invest. We are very purposeful around seizing the market opportunity within the current portfolio. Cognigy was a big acquisition that opens a market opportunity that is immense for us, both in capturing the automation play on where NICE doesn't play, the obvious installed base opportunity in bringing that together, but then under Jeff and Phil's leadership being able to bring it under a single platform. That platform allows us to go into the market adjacency into the mid and back office and that platform allows us to go beyond customer service into sales, into marketing, into other scenarios.

Having said that, the amount of innovation that's happening in this market that can be leveraged either through partnerships or through potential acquisition, Beth made the comment that we would look at primarily tuck-in -- technology tuck-in acquisitions to expand in adjacencies that would support us.

So we're always open to that as long as it delivers long-term shareholder value. And if it's going to be large strategic ones, it really needs to be justified. We've got very high bar threshold about the return that we would bring. So everything that is being presented does not assume inorganic moves. It is very much around our current capability, obviously, with significant organic investment that we've talked about to be able to seize upon it.

Let's go right here, please, in the second row.

Sam Brandeis, Wedbush Securities. I have a 2-part question regarding competitive landscape. This summer, Salesforce and ServiceNow announced a $750 million joint investment into Genesys. Well, I know you guys made your own deal with ServiceNow and actually tightened with Salesforce recently. What does that joint investment signal to you? And how do you guys view your positioning versus Genesys specifically?

Then Scott, I know you touched a little bit on like hyperscaler competition. How do you see those players, I guess, evolving into 2026? And as they talk about AGI, ASI, if they were to achieve that one or multiple of them, would you see -- would you view that as a risk to you guys and overall industry?

Okay. I'll let you sort of cover the second part, Beth. So on the first part on the investment. Look, I think there's a couple of things to note. And it's not just the investment that Salesforce and ServiceNow made in Genesys. I would argue the amount of the investments that are going into CX AI players and pure play that are trying to -- it is significant. It's a great market.

This is a great market. I can't stress that enough. This is a growing market in its own right, even without because you've got increased demand of volume of interactions, you've got a volume of -- again, I'll just go back to Nick's presentation where he talked about, hey, we're going to -- the way consumers interact with brands, they use websites, apps, mobile, the convergence and the opportunity for us to be a primary engagement platform drive the volume, irrespective of the competitive landscape. So number one, I think those investments, and I can't speak on behalf of those 2 companies, but I think it recognizes that this is a growth potential.

From a competitive landscape for us, all I can tell you is at the same time they were making those investments. They were aggressively pursuing expanded partnerships with NICE because of our market leadership, our platform. So they need our reach, our engagement platform, and they don't want to be limited. And I guess we use it. We're very happy about the competitive scenario because let's face it. We've got a native AI platform. The others don't.

You're going to have to use either ServiceNow or Salesforce's AI platform in the CCaaS space. We don't have that concern. We're able to give the complete end-to-end on our stack, including integrating natively with ServiceNow and Salesforce and Amazon and the others, and we're able to do so in a proactive way. So I believe it actually strengthens from a competitive standpoint, but we keep a close eye -- close watch on that.

I'll comment on the hyperscaler and then I'll quickly get.

On the hyperscaler side, look, we collaborate with the hyperscalers. I mean, Amazon, we've got a great partnership. We've got hundreds of millions of pipeline being generated through the Amazon relationship because they've got a reach and a go-to-market that they can bring. Our Cognigy business actually works openly on the Microsoft -- sorry, the Azure on the GCP or on the AWS platform. So it's got a public cloud opportunity to be able to work there.

What I would say is this is those organizations clearly want to be able to advance their technology on a large number of use cases and scenarios. So we're obviously aware of it, but they are -- the depth and the breadth that you need to be purpose-built in this market requires very targeted investment that goes over and above what you're sort of making publicly available.

So I guess what I -- available across all of those different spaces. So we're using precision and focus to be one of our competitive moats. Speed is a choice, but also speed is a moat. If you're able to be deep and targeted and specific, then even if those platforms are or those companies are getting there, you're able to then still get competitive advantage. But do you want to talk about anything specific?

On the AI side, clearly, these models are advancing very quickly. And we see those as very complementary to what we do. Because those models need to execute on a CX contact center platform that has compliance, security, observability end-to-end. So again, massive advancements, just even OpenAI has the real-time GPT or GPT real-time model that's voice to voice, super complementary, right? So we'll drop that in where it makes sense, but that's going to run on top of that substrate that is hardened for contact centers and CX.

So we keep on top of the latest AI. Phil and team are already working with the GPT real-time model to see where it makes sense to use those kinds of frontier models, and we'll just continue doing that. We'll stay up to date. We'll stay on top of the frontier, and it will be complementary to what we're doing.

Let's go to the front.

Willow Miller for Arjun Bhatia, William Blair & Company. So thinking about one of your more historical and ongoing growth drivers, migration to the cloud, can you help us understand what the ARR uplift from on-prem to cloud looks like now, especially the migration includes AI or even Cognigy at the get-go. In the past, I believe you framed the uplift as 2 to 3x.

Yes. So make sure I just understand your question, the ARR uplift that's already embedded now?

Right. So in the past, you had mentioned when a customer goes from on-prem to cloud, you could see a 2 to 3x uplift in ARR. So I'm curious to hear how that could trend now as customers think about AI with that migration.

Yes. Okay. Thank you for clarifying. Yes. So that's correct. When we look at the transition and the migration we've seen of large enterprise, as they migrate, first, if we talk about our own installed base that were prior and previously on our legacy on-prem solutions, as they've migrated over to CXone and our cloud AI platform, I would say, on average, we see about that 2 to 3x uplift of ARR for a typical customer, but we actually have quite a few customers that have given us 8, 9 and 10x uplift.

And if you recall, I showed you a slide earlier today about the number of applications that the customers have deployed, the solutions that are embedded within CXone. They're all seamlessly integrated, but you could see on that slide how I showed that routinely quarter -- each and every quarter, we've seen that customers are kind of cross-selling and buy-selling. And so that just demonstrates the opportunity that we have there.

And during the break, actually, someone asked me as well about some of the customer -- or 2 of the customer success examples that I shared earlier as well. They noticed that not only did we see this great expansive growth in the AI, we also saw it in both of those customer success stories on the non-AI portion. So once again, it's demonstrating that our customers are coming back. They're large enterprise. They have complex needs, and they're buying more and more of our capability.

So when we first introduced CXone, it was the seamless integration that was native to the cloud of workforce engagement and analytics and CCaaS, the ACD. And so that all still exists. And many customers continue to buy that, of course, in the core capabilities we have. So then our AI capabilities, Copilot, Autopilot, Cognigy, of course, the Autopilot, all of that is now further incremental revenue that they're buying. So further deepening of their relationship with us and extending the customer lifetime.

Just to be clear, we haven't actually modeled out what is it with AI. I think it's a little early to be able to say exactly what that ratio is because what we've seen with AI, and Beth mentioned this earlier, most customers start with a number of use cases and then they build out. So you get natural expansion as more and more scenarios, then they start doing auto self-service, they do with assisted, they'll do orchestration journeys. So it's not that they implement everything all in one go, it's an incremental build-out, but we can probably relook at that, and maybe we'll give further update. It's actually a great question.

Yes, it is a great question. And I mentioned it earlier, but also you should recall that our AI is still in fairly early days when we're talking about our AI ARR. So many customers are still in the infancy in terms of adoption. And so it has a natural expansion in the path. And of course, you've seen that those interaction volumes we've shared are just growing tremendously. So that will continue to feed into our AR and AI ARR revenue.

There is time for one more question.

This is Nick here for Pat Walravens from Citizens. Scott, you mentioned earlier today that you were working on decreasing the time to implementation. I was wondering if we could get kind of a baseline for, like say, timing on that right now, and maybe ideally what a potential goal is in terms of implementation?

Yes. I'll say 2 things. So first of all, we have internal metrics. We haven't actually -- we don't show that, but we have increased or improved our time to deliver. I think it's maybe 30% or 40% we've already increased -- we've already improved, I'm sorry. Importantly, though, it does really change depending on what scenario a copilot, where you're doing assistance using the data on the platform, and you can do, those cases have a much shorter time frame versus maybe when you're introducing your self-service for the first time, you're putting the checks and balance the guardrails. Cognigy has a proven method and way of being able to roll out. We are very focused on the assistance that we provide for them.

So the first deploy use case might take a little bit longer, but then after that, then they're rolling out and they're implementing themselves. So it does depend a little bit. There's not like one model. I guess what we are focused though is to make sure we're assisting customers to be able to do it as quickly as possible.

What are the issues that we're actually doing? We've already got the prebuilt connections. We've already got the data. We've already got the knowledge. We already know what the agents do, but putting that into that platform where you build it, where you've got the same or better quality level, so you're testing to make sure that the AI agent doesn't hallucinate, delivers on the service, can manage to at minimum equal or better than what your human agents were doing, those sort of things you need to make sure that you configure and get it right upfront.

Once you do, then you then go and scale the deployment. So yes, this year, we've seen a significant reduction because we did invest in the AI center of excellence, and I spoke about that. So we have seen an improvement by about 30%, but maybe I can give more information in the future -- in future earnings calls about what we're seeing there. It's definitely a focus.

And it continues to be one of the areas that we highlighted that we're going to fuel the investment as well. As you said, Scott, we already did a lot of improvement there with like around a 30% improvement, but continue to be one of the things I highlighted as part of the incremental spend looking ahead as well.

Thank you, everyone. I appreciate your time today. Those who are online, I really appreciate it. Hopefully, you got a lot of value. We're in growth mode. It's exciting times, but I look forward to answering any other questions following on from this event. Thanks, everybody.

Welcome to the NICE conference call discussing third quarter 2025 results, and thank you all for holding. [Operator Instructions] As a reminder, this conference is being recorded, November 13, 2025. I would now like to turn this call over to Mr. Ryan Gilligan, VP, Investor Relations at NICE. Please go ahead.

Thank you, operator. I'm incredibly excited to join NICE as the company's new Vice President of Investor Relations, and I look forward to working closely with all of you in the investment community. With me on today's call are Scott Russell, Chief Executive Officer; and Beth Gaspich, Chief Financial Officer. Before we start, I would like to point out that some of the statements made on this call will constitute forward-looking statements.

In accordance with the safe harbor provisions of the Private Securities Litigation Reform Act of 1995, please be advised that the company's actual results could differ materially from these forward-looking statements. Additional information regarding the factors that could cause actual results or performance of the company to differ materially is contained in the section entitled Risk Factors in Item 3 of the company's 2024 annual report on Form 20-F as filed with the Securities and Exchange Commission on March 19, 2025.

During today's call, we will present a more detailed discussion of third quarter 2025 results and the company's guidance for full year 2025. You can find our press release as well as PDFs of our financial results on NICE's Investor Relations website. Following our comments, there will be an opportunity for questions. Let me remind you that unless otherwise noted on this call, we will be commenting on our adjusted results of operations, which differ in certain respects from generally accepted accounting principles as reflected mainly in accounting for share-based compensation, amortization of acquired intangible assets, acquisition-related expenses, amortization of discount on debt and loss from extinguishment of debt and the tax effect of the non-GAAP adjustments.

The differences between the non-GAAP adjusted results and the equivalent GAAP figures are detailed in today's press release. The information and some of our comments discussed on this call may contain forward-looking statements that are subject to risks, uncertainties and assumptions. I will now turn the call over to Scott.

Thank you, Ryan, and we are thrilled to welcome you on board and have you join our team. Good morning, and welcome, everyone. Well, let me start by saying the renewed strategy that we laid out for NICE at the beginning of the year is now producing clear tangible results, reflected in both our financial performance and our growing market position. We're seeing great momentum across our entire business, setting a solid foundation for sustained growth. We're pleased to report another strong quarter underlined by exceptional cloud and AI bookings, stemming from the continued expansion and execution of our AI-first strategy, our international expansion and our robust go-to-market performance.

This quarter reinforced the strength of our AI solutions, driving real transformation for our customers with exceptional cloud bookings, driving a cloud backlog increase of 15% year-over-year and with our AI capabilities included in every new 7-figure CX deal. In Q3, total revenue was $732 million at the high end of our guidance range, with cloud revenue reaching $563 million, up 13% year-over-year. Our cloud revenue growth was primarily driven by our AI and self-service offerings, whose ARR accelerated to 49%, driven by sustained organic momentum and the contribution from NICE Cognigy, which closed in early September.

This demand for our AI offering is reflected in strong bookings for Autopilot and Copilot deals more than tripling in Q3. We also achieved a higher win rate against our key CX competitors, underscoring the growing customer appetite of our AI-powered and domain-rich solutions. Furthermore, it reinforces our conviction that we operate in a vibrant growing market where organizations are showing robust demand for accelerating their AI transformation using our offerings.

We at NICE perceive AI not only as a catalyst for our groundbreaking innovation, but more importantly, as a fundamental force for reinventing how business, technology and humans interact in each of our markets. In the world of customer experience, our leading CX AI platform, CXone, is using purpose-built AI to reshape customer journeys in exciting new ways. Our AI-powered orchestration allows us to perfectly blend human and AI agents, creating seamlessness in the end-to-end experiences that go well beyond the contact center, delivering automated workflows that move from accurately identified customer intent all the way to organizational fulfillment and resolution.

We're also seeing increased demand for our leading NICE Cognigy conversational and agentic AI solutions, available for implementation on any technology environment, allowing companies to design, run and optimize AI agents quickly and simply with little to no code requirements and with specific CX-built functionality and vertical know-how. There's tremendous added value that we're seeing for the powerful combination of CXone and NICE Cognigy together. Our ownership of the point of engagement awards us a distinct understanding of customer intent, sentiment, preference and context across literally billions of engagements. This distinct AI-ready foundational data then forms the basis for automated creation of smart agentic AI, turning this data into CX-built workflow intelligence.

The symbiosis of CX engagement data dynamically informing AI agent conversations and actions, all happening as a part of a single unified platform is at the core of our differentiation and what sets us apart in our markets. Our innovation road map is already well ahead with many NICE Cognigy integration capabilities already completed and many more underway. NICE Cognigy drives further growth of the CXone platform and CXone accelerates the NICE Cognigy expansion in our customer base, particularly in the enterprise segment.

Combining sophisticated agentic AI with engagement-based data also enables us to change the paradigm of customer engagement from a reactive to a proactive framework identifying business-initiated intents that can utilize human or AI agents to reach out to consumers, increasing sales, reducing effort, improving loyalty and trust. Our CX AI solutions are resonating with organizations of all sizes and verticals as evidenced by some of our key deals in the quarter.

In Q3, one of the leading global auto manufacturers chose CXone to transform their customer experiences as part of an 8-figure ACV deal, underscoring NICE's continued leadership in the cloud contact center transformation and reinforcing the completeness of our CX AI platform. Their decision reflects the growing enterprise shift away from fragmented legacy systems towards a unified cloud and AI platform that enables modernization, agility and superior customer engagement.

In another substantial Q3 deal, AI to cruises chose NICE Cognigy for their FAQ automation initiative, creating accurate dynamic responses to customer requests. Our integration with their existing environment allowed AI to cruises to capitalize on their existing data and workflows while modernizing the overall customer engagement experience. Our AI solutions are also generating strong upsell momentum. Consumer Cellular, an existing NICE customer added AI agent augmentation using our Copilot solution in a 7-digit ACV deal, enabling real-time proactive triggering of agent guidance, injection of knowledge and conversational suggestions and improving the ongoing customer engagement.

Q3 also saw continued momentum in our international business as an increasing number of organizations across the globe look to NICE for their CX transformation. DWP, U.K.'s Department of Work and Pensions, extended their CX sovereign cloud initiative with NICE's self-service solutions in another 7-digit ACV deal, modernizing citizen engagement through automation and digital self-service. They chose NICE for our compliance with sovereign cloud standards, proven public sector standards, platform scalability and our ability to execute on their AI and digital transformation road map.

Our overall strong Q3 performance is further proof that our strategy is hitting the mark and that we're delivering across all our key focus areas. Our commitment to leading the AI revolution in all our markets and specifically in CX with CXone and our NICE Cognigy solutions. The emphasis on developing our ecosystem and strategic partnerships to scale our impact, leverage our collaboration with major technology and GSI partners and with many more to come.

Our international expansion and cloud adoption acceleration in global markets and of course, maintaining our financial strength with both operational rigor and industry-leading profitability while thoughtfully deploying capital through acquisitions and share repurchases. This is the perfect opportunity to remind everyone that our Capital Markets Day is coming up in just a few days on Monday, 17th of November in New York City.

The event will feature presentations from our executive management team covering in more detail our long-term strategy and the future of the CX market, our CX innovation road map with NICE Cognigy and our financial overview, including midterm outlook. If you've not registered yet and you'd like to attend, please contact our Investor Relations team at [email protected]. We look forward to seeing you all in person at this event. And with that, I will now turn the call over to Beth.

Thank you, Scott. I'm pleased to share another quarter of strong financial execution underscored by robust cloud revenue growth and continued positive momentum from our AI and self-service business. Our acquisition of Cognigy, the global leader in AI-driven customer service solutions closed in early September, earlier than originally anticipated, and Cognigy's performance is included in our third quarter financial results. Total revenue of $732 million came in at the high end of our guidance range, increasing 6% year-over-year for the third quarter.

Cloud revenue increased 13% year-over-year, contributing $563 million, representing a record 77% of our total revenue. Excluding Cognigy, cloud revenue increased 12% year-over-year, in line with our expectations. Our cloud revenue growth in the third quarter continued to be driven by the strong performance of our CX AI and self-service ARR, which totaled $268 million in Q3, increasing 49% year-over-year and 43% year-over-year, excluding Cognigy. This key growth driver in our business continues to expand and next-generation CX AI now represents 12% of our overall cloud revenue.

Our fast-growing CX AI is expected to becoming more meaningful in the coming years, especially with the addition of Cognigy, which we expect will further augment our AI and self-service growth trajectory. Our cloud NRR for the trailing 12 months of Q3 was 109%, reflecting continued strength in customer loyalty and expansion activity as we scale across a larger base. Our NRR is reported on a last 12 months basis and naturally lags current trends as demonstrated by our consistent cloud revenue growth year-to-date and the strong 15% year-over-year growth in our cloud backlog, as highlighted by Scott, we're seeing positive underlying indicators that our healthy NRR can inflect upward over the next few quarters.

Our on-premises business performed in line with expectations as services revenue of $139 million represented 19% of total revenue and product revenue of $30 million represented the remaining 4% of total revenue. From a geographic breakdown, the Americas region, which represented 84% of revenue in Q3 increased 5% year-over-year with double-digit cloud revenue growth and strong product revenue, which was partially offset by a decrease in services-related revenue as our customers continue to migrate their maintenance to our cloud.

Our international business demonstrated strong revenue growth in the third quarter as our cloud business continues to drive momentum with our continued success of large enterprise scale wins in the international markets. Our international revenue contribution increased from last year, and we expect this trend to continue. EMEA revenue increased 7% year-over-year and APAC revenue increased 19% year-over-year. Together, our international revenue increased 11% year-over-year.

Our international markets represent one of our most compelling growth opportunities. These regions remain relatively underpenetrated in terms of cloud adoption, creating a significant runway for expansion. We're seeing tangible traction with large enterprise wins in both EMEA and APAC now going live and contributing to our revenue results. Our ongoing investments in sovereign cloud infrastructure are proving instrumental in securing these opportunities, offering local compliance, data residency and trust advantages that customers increasingly prioritize.

In addition, Cognigy's strong presence and brand recognition in EMEA, coupled with their growing presence in the Americas, further enhance our reach in the region, serving as a powerful catalyst for growth and enabling cross-selling of our complementary AI and self-service solutions.

Turning to our business segments. Customer engagement revenue, which represented 84% of our total revenue in the quarter was $613 million, increasing 6% year-over-year, driven by the continued strength of our CXone AI cloud platform across all geographies, which more than offset the continued transition from our on-prem business. Revenues from financial crime and compliance, which represented 16% of our total revenue in Q3 and totaled $119 million increased 7% year-over-year. This was due primarily to strong cloud and product revenue growth.

Moving to profitability. Our total gross margin was 69.9% compared to 71.7% last year, reflecting our deliberate investments to scale international operations and to continue to expand our global cloud footprint where we are already seeing dividends as highlighted in our strong international revenue growth. Our operating income in Q3 increased 5% year-over-year to $231 million, and our operating margin totaled 31.5%. The impact of Cognigy on our profitability was immaterial on our gross margin and operating margin in the third quarter.

Looking forward to the fourth quarter and beyond, we expect no significant impact to the gross margin from Cognigy. However, we do expect dilution to the operating margin, which we previously communicated and is factored into our updated guidance that I'll touch on in a moment. Earnings per share for the third quarter were $3.18, a 10% increase compared to last year. Our cash flow from operations in Q3 was $191 million, up 20% year-over-year, underscoring strong operational execution and profitability.

During the quarter, we deployed significant capital to advance our strategic priorities, repurchasing $41 million of shares, fully repaying $460 million of outstanding debt and funding the acquisition of Cognigy. We ended the quarter debt-free with total cash and short-term investments of $456 million, demonstrating both the strength of our balance sheet and our capacity to invest decisively in durable, profitable growth and create long-term shareholder value.

In summary, we delivered another quarter of strong execution, driven by sustained cloud growth, accelerating AI and self-service adoption and disciplined financial management. Our recent momentum, together with Cognigy now part of our portfolio and a debt-free balance sheet, we are entering the next phase of growth from a position of exceptional financial and operational strength focused on driving innovation, scale and long-term shareholder value. We're excited to share more financial details at our upcoming Capital Markets Day, including a 2026 and midterm outlook.

Now I'll close with our guidance for total revenue and non-GAAP EPS for the full year 2025. Our updated guidance includes the expected results of Cognigy from the date of acquisition through year-end. We are increasing our full year 2025 total revenue guidance, which is now expected to be in the range of $2.932 billion to $2.946 billion, which represents a year-over-year increase of 7% at the midpoint. We are increasing our expected year-over-year cloud revenue growth to be in the range of 12% to 13% for the full year. Previously, we shared an expected year-over-year increase of 50 basis points to our operating margin. Our expectation for our organic operating margin, excluding the impact of Cognigy, remains unchanged. As a result of the acquisition of Cognigy, we now expect our operating margin to slightly contract.

Previously, we shared an expected year-over-year growth in non-GAAP earnings per share of 12% at the midpoint. Our expectations for our organic non-GAAP earnings per share, excluding the impact of Cognigy, remain unchanged. As a result of the acquisition of Cognigy, we now expect the full year 2025 non-GAAP fully diluted earnings per share to be in the range of $12.18 to $12.32, which represents an increase of 10% at the midpoint. I will now turn the call over to the operator for questions. Operator?

[Operator Instructions] Your first question comes from the line of Siti Panigrahi with Mizuho.

I just wanted to ask about Cognigy. You closed in September. So what's your expectation of Q4 revenue contribution from Cognigy? And specifically, how are you planning to position Cognigy in terms of go-to-market? And any changes to the partnership they have with other CCaaS vendors?

Yes. Thank you, Siti, for the question. So I'll start off with the financial aspect of the question. First, we are very pleased that we were able to close the acquisition of Cognigy earlier than originally anticipated. We originally anticipated a Q4 close, and we were very excited that we received the regulatory approvals earlier than originally anticipated. What it means for our revenue contribution is that in the third quarter, it contributed roughly about 50 basis points to our cloud revenue growth from the inclusion of Cognigy. And what we've anticipated and that's included in our updated guidance for the full year is that it should include an increase about 150 basis point impact and increase to our cloud revenue growth during the fourth quarter. So those are the assumptions we've made on the financial inclusion and as a result of the Cognigy acquisition.

And on the go-to-market side -- thanks, Beth. On the go-to-market, it is really clear that Cognigy is a world-class leading conversational agentic AI platform. And they are actively and we will expand and grow going after all of the CX market, whether NICE is the underlying CCaaS platform or not, but more importantly, going after that market because we know those companies who are running on other platforms don't have an integrated solution. They need an AI platform and the Cognigy solution is ready-made and we will go after that market. So we're excited about the potential that brings. And you can be assured that the Cognigy team are very excited to have the power of NICE behind them as we go pursue that.

And Scott, just a quick follow-up to that. We keep hearing from a lot of customers who are not yet in cloud or CCaaS. They use Cognigy for AI. Do you see this is an opportunity now for you to even accelerate or reach out to those customers and move them to cloud as well?

Yes, for sure. I mean if you think about it, we have 3 growth vectors for our Cognigy business that we're really excited about. First, a customer that is in the cloud that have already done the CCaaS migration, but they're looking to do their AI transformation, Cognigy is the market leader. They are fantastic at being able to provide that automation, that customer service experience.

And so secondly, is the nice installed base and the tremendous opportunity in the enterprise customer base that we have, bringing Cognigy into that installed base. And then third, to your point, is we are the only company that has the combined world-leading AI platform and the world-leading CCaaS platform that we combine together. And if they want to start with their on-premise, they want to start with AI transformation, they lead the way with NICE Cognigy. If they want to do their cloud migration on CXone, they start there. But either way, we can give them the end-to-end journey on a unified platform. So it does give us real optionality for our customers in terms of their transformation journey from their on-prem. And that's obviously very exciting.

Great and look forward to hearing more on Monday.

Look forward to it.

Your next question comes from the line of Patrick Walravens with Citizens.

Great. Congratulations to you guys on all the momentum in the business. It's great to see. So Scott, with Cognigy, as you're getting deeper into all these sales cycles, can I ask if you're seeing Sierra? And I bring it, I'm sure you're getting this question a lot, but for anyone who doesn't know, they just raised $350 million in September at a $10 billion valuation. So it would be great to hear your thoughts in terms of what the competition looks like.

Yes. Great question. So let me first say, the growth and the expansion of AI in the CX market is clearly evident. And we've been talking about this for a period of time. But when the introduction of new players, it's a validation of the attractiveness of the growth potential that this market brings. And I guess you can see our move of acquiring a proven market leader. Cognigy is a proven market leader in conversational and agentic AI. They're already there. They're proven with some of the world's leading brands, and it's a testament of our leadership and our ability to capitalize on the opportunity.

And just as a reminder and why we feel really strongly about our competitive positioning, Cognigy was specifically targeted because of its enterprise scale. It is already delivering at the enterprise, the top end of what organizations need of scale. It's easy to adopt. There's no words like forward deployed engineers by our Cognigy team. We don't need services surrounding. It's easy to adopt, and it's proven customer value that we can scale with both CXone and non-CXone customers. So yes, we see new entrants in the market. It's a validation of the potential that market brings, but it also gives us renewed confidence about our ability to lead on an AI-only play, a CCaaS and then the combination of the 2 together. And I think we'll be able to share much more details, Patrick, in our Capital Markets Day on Monday, where we can really showcase that capability.

Your next question comes from the line of Elizabeth Porter with Morgan Stanley.

Now that we're a few months out from the renewed and expanded RingCentral partnership, are there any changes that you're seeing in pipeline velocity or average deal size through this channel? And understanding we're probably going to get a little bit more next week, but any context for how we should think about this as an incremental driver to fiscal '26 bookings?

Yes. Look, it's a great question. So first of all, Vlad and I and our teams have been in really tight collaboration with the renewed partnership. We've got an updated go-to-market. We've got the real potential to have an expansion. I'll give you 2 key levers. One is RingCentral were already an existing partner of Cognigy and a proven scalable partner of Cognigy. So not only in the combined installed base that we have with RingCentral together, but as their go-to-market, as their agentic and conversational AI platform supporting their solutions, it is a great collaboration. We're doubling down on that super.

And then secondly, as you rightly point out, with our renewed partnership commitment, we're able to give confidence to our customers across all segments around combining world-leading UCaaS platform with the best-in-class CCaaS and now agentic AI platform as a unified offering. So yes, identified leads, clear go-to-market momentum and collaboration between our 2 go-to-market organizations means that we do expect renewed growth, and I know that the RingCentral team feel the same way.

Your next question comes from the line of Samad Samana with Jefferies.

Maybe one, just Beth as a housekeeping question. If I think about the guidance increase for the year, was any of that on the cloud side an organic increase as well? Or was it largely due to Cognigy? And then I have a follow-up.

Yes. Thank you. We have maintained our expectation of 12% growth in the cloud, excluding Cognigy for the course of 2025. So that is remaining unchanged. And so the increase that you're seeing in the range in the midpoint -- up to the 12.5% midpoint is predominantly coming from the inclusion of Cognigy.

Great. And then maybe just zooming out from that very specific question, Scott, and I don't want to front run the Capital Markets Day on Monday, where I'm sure you'll dig into this in detail. But as you think about the early days of Cognigy being folded in, and what they brought in the NICE team. How are you thinking about the joint go-to-market effort right now? What have the early observations been? Is it better together? And are customers appreciating that better together story? Or is it still today CXone and Cognite maybe going a bit separately, but you'll fill that in over time?

Yes. Thanks, Samad. So a couple of observations. First of all, I was really pleased, and I talked about our cloud backlog growth and the growth of it. NICE Cognigy has already been an injection of positivity to our backlog. It's -- as a stand-alone business that has a really great pipeline that has a really great brand and recognition in the market. It has not been diluted. In fact, it's been enhanced.

So that's exciting because it means the acknowledgment of the market that a leading conversational AI platform in its own right, competing head-to-head with competitors in that space, they stand really, really strong. We obviously have been really active in making sure that the NICE teams are fully up to speed. So it was quite advantageous actually. We didn't expect the closing to happen in September. But because it did, we were able to get ahead of the enablement of our go-to-market, the large coverage we have, including our partners. Don't forget, our partners play a huge part of our go-to-market execution.

And so through September, we really ramped that up, which means we're able to hit the ground running in Q4 and as we lead into '26, with the NICE team being really equipped about leading those conversations on the AI and the automation play that Cognigy brings.

So those 2 are really good -- and the resonance that we're getting from the NICE customer base is also really strong. But the third part that I guess I want to just reiterate what I replied before to Patrick or Elizabeth when we're just talking about is there is a large -- it might have been Saudi actually. There's a large amount of market, both internationally and in the U.S., which are evaluating their transformation journey where they've got an on-prem suite, fragmented solutions and they're trying to figure out what's my transformation road map.

And what it's meant for us is instead of saying you've got to do your CCaaS move to the cloud first and then do your AI, they love the optionality, "hey, I might lead with my AI, get some real productivity and automation savings that will drive through", but then the unified platform gives us that potential to have even higher. We've already increased our win rates, but we're looking at even higher win rates as a result of NICE Cognigy.

So look, Samad, I guess it's -- you're right, we will share more on Monday, but we do expect that the benefits that we had planned for and expected through the acquisition, the early indicators are really positive, and that forms a big part of our growth potential not only in Q4 but 2026 and beyond.

And one additional point that I would add to what Scott just said as well is when we think about the cloud backlog, of course, we're excited about the momentum Cognigy is bringing and what that means for us. But when we looked at the cloud backlog at the end of the third quarter, it's important to highlight that the growth, excluding Cognigy, also was increasing to 13%. So when we look ahead to our expectations stepping into 2026, we see the positive sign there of the ability to inflect and see further growth in the cloud revenue, which is exactly what we'd like to see and we expect to see going forward.

Yes. We got the organic, the inorganic and then the better together, so really positive effect.

Your next question comes from the line of Tyler M. Radke with Citi.

So Scott, I think you talked about 15% cloud backlog growth. I know it's not a stat we get every quarter, but certainly 15% is higher than where you're getting -- where we're seeing cloud revenue. So could you just talk about, is there any Cognigy impact there or anything on duration? Or is that a good read for where perhaps cloud revenue growth could go going forward, perhaps into next year?

Yes. So Tyler, I'll take that question, and it's actually what I was trying to clarify after Scott made his comments in the prior question from Samad. With the cloud backlog that we referenced, so the 15% year-over-year growth, we did have inclusion of Cognigy. If you exclude the backlog of Cognigy, we had cloud growth of 13% year-over-year. So the 13% year-over-year backlog growth compares to our 12% growth expectation this year. So of course, that builds a lot of confidence for us as we look forward into 2026 in our ability to further accelerate our growth.

Which we'll share more details on Monday.

Yes. Okay. So no duration impact, but 13% is what we should be thinking about. Okay. Perfect. And then just on the margin side, I mean, I know there's some moving pieces with the international expansion and bringing on Cognigy. But maybe just help us understand, are there additional sort of investments you're making that should pressure margins on a go-forward basis? Obviously, we can kind of see where margins are with the first full quarter of Cognigy here in Q4. But should we expect kind of additional pressure, additional kind of costs that are going to lead revenue, whether that's international expansion or AI beyond Q4?

Yes. So it's a great question, Tyler. And we'll talk a lot more deeply about this specifically on Monday as well as we start to talk more around what you should expect to see in 2026 and the midterm outlook, '27, '28. But in general, I think what you should expect is that this is an area of investment for us. When we think about this area, we've had great success internationally. And often, that requires some sovereign cloud infrastructure. So you're building that infrastructure, putting it in place internationally ahead of the impact of the positive accretion that you get from natural growth in the cloud.

So we still haven't seen all of the benefit from the great business we've been signing internationally that will continue to drive leverage in that margin. But in the short term, we are going to continue to make those investments. We see tremendous opportunities internationally. We've been very successful there. And so yes, you should expect that you'll see in the near term a slight pressure that you're seeing during the course of Q4, and we'll talk more again about expectations for 2026 and beyond on this coming Monday.

Your next question comes from the line of Jim Fish with Piper Sandler.

Appreciate the color on Cognigy and breaking it out. Beth, 50 basis -- I'm sorry, 1.5% impact for Q4 gets you to about $8 million. But some quick math after that would kind of point to a big ramp to get to that $85 million ARR exiting next year. I guess, how do you get there? And how should we think about the impact to expansion rate from here just because if you kind of look at that 111% last quarter that you had on cloud net retention rate, now we're talking 109%. You have the ability to cross-sell this into the base, but it did imply a fairly decent drop sequentially. So it's really 2 questions, and I'll be quiet. And it's essentially that how do you get to that big ramp? And secondly, what's going on with net retention rate? And how can Cognigy kind of fill that hole?

Yes. Thank you, Jim. I'll try to break it down. Let's start with the $85 million because it's really important that we clarify that, first of all. The $85 million, we expect as our exit ARR for Cognigy at the end of December 2026 as we exit the year. That means that's the run rate coming out of the year. It does not mean that it represents the revenue contribution we expect from Cognigy during the course of 2026. So of course, the revenue is going to be distributed and ramping up through the course of that year. And so that is the exit point. So that's the first thing that I would clarify there.

I think that as you think about Q4 and what we're predicting for the fourth quarter, in particular, first, I would say it's a little bit of early days with this acquisition. So we are factoring that into our expectation in the near term, but we have already seen the positive momentum that's really exciting even out of the gate from the Cognigy business. So we do expect to see that inflection continuing to happen throughout the course of 2026. And so I think that's built into everything that I've described.

Maybe let me just quickly add, Jim. I just want to reiterate our expectation of our -- of the exit 2026 ARR at the $85 million, we feel very comfortable that that's on track. The early indicators, as Beth mentioned, is very positive. That's not only on the revenue that you're seeing that you mentioned in Q4, but the momentum around backlog, bookings, pipeline that then generates into revenue or more importantly, into ARR by the end of next year.

Your next question comes from the line of Arjun Bhatia with William Blair & Company.

I'm Willow Miller on for Arjun Bhatia. Can we get an update on LiveVox? Are you seeing stability in the business after seeing some elevated churn earlier this year?

Yes. Thank you for the question. I think it's -- first of all, you'll see that our cloud revenue growth during the quarter achieved exactly as expected. We achieved the 12%. And of course, LiveVox is a part of that. So really, what it emphasizes is that the core of our cloud business is growing even better than what you see externally. With respect to LiveVox, in particular, it has a positive outlook, and it's actually forecasting ongoing growth in cloud revenue. So all good and healthy signs that we're seeing in that part of the business.

Your next question comes from the line of Michael Funk with Bank of America.

Beth, earlier in the prepared remarks, you mentioned the NRR trends. And I think you commented some expectation or hope of positive inflection in NRR. So can you just talk through the NRR trends intra-quarter? I know your metric is a trailing 12 month. And then related, can you talk about your pipeline, the strength of the pipeline and quality of pipeline and overall feedback you're hearing from customers about their appetite for spending?

Yes. Thank you for the quarter -- I'm sorry, for the comment or the question. So for NRR, in particular, I did highlight in my comments, and it's important to highlight that NRR is not in-quarter specifically. That is looking at the trailing 12 months and of course, reflects some of the change that we saw in our cloud growth that was happening during 2024. When you look at the current impact in quarter of the NRR, we see exactly what we would expect, which is stabilization that's consistent with the 12% growth that you've seen throughout the course of this year. And we talked about the ability to positively see that inflect in a positive manner looking ahead. And of course, we're looking at cloud backlog, but some other trends that we see as well that give that positive confidence in the growth and great cross-sell and upsell efforts we have with our existing installed base.

Yes. Maybe I'll cover the pipeline question. So Michael, the pipeline is strong. And you can probably tell the sentiment that I'm sharing, it's based on not only execution of what we see and what we've experienced in Q3 and our execution against the strategy, but it's also based on what we're seeing in the market. I think the first thing that I will say is there is lots of questions about AI in the market, and I understand why that potentially is the case. That is not true for CX.

In CX, the proven benefits that you -- with a world-class AI platform that drives automation, great experiences, reduced cost, increased loyalty, ability to be able to drive upsell and sales and benefits for your customers, we can prove that with real customer references today. So the demand of that to be able to improve customer experiences as an AI transformation initiative in the -- we -- it's positive momentum. Whereas in other parts of AI, you can question, you don't question it here.

But I would also add our growth drivers, and we'll talk more about this on Monday, but if you think about the growth drivers that we have, we've clearly got still a significant market on the jump balls of on-prem to cloud. We're improving our win rates. We see increased pipeline, very good. Our international expansion on the back of the investments, we see a lot more on the international side. We see that in our pipeline.

And of course, I'm very optimistic on all the things that I talked before about NICE Cognigy inside of our business, whether it be the net new market where NICE doesn't have a role today, where we're going after that, the installed base where we're going after that and then an accelerated opportunity on those jump ball scenarios. A lot of that pipeline, we haven't even put into -- we're in the early days of bringing that into our business. So I guess it's not only on the current pipeline that we see that is strong and the buying sentiment, but the potential that we have now that we've got the complete end-to-end capability. So yes, it is borne from the trends being in our favor, which we were predicting, but it's good to see that it's coming to life.

Your next question comes from the line of atharine Trebnick with Rosenblatt Securities.

I have one for Scott. Most of your Cognigy customers are using speech to text to LLM and back to speech. OpenAI and others have recently released direct real-time voice APIs. And are you seeing competition from these APIs? And why or why not? Sorry, that was more technical, but I had to ask...

No, no, no, very happy to answer the question, Catharine. Look, I think we've got to just pause a little bit and look at this market for the reality it is. Anyone can create a bot, anyone. I can do it myself in 10 minutes. But creating an AI agent, whether it's teach -- text to speech, speech to text and all the other capabilities, but creating an AI agent that delivers superior customer experience, exceptional customer experience, advanced from what a human does today. That takes a whole lot more than creating a bot with some simple capabilities.

And so we actually don't see the LLM providers as competition in this space. In fact, we see them as partners within our ecosystems. Their models are really good. They're general purpose, they've got an expanded capability, but with NICE and in particular, with our Cognigy, we provide the contextual CX-specific AI built, that's built on rich customer interaction data. It's built on the knowledge of what that data is, the sentiments, the context as well as the intents -- and that contextual knowledge, together with the guardrails, together with the regulations, together with the knowledge and the standards inside the enterprise, integrating those also with the legacy systems that you need to connect to, to make sure that you're delivering according to the standards that an enterprise needs. No simple bot does that. You need a complete platform.

And so I guess we see the goodness of the demand because what happens is a customer often says, "Oh, I'll try to build it myself on this, on -- whether it would be OpenAI or Anthropic or other platforms, fantastic. But as soon as they see the reality of you need much more richness to be able to deliver a great consumer experience with that AI agent, it quickly comes straight to us, and we're able to leverage that. So we leverage the large language models. They're super. They're really important, but also the complementary of what we bring with the contextual intelligence means that it actually drives demand for us in a really positive way.

So I love the question because we get it a lot, but it immediately then translates to validation of why the domain-specific capabilities that we have are really critical when you're in delivering to your consumers because no one is going to introduce inferior customer experience to their customers, no one.

Your next question comes from the line of Tavy Rosner with Barclays.

Most of my questions have been asked. I just wanted to touch on Actimize for a second. What's the competitive dynamic? It does feel like more players are trying to disrupt the market. Is there -- do you feel anything on your end?

Look, I guess I would say a couple of things. Obviously, we've put a lot of emphasis around the CX business. And it's obviously an exciting inflection point in the CX market with the AI potential momentum, everything that we've talked about. And we're clearly proactively positioning our leadership in that and winning, which is why we've emphasized that so heavily. But we have got a really strong business in Actimize. It's the market leader. There continues to be high demand.

The regulatory environment around the standards and the expectations around compliance and avoiding financial crime and compliance continues to be a really important aspect for financial institutions. So that business is in a really positive place. It's got a lot of cloud potential and momentum still to come. But the thing I love about the Actimize business, candidly, it is the retention rates and the -- it's -- we don't lose a customer because once it's implemented, it just provides an ongoing value and model that resonates to the largest financial institutions on the planet. So that industry definitely benefits from continued focus on compliance and financial crime, and that is a driver for us. And yes, we're positive about the outlook of that business.

That concludes our question-and-answer session. I will now turn the call back over to Scott Russell for closing remarks.

Thank you. Look, so first of all, I appreciate the time for everyone today. As you can clearly see, we're excited. We're excited about our ability to be able to execute on the strategy that we laid out, the renewed strategy that I've talked about on many times on these calls and seeing the results. And frankly, the expectations is Q3 is a part of a proof point of a long journey in front of us to really lead and win in this market and be excited about it.

We're also excited to be with you next Monday to join us. I think it's really important that you can understand and see really the NICE Cognigy platform, how it then benefits with the CXone platform and how bringing the 2 together, the 1 plus 1 equals way more than 2, it's 5, it's 10 and the potential that brings, but also from Beth and I, the updated strategy, the midterm outlook and how that plays out. So I appreciate the time and look forward to seeing you all on Monday.

Ladies and gentlemen, this concludes today's call. Thank you all for joining. You may now disconnect.

Tyler Radke here, Citi's Co-Head of U.S. Software. Welcome to the day 2 afternoon software track. We have NICE up next. Excited to have Scott Russell, the newly appointed CEO this year. And Beth Gaspich, the CFO of NICE. So Scott, thanks for making the appearance to the conference.

And just given that you recently joined the company, I think it would be great for the audience, a little bit of the background, just for those who maybe didn't know you at SAP? But what are your key priorities? And how do you kind of think about where NICE is in the evolution?

Sure. So good afternoon. Good to see you. So background, I've obviously been in enterprise technology for a long period of time. Before I joined NICE, I was the Chief Revenue Officer for SAP. And if you, I guess, over the 4 years that I was in that capacity and did that with running a number of their global businesses, we -- they doubled their cloud revenue from $8 billion to $17 billion. And then I think this year, they're delivering around $21 billion to $22 billion. So a significant acceleration of an on-premise company into the cloud and driving that, and I ran half the company.

So I guess I have a good understanding of how to drive scale and growth and using technology in the international markets. When I come to NICE, and that's obviously why we're here, there is an incredible market opportunity. Why am I here? It's because this industry has been through multiple pivots. There was the pivot where you were trying to do automation many, many years ago. You saw the advent of IVR. You saw NICE's history around workforce management with call recording, then that moved into the contact center and the CCaaS space and the pivots that they made, and it was quite groundbreaking, but the biggest and the most impactful move is yet to come.

So the role that AI plays, and it's not about AI itself, it's about what it allows companies to do in its orchestration and interaction with its -- with their customers is to be able to significantly automate, to be able to significantly improve the engagement that they have with their customers at scale more than they've ever been able to do before. And to do it in ways that doesn't rely on the intellect and the capability of humans that are sitting in the contact center.

So what am I excited about? What are my priorities? Number one is to be able to spearhead and lead the industry in that transition. If you are in the CCaaS space and you do not have a clear underlying technology capabilities that manages the transition to AI, you are going to lose, because the market will move, is moving, currently happening. Our growth in AI that we've already done that we've shared in the 42% growth, which is now 11% of our total cloud revenue, is a testament that we're already well under the way, but significantly accelerating that pivot and change, and I can explain how.

The second is to expand through partnerships. You will have seen that we've significantly enhanced our relationship and our partnerships with Salesforce, with ServiceNow, with Amazon, with Snowflake. We also are with our systems integrators, with other resellers. Why? Because as a company, we have great products. But we weren't necessarily leveraging and expanding through the ecosystem to bring us to market through their channels as much as we were through our own means. It also means that our interoperability of a Salesforce's AI and ours needs to be seamless. We don't operate in isolation. Service Cloud Voice and other capabilities will interoperate with ours, and we clearly are going to aggressively pursue that rather than react to it.

The third is international expansion. We're very bold. We've made some significant investments around our sovereign cloud capabilities, which has borne fruit already in major wins like DWP, most recently in the U.K. or in Services Australia, but there are other cases where we see significant growth because the on-prem to cloud move in the international markets is nowhere near as progressed as what it is in the U.S. But even in the U.S., there's still a significant opportunity. So being able to capitalize on that.

And then last but not least is, and I'll probably highlight it is given the pending onboarding of Cognigy post -- concluding on the closing process, our ability to be able to, at scale, deliver automated AI auto, so agentless platform and their agentic platform is game changing. Our data on their platform becomes an exciting opportunity that no one else in the CCaaS market can offer.

So you put all those things together, it means we've got multiple growth drivers beyond the on-prem to cloud move, which has obviously been an important part and will continue to be. But let's keep it as busy.

Yes. Well, sounds like a lot of exciting things to tackle, as your first year. Maybe to follow up on a few of those. So you talked about how AI is going to be kind of the biggest evolution this industry has seen. So I guess just, clearly, there's a lot of concerns on a lot of software companies out there including yours and you saw Salesforce report last night as well. But like how do you think about your business? I mean, obviously, the AI growth is impressive, 42% accelerating. But then -- how does that play into the rest of the business? Like is there a part of the business that's kind of more traditional at risk? Like how do you -- or is this all just -- do you think the growth accelerating for you?

Incremental. So I'll get -- Beth, you might be able to comment a little bit on the financial side. But strategically, there's a few data points that are really important. The volume of interactions between consumers and their brands continues to increase and it is unabated. It is increasing invoice. It is increasing in memo. It is increasing in chat. It is increasing in all digital channels. So all of the routes in the -- that their consumers are interacting with their brands is not declining, it's increasing. And so the demands on the existing contact center are actually increasing despite the role that AI is starting to play.

The second is, you cannot solve complex user customer cases with generic AI. If you could do it, we -- the simple cases are easy. OpenAI can do it. Microsoft can do it. We can, anybody. The simple stuff is not where the money is. It's the things that are more complex that require deep understanding of the interactions, the use case, the knowledge, the workflows, the tasks in an enterprise that are not just in the front, the mid, in the back office. For the first time ever, we've got the ability to use AI to automate that, that we've never been able to before. So we've been stuck at handling the call or the chat, but then handing off to another platform. We don't need to hand off anymore.

And then the third thing that I would say is consumers' interactions with their brands are not limited to the problem where it's a problem that I need solved. Will you use -- you'll have a conversation with your brand of choice. Sometimes it's because you've got a problem, sometimes it's because of [indiscernible]. But you're not going to log into a website to go and enter a whole lot of data to go and -- you're just going to converse. So the platforms and conversing that conversational platform that handles voice at scale, which we already have in all the routing, but also the AI becomes an integral part of the way you're able to provide that to the customers.

So right now, that is not leading to any decline on seats. The number of seats actually still increases. But what I would call it is it's a flattening because what any productivity gains we're getting, so not a large number of our customers use Copilot. Then that is able to give real-time insights for them to have a more productive call, reducing call handling time. So the average handling time is down, the call resolution is faster. But you're not reducing the number of agents, you're handling that increased volume that's coming in, and you're able to do so in a more productive way.

I think what we will see is as we're able to do more and more automation of more complex scenarios, which we are uniquely placed to do, if we capitalize on it and that takes investment, we're able to manage that transition where the monetization exponentially grows through the AI side, and we manage, obviously, the seat base. So if you were looking at our business, I would be looking less about the number of seats and more about the number of interactions, the number of sessions because increasingly, that's going to be -- and we're already seeing that in our AI business. And maybe Beth...

Maybe I'll just share a couple of data points. I think AI, we see as a key growth driver of our business. If we look at our new bookings across all segments of the market, but across markedly, if you look at the 1 million ARR plus customers, we see AI in almost every single deal. It's a key growth driver. You've seen the acceleration in our AI and self-service revenue. We went from 39% in the first quarter, up to 42% in the most recent quarter. And when you look on where that's coming from and in terms of the pricing model to the customer, more than half of that now is originating from the AI and self-service pricing model, which is non-agent based. So we're already seeing that taking hold and really driving the growth.

Got it. So -- you talked about kind of the opportunity to address some of the more of these complex service use cases. Obviously, that requires more deeper workflows. It's -- to bring that into AI, it's a lot of different systems you're touching. So help us understand how this kind of looks because we hear from ServiceNow was here yesterday talking about kind of their agentic push. Salesforce has agents force. I know you had ServiceNow at your conference. You have partnerships with both.

What are you doing? What are they doing? Why should investors not be concerned about their own -- those companies push into agents?

Yes. I think there's a few things. So first of all, there is an enormous amount of tasks to be done in an enterprise that can be automated and agentically delivered that has nothing to do with customer service. And so both of those organizations and many others, if you think about whether it be purchasing, supply chain, procurement, employee, HR, let alone, sales, marketing, et cetera, there is a lot of space here.

When it comes to customer service, because it's not just about a task to be done, you've got a consumer at the other end of the line, one way or another, which means your engagement with them and how you handle that engagement is incredibly important. It's not enough to have an agentic capability if you're not handling the customer in a way that is congruent to their expectations according to your policies, according to the flows. So you've got to be able to do that, and it's got to be able to interoperate.

So what we expect is fulfilling the needs of a consumer who are waiting, who wants fast resolution in a human-like way will require not only a great single pane of glass engagement platform, us, but then the execution of tasks, jobs to be done, a credit card limit increase, a claims approval, whatever those -- and that will either be done by a human agent that will trigger maybe something that ServiceNow have built or it will be our AI agent to their AI agent and we fulfill the task, which is why I've done the partnerships.

So what am I actually doing with Bill and with Mark's teams? We are prebuilding the AI flows between our platform and theirs. So as they build it out, we natively can exploit their -- what they're building. And then everybody then says, well, that then they could then take over ours. They will not take over the CCaaS platform because they don't want to. Why would you build a partnership if you could replace it? They're not going to do the voice. They can't do the routing and the scale of it, and no one at the enterprise is going to be able to hand it all to AI. It will not happen, not in the next foreseeable future.

Too much complexity, too many rules, the quality of the data, the consistency of it, you can't be wrong to your customers. So our system of engagement platform becomes a really critical asset, which they see, which is why they want to partner with us because they want to leverage that but still initiate and leverage theirs as it goes into the mid and back office.

I want to be clear. There is an overlap at the front. You can do some of their capabilities in the front office. The last thing that I will say is many companies have been forced to use a disparate set of technologies, a conversational bot here, a Service Cloud Voice here, a CCaaS platform here, and they're trying to stitch it together. What happens? An inconsistent poor consumer experience with their brand, you're not reducing cost because you're still keeping the same number of agents, you're not getting the consistent flow of data, and the task to be done isn't any more efficient. So we believe as an engagement platform, single pane of glass, we have a unique opportunity to be able to have an end-to-end platform that can fulfill that.

How deep I go into the mid and back office is a question mark. But what I will tell you is, if I can perform the task from the point of interaction that solves the consumer requirement at the get-go, why do I need to go to another system? I'll do it myself. But if I need to, then we will.

Got it. Okay. And you talked a little bit about the different pricing model, obviously, in the AI business today, I think about half of it is not agent-based or seat-based. Where do you think the customers are at in terms of kind of philosophically buying into more of an outcome-based or value-based selling, this idea that you can capture a greater share of the labor pool, right, if you do see those seats come down. Is that something that you think is widely adopted or still kind of early innings of...

Early innings. Early innings. So -- and Beth, you can comment on it as well. I think they're very interested. Yesterday, I had my customer advise -- Executive Customer Advisory Board. So we had a group of 15 of our largest companies, customers around the world that came together. And we were going through our road map, and we talked about pricing and value-based and things like that. They're very interested. Their primary concern right now is not having a deterioration of the customer service that they have invested heavily with us over years to deliver a great outcome from their customers.

So the infusion of AI within that framework is really important to them. It cannot result in an inferior outcome for their customers because that's ultimately where they're measured, average handling time, resolution time, call handling time, et cetera. But they're excited about the automation opportunities where you're able to then ultimately reduce the number of seats and then transition.

So I think the value-based pricing is a potential future one. Right now, what they're wanting is an interoperable platform that as a consumer contacts them, they can fulfill and resolve through AI quickly. If it gets more complex, it's seamlessly hands to a human agent, then back to AI. It can be done synchronously or asynchronously and can be done on a single platform. That's what they're driving towards. In the future, I suspect they're going to come to us and say, well, now give us the savings and can you guarantee that through that, but that's not the economic model today. The economic model is very much on a session basis for the AI versus seat basis for their agents.

Yes. I would just add to that, Scott, that I think at NICE, we're uniquely positioned to be able to even consider that potential of a future pricing model given the data that we have. So we have a significant amount of interactions happening through our software that gives us the unique opportunity to really understand the use case and on a vertical-by-vertical basis for our customers as well. So being able to fulfill the promise of driving better customer satisfaction and lowering their costs and delivering that ROI, we are really well positioned to kind of lean towards into that in the future.

Great. Great. And I did want to hit on the Cognigy acquisition, which was recently announced. How -- just walk us through again the rationale. How does this fit in to the model?

So right now, if you're -- I think everybody understands and sees the value of being able to do contact -- agentless interactions between a consumer and their brand. And it's actually in the third generation now. There's been 2 generations of companies that have been built over time and the latest Gen AI generation. Cognigy bring -- we've been working with Cognigy and all the other conversational AI players for a number of years. Why? Because they need our data, they need our flows to be able to then fulfill the things that you then go and build on their platform. So whether it be Cognigy or [ Kore or Poly or Palo ] or there's many, many players that are out there.

So there was 3 things that really Cognigy brought to the table that were really, really critical. The first is, as a core platform that didn't require technical skills, it is outstanding. Their customers are building the flows themselves. The vendor is not doing it. Cognigy is not doing, the SI is not doing it. They're able to self-build using prompt. The airline, Lufthansa, you might start with a flow around a flight upgrade or a changer or you want to -- you've done a change, you want to credit back, and you're canceling a flight. There's so many different scenarios. They're able to self-build them natively, easily, and they're able to do so from day 1. Most conversational players, AI players require a level of services work around the configuration of those and it require technical skills. So they've built an outstanding platform.

The second thing is they've already proven to have enterprise scale. All of these other players get to a threshold. And remember, we deal with millions of concurrent conversations at the same time on our platform. If you want to move that into AI, it's got to work, it's got to scale, and that was a key criteria for us because we're not dealing with small and midsized companies only. So that discounted a lot of those players who aren't able to do that in this space, and they were able to prove that.

And then last but not least is their agentic capabilities were way further progressed than we had even originally anticipated, which I guess is more in line with third-generation AI players, the Gen AI players. They've got a significant capability, which meant instead of us organically trying to build that out, which we were doing with our Mpower platform, we're able to leverage that from the get-go.

I would just round it out by saying this, we do 20 billion interactions a year, and we're growing quickly. Those interactions are underpinned by 1,000 CX-specific foundational models, what a bank does, what an insurer does, what a telco does, what an airline does and not just then, what the different types of institutions. Right now, all the conversational AI players, all the big AI players have to figure out what those flows are. They don't have that 20 billion interaction data. We are going to preload that into the platform as quickly as we can, so you get an out-of-the-box capability. So we don't want to just compete, is our AI better than somebody else's. It's going to be better, and it's going to have the embedded data and logic and orchestration that we already have with our CCaaS strength. That is something that no other CCaaS player, nor any CRM, nor any hyperscaler, nor any other AI player has. So we clearly need to use that as a means as to why they would run on our platform versus potentially using something else.

Right, right. Okay. And it sounds like a pretty exciting opportunity ahead and accelerate...

Our installed base, they're an international. It's icing on the cake for us that where they're an international wasn't the reason for a European business. It was just great technology that fit us strategically. None of it is about 2025. It is all about -- our strategic partnerships are not about 2025. Our acquisition of Cognigy is not about '25. Our expansion internationally is not -- it's about building long-term sustainable cloud growth that ultimately delivers shareholder value. And so if you think about Cognigy as well just tactically, we're going to continue to drive that business where it will grow on customers that are not NICE. They do a lot of business with our competitors. We will continue to expand that, and it is a great growth driver, and that stacks up on its own right.

Then you take that capability and you put it into our massive installed base with a native capability, then we've got the cross-sell opportunity. And then last but not least is when we're trying to win the on-prem to cloud shift and they're evaluating AI as well and we embedded the data, as I said before, it gives us a differentiated offer that we otherwise wouldn't do. We were navigating right as we are with OEM and third-party partnerships, which is what the others do as well. The challenge with that is as the market moves to have its interactions that are not only agent-based, but are AI-based, if it's not a native part of your stack, I think in the long term, you're not going to be a winner in this market, and we needed to be in front of it, not behind it. So the move was -- it's a significant one in the long-term growth of the company.

Yes. So I mean, it seems like you mentioned earlier kind of still sort of undecided desire on how deep you want to go in kind of the back and mid-office. And like what are -- I guess, what are you sort of weighing on that expansion?

I think there's some nuances around the mid and back office. So there's a lot of companies that are really enamored about agentic AI and the role it plays to replace what humans do in the mid and the back office and in the front for that matter. We look at it a little bit more of a nuanced way. So we look at it, well, who are performing tasks that fulfills a consumer need. I'll give you a very simple example. If you're a financial provider for taxation, you have a season or a window where one of the core things is to schedule appointments with your tax adviser. And it's not just a case of who's available, the needs of us, me as a consumer, where my revenue is, all of these things determines the type of tax adviser and who to get.

When that call comes in or that chat comes into the agent or to the AI agent, routing and understanding and interacting with the mid-office, i.e., the tax advisers themselves is a timely heavy activity that happens. We can automate that, and it's not just leveraging our AI capabilities, it actually leverages our workforce management, which we are the best.

So managing that workforce in the needs of a consumer in the mid and back office is a huge opportunity for us to automate. Now that is a great opportunity. If you want me to be the company that is going to build to update a CRM record for a sales opportunity for a purchase that just happened, frankly, there's going to be a ton of others that are going to be going and trying to build those. But can I initiate it from my Copilot or from my autopilot and initiate that agent? Of course. So I think that's where we're going to be leveraging what others build, but we're going to be unique in what we create ourselves, and it's very geared towards customer experience. It is not going to be to do any task in the mid and the back because it obviously needs to fulfill the consumer at the other end of the line.

I got you. Okay. I did want to hit on international. Obviously, you have a big international background, not just your accent, but...

Yes, I had not lost my Australian accent despite 25 years.

But I mean, to me, the international opportunity for NICE has always been arguably kind of an untapped area just given how low it is relative to others in the space. So what are some of the things you're doing to accelerate that? How big do you think that, that could be over time as a percentage of the business?

So there's a few factors. First of all, I need to give credit to the team that we've been investing in our international capabilities, so sovereign cloud capability, which we're still investing in U.K., Australia, the wins at DWP at Services Australia, they don't just happen. You need inherent investments that we had done previously. Same in Africa, same in UAE, same in Korea, same in Europe. So we've got -- we've already done significant -- that gives us growth to capitalize on that, but we've got more to come.

So we're now positioned to be able to grow, whereas before it was more about the building blocks to be able to then seize upon it. You can clearly expect, given the CCaaS move, the on-prem move in the international markets is, in some places, significantly further behind, in some places, moderately, i.e., they haven't moved as much to the cloud as what has happened in the U.S.

So that, combined with our international capability that Cognigy brings as well because they're very strong in Europe, we feel we're well positioned based on the investments that we've made, the knowledge that we've got and also the sales and marketing and partnerships that we've built across the region. So I definitely agree.

I would just caution one thing. I'm not going to go to 50 countries. We're going to be really sharp on the country. So the major markets in Western Europe, in Asia, such as India and Japan, there are certain markets that have got real sizable growth and opportunity that we can capitalize on, and it is clearly a growth engine that we maybe didn't have in years gone by.

Yes. And just kind of back to the, I guess, the non-AI drivers of the business kind of being the CCaaS systems moving to the cloud. I think the latest stat is -- I mean, it's still well under half of the market...

Yes. I mean we approximate about 60% to go.

60% to go, right? So how do you think about just the pace in which that moves over? Like on one hand, we've heard from a lot of companies around the data readiness, like having your data in the cloud helps accelerate AI and take advantage of AI. But on the other hand, some enterprises have started to put the brakes a little bit on AI just as they evaluate business process at all. So do you think the AI conversation is like helping or hurting that cloud migration?

I would say it's a really dynamic space. It depends on the industry. So in public sector, which some of these big wins, they are clearly evaluating our AI capability, but not buying it upfront. They just want to get the CCaaS right. They want to get the data right. They want to be able to make sure that they are able to move, but that roadmap matters. On the flip side, some of our -- the industries, some other industries are much more interested in starting with the AI, proving out the automation and potentially not even buying that they're buying, they're moving to CCaaS, but in a refined way rather than trying to -- because they don't want to have to move what they ultimately don't need in the future.

So you see a bit of both. It does depend on the industry. What I would say is all companies have an AI road map -- plan. They want to know the plan. And if we haven't got an answer to it, they will find a solution from someone else. So the fact that we now have a core platform that has that is a really important message. Our direct competitors do not. They are relying on somebody else to perform that AI road map. So that, for me, is a really important distinction.

So whether they buy -- do it upfront, whether they do it later, as long as they're making their transition to a CX, AI, CX platform that enables, we'll actually handle all routes. And again, 12 months ago, 18 months ago, our primary route to market was win the CCaaS move compared to our competition. I can easily go to them and say, just start with Cognigy, just get going, up and running, leave your on-prem here for a little bit longer. If you're not quite sure, let us build it out and we'll move you progressively onto our unified platform rather than forcing that jump ball decision straight away because clearly, they can't invest in all of these things. There's not even a financial concern, it's also their ability to manage the change.

Remember, number one, they are not prepared to dilute the quality of service they're delivering to their customers. So as exciting as the AI transition is, it's always got to be within that context, which is why, by the way, generic AI, that OpenAI and others can offer will never hit the scale to what they need because it will never have the context richness that is needed in the CX models that we can obviously provide.

Right, right. I did want to ask you just about competition broadly. One of your more modern competitors recently announced a pretty big funding round for both ServiceNow and Salesforce. So curious your thoughts on that. I think you're smiling over there...

I'm smiling because I see -- look, I guess what I would say is, I can certainly understand why ServiceNow and Salesforce are wanting to partner with us and are wanting to look at their already existing investors and they might want to look at because the reality is, they see this industry, this market is very attractive, and it is. There is a huge opportunity around AI and the capabilities and to be able to automate and they want to be relevant. So I can certainly understand from their perspective, but it's not an exclusivity because at the same time, they were doing that, we were signing up agreements. We're doing a lot of R&D together to build out. We are obviously the market leader in terms of size and revenue of -- in the CCaaS space.

The one that I guess I'm more -- that surprised me is my competitor in the CCaaS side because what they're really doing is they're foregoing their future opportunity in the AI. They're basically saying that is going to my partner. Now I don't see how you can be a CCaaS leader in the next 2 to 5 years if you're not having an inherent native capability in your platform that delivers self-service, augmented service, proactive -- you've got to have that AI capability. Otherwise, what you're really doing is you're commoditizing into a voice capability and letting all of the innovation happen around you.

So from a strategic standpoint, it makes no sense to me. From a financial standpoint, I understand why it happened. So my view is it's actually positive for us. But it is a dynamic market where we need to prove the unified platform is ultimately going to be a better choice, which drives long-term shareholder value because we're going to drive long-term accelerated cloud growth.

Got it. Well, maybe in the last under a minute here, just anything you wanted to close with for the audience or maybe misconceptions that -- about the business or stock that you want to....

I think there's a couple of things. I certainly understand the history and what I inherited and what I walked into in terms of concerns around the cloud growth. All I can tell you is this, every move we're making right now is strategically to drive long-term cloud growth, accelerating cloud growth. We've got work to do. The market opportunity is immense. AI is disrupting, but it is a positive disruption for us if we've got the assets to seize upon it. Cognigy is one of many, but we are enabling that and our financial strength gives us that ability to do so together with the partnerships, together with the international expansion.

So our levers of growth are way broader than what they were before. Our strategic technology capabilities are way more enhanced than what they were before, which means as the market pivots to AI, we can seize upon it, which maybe we weren't as well placed before. And please look at that in the longer term because this is -- all these moves are around sustainable, long-term accelerating cloud growth, and I look forward to sharing more in Capital Markets Day about what you can expect from NICE in the midterm.

Great. Scott, Beth, thank you very much for the time. Appreciate it.

Thanks, everybody.