ServiceNow, Inc. Aktie

Hello, everyone. Thank you for joining us, and welcome to the Third Quarter 2026 ServiceNow Earnings Conference Call. [Operator Instructions]

I will now hand the conference over to Darren Yip, Senior Vice President, Investor Relations and Market Insights. Darren, please go ahead.

Good afternoon, and thank you for joining ServiceNow's Third Quarter 2026 Earnings Conference Call. Joining me are Bill McDermott, our Chairman and Chief Executive Officer; Gina Mastantuono, our President and Chief Financial Officer; and Amit Zavery, President, Chief Product Officer and Chief Operating Officer.

During today's call, we will review our third quarter 2026 results and discuss our guidance for the fourth quarter and full year 2026. Before we get started, we want to emphasize that the information discussed on this call, including our guidance, is based on information as of today and contains forward-looking statements that involve risks, uncertainties and assumptions. We undertake no duty or obligation to update such statements as a result of new information or future events. Please refer to today's earnings press release and our SEC filings, including our most recent 10-Q and 10-K, for factors that may cause actual results to differ materially from our forward-looking statements. We'd also like to point out that we present non-GAAP measures in addition to and not as a substitute for financial measures calculated in accordance with GAAP. Unless otherwise noted, all financial measures and related growth rates we discuss today are non-GAAP except for revenues, remaining performance obligations, or RPO, current RPO and cash and investments. To see the reconciliation between these non-GAAP and GAAP measures, please refer to today's earnings press release and investor presentation, which are both posted on our website at investor.servicenow.com. A replay of today's call will also be posted on our website.

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

Thank you, Darren, and thank you, everyone, for joining today's call. For more than 7 years now, I've said ServiceNow is a one-of-one company, one of one. As you'll hear, these Q3 results represent a trifecta moment for ServiceNow, quarterly results beating expectations across the board again, significantly accelerating AI performance at the largest quantum yet, a hybrid business model shifting more to consumption.

So let's do the standard results first. Subscription revenue growth was 20.5% in constant currency, 50 basis points above the high end of our guidance. cRPO was 21% in constant currency, 100 basis points above our guidance. Operating margin was 32.5%, 150 basis points above our guidance. Free cash flow margin was 20%. We had 19 deals greater than $5 million net new ACV in Q3, up 135% year-over-year. We have a $30 billion remaining performance obligation growing at 23% year-over-year. That's growth at scale.

To my trifecta point, here is where the Q3 print gets even more dynamic. For many quarters now, we've been aggressively building the consumption engine into the business model. Our ambition is to be the governed execution layer for enterprise AI with multiple commercialization paths, all driven by customer choice. Q3 is the banner achievement to date. The strategy is working. We have tangible AI monetization. AI, net new ACV was 65% year-over-year growth in Q3. Control Tower, net new ACV grew over 6x year-over-year. Our agentic front door EmployeeWorks reached $100 million ACV in less than three quarters. The number of $1 million-plus AI deals grew 4.5x year-over-year. Year-to-date, agentic AI consumption in production is up 13x year-over-year. If you look at the consumption of Action Fabric assists alone, that number is up 500% month-over-month. This is not only the direction of our customers, this is where they want us to go. It's the right direction for long-term shareholder value creation as well. As a reminder, we began the year with a $1 billion AI target by year-end. We raised that target to $1.5 billion at Financial Analyst Day in May. Today, we are raising that target again this time to $1.7 billion plus by year-end. And as you've come to know me pretty well by now, I've challenged the team to even surpass that number.

Overall, the company is now full speed in our Q4, and Gina will give you the guide shortly. But I don't want you to wait too long. She will raise. As everyone on this call knows, ServiceNow always closes strong. We have no intention of delivering anything less than the best year in our history.

Let's spend a few minutes on what remains a very complex environment for the enterprise. We hosted our biannual CEO event with more than 125 CEOs a few weeks ago. Here's what I heard. All of them are investing in the intelligence revolution. They've spent billions on it so far. They all went through the token maxing phase. Here's the big lesson they all learned. All of the vibe slop flops, sprawl and lack of integration are even greater risks in the AI world. When I spoke to them about ServiceNow's role as the Super Intelligence Control Tower for business reinvention, their endorsement was universal. Our SICT, Super Intelligence Control Tower, brings together the right model for the right workload to solve the right problem and unlock the right opportunity for our customers. businesses in every industry need a harness for enterprise AI. This is more than orchestration, governance or security alone. It's the nexus of all three categories coming together.

We're now in the rules and rails phase of enterprise intelligence. 94% of enterprises report gaps in AI visibility. 88% can't even distinguish personal AI accounts from corporate instances. ServiceNow's Control Tower discovers and inventories the entire AI estate. As stories of rogue agents persist, ServiceNow controls what agents can do. That's why we introduced AI Passport to issue every agent an official attested record based on context in our platform. Who owns the agent? What's it allowed to do? What data can it access? How much risk exposure is it allowed to take? This enables the most capable kill switch available in the enterprise today. When our Control Tower revokes a passport, NVIDIA Century stops honoring it and the agent stops at the infrastructure layer. We are scaling that capacity everywhere. Our Control Tower signals Okta, Microsoft Azure AI Foundry and Google Gemini enterprise agent platform, so they can cut off the agent's access wherever it runs. ServiceNow already sits at the operational core of the world's largest enterprises, the CMDB, the Workflow Data Fabric, 20-plus years of embedded operational intelligence and context across IT, security and risk.

With Armis and Veza, we can now pinpoint specific known vulnerabilities against the cybersecurity landscape that has irreversibly changed. We call this Shift Zero. It moves security from remediation to prevention from human speed to machine speed and from blind to govern. The average enterprise runs more than 70 security tools. ServiceNow offers a single govern system with proof of what acted, why and who is accountable. This is not an incremental improvement to a reactive model. It is the replacement to consolidate a fragmented market. It is the gateway to autonomous defense. That's why we're the fastest-growing cybersecurity company at scale and why the growth is accelerating so rapidly.

When you're operating in the super intelligence era, the pace of innovation has to keep pace with the growing size of the opportunity. I'm really proud of what the ServiceNow team has delivered. Our Level 1 service desk specialist resolves incidents 85% faster than human agents. This is now in full autonomous production across customers of varying size and sector from a global automotive leader to a leading enterprise technology company. Our AIOps specialist has already reduced median time to resolution by 40% within the first month. We now have over 100 customers actively innovating with our AI specialists, AIOps, HRSD and CRM specialists are expected to become generally available in Q4.

As enterprises rethink the mandate of their CRM systems, ServiceNow is leading the way. The old CRM was built for sales teams. The new one has to work across your entire business. That's a different product. That's a different architecture. And that's why we're seeing customers rip and replace not just add alongside. Conversational voice AI is the next big leap in connecting the front office to the entire enterprise. The customer conversation is where the work starts. The platform has to carry it through every system and workflow behind it. We're redefining how enterprises engage with customers. Our tuck-in of Sweep adds deep expertise in rapid agentic deployments, giving us another gear to accelerate while improving customer outcomes. And one year after we brought Logik AI into ServiceNow, we've been named the leader and customer favorite in The Forrester Wave for Configure, Price, and Quote solutions. We see a similar change in gravity for the employee experience.

For the Fortune 500,000, we introduced Flow. There are many enterprises that want leading domain expertise but aren't ready for formalized ITSM. Flow fills the gap, a new conversational service desk that is self-serve and consumption build. A customer that signs up for Flow today can begin using Flow today. That's a big reason it's off to a lightning fast start with businesses and government agencies around the world. ServiceNow EmployeeWorks continues to be a fast growth machine. This gives enterprises one place to search, knowledge, get things done and route work across IT, HR, finance and procurement. It also becomes the destination for employees to build AI assistants, agents and automations, all secured by enterprise guardrails. This is only scratching the surface of the groundbreaking innovation on the ServiceNow platform. Even the best platform won't deliver for enterprises alone. ServiceNow Control Tower Alliance is a new ecosystem of leading companies in AI, cloud infrastructure, security, governance and token management who will help customers adopt trusted enterprise AI safely at scale. Founding partners include Anthropic, AWS, Cisco, HiddenLayer, Kong, Okta, OpenAI, WitnessAI and Zenity.

Today, ServiceNow announced an expanded partnership with OpenAI to help enterprises move seamlessly from AI reasoning to governed action. The partnership expansion starts with a new ServiceNow plug-in for ChatGPT, enabled by Action Fabric. We aim to develop security and risk solutions powered by OpenAI cyber models, a Codex integration and AI workflow factory and voice-driven governance for ServiceNow's Super Intelligence Control Tower. We have very big plans for this partnership, especially in cybersecurity. We expanded the partnership between Google Gemini Enterprise and ServiceNow Action Fabric. Gemini Enterprise provides the conversational front end, while ServiceNow provides the governed industry workflow execution. Our partnership with INRY, a Cprime company, shows what happens when a partner builds on ServiceNow before they sell it. INRY went live on EmployeeWorks in six weeks. That's the new bar for time to value rather than the exception. They didn't sell the solution until they lived on it themselves. Median submission time is now down 60% completion rates, 97% ServiceNow and Aramco Digital established an agreement to standardize and govern digital workflows across Aramco's affiliates, subsidiaries and joint ventures in more than 50 countries, and the list goes on and on.

I could end on the countless industry accolades we've earned three new Gartner Magic Quadrants, two new Forrester Waves, IDC reports and many more. Instead, I'll close with the ultimate measure of a defining enterprise technology company, our customers. A major Asian telecommunications leader with over 130,000 employees and contractors became the first enterprise in the region to deploy ServiceNow Autonomous Workforce for a zero-touch help desk in IT and HR. This will handle 70,000 IT requests and 6,000 HR inquiries annually. The Salvation Army, Australia is using ServiceNow AI specialists to give frontline employees more than 5,000 hours back so far, time that is redirected towards supporting community members that are in need. Germany's professional soccer league expanded with ServiceNow as its official CRM partner. It's about one month, only one month. They've already consolidated fan services from seven digital channels into a single ServiceNow platform, resolving 89% of inquiries at first contact, cutting previous case volumes in half.

When a global logistics leader shipment, operations were drawing terrible manual work processes across siloed systems that was soul crushing. ServiceNow built them an AI partner, the shipment issue analyzer. The result is nearly 100,000 hours saved annually, resolution from three days to less than 30 minutes. Jack Henry & Associates, one of the leading financial technology companies in the U.S. chose ServiceNow CRM to modernize its CRM capabilities with AI that automates routine tasks and strengthens post-sale operations. At a consumer finance company, spotting risk meant sending it nowhere, multiple channels, unclear ownership, legacy systems swallowing signals.

Our applied AI FDE team fully deployed engineers, built them the AI Risk front door, a two-layer agent architecture targeting 85% accuracy. It compressed signal to routed case time by more than 85%. Nestle has started to leverage our Control Tower to scale AI with strong governance across its operations. They are progressively deploying agentic marketing operations across 60 countries with the potential to reduce marketing campaign coordination by 25%. And together, we continue to drive innovation across all key business functions. InterContinental Hotels Group, one of the world's largest hospitality and travel services companies is using Veza from ServiceNow to govern who and what can access its systems so it can safely scale across its 7,000 hotels worldwide. These amazing enterprises are putting AI to work for people. They're doing it with ServiceNow on our AI platform with the security of our Super Intelligence Control Tower. We see clear momentum in AI monetization driven by our organic innovation, our pricing and our intelligent packaging.

Our security business is differentiated with the potential to be even bigger in a few years than all of ServiceNow is today. We're strong across industries, including the public sector, which once again delivered in its biggest quarter of the year.

We're not compute constrained. We don't have capital constraints. We're activating a hybrid business model. As you'll hear in the raised full year guidance, we're a company going from the rule of 56 to the rule of 57 on our way to the rule of 60. That, of course, is free cash flow plus revenue growth. We have six businesses that have now surpassed more than $1 billion run rate with a TAM that continues to multiply and expand. What other businesses are there that can even contemplate these fundamentals? And it's only getting better as the cost of intelligence falls, the tailwind for software is strengthening. We are a one-of-one growth company. We have deep incumbency in the enterprise with proven global distribution. We're honoring the principle and the promise that the world works with ServiceNow.

I really appreciate your belief and support. I look forward to your questions. And now I'll turn things over to our President and Chief Financial Officer, Gina Mastantuono. Gina, over to you.

Thank you, Bill. We delivered another strong quarter, exceeding the high end of our guidance across every top line and profitability metric. Q3's results reinforce that ServiceNow is becoming even more strategic as enterprises move from experimenting with AI to deploying it at scale. Customers want the productivity and growth that come with super intelligence, but they also need the visibility and security to do so with confidence. With the ServiceNow AI platform at the operational core of the world's largest enterprises, we are perfectly positioned to help customers put AI to work across their business, govern every agent in action and translate intelligence into secure, measurable outcomes.

Q3 subscription revenues were $3.988 billion, growing 20.5% year-over-year in constant currency and 50 basis points above the high end of our guidance. RPO ended the quarter at $29.7 billion, representing 22.5% year-over-year constant currency growth as average customer contract duration continues to expand. Current RPO was $13.65 billion, representing 21% year-over-year constant currency growth, a 100 basis point beat versus our guidance. Across our workflows, we saw widespread demand. Technology workflows had 54 deals over $1 million, including 6 over $5 million. Demand for our core workflows remains robust as every new AI asset and agent introduces greater requirements to manage, monitor, secure and govern the enterprise. ITSM was in 11 of our top 20 deals, ITOM was in 9 of our top 20 deals with 14 deals over $1 million. Asset Management crossed $1 billion in ACV this quarter and was in 13 of our top 20 deals with 11 deals over $1 million, and our Security and Risk solutions were in 16 of our top 20 deals with 13 deals over $1 million. CRM and industry workflows maintained its rapid growth trajectory and we were in 13 of our top 20 deals with $1 million-plus deals surging to 28 in the quarter. Core business workflows had 15 deals in the top 20 with 24 deals over $1 million, and Creator workflows had 19 deals in the top 20 with 13 over $1 million. From an industry perspective, business and consumer services led the way with net new ACV growing over 3x year-over-year. Technology had robust growth as well at nearly 40%. Our U.S. Federal business also delivered an excellent quarter with deals over $1 million growing over 30% year-over-year. We expect federal net new ACV growth to accelerate further in Q4 as agencies increasingly see ServiceNow as the AI operating system for the enterprise.

In Q3, our renewal rate remained best-in-class at 98%, reflecting the enduring value we deliver to our customers. We ended the quarter with 680 customers generating more than $5 million in ACV, with 31 additional customers surpassing $20 million in ACV over the past year. As our largest customers continue to scale with ServiceNow, they're expanding their platform adoption with 19 of our top 20 deals, including six or more products. The momentum in our AI solutions continues to build. We continue to exceed our AI expectations for the year with AI net new ACV growing 65% year-over-year in Q3, allowing us to raise our AI ACV target for the second time this year from $1 billion at the start of the year to now $1.7 billion by the end of 2026. In Q3, the number of AI deals over $1 million grew 4.5x year-over-year. We're also seeing customers embrace AI more broadly across their enterprises with deals spanning five or more AI products increasing over 8.5x year-over-year.

AI adoption is pervasive across the platform, evident in every workflow. ITSM AI deal volume increased nearly 80% year-over-year. HRSD AI deal volume nearly doubled. Newer AI solutions saw deal volume grow even faster with ITOM growing more than 7x and portfolio management more than 6.5x. We also saw strong net new ACV momentum with security and risk AI growing more than 4.5x year-over-year. App Engine AI more than 4x and Asset Management AI nearly tripling. CRM AI had a standout quarter as well with net new ACV tripling both quarter-over-quarter and year-over-year.

Just as importantly, customers are moving rapidly from adoption to production. As Bill mentioned, our year-to-date consumption of agentic AI in production is up more than 13x year-over-year. We're passionate about helping customers realize value faster. With the help of our forward deployed engineers, we've seen an accelerated time to value of 80% year-to-date. For example, one European customer went live in just 12 weeks and is on track to consume nearly 1.5 million in annual assist. When we provide deployment expertise as we've seen AI adoption move twice as fast in just the first five weeks of involvement.

Turning to profitability. Non-GAAP operating margin was 32.5%, 150 basis points above our guidance, driven by the revenue outperformance, efficiency gains and timing of spend. From a productivity standpoint, our internal use of AI is now generating more than $1 billion in annualized value, more than double the level we exited 2025. Free cash flow margin was 20%. Together, these results continue to demonstrate our ability to drive a strong balance of world-class growth, profitability and shareholder value.

Moving to our outlook. For 2026, we're raising our subscription revenues by $15 million at the midpoint from $15.77 billion to $15.785 billion, representing 21% year-over-year growth on a constant currency basis. We are raising our full year free cash flow margin target by 100 basis points from 35% to 36%, driven by lower CapEx spend. Against the backdrop of growing investor scrutiny around AI-related infrastructure spend and leverage, ServiceNow is positioned to capture the AI opportunity while reducing its CapEx and expanding free cash flow margins. We continue to expect subscription gross margin of 81% and operating margin of 31.5%, up 50 basis points year-over-year. Our execution has enabled us to fully offset the dilution from acquisitions this year and still deliver meaningful margin expansion across both operating and free cash flow margins, reinforcing the strength and scalability of our business model. Finally, we expect GAAP diluted weighted average outstanding shares of 1.04 billion. For Q4, we expect subscription revenues between $4.245 billion and $4.255 billion, representing 21.5% year-over-year growth on a constant currency basis. We expect cRPO growth of 18.5% on a constant currency basis. This reflects a higher mix of on-prem deals and excludes a rising balance of T4C backlog, both of which contribute to revenue but not cRPO. We expect an operating margin of 32%, and we expect 1.05 billion GAAP diluted weighted average outstanding shares for the quarter.

In closing, Q3 was another strong quarter of execution and accelerating AI adoption. What excites us even more is the scale of the opportunity still in front of us. From SI Control Tower and Autonomous Security to EmployeeWorks and our growing portfolio of AI specialists, we're helping customers operationalize AI across the enterprise, turning innovation into measurable business outcomes and ROI. Just as important, we're helping customers accelerate adoption without losing control. This is where ServiceNow is differentiated. By combining workflow, data, AI and governance on a single platform, we can help customers manage the complexity of the AI era while unlocking its full potential. This gives us confidence in the substantial growth opportunity ahead and our ability to create long-term value for customers and shareholders.

Bill and I would like to thank our employees around the world for their continued focus, execution and commitment. Their ability to innovate while operating with discipline is what enables us to consistently deliver quarter after quarter. With that, I'll open it up for Q&A.

[Operator Instructions] Your first question comes from the line of Brad Zelnick from Deutsche Bank.

Bill, we increasingly hear about AI-native applications companies implementing outcome or value-based pricing. And I was just curious to what extent you're seeing customers asking you to go down this path? I know you have a perfect mix of subscription and consumption, but it seems like the market is moving in this direction.

And maybe for Gina, I imagine this is something you've contemplated internally. What would the impact of something like this be on the financial model?

Brad, thank you. We have the best of both worlds in the sense that the customer likes the predictability of the seat-based pricing model for their budgeting purposes, people that run Fortune 2000 companies run on budget. So we give them that. And also, we're driving consumption. And the idea is simple: get the customer live fast. And once they're live, the token economics take off, whereby we have a chance to improve our revenue per user by a factor of 5x. And that's only because the customer derives substantially more value than that. So it's kind of a win-win.

I would also point out that with the announcement of Flow, the native AI stand-alone autonomous service desk type of provider are no longer required as we have that now shipping it globally. So you can buy it online and you can go live in the same day. So that will be yet another net new ACV engine for the company and obviously, a problem for the competition. So again, best of both worlds.

One thing that really is interesting with the Super Intelligence Control Tower, you should know a 500% growth month-over-month in terms of the AI action that's activated in that Super Intelligence control tower, coupled with a 13x improvement in AI consumption. So clearly, we're benefiting from our current model because we're growing 21% year-over-year. And this hockey stick formation has yet to be fully realized. And so I think that is yet another exciting point for the investors to contemplate.

And then, Brad, from the impact on the financial model, as Bill said, our customers are very focused and quite happy with the hybrid model that we have today and are not asking at all for outcome pricing. And so you would imagine if the day were to change that we'd be ready and waiting for that. But as of now, our customers are very, very happy with the hybrid model, as Bill talked about.

Your next question comes from the line of Alex Zukin from Wolfe Research.

Congrats on another strong performance. I guess maybe, Bill or Gina, for you, there was some nuance on kind of some of the impacts that you're seeing on the numbers and the guide, particularly for Q4 on cRPO and subscription revenue. Maybe to the extent that, again, all of the metrics that you're citing sound like you're expanding your growth opportunity, expanding your growth potential. Obviously, the stock is down pretty meaningfully after market on some of the, I think, the 4Q guide. But any constant kind of comments on your confidence in growth going kind of either staying high or going higher, particularly even for next year as some of these nuances normalize and they don't necessarily impact subscription revenue as much as maybe the cRPO deceleration would imply?

Thank you, Alex, and I appreciate the question. And yes, so first and foremost, we remain as confident as ever in our growth opportunities, as I hope came through very clearly in both Bill and my prepared remarks. We had strong beats across the board, revenue, cRPO, op margin, free cash flow. We raised free cash flow margin.

On the revenue beat, what I'd say is that while we actually passed through half of the beat all of the FX and half of the beat that we saw in Q3 to the full year guide. With respect to why we didn't raise by the entire beat, there's a couple of things. And so number one, with our scale, the speed is really strong, and we feel really good about that. But to help our customers realize value even faster at scale, we've made the strategic decision to invest in their success by including delivery expertise with our platform solutions to accelerate AI deployments for select large deals.

From an accounting perspective only, the value of those deployments are carved out as subscription revenue, and they're included in professional services rather than subscription revenue. Notably, upon renewal of those contracts, the value of those services return to subscription revenue. So it provides a structural acceleration to growth. And it's not huge, about 25 bps in Q3 and expecting it to have approximately 50 bps in Q4, which is the only reason why we didn't pass through the full beat in Q3 into the rest of the year. So subscription revenue, feel really, really strong about that.

With respect to cRPO, we saw strong early renewals in Q3 that contributed about half of the beat in Q3. Now that has a negative impact in Q4 because we pulled those deals out of Q4 and into Q3. So that growth is already in Q3. A couple of other things to factor in. Strong public sector demand is driving higher on-prem mix in Q4, which is actually a great result. But that is driving a 25% -- sorry, 25 basis points headwind in Q4 cRPO, but will absolutely hit revenue and the part of revenue. The other thing is those incremental investments in deployment expertise, a small modest RPO headwind also does not impact revenue in the long term.

And just more generally, I'd note, and we've talked about this before, right, cRPO is a very nuanced accounting metric, and it doesn't necessarily capture all of the momentum in the business. A good example for that is there's approximately 50 basis points of year-over-year subscription backlog growth that's excluded from cRPO in Q4 due to T4C provisions, but absolutely will be included in revenue. And so while cRPO is a good indicator of next year's revenue, it's certainly not perfect. And the momentum you're hearing in the business, especially around all of the AI amazing things will absolutely translate to strong revenue growth in 2027 and beyond. And at the end of the day, we feel as confident, if not more confident today in our growth opportunities than ever before.

Your next question comes from the line of Adam Wood from Morgan Stanley.

This is Sanjit Singh for Adam. I wanted to just zoom out a little bit and just talk about the momentum you're seeing on the AI ACV side. Gina as you noted, you've raised the guidance twice now to $1.7 billion in revenue. At the same time, if we look at just the broad story of cRPO, we could call it stable, maybe on an organic basis, modestly decelerating, but sort of generally stable. So my high-level question, Bill, is just when do you think the AI momentum will start to translate to overall top line acceleration, cRPO acceleration? And with respect to that, in terms of the go-to-market motion, you guys have made a lot of pricing and packaging changes. You guys just noted that you're doubling down on delivery. Do you feel you have the sort of AI and sales go-to-market motion right? Or is there room for improvement on that front?

Thank you very much, Adam. First of all, let me just be extremely clear. The business has never been in better shape than it is right now. And I think one of the luxuries that you have when you have the Super Intelligence Control Tower and every partner, that's a hyperscaler or a lab company, these are great companies from NVIDIA all the way through to the labs are teaming up with ServiceNow and realize the importance of coming through our Super Intelligence control tower to drive enterprise value for their customers also. And that's where the network effect is really starting to kick in to extra high gear. So I want you to please register that as a significant momentum advantage that we are experiencing. And also, we are very cognizant of the importance of getting these customers live fast. They have to get value out of AI now. And so as Gina said, we've made the necessary decisions strategically to get them live fast, invest in doing that, so ultimately, they can not only derive the benefit from the license, but they can also activate the tokens to create the tokenomics that our shareholders are looking for and also that their shareholders are looking for. So that virtuous cycle is kicking into high gear. And as I mentioned, we have a 500% month-over-month increase in the activity on the Super Intelligence Control Tower and a 13x improvement on the AI consumption itself. So the strategy is working, and yet we're still in the early days.

You will absolutely see in some now, but also in 2027, as Gina said, the true acceleration because it's all about the customer getting these implementations and getting these tokens activated in their workflows or their business processes. But we have made a decision as a company and our ecosystem to do that because that's where the long-term value creation exists for us, for the shareholders and most importantly, for the customer. So I feel great about it.

And then -- and I'll just take you back to Financial Analyst Day, Adam, when we talked about by 2030, our AI business would be 30% of our ACV. And so we're absolutely on path and trajectory to get there, if not actually ahead of schedule, as you can tell by our continued raise of AI, but we are well on our path.

Your next question comes from the line of Samik Chatterjee from JPMorgan.

Maybe if I can just go back to the strategic decision to invest with your customers to accelerate AI adoption with them. It sounds like you did some of that investment in Q3 already. Any early data points in terms of those engagements that is driving the confidence about sort of expansion on AI adoption from them? And what you -- what are sort of the ideal metrics you've been focusing on to measure that outcome there with the customer?

Absolutely. And as you can imagine, this market for AI is moving very quickly, and so are we. And we noticed that customers receiving the support saw AI adoption progress twice as fast during just the first five weeks of that support with multiples higher of assist consumption and product usage versus those without support. So that assist consumption and product usage are the metrics that we're looking at. And when we're seeing accelerating customer AI consumption, as you would expect, it unlocks a significantly larger monetization opportunity, making the ROI very compelling. Therefore, we're reacting by building more of these deployment teams into our forecast because we're seeing such incredible results.

And I would add to that, Samik, just one very interesting move that we made, which was the acquisition of Sweep. And as you know, one of the big reasons why customers sometimes have a more difficult time changing from one CRM system to another is they have a long implementation cycle, and nobody wants to have a long implementation cycle, especially when it relates to taking care of their customers. And so now we're able to accelerate the deployment times for CRM to -- instead of talking years, we're talking a month. We're talking like days, 30 days, 60 days for a serious company of serious scale. This same logic also applies to the enterprise super intelligence control tower and all of the workflow processes on ITSM as an example. In 24 hours, we activated that.

So what we're looking at here is a Super Intelligence Control Tower, a completely open ecosystem feeding into the rules and the rails of the way the enterprise runs, connecting the fabric of the data and the processes, and we're going to do this at record pace. So it's going to drive implementation cycles to record speeds, which is necessary to get the tokens fully consumed, activated and generating revenue.

As I always want to remind everybody in our company and otherwise, there's no other company growing at the rule of 57 in the enterprise software industry. If you could find them, please let me know. I want to talk to them. I want to get the best practices with 21% growth on revenue and 36% growth on free cash flow, all while building the most superior super intelligent control tower that the world has ever known. So I want to meet that company.

Your next question comes from the line of Peter Weed at Bernstein.

I think one of the impressive things you've been doing is investing internally in productivity optimization. And I think we're seeing that come through pretty significantly in some of the headcount numbers. Can you help us understand how that's playing out because it looks like a lot of it is actually focused in maybe front office product and sales and marketing. And how are you able to get that productivity in these areas to the level that you want while this is also what will be driving revenue looking forward?

Thanks, Peter. So, first and foremost, so, so excited to say that we've crossed $1 billion in efficiency gains through our own internal use of AI and the lion's share of that is coming from our own use of our own products Now on Now. So it's just incredible. And yes, that efficiency gains means that we're able to not hire as many people. That being said, we're absolutely hiring folks in the right spots. And so while you might see total sales and marketing headcount come down, actually quota-bearing heads are up double digits, while sales operations, for example, is down significantly.

And very similar in the R&D organization. As you would imagine, real increases in AI engineers in top talent, but there's lots of efficiency gains that we're driving through AI. That means that we don't have to hire as many support people, for example, or overhead in the R&D organization. And so we're absolutely still hiring across the board in both go-to-market and R&D. We're hiring in the right places, but that's being offset by incredible efficiencies that allow us to bring those more operational roles, those headcount roles down significantly.

And I would build just to share with you, Peter, a couple of things that are very interesting. We have our own EmployeeWorks solution in the company. And so if you think about our great go-to-market machine, which is the best in the industry by far, they all have a coach, and that happens to be EmployeeWorks. And so it is autonomously activating all of the controls that are necessary to build great customer relationships and bring all of our innovation to the customer. This is being done autonomously, not that they have to even request it. They're also getting the insight pushed to them to make them more productive on the front line. Think about it. If you go back 3 years, that was like 100 people in the sales operations department moving around information on e-mail. that is now completely autonomous. It's a sales coach in the pocket. It's driving enormous productivity. And just to be clear, we're actually significantly improving and increasing feet on the street. And while our ultimate headcount has actually slightly declined, which is a gorgeous situation, as Gina pointed out, the 90% response time to customer service or employee service inquiries is now done autonomously in a way that is so much easier for people to deal with, and it gives them an improvement in their life experience here at ServiceNow.

Finally, while the headcount may remain consistent, we continue to strengthen the workforce. So we continue to bring in net new talent in AI on the innovation side and on the quota-bearing side, we have a higher standard for the kind of individuals we need to take us from here to there. So while the headcount is steady, the innovation and the improvement of the human capital condition has only increased substantially. So that's a very important thing that sometimes doesn't show up in the numbers.

Your next question is from the line of Arjun Bhatia from William Blair.

I'll add my congrats on a good Q3. I want to go back to an earlier question. Bill, one of the most important sort of biggest debates and questions that we get from investors is whether AI is cannibalistic or accretive to software companies. And we're kind of seeing this in your results where the AI adoption is increasing and accelerating and you're seeing raises on that guidance and then some of the other metrics are sort of not yet inflecting.

And I'm just curious, and I'm sure there's a timing mismatch there. But when you look at your early adopters and your most advanced AI customers, what are you seeing in terms of how their overall spend with ServiceNow is changing as they've adopted Now Assist and your AI capabilities?

Yes. There's no doubt. First of all, I really remind people, including at the CEO meeting that I referenced, the world GDP rests on super intelligence and this intelligence -- really this intelligence generation that we'll look back on 10 years from now and say that was a renaissance moment. And so all the business cases that are tied to return on invested capital from AI are a factor 10x greater than anything that preceded AI solutions.

So this is really like unbelievable stuff. I mean, just take ourselves. Gina talks about $1 billion, $1 billion is a lot. $1 billion in a year is a lot of money. And what's unbelievable in terms of the operational performance of the company, we continue to grow the company at a pace consistent on a much larger base than we were growing before we saved $1 billion. So less people doing extraordinary things, enjoying their work much more because the autonomy of the AI platform has taken the pressure off of them so they could do the work that really matters. So we're one example. But the business cases, and we review them all the time with Amit and Paul, they have a 10x improvement over anything that we've seen before.

And Amit, feel free to comment on it.

Yes. Arjun, on your question about the use cases and how we're seeing that adoption grow. Many of the customers typically start with one or two use cases where we help them or they decide like incident management or triaging or resolution planning. And once they see that go live, we've seen that go up to 3x, 4x usage, but also new use cases emerge because now they're seeing it in the production environment. So that's really been the growth. I mean if you see a lot of the customers we talked about in last quarter as well as now, they're re-upping their licenses and the new renewals with higher tokens because they're seeing the adoption go up as well.

We have customers like Nestle, for example, they went live in six weeks with this marketing optimization, agentic workflow. And now they're unleashing that in 90 different countries, and they're starting to now use it across the world to get value out of one time the use case they build and grow it significantly across the world as well.

So those are kind of the common patterns we see. And then we're seeing this autonomous IT, for example, and then with that kind of use case going into AIOps, CRM optimization and other industry industrial use cases as well. So very, very easy to kind of start seeing that growth come through.

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

So, Gina, I just wanted to ask about the decision to have resources for large customers to accelerate AI deployment. I'm curious, I guess, when was that decision made? And I'm just curious how we should think about modeling that? Is this something that will be broadly available? Is it something that's on a customer-by-customer basis? And then is there anything that we need to make a consideration for given the rev rec on the margin side as well? Maybe just help unpack that for us and what you're assuming in the forward guidance given -- I know it's not the biggest thing that happened, but it did sway, I think, the guidance a little bit. And so I think investors would get some more comfort if we had more color on how to unpack that.

Yes, perfect. So yes, as I said earlier, Samad, the market for AI is moving very quickly, and so are we. So when we saw the real inflection with customers that were receiving the support, we decided to double down because that consumption flywheel is going to drive significant incremental growth, right? And so deployment times are rapidly improving, and these services are being, as you say, provided for a select number of large deals, and we talked about it's in the number, 25 bps in Q3 and 50 bps in Q4. And we don't expect to include this delivery expertise over the long term. As with other new technology adoption cycles, it's really about optimizing the first wave of adopters and leveraging the know-how in a repeatable and scalable way. And as the AI gets better, the ability to autonomously deploy gets easier and easier. And so we don't expect this to be long term, but we absolutely believe it's the right thing for the business and is going to continue to help drive that consumption flywheel.

I'll add on this, Mr. Samad. We're also building -- using AI implementation agents. So what -- when we help our customers go live, a lot of the heavy lifting is done by AI. This is really identifying the early use cases and make it simple for them to go live with it. And once they get 1 or 2 of these live, then the volume goes up very quickly. So this is not a long-term engagement. It's very short, but we get that value quickly for customers.

Your next question comes from the line of Kirk Materne from Evercore ISI.

Bill, I was just wondering on Control Tower. Obviously, everybody is getting ready to have to build an orchestration layer to take -- to sort of manage their agents at scale. Are they doing that now? Or are they waiting until they get more deployment in production? I was just wondering how you guys see that playing out where they're going to lay out sort of a baseline and then they can drive consumption once the Agentic population builds up. I was just wondering if you could give us some color on that front.

Yes, sure, sure. First, I'll just say big picture, the Super Intelligence Control Tower is basically redesigning what the enterprise visibility, governance and security posture is of these major corporations. And if you look at the partnerships we announced today across the board and especially OpenAI, it's clear that the best and smartest companies in the world realize that this Control Tower and activating that across rules and rails that are deterministic and companies rely on to run their business is a pretty important thing to do to grow their businesses.

So Amit can give you some color on exactly how we're driving this and the impact that it's having.

Yes. Thank you, Bill. So Kirk, usually, I think if you look at last year, the concerns many customers had when we speak to them is they had no idea of what's going on with AI, how many shadow projects are going on, what agents are doing. So Control Tower really resonated very well when we introduced it last year because we are kind of putting this in front of the AI deployments. This is really the governance, the trust and the safety layer, which gives you a lot of confidence and the ability to really have trust in the system. And as we have built out the discovery capabilities across multiple third-party AI systems out there, any kind of in-house build AI agents, you have one place to monitor, manage, including cost, but also really have the ability to kill any agents which should not be going and doing something which they're not allowed to.

So it's become a very strong part of a governance layer, but also the runtime layer. And this is where the difference comes in. So it's coming in first before AI goes in production. And the volume of usage just starts going up because as you start building out more AI as you get confidence, we are really helping them manage it. It's not about orchestration really. It's really the visibility, the control and the safety. And then we can orchestrate many things underneath the covers depending on what our systems customers might be using.

So this really upfront first investment customers are doing and unlocking a lot of value for us going forward. And it's built on our core competence we had with CMDB and the asset management and the introducing ability to do any kind of physical assets as well as physical AI and nonhuman identity in one place. So it really resonates and works very well for our customers if they want to really scale AI.

And if it helps you, an example might be think about AI adoption, unifying IT, audit, legal, risk and this single governance framework that Amit is discussing. Accenture has over 800,000 employees, I believe. And every single corporate function now is running on ServiceNow. So they use the Control Tower to govern nearly 900 ServiceNow native AI assets, and they measure the business outcomes across all of their departments. And what it's done for them is, like it's done for us, a substantial increase in productivity across the enterprise as they scale agentic AI.

I can also tell you about a global tech leader that's basically using the Super Intelligence Control Tower and their driver was Armis and Veza because they wanted to manage the identities of obviously, the people and the agents. But at the same time, they wanted to secure the operating technology environment of the company, networks, devices, critical infrastructure and so forth. and lower their cost to serve, drive their productivity and remediate things at machine speed. That's going to be a consistent theme that you're going to hear. And when you think about it, this particular company had about 80 different security tools, and that's pretty dangerous.

And I use Nestle as an example in my remarks, but they've expanded their footprint of ServiceNow through the prism of the Super Intelligence Control Tower, and they're running their governance across a very complex large global corporation and all of their operations are governed by the Super Intelligence Control Tower, and we're just getting started with them. So there's just so much in front of us, so much bandwidth that we bring to the customer. And the word is out there now. We're ready to roll.

I'll just add one thing, sorry, Bill. the idea that we can discover, but also the SecOps products we have built for many years, you're combining this ability to discover, preempt any kind of issues as well as proactively remediate in one platform. And that's when you combine this control tower with what we do in SecOps, Veza and Armis, suddenly you have a platform which completely has visibility, but also the ability to save you if something goes wrong.

Your next question comes from the line of Michael Turrin from Wells Fargo.

Bill, given it's early November, I'd just be curious to hear how you characterize the tone of overall IT budget discussions you're hearing, how ServiceNow specifically is positioned where Armis and some of the agentic offerings were talking about fit and just how that impacts where you focus the company, both into end of year and towards a successful '27.

Yes. Thank you very much for the question, Michael. Yes, I feel really great. The most important thing is strategic relevance. And that's what we have. We have a system of record that has been trusted for a couple of decades and the net new innovation from ServiceNow is truly breathtaking.

And what I see is solutions that don't matter or point solutions, they will get eliminated while strategically relevant platforms will not only do well, they'll do a lot better, especially if they're relevant in this era of super intelligence. So we are seeing our pipelines grow extremely well. The Super Intelligence Control Tower, Veza, Armis, Moveworks. I mean, in three quarters, you created $100 million in ACV. All these businesses are way ahead of what we had anticipated when we brought them into the family. So too is Logik AI. So what you're seeing is we're building lots of innovation, thanks to our great innovation machine led by Amit. We made the right strategic choices to complement what we were building and our customers really love it.

So our biggest opportunity right now is to get out there in front of the customer and make sure they understand because they're getting hit from all angles. But the one angle that is consistent everywhere is they want ROI now. And we're past the proof-of-concept phase. We're past experimentation phase, and we're past point solution or vibe coding or do-it-yourself phase. We're now in serious enterprise phase where it's all about get the job done, deliver real value. And this platform is one of a few that will do extraordinarily well now and in the future.

We have time for one more question. Your last question comes from the line of Mike Cikos at Needham.

This is Matt Calitri on for Mike Cikos over at Needham. We wanted to ask on Action Fabric monetization, particularly with the OpenAI like partnership expansion announcement that came out with earnings tonight. What sort of spread are you seeing between early adopters that are moving with EmployeeWorks versus using external agents? And what are the monetization implications of this?

Sure, Matt. So I think our view always has been that we provide customer choice. customers should be able to use whatever tools they want to access capabilities in ServiceNow and be able to do actioning, which is where we have really great differentiator and capabilities. So with Action Fabric, what we've allowed customers to do is to go through MCP and A2A kind of interactions and build any interface they want. What we're doing with OpenAI is allowing ChatGPT as a way to interface into ServiceNow. But all of the work happens inside ServiceNow. It's just a call coming from ChatGPT. And then the work which we were doing typically through our user experience now happens through this interface, and we get full value for it from the monetization perspective because you're burning down assist for every work you'd ask ServiceNow to do. And that work is not able to be done anywhere else because we have the context, we have the ability to understand what you're trying to do and all the connectivity to all the third-party systems as well as the workflows, which are running already inside ServiceNow for any enterprise customers.

So we're just opening up the ability for any ways to access ServiceNow, and we get an opportunity to monetize this much more than we typically would have done by just providing our own interface. Of course, EmployeeWorks is also another option for customers to use, but the EmployeeWorks provide a lot more capabilities than ChatGPT can provide or Gemini Enterprise can provide because they're just a calling part of it. What we do with EmployeeWorks, we are doing a lot of the reasoning, the orchestration, the planning as well as providing specialized agents, which gives you, again, as an employee, a lot more capability than you would get typically from other third-party front doors.

So there's a lot of differentiation built in, in EmployeeWorks. But again, we do want allowing customers to use Action Fabric in another way to interface and still get value out of ServiceNow investment they made, and we continue to monetize, so we get ability to really grow our revenue through many, many mechanisms now. As the partnership with OpenAI is great. I mean I think there's a lot of capabilities we'll deliver with them from a skills perspective, but they're depending on us to really do the work, and that's where the value gets created.

And if you think about it, as Amit said, ServiceNow basically is the execution layer. And I believe we're the execution layer for the entire AI economy. And if you look at what's happening with the partnerships we announced today and many more to come, it's not just where the work gets done, but it's where every human and every agent in the enterprise is coming to get things done. And that's a large market. We're positioned at the center of it. And if you say, well, how should we know? Just keep in mind that Action Fabric has seen a 500% growth in assist in less than 30 days. So it's multiplying so, so quickly. And I think this represents a business model innovation that will be substantially larger in a very short period of time than the entirety of ServiceNow is today.

We have reached the end of the Q&A session, and this concludes today's call. Thank you for attending. You may now disconnect.

Absolutely excited and delighted to welcome Bill McDermott to the ServiceNow keynote at the Goldman Sachs Communacopia Conference. Bill, thank you for being here so many years in a row. We really appreciate it.

Thank you, Gabriela. Great to be here with you.

Bill, the conversation we were just starting to have off stage, when we think about the promise of agents, and we've seen select examples in the developer community about where the technology is and how sophisticated it's become. And then we turn around and come back to our enterprise environments, and there's a massive gap between the potential and what we see on the ground. So talk to us a little bit about your conversations with CIOs and CEOs. Where does ServiceNow help bridge that gap? And is the gap starting to close?

Yes. The enterprise is a whole different scenario from the consumer experience. And I think for years, the complexity of the enterprise has surprised people. And so we've moved from an environment of, I would say, token maxing to token economics. Every CEO wants to grow their business, they want to expand their margins, and they want to do everything in a highly secure manner. And so what we're seeing is you have to manage the identity of humans and agents and robots and thinking machines and do this all on a common platform. And I guess our moat is context because we have 100 billion workflows doing 8 trillion transactions in the global economy right now.

So that configuration management database knows all the people, places and things that are going on in the enterprise. And it's that rich context engine that understands the rationale of how that work is flowing to whom it is flowing, why it is flowing and everything has to be auditable and highly secure. So I like to say we're the rules and rails of the enterprise, which is very different than the do-it-yourself vibe slop that's happening in a lot of companies today, creating even more technical debt and risk than ever before.

Well, let me ask you about less the risk of ServiceNow being replicated or displaced. And more of the question of what happens to the agentic workflows that perhaps get built outside of ServiceNow such that there's value abstraction away from the ServiceNow platform. Maybe push back against that hypothesis.

Well, first of all, I think vibe coding is happening everywhere. And what you're seeing in enterprises today is a lack of visibility. 90% of the organizations in the world economy today do not have visibility on the agents, whether they're -- bring your own agents or the enterprise agents in an enterprise. Just think about that risk just for a second. And we don't even have to get into the Hugging Face example or lack of kill switches, which obviously ServiceNow has all of that.

So I think what we're seeing here is initially, companies were very interested in this because they're like, "Hey, can I do it better, cheaper, faster by vibe coding myself beyond these enterprise platforms?" And what they found out was that there's a 5 to 10x TCO difference, meaning, it's 5 to 10x more expensive to even try that than actually use a proven platform like ServiceNow because you have the integration challenges that have been around for 60 years. You have the security challenges that are getting more and more relevant every second of every day. And then you have the ongoing support and maintenance of these systems.

And of course, if everybody is doing their own thing, nothing actually integrates at a business process or an execution level from one department to another. And one simple example is if I vibe code myself to a sales question and say, "How are sales doing today," I might get an answer that sales are up or down. But it's not looking into the product development cycle, the supply chain, the ad campaigns that may or may not be running and what's going on with the coverage strategy in the company, who's in what phase of what pipeline.

And ultimately, after you make the sale, that's a good thing. But now we got to get the customer live, productive, adopting these things and being successful, which is going to touch every department in a corporation. So when we talk about enterprise, we're talking about a whole another ball game from experiencing the convenience of these great thinking machines on your living room couch on a Saturday afternoon. That's the bottom line.

You've mentioned security twice in the last few minutes. As someone who spent time in security over the last decade, a lot of our conversations used to be about network, they used to be about endpoint, they used to be about identity. Today feels a little bit different. It's become a lot more about visibility. It's become more about governance, right at the same time as you've acquired Armis and Veza.

So historically, I would have been skeptical about an application software company getting into security. But it feels like the domain is changing around us. So talk to us a little bit about that.

Well, if you think about security, the surface area of these attacks is expanding every moment of every day with the power of AI. And what we've learned is having a broad security operation of our own, which ServiceNow has had for many years, where we integrate with all the major security players in the world. And so we always had that uber vision of what's going on in the security landscape in the corporation. And keep in mind, the average company is using 47 different security tools in their enterprise at any one given time. So that's already a point solution mess. And now we have that uber view of security operations.

But now we have built and are well on our way to building the most integrated secure enterprise security platform the world has ever known because you have security operations, which was already over $1 billion business for us. You have identity management, you have asset management. You have operating technology, which takes into account IT, IoT, medical devices, critical infrastructure, networks, devices. We already have 7 billion devices under management, but there'll be billions, another 40 billion more that come into our purview in the next few years. So we are the fastest-growing enterprise security company in the world. That's just a fact.

And we're now the eighth largest with an ambition to be #1. And so I think that's well within our reach, and we're going for it because the customer wants not just to know what the security issue is, but because of our workflow automation platform, our unique CMDB and context engine, we not only can find the problem, so we identify the problem, but we can put the workflow into action to resolve the problem and close the loop in a fully audited secure manner. And no other company in the world can do that.

To what extent is that vision complementary to those other 47 point product vendors?

The fact is it's not interesting actually to compete with the other 47. It's actually to make them all work better. I've always said if every enterprise software company would just adopt ServiceNow as the platform of all the platforms or the AI of all the AIs, their growth prospects would go up dramatically. So if they do that, we partner well with them. If they don't do that, the customer has us do it anyway, but that's why we just keep winning.

Let's talk a little bit about the vision with ITSM. One of my favorite parts of the Knowledge conference was when you talked about the pilot customers, and I think you had a couple of flagship examples of the before and after, where when you actually go through automation on the ITSM platform, the ROI gets better, you could see the productivity improvements, the business gets strong, all that good stuff. So maybe for those of us who weren't at Knowledge, talk to us about what the customer journey on ITSM looks like?

Sure. So ITSM is our service management platform, and that is the core of the core. And what's extraordinary about it is not just that it's a multibillion business, but also that it grows in steep double digits. And I always like to think of the core of any company as the moat that you really build everything else on. So as you think about ServiceNow being able to service the business, manage its assets, manage its operations, do all of this in a highly secure manner, that extended out into the employee experience.

So how I recruit, how I hire, onboard, provide all the services to an employee or how I onboard a customer and I fulfill their order, configure pricing and quoting supercomputers is pretty hard to do. That's why NVIDIA uses us and does it in seconds instead of days. And then you fulfill the order and obviously service the customer all on one common platform. And so what you're seeing now in the global economy is this need to get away from all of the platforms and center your focus on the vital few where you can really put AI to work, put AI to work for all the personas in a corporation.

And so the extensibility of our platform, whether you're taking someone else's data from an ERP system or an HR system or a CRM system and operationalizing that in our workflow or you're simply doing it in ServiceNow, you are autonomizing entire companies now. And so we have 20 Level 1 employees that are agents badged into our company. 90% of our customer service, our employee service and various tactical things that used to require tremendous human labor is now being done by Level 1 agents. We have airlines now wiping out call centers, basically doing everything on AI voice with ServiceNow. And I'm talking about millions and millions of calls.

So the word is getting out there that we're on the move, that our AI actually really works, which is why it's up ninefold in 9 months, why our CRM is doubling on a year-over-year basis, and it's crossed $2 billion in ACV. And the same is true also for the employee experience. So the integration power of that ITSM platform is everything. But let me help you out with another thing. It's very clear that people want these simple AI security desks or these simple AI help desks. We have something coming for all of those people. We're going to take it to 500,000 mid-market customers globally.

We're now in a very, very highly exciting beta with many of the biggest companies in the world, and we're going to be able to take this now to 500,000 customers globally, but also the existing customers will be able to integrate it back into the ITSM core, so they can actually use a simple AI help desk for simple AI tasks and then integrate it back in with pure, pure visibility into all the assets, into all the logs, into all the actions in the company in a fully audited manner, so it's not a one-off point solution. So I think this will really change the market dynamics for some of the point solution providers that have a good time copying all of our information as if it was theirs. So it's going to be a lot of fun. It's coming to theater near you real soon.

Stay on this beta because I can tell you're excited about it. What is unique about the way that this beta addresses the problem of ITSM that hasn't been done before?

Well, I think it just makes it clear that you can do very large-scale things. And if you choose to do smaller things in, for example, a satellite operation or a satellite department, there's nothing wrong with doing that, but having it integrate back into the core system so you don't have the vibe slop that's getting created now. I was talking to somebody earlier today here at this conference where one of those vendors walked in and they said, "Oh, let me do something for you. I can do that." And the decision-maker in the company basically said, "If I wanted to vibe code it, I could have done it myself. You didn't do anything, that's nothing." What we are looking for is, can you do something at an enterprise scale level? And the answer was no, we can't. So I think to have it both ways, to have total choice is something we want to bring to the market.

There's been a lot of debate just in the past 2 weeks on what a healthy relationship between an application software company and a frontier model looks like? Would love to hear your comments.

Yes. First of all, this is a terrific thing. If you think about the compute power that is taking place in the world economy today, it's inspiring. If you think about the lab companies and the massive intelligence they're creating, it's inspiring, but it's also very costly. And it will be very costly to continue the pace of keeping that knowledge revolution going. What's so exciting about being ServiceNow is we could take advantage of all that compute, of all that intelligence and then we put all of that to work in our AI platform for the enterprise without the cost associated with diving deeply into compute or deeply into the lab model where they have to spend billions and billions to create this knowledge. We just get to benefit from all of it.

So while others have made marketing moves announcing those exciting partnerships, and they are exciting. We've already been doing that for months and months now with complete integration into all the lab models. And so the cool part about ServiceNow is we will hire the right model for the right job and will enable the customer to manage the economics of their token usage by using the right platform for the right use case. And so now you're into the token economics game.

And so we understand that game very well, and we're partnering with all of these wonderful companies. And I think they're all tremendously exciting. And the best is, if you're a ServiceNow customer, you get to take advantage of all of it. You have total choice. So we didn't need a marketing event to actually pull that off. We did it at a deep engineering level, and we did it months and months ago.

Let me ask you now about your early example on the airline cutting costs because they were able to cut out their call center. One of the questions we get from investors is, look, when you start adding up all of this CapEx and all of the frontier model spend, you can't just save cost. You also have to expand the pie. There has to be some GDP derivative implication. There has to be more revenue that also comes out of the pool. I'd love to hear your thoughts for ServiceNow customers, I know you talk a lot about the labor argument, the cost argument at Knowledge. What about the revenue expansion?

No, it's absolutely. I mean the revenue opportunity is massive. If you think about companies literally taking advantage of 20 L1 jobs now that are fully agentified at ServiceNow and you just think about CRM growing on a doubling basis on a year-over-year level. I mean these are, like, huge kinds of numbers. That's because customers now are trying to connect all the things that a customer can do in any channel. They want to meet the customer where they're at. They want to fulfill whatever the customer requirement is and the configuration that they want and they ultimately want to serve the customer on a net present value to create the loyalty effect for life.

We can actually do that. We're also arbitraging labor in the growth of company or the aspiration of company, where now with AI, instead of having like triple the workforce to have a services model to deliver a decent margin, they can do it with 5x less people, but still actually grow revenues that go into markets they weren't even participating in before because of AI. And so I think the GDP effect of AI, AI done well is enormous. And I do think this rising tide will lift all boats. I see our own business model. People made a big deal out of, "Oh, seat-based AI, is it going away?" And now everyone is finding out that not only did it not go away, but it's actually increased.

But on top of that, if you take that seat, we predict that, that has a 4.5x increase in terms of the revenue of the original seat on the date the contract was signed throughout the fulfillment of the contract because the AI effect and the use cases across the enterprise and the flow of work to reinvent business processes are so powerful and so growth inducing and so margin accretive that companies are going to run to this model. And as they do so, they will increase their growth, they will increase their margins. And obviously, they will do all this in a highly secure manner. And that's what it's all about, executional excellence.

We're a big believer that when software companies drive value for customers, they're then able to capture a piece of that value by monetization. Tell us a little bit about how you pick the price point for some of these new AI products. You've already talked about how more than 50% of net new revenue is now coming not from seat-based contracts. So tell us a little bit about how when you have these conversations with customers about value, how do you decide how much of that value to then take in price?

Well, let's just look at ServiceNow because this -- as a matter of public record, we tell the story publicly. Our value accretion with our Level 1 agents is $1 billion. And it's about 2.5 million hours of work that have been taken off of the backs of people that were doing jobs that were somewhat soul crushing and now those excellent people can be retooled and reskilled and do things that are far more productive in service to the customer, whether they're writing code, they're focusing on presale, they're participating in the selling process of the post-sale go-live process or the adoption and the token utilization process.

Now we got people doing more important work. And 90% of the cases, as I said, are being resolved by AI. If you take a company like Robinhood, as an example, which everyone has heard of, they're now using our ITSM product, and it's all autonomous. And 70% of the cases that they used to manage with humans are now being managed by agents, and they're getting a huge ROI on that. If you take a company like Rossmann, they have 5,200 drug stores across Germany. They used to resolve customer cases in 5 to 9 minutes. Now it's being done in 5 seconds. And so the implication is the customer is happier. They have more time to shop, more money to spend and more loyalty to that brand.

If you take these companies, 3M, taking a portal approach to managing the whole customer relationship instead of having 26 legacy point solutions, consolidate everything on one portal approach to running the business in a smarter way. You could also say this for Starbucks with thousands of locations across the United States as one example, 4,000 at least now converting to ServiceNow customer service management. And I could talk about Zoom, and I could talk about so many different instances where there's large corporations now fundamentally rethinking how they run their company. And that varies by industry, but they're all exceptionally exciting.

I had one company who was in the insurance industry and basically gave me a full day on a Friday afternoon to rethink the business processes of like 17,000 agents and how you can put them to work in a holistic manner that's fully integrated into the core company with the sole intent of really meeting that customer where they are and keeping them for life and also making the agent's life so much easier, all by leveraging workflow automation and AI. So this is, like, such an exciting time.

The other thing that's really underreported is data. There's lots of sources of data. We were the only company that fully integrated into all 3 hyperscalers and into those data sources, not to mention the great lab companies, but now all the data companies with the right connectors, we can make a 0 copy of any data source in any enterprise from the systems of record to the various data stores to the hyperscalers without ever moving a piece of the data, 0 copy and continuous operations at AI speed. So all of these things come together in a super innovative AI package from the AI Control Tower from ServiceNow.

Let's stay on AI Control Tower because I think sometimes investors hear a system of action, and they think that it's as easy as plugging in APIs. Now you're talking about being one of the -- you talked about the full integration that you have with hyperscalers, frontier models, et cetera. What is the difference between fully integrated when ServiceNow says it versus perhaps when your competition talks about API connectivity?

If you think about an agentic front door, everybody has to come into an aggentic front door. The good thing is about ServiceNow, if you want to come to a headless front door, that's up to you. But we provide you the agentic front door. And so now you can come into your corporation into one clean pane of glass instead of swivel chairing in and out of 17 different application experiences a day burning up 1/3 of your productivity. So that's a choice. Make the choice, we give you choice.

But if you come into the agentic front door, either as an employee or a customer, you have an unbelievable simple experience. You simply have an autonomous experience where you're asking the system a question. The system will go source any data relevant to the question that you asked and give you the necessary answer so you can go about your business just like you would using one of these great thinking machines on the weekend. The best part now is you're also activating not just the people, but the AI agents. And the cool thing about ServiceNow is it doesn't have to be a ServiceNow agent. We will work with all of the agents of all of the corporations that companies utilize in the enterprise.

So now the AI of the AIs kicks in. And that could also be a robot. You got to treat them the same way as you treat a human or you treat an agent. And we also, as I said, integrate with all the labs. So we now have that in the Control Tower completely worked out. But now you have to integrate with data. And so I've already given you the action layer. Now I'm going to get into the workflow data fabric layer where we can connect into any data source, which could have been a Snowflake or a Databricks or a hyperscaler or completely your own rendition of what a data store is. And of course, the systems of record that you spent the last 6 decades investing in, we got you.

And then where Armis really comes in was on the operating technology side. So think about all the assets of a corporation. One of the reasons our public sector business is doing so fabulously, and it's a much bigger setup this year than it was last year is because we know all the operating technology in any environment. So we already know and we can go into any agency and basically show them how little visibility they have into their assets, and that's probably not a good thing. And so we can immediately remediate that with our operating technology from Armis.

So any of the assets, IT, IoT, OT, all on one common platform. And if you think about major banks, they care a lot about critical infrastructure, networks, devices, the people that roam in and out of the buildings and all that, and it's now being managed by Armis. So we got you on the identity side. We've got you on the agentic front door as you come into the enterprise, which is huge. And we've got you on all the fabric contained in the data of your corporation and of course, the operating technology. And all of this is done in a highly secure way. And I repeat, we are the only company in the world that has integrated risk management, security operations, identity management and operating technology on one common platform.

And Gabriela asked me a question earlier about ITSM. That was always the fabric and the moat where you have the configuration management database and you have the context engine for all the people, places and things, and that fabric has been built over 20-plus years, 100 billion workflows, 8 trillion transactions. And so now you're talking about enterprise scale, and that's why we made the bold move into extending more broadly into security because that's what our customers wanted from us.

Let me ask you a little bit about the R&D organization.

Sure.

There is a view that ServiceNow's been established incumbent for a long time. Therefore, to take new technologies and make them backwards compatible, you run into an issue of technical debt. And at the same time, you're acquiring these companies, they have to be beautifully integrated. That's not easy. How did you -- and maybe Moveworks is a great case study here. How did you look at your organization as a whole and say, we've got to be able to move really quickly here and not let any -- use the technical debt. And I don't even know if that's how it works, but not let that hold you back and transform the tech stack such that you can actually move quickly.

Right. Well, it's really interesting. I've been here 7 years now. I don't know where that went, but it was quick. I can promise you that. One of the first moves that we made in the company was a company called Element AI who had a Turing award-winning founder, and they were in Montreal, Canada. And we did that, like, in the first 120 days when I became CEO of ServiceNow. So we immediately had a vision, immediately had a vision for where AI was going to go. And we were building models with Jensen and NVIDIA right from the start. And so it's just one of the real beautiful partnerships, a really sustainable one and one that we're super proud of.

We have really great engineering. And anything, whether it was Moveworks or it was Veza or it was Armis, we are immediately focused on integration. So the calling card of d ServiceNow and how we got big fast was really recognizing that the enterprise is a thorny complex place. And the #1 reason why digital transformation failed to deliver a positive ROI for 85% of the companies in the global economy was because integration held it all back, which is why everybody was operating in silos doing point solutions. And we knew that for the platform to transform companies, it had to integrate beautifully into all these other systems.

So in the flow of work, you could fundamentally change how companies ran without actually ripping and replacing the infrastructure that they spent billions on and years implementing and years customizing. So that was our solve for that. And so when we took on Moveworks, and it was really interesting. We acquired Moveworks in April of 2025. The deal didn't close until December. And we wanted the AI Control Tower. We are a company that's destined by our strategy and our vision. And we had the AI Control Tower vision. And so Veza was a very important part of that, and so was Armis and so was Moveworks. But you all dealt with a 72-hour period where we closed Moveworks and then Veza and Armis were announced and you're like, "What, what's happening? I thought they were an organic growth company." We are.

But we had to have the AI Control Tower to give you the organic growth and print cash for many years to come. And so now everyone is like, genius move, Veza, Armis, all these companies are unbelievable. All the customers love it. All the people that work for us love it. The investors now love it. So I think what's happening is they're seeing the power of integration on an enterprise scale platform that serves multiple industries that satisfies multiple personas in every corporation we serve, and we actually deliver extraordinary ROI. And so our business cases are dynamite. And I think that's the real critical difference that we can do it, that we integrate well and that we do what we say we're going to do and we give you a great return on your invested capital. And that's what customers want, but they also want it in a secure way.

We're at a moment in time where enterprises have a lot of choice. And there are a number of new entrants in the space. There's a lot of confusion. You may even have different factions within a customer on the right way to do things. And ServiceNow comes in with a pitch like AI Control Tower, and you have the case studies like FedEx, for example, of what true transformation on ServiceNow looks like.

How do you get more customers to commit? How do you get them over the hurdle of, "Hey, we want to experiment for a while. Everything is changing so quickly. Let's just see how things go." What does that conversation on conversion look like? How can you enable more of your salespeople to cross the chasm, so to speak?

Yes. First of all, you're right. I mean there's just a lot of confusion out there. There's a lot of FUD out there. It's silly season with vibe coding and the point solutions and the claims that are not based in fact. And so we, like everyone else that has a scalable substantive company has to be ready to handle that. And what you find is the higher you go in corporations, the easier the people are to talk to because they just want to win. And so if you have a winning formula and you have a C-suite relationship, and we definitely have that across the world and a Rolodex that I think would pretty much compare with anybody's.

That's really the basis of understanding. You have to really deal with executives that are trying to transform their company. And then ultimately, what we did is we not only invested in engineering, but we also invested in forward deployed engineers where we actually go to the customer site, we actually implement with the customer and deploy the software and get them live at a record clip. And especially now in CRM, we're particularly interested in that discovery to adoption to ultimately tokenization process to create the value chain for the customer. So you got to be in it to win it.

I think that's a perfect place to leave it, in it to win it. Hey, please thank me -- please join me in thanking Bill McDermott.

Thank you very much. Appreciate you. Thank you, Gabriela.

Thanks for joining day 2 of Citi's TMT Conference. I'm Tyler Radke, Citi's Co-Head of U.S. Software. We got a packed room, probably standing room only at this point. So really excited to kick off the discussion with ServiceNow. We have Gina Mastantuono, the CFO and COO of ServiceNow. Gina, thank you for coming to the Citi Tech Conference once again. I know we were just catching up. You've been busy on the road meeting with customers, partners, obviously investors as well today. Maybe just give us a sense, what are your conversations like with customers as you're meeting with them? How would you kind of compare the level of enthusiasm, the -- all the dynamics that go into their conversations with ServiceNow versus 3 months, 6 months ago?

Thanks for the question. Thanks for having me. I love being here back in New York in September. It's perfect.

So number one, conversations with customers are just fantastic. It's one of my favorite parts of the job, as you can imagine. We're so focused on helping customers really drive value in this agentic AI world that we find ourselves in. And so what I'd say is that AI is just top of mind for everyone, right? And what it means for these companies, not only from a productivity perspective, but from a business model innovation perspective. And I think that a lot of people focus right now, and it's not surprising immediately on the productivity and efficiency gains that can come from AI. But even more importantly, sometimes or certainly as important is the business model innovation that they can really drive and how can AI really help them drive not only incredible productivity and efficiency, but top line growth.

But one of the things that has been a huge focus over the last several years, and we got this comment so much from customers when we would ask is what's the biggest obstacle to large-scale deployment of AI. And uniformly across the board over the last several years, it's all been about security and risk. How do we really make sure that if we scale, deploy these assets that we're able to manage them, govern them and secure them. And so we've been super focused on how do we help customers think about that and how do we help customers solve that problem. One of the reasons why we have had incredible success now with our AI Control Tower. And the ability for our customers to really manage end-to-end across their tech estate any asset, whether it's an AI asset, whether it's an OT, IT asset and really manage it, secure it in one spot, in one place.

And by the way, this is for any agentic capability, whether it's ServiceNow's agentic platform or it's a third-party agentic platform or it's agents that are homegrown, the ability to manage it in one place, end-to-end, the ability to really govern it to make sure it's secure, to kill it if it's doing things it's not supposed to be doing, kill switch is a big top of mind subject today. And then manage it from a cost perspective, right?

You hear all of the articles about costs going through the roof and managing that. Well, you can manage it literally in the AI Control Tower by department, by manager, you can shut it off if they're exceeding, you can override the shutoff, if it's valid, you can optimize. Lots of people are looking at how to optimize spend. Do you really need the Rolls-Royce of models to do a task like driving to the 7-Eleven? No. But you might need the Rolls-Royce if those agents are building your products, right, that are going to touch your customers every day and the ability to manage that and optimize that. And then in the same place, AI Control Tower, the ability to really see the ROI on each and every investment so that you can redeploy and make sure that you're focused on allocating capital that's driving the best return. So all in, AI first, how to manage it, how to control it, how to secure it and really leaning into this conversation on AI Control Tower has just been the #1 conversation across the board.

Okay. And for investors that may not be as familiar with AI Control Tower, can you just give an overview, how does a customer buy it from ServiceNow? What type -- how does that translate into ACV growth for you?

Yes. I mean it's the same way they buy any other products from us, right? It's an area of focus. It's part of the product portfolio. They usually don't buy it in isolation. It's part of kind of their strategy with AI and how to deploy it. And we talk about really the value capture. And it's an ability for customers to be able to really think about scaled deployment in a secure governed way that's managed from a cost perspective, that's really enabling insights to ROI and at the same time, delivering incredible value to the organization.

Right, right. Got it. And one of the dynamics we've seen kind of on and off within software is just kind of this issue of deal elongation, extended sales cycles. You were one of the first software companies to report and had very strong results. I think we're a bit measured in your outlook. It sort of seems like we've seen a little bit of an attenuation in this SaaS apocalypse concern, at least up until Labor Day. But as you're speaking to customers, like is there still the sense of hesitation or AI distraction that we had at the beginning of the year? Or has that kind of moved away, especially now that you're obviously leading with a lot of really interesting AI products?

Yes. I think -- listen, I think there's been a ton of noise in the market, right? And so what customers 6 months ago were dealing with was everyone saying the same thing. And it's interesting to be first in the market when we announced when we do a lot of things because I was like, "Oh, that's interesting," and then literally a minute later, you hear the same thing coming out of 20 other folks' mouth, literally word for word. And so there's a lot of noise in the market or there was a lot of noise. And so how customers can kind of break through that, there was lots of conversation on build versus buy.

I think fast forward to today, a lot of those conversations are much cleaner, right? I think the build versus buy and the understanding that the large language models aren't going to do it all and can't do it all. We see announcement after announcement of partnership agreements, right, with software providers and the models. ServiceNow has always been very focused on openness. How do we integrate with any large language model, any hyperscaler, any application provider, any data warehouse. So our customers have the choice on how they want to evolve their tech stack. That has always been innate to ServiceNow was and is, I think, helping us in this environment because customers really want to have choice and want to have the ability to change their mind sometimes, right?

For a long time, folks are like, "Oh, we're going to go with this model provider because they're the best". Well, very, very quickly, open source is coming up to speed. Very quickly, the models are competing with each other and getting better and better. And so the ability to morph the strategy somewhat, optimize and then you have ServiceNow that allows you to do that pretty easily and more broadly, I think, has been a real differentiator in the space. And at the end of the day, I think there is still noise in the market. You continue to see ServiceNow execute and perform extremely well. We've been very focused in our entire existence on value selling. And I think value today is as important as ever. And so the ability to POC really quickly and show customers how they can get to value very quickly, enables you to cut through the noise pretty dramatically is what we're seeing today.

Yes. And back a few months ago at Knowledge, doesn't feel like that long ago, but you announced some new product changes, different SKUs and pricing packages. Can you just talk about that? It's come up a lot in our investor conversations and customer conversations just for folks in the room. What did you announce? And kind of what's been the feedback that you're hearing from customers?

So we announced some new native AI packaging and pricing. And the real reason for that was, again, very focused on what customers were asking us and what customers wanted from us. And so prior to the native, the AI-native pricing and packaging SKUs, in order for you to really get our our incredible AI portfolio, you had to really go to the highest tier, which was our Pro Plus SKU, which now we're calling our Prime SKU. So that has the most advanced AI capabilities. And that has not changed. We will continue to put the most advanced capabilities in that family of packaging and pricing, and that pricing didn't change.

What did change is that we launched these other tiers. So we have Foundation and we have Advanced, which allows customers, if you're not ready to really go all in an AI, but you want to get some AI capabilities. And it's about how do we get our customers to value with AI a lot quicker. If they're not ready for full-scale deployment, maybe they want to test the waters with some basic AI functionality. Well, that's our Foundation model. And that sees -- and then we have an Advanced, which is somewhere in the middle. And between Foundation and Advanced, the pricing uplift expectations were 20% to 30% with the most advanced Prime SKU. Again, that pricing didn't change, and we continue to see about 30% pricing uplift.

So what this enables customers to do is to really pick and choose the bundling of what's most important to them and what capabilities are most important -- dependent on where they are in their trajectory. And so what we didn't do that I think was a little confusing to folks and listen, there's always a little bit of noise when you have some pricing and packaging changes. But what we didn't do is we didn't raise like-for-like pricing on the base standard SKUs. If you don't want any AI, the price did not go up. But we certainly were encouraging customers to expand into our AI functionality really because we see the value. And the value capture is great even at a 20% price uplift. And so that's really what we announced.

The takeaway has been really great. We have more than 50 customers paying $1 million plus to these new AI packages. We see continued growth, 45% increase in folks that never bought AI buying AI for us in Q2. And so far, so good. And the pricing uplift that we expected, we are seeing in actual realized pricing. And so that's basically what we did.

Yes. And I wanted to spend some time on the product side, which is also very -- is probably the most exciting thing that's going on. I know we don't have Amit here, but take us through some of the key announcements from Knowledge to me, some of the ones that stood out was this vision for the L1, L2 support agents, kind of this theme we've been hearing throughout this conference of agentic labor, right? I mean these are -- you talked about 30% uplift. This could be much larger than that. So walk us through the vision on agentifying the ServiceNow workforce and what are customers doing with those agents?

Yes. So it's extremely exciting. And if you think about automating, we have billions of workflows running through the ServiceNow platform every single year. And if you agentify just a small fraction of that, the ability to drive real, real value for customers and obviously, a consumption flywheel is fantastic. And so we announced them early, early innings, but we're seeing incredible uptake. We have -- the City of Raleigh was the first municipal government to go live with our L1 IT Specialist. And immediately -- and by the way, they put it in place with no engineering backbone at all, very limited. So it went live pretty quickly.

First touch seeing 98% accuracy and driving 65% reduction in IT service desk costs. And that's one use case with one L1 Specialist. So real value add for the customers. And now what they're doing is they are going one ticket desk at a time, and they're agentifying the whole thing. And so that's one great example of where we really see incredible uptake value for customer and then the flywheel of that consumption is going to really...

They buy more credits...

Exactly. And it kicks in. We have another incredible energy company in Europe, working with our FTEs, they looked to automate 500,000 IT service requests a year. That one use case is generating over $5 million in savings. And now -- and that was just a proof of concept that we did in 8 weeks to 12 weeks. And so now they're leaning in on us and saying, what more can we do? What other use cases can we tackle with these specialists?

And so very early days, but this is the dream of agentic, right? How do you really automate less touch, more accuracy, driving real value for customers. And the more you automate, the more consumption is required, which means that the flywheel really starts to move. So extremely exciting product offerings. And while very early, very strong uptake so far.

Yes. And just as you look at the customer base as well as the products that are coming out, how do you think about the timing of when that flywheel really starts to kick in, meaning customers are starting to buy these top-up credits in mass? Like is that something that could happen this year? Is it more '27, '28? How do you just think about the timing of that?

I think it's important to understand, and I'm trying to -- I've been trying to educate investors that even the initial subscription is consumption, right? Because you get so much -- and by the way, initial subscription in that highest tier was a 30% price uplift. So we gave them a very good amount to be able to really drive innovation in use, but it's all consumption. Now what happens is if they don't necessarily top-up on the assist packs on top, they more -- they renew early. Right? And so there's lots of actual consumption happening. What we saw in Q2 that I talked about is the actual usage, right? So how do you manage the usage was up 9x Q2 to Q1. So -- and the last thing I'll just say is that, that consumption increase is actually trending better than initial expectations. And so it's in the number. It's the reason why we were able to increase our $1 billion target to '26 to $1.5 billion. We crossed $1 billion in Q2, well on our way to $1.5 billion. And so the flywheel is already kicking in.

Right. And would you say that increase from $1 billion to $1.5 billion, a lot of that was kind of consumption-driven even either new customers buying consumption packets included with a subscription or top-ups?

Absolutely, sure.

Got it. And then I guess, as you think about just your long-term targets, right? You basically said you're going to double the company by 2030. And I think the AI ACV will be about 30% of the business by then. How do we get there? What are kind of the things that need to go right? And how do you get maybe above 30%? Like what are the things that can take that even higher?

Surprising. That's like the biggest question I got all day today from all of the investors. I love it. You put a target out not 2 months ago and everyone is like, how can you get more than that, which is fantastic. I love that question. Because, by the way, we're asking ourselves that every single day.

A couple of things. So two very big assumptions in the $30 billion to $32 billion model. Number one is on penetration, like customer base penetration for AI. So the AI start-up packs, the AI-native pricing, getting more people even in the base foundational, getting them used to working with AI, seeing the value that the base capabilities are giving you, it's going to drive even more penetration to the higher-level SKUs. But that penetration rate in that number is a big part of the assumptions. What I'll tell you is the assumptions that we put in there, but even the $32 billion model was -- is more conservative than the penetration that we saw from our base product to our Pro product when we first launched our base AI capabilities back in 2018. And so penetration rates arguably should be faster in this world in '26.

And so far, you're seeing it...

And so far, we're seeing that. But I put -- I wasn't getting a whole lot of credit back and made it to be super overaggressive. So I wasn't. But that's a big area of focus, penetration. How do we -- and by the way, that AI-native packaging was a very big part of the strategy to really drive that penetration even though to date, we are ahead of those models.

The second big piece is usage, right? How do we get more people using more agentic capabilities driving more of that consumption flywheel. What does that look like in 2030 versus today? We had fairly conservative assumptions in there. Obviously, these L1 Specialists are part of that. But if we're able to just agentify a fraction more than what's in the conservative model, there's a very clear path to something potentially even higher than the $32 billion. So that's kind of the AI piece of it.

And then we talked about Security and Risk, CRM, Data and Analytics, all growing in excess of 25% from a CAGR perspective over that time frame. And you'll continue to see us invest there. CRM, we just announced a small acquisition, very small tuck-in of agentic capabilities to easily deploy CRM in new customers. So if you're able to take down implementation time in CRM from on average 12 months to 18 months to 3 months to 6 months. Well, that drives huge value for customers and is a competitive differentiation. So you'll see us continue to lean in on CRM, Security and Risk. I talked earlier about, again, customers' perspective on the most important thing to scale deployment of AI being all around Security and Risk.

And so you saw us do the acquisition of Veza. You saw us do the acquisition of Armis, which closed 3 weeks before Mythos, right? That should tell you a little something and the ability now for customers to really end-to-end manage AI deployment in a Mythos world. And our Security and Risk business prior to that crossed $1 billion back in Q3 of last year. And so add on now Armis and Veza and continued organic investment in our Security and Risk business, that should show you how important not only is AI, but all of those other pieces to the puzzle. But it all comes back to the strategy of being the AI platform for business reinvention across the board.

Right. Yes. So we should probably be approaching $2 billion here soon with the addition of those?

Yes. We're a top 10 security vendor, fastest-growing top 10 security vendor. And I think that's actually something that's under-known. And so that's something that we've been talking about a lot now.

Well, yes, let's dive into that a little bit. I mean, as you think about that scale, the growth rate, but also the product portfolio, obviously, you're not approaching this from a traditional security standpoint, selling firewalls or things like that. But like a, what gives you the right to win should we expect to see more M&A in this category? And like, yes, how big of an aspiration is this?

Yes. I mean I think at the end of the day, it goes back to what's really important and what's top of mind for CEOs, for Boards, for CISOs, for CIOs. And it's AI-first. And when you talk AI, you cannot talk AI without talking security and risk, right? And so the ability to really end-to-end have a security journey where most vendors are able to detect and alert. But we're able to detect, alert, reason what we should do about it next and then act on the resolution, all end-to-end, right? And so you have with Veza and Armis, right, you have the visibility piece, you have the identity and access and privilege controls and then you have the ServiceNow platform that enables resolution once something is highlighted. And so the ability to do that, the ability to build that security risk into AI Control Tower enables AI Control Tower to be stronger than ever.

It's just -- it's a continuation of what we believe is the most important thing right now on the minds of any CEO, any CIO, any CISO, any Board. And so we're very excited about that, what we've been able to build. I'm super excited that the M&A has gone so well. Armis will tell you that as CEO, they're closing deals so much faster being under the ServiceNow umbrella than a small private company. And most importantly, the conversation with the CISOs and the CIOs, not only are we selling Armis and Veza, it's pulling the core and not just the core Security and Risk products, but ITOM. And our IT portfolio, the core is actually being pulled as a result, which I think is really, really, really strong M&A, not only is able to drive the incremental revenue of the company you buy, but when it's able to pull the core along with it, it's pretty fantastic. And so that's what we're seeing.

We've talked about the fact that we're not looking at large-scale M&A. We feel really good about what we've had in this space. We never say never, but the hurdle rates are always high with us, right? We are able to, within a year, offset any dilution from that acquisition. We were able to integrate the product portfolio within months and driving very strong top line because we're able to really push these incredible products that are very adjacent to what we're talking about with our customers into our strong go-to-market pretty quickly. So excited about what we've seen so far and as well as what's to come.

I think Bill commented that the Armis acquisition was like buying an Instagram at the time.

Well, it's interesting, and then Mythos happened right after that. And so again, it goes back to when you really think about any acquisition and you want to drive real shareholder value, it has to start with the customer. You're not going to drive shareholder value if you're not driving customer value. It goes back to what do customers need, what are customers asking us for. And when they literally tell you for 2 years, security and risk, security and risk in AI world, and we bought some incredible assets, and it's resonating extremely well.

Yes. Great. And I guess you touched on kind of the high-level M&A philosophy, no major transformational deals. Tuck-ins, there's some stuff going on in CRM. Like what other focus areas would you say are topical in terms of M&A?

Yes. Well, M&A, I was talking specifically, you asked me about security. More broadly from an M&A perspective, I'd say our philosophy is unchanged. So first and foremost, we are an organic innovation company, right? That is the DNA of who ServiceNow has been and will be from the founding of Fred, right? And you will continue to see that. So organic innovation, first and foremost, we are incredible at that, and that will always be primary.

You've seen us do tons of small tuck-in of talents and capabilities integrated into the platform. You'll continue to see us do that. A tuck-in at our scale today probably looks a little bit different than a tuck-in 3 and 5 years ago, right? Arguably Veza and Moveworks, tuck-ins, a little bit larger, but tuck-ins.

We continue to do share buybacks, right? So return of capital. We started that a few years back. We did $2 billion in Q1 alone. We've got $4.2 billion remaining. So we're super focused on capital allocation across the board. I'd say the one thing that might be different is that the technology landscape is shifting so quickly and the ability to think you can build everything organically and not maybe do a little bit of M&A probably is a little bit different today than in the past. But what isn't different is the high bar that we will always think about. Number one, first and foremost, can we build it ourselves better? Number two, is it accelerating our road map? And does it really drive something of value to customers? The bar is super high from a financial perspective. Does it really drive customer value? But at the end of the day, the philosophy has not changed, and you'll continue to see us do more of these tuck-ins. You'll continue to see us do more focus on capabilities, but we wouldn't be doing our job if we're not looking at the market, but nothing has changed significantly from how we're thinking about it.

Yes. One of the questions we often get from investors just about software in general, but also ServiceNow specifically is as we see the AI kind of drivers of these businesses hit mainstream, does that drive an overall revenue acceleration? And I think for you, I mean, clearly, you're at a massive scale. Your growth rates pre-AI were best-in-class for the scale. But if I look at your long-term targets, we don't really see -- we kind of see more of a sustained growth versus an acceleration. So is there something -- is there some offset to that AI? Or should we just think about that as being prudent? And obviously, you gave those targets in May when we were in a different environment? Or can there be a reasonable scenario where AI does accelerate the top line?

I think there's a reasonable assumption that it could. I think that -- I argue you're seeing it already in that most companies at our scale would be decelerating at this scale in large, and you're not really seeing that, right? And so part of that is because AI is offsetting that and accelerating. There is prudence. I talked about there's some real conservative assumptions in the model. And there's definitely the ability to really have AI supercharge the numbers. I think at the end of the day, time will tell what that looks like, but if we really think about the ability to agentify these billions of workflows and really drive that consumption flywheel, there's absolutely upside.

Yes. Got it. And Gina, maybe in the last minute or 2 here, if you are sitting in the seat next year, which we hope you come back and we get nice weather in September, too, what are the one or two areas that you want to be able to sit here and say these were the top two things we executed on and got right?

Yes. I mean, listen, we have to get AI right, right? So the continuous innovation, the ability for these L1 Specialists to go more broad and really do more complex workflows, huge area of focus for us. And so we've got to get that right. What I'd say is I think you've seen us execute pretty darn well over the last few years, and we'll continue to do that.

The other thing I'd say, really excited about the fact that AI gives us the ability now to really think about the mid-market and SMB in a different way. And so we're going to be announcing in the back half some AI-native products to help serve those markets, mid-market and SMB with a much lighter go-to-market touch required that we're very excited about. And so I think that's something that's super exciting. I can't just pick one or two, though.

And then the other couple -- I talked about it, continued execution on the M&A that we've done. We've seen such incredible traction with the customers and how do we continue to execute there and continue to really drive Security and Risk, Data Analytics, CRM, they're incredible growth trajectory product lines for us. And that's the ball game. If we can execute all of those in a great way, I think you're absolutely correct that $32 billion is just scratching the surface of what we can do.

Awesome. Well, we look forward to asking you why its $40 billion next year get one up to [indiscernible]. Gina, thanks so much. Appreciate it. Thanks, everyone, for joining packed house. Thanks.

Okay. I think we're live. Welcome back, everybody. I'm still Brad Zelnick, Deutsche Bank Software Equity Research. And for this session, truly delighted to be joined by none other than the Chief Financial Officer of ServiceNow. That's Gina Mastantuono. Gina, thank you so much for being here.

Thank you so much for having me, Brad. Happy to be here. Good to see everyone.

Always good to see you. It's always good to see you in Southern California.

Yes. Although, it's super hot down here right now.

Although super hot. So I don't think you need really much of an introduction. But I want to jump in. When I think of ServiceNow, I often think back to the founding of the company. I think about your founder, Fred Luddy, and the platform nature of what he built and how it's endured the test of time. Can you just help us bridge from the past into the future, why are you so confident that ServiceNow will continue to lead in the AI era?

Well, listen, I think, first and foremost, Fred is just an incredible founder, incredible human being. And he built this incredible platform, one data model, one architecture, one platform. 20 years ago, people didn't know what a platform was, so funny, right? And so they're like, "Platform? What's the platform? Give me a use case." And he was an IT guy. So he gave the most important IT use case solving the problems of the people that he works with every day. And from there, we built out, right? Because our customers saw that this incredible platform that was amazing for IT and had great workflow capabilities was able to do the same thing across the enterprise, whether you're in HR, customer.

And so we've been customer-focused even from the beginning. And AI just makes it even more important to have a platform that drives incredible scale and workflow. And so we're really excited about continuing to build out this platform that he built for us. Fred is still on our board, and he's just an incredible human and leader. And in an AI world, autonomous work is more important than ever. How do we automate this work? So we have billions of workflows on our platform, trillions of transactions each and every year. And now how can we help our customers automate them even more in an AI world. We have the context. We have the data. We have the rules and rails to manage it all in one platform with ServiceNow. And so it's why I'm so excited about the future and AI just makes it -- makes ServiceNow even more applicable.

Excellent. And I just learned recently that Fred is a real tennis fan, which makes me like him even more.

He is a huge avid tennis player and tennis fan. That is true.

Awesome. Well, a tip of the hat to Fred. Maybe just turning to the exorbitant amounts that customers are spending on AI, headlines of enterprises blowing through token budgets, investors have really been concerned about AI spend crowding out other spend. To what extent do you think this is really happening? And is this something that we should think of as a net tailwind or headwind for ServiceNow or perhaps neither?

Yes. Listen, I think the headlines are accurate. I talk to CFOs, my peers, every single day, and all of them are talking about how do they manage their token budgets going forward. So it's real. People are spending. Listen, Anthropic and OpenAI have huge revenue numbers. So we know that folks are spending. The question I get often is, "Is it taking away from your budget?" And I would -- and our customers spending less elsewhere as a result? And I'd say there's probably some customers that are spending less in other areas because of their token spend. What we're seeing though, specifically in ServiceNow more directly, is that while they might be spending more in one area, if they're really seeing value from a product.

And even internally, I'm spending more on tokens, but I'm still leaning in with my software providers and spending more with the ones who are building incredible AI into their products. And that's what we're seeing with our customers. And so what I say is when you're able to drive real time-to-value quickly in this market that we find ourselves in, we're not seeing a crowding out of spend. And in fact, what we're seeing is a lot of companies seeing incredible productivity as a result of the AI that they've been investing in. And so they're able to tap into the labor pool much more broadly and really find dollars there. So ServiceNow, a great example.

We're growing our top line. Q2 was 23%. So above 20%. We're keeping our headcount flat this year, and this is after absorbing M&A. How are we able to do that? Because we're seeing $500 million worth this year alone of AI efficiencies, which allows us to not increase our headcount, right? But still growing at 23%. And so we're seeing a lot of customers lean into a labor pool dollar budget for spend. And so it's why we've been able to continue to see great growth. And you continue to see -- we talked about our AI business crossing $1 billion in Q2, well on its way to the $1.5 billion guide we gave for the full year. And so that's not a business that's being crowded out. That's a business that's, I think, thriving.

I don't know about you. I think you're going to blow past that $1.5 billion, but I don't expect you...

Don't guide me. Don't guide me up. But I feel very good about our numbers. I feel very good about our numbers.

I would never do that to you, Gina. I have to think, Gina, this has got to be perhaps the most demanding time to be a software company CFO.

No. This year? Come on. What's going on?

But you are the CFO of a leading technology company. We're in the midst of a paradigm shift here that -- and I'd be curious to get your thoughts on how that changes the way you think about allocating capital, where the future just seems far less certain and things are evolving so quickly.

Yes. I think -- I don't think the future is that uncertain. I'm very confident in ServiceNow's ability to make this transition, and you're seeing it in our numbers. You're seeing it in our product portfolio. And what I'd say is that -- I think it's a trying time in general in software. But the narrative, I think, is starting to shift in that the real value is in the system of action, the orchestration layer, the ServiceNow platform that has the 20 years' context. It has the data, right? In an AI world, you need data, you need AI, you need the reasoning and you need the workflow altogether to be able to go end-to-end to not only understand what the issue is, but then understand, detect, alert, and then remediate response.

And so I'm excited about what the future holds for ServiceNow, number one. Number two, to your question specifically on capital allocation, I think it's not that complicated for us, right? So we've been, first and foremost, always have been an incredible organic innovation platform company. And that has not changed. That's in our DNA from Fred, from -- like across the board, we are -- we will always be an organic innovation center, and that doesn't change. So #1 priority for capital allocation is always going to be on organic growth and organic innovation, first and foremost.

You'll then see us do the tuck-in type of M&As, the talent acquisitions that we've always been doing. Listen, as we scale up, sometimes those tuck-ins are scaling up, right? And that talent, especially for incredible innovation and incredible products, it's a little bit more expensive right now. It just is, right? And then third, we are very focused on shareholder value always. And so we did a $2 billion repurchase in Q1. We've got $4-plus billion left in authorization. And so you'll continue to see us think about making sure that we are really focused on capital allocation top to bottom.

And I'm always reminded what Bill has always said that organic is delicious.

Delicious.

Yes. We -- I tend to agree. If I could take us back to Financial Analyst Day, which seems like a long time ago, but it really was only a few months ago. Your targets imply both sustained growth at significant scale and substantial free cash flow margin expansion from where we are today. What are the 2 or 3 operating assumptions that matter most in achieving the base case? And what would need to develop for ServiceNow to reach the upper end of the range faster?

Yes. So a few things. So we were actually a bit conservative in our numbers because back in May and even now, I don't think -- I'm not going to get a whole lot of credit for being overly aggressive. And so there's actually an amount of decel in our core just because of the law of large numbers. But more importantly, there's incredible growth assumptions in there on our AI business and then our 3 other key growth vectors. So security and risk, data and analytics and CRM. We talked about at Financial Analyst Day that all 3 of those portfolios would be growing in excess of 25% over the 3-year period. And that's with AI infused in everything.

We also talked about AI being at 30% of our product -- of our revenue by 2030. If you think about $1.5 billion this year on almost $16 billion, so 9.5% going to 30% over time. And so AI is a huge part of how we think about growth in the business, and we are continuing to see incredible traction I talked about earlier. You said I'd blow out. I said I'm very confident in my numbers. And as we think about infusing more and more AI into our products, I think that, I think, could be a hockey stick to help achieve us even faster. We talk about security and risk. You see the market right now and the importance of security and risk, always important, even more so in the world of AI. And we've done a lot on acquisitions in that space because of it.

When we announced the acquisition of Armis and Veza, we got the question, why? And at the end of the day, it goes back to our theory and our thesis always on what our customers want and where our customers are taking us. And the customer said for 2 years, the biggest obstacle to scale deployment of AI in the enterprise was all about security, risk and governance. And so we had an incredible security business that crossed $1 billion in revenue in Q3 of last year, but it was only a piece, right? And so now the ability -- other companies detect and alert, now our ability to detect, alert, decide and remediate all in one platform, end-to-end security journey for our customers in an AI world, it positions us incredibly well in a space that continues to grow fast and is a top priority for every Board and every C-suite, every single company.

And so $30 billion to $32 billion were the numbers we gave. I feel extremely excited and confident about achieving those numbers. And remember, when Bill and I started here 2019, November 2019 for Bill and January 2020 for me, in that first Investor Day, we talked about hitting $15 billion by 2026. We're going to close at $15.8 billion. And even if you take out some M&A, it's like $15.6 billion, pretty darn good. And so I think we have a really great track record of doing what we say. And I think the innovation that continues to be built within this company is stellar and top-notch. And we're well on our way to hitting the 2030 goals.

Awesome. I want to dig in more into some of the products, some of the market opportunities.

No, I didn't think you'd go there at all.

Before I do, though, I want to just touch a bit on the migration opportunity, taking existing customers up to greater bundles and higher-end SKUs that they can take advantage of all the platform has to offer. So just how should investors think about the opportunity within the base, including the pace at which customers move to Prime, the durability of the initial uplift and the incremental consumption opportunity once more AI use cases are deployed in production?

Yes. So I think the standardization -- so what we've done with the standardization of our AI native bundles, I think, is going to be really helpful for the market. And what it allows our customers to do also, it allows them to have a different journey depending on what phase they're in, right? And so you could start off really, really light with some basic AI capabilities and you can get them really fast. You don't have to jump to the hugest price uplift up there, especially if you're not ready. And even in that base package, you get the Moveworks front door, you get really nice AI capabilities that allows people to kind of feel their way in an AI world, right?

But at the end of the day, if you have a customer that's more advanced and wants to go faster, they have the ability to upgrade to Prime pretty quickly. And so what we really wanted to do was give choice to our customers. And what we're really trying to do is even folks that are the most price-conscious to give them some AI capabilities because at the end of the day, AI is going to be everywhere. And customers who have no AI are really not going to be successful. So we really want to help them at least get kickstarted on their journey.

We're continuing to see upwards of over 30% price uplifts in the Prime bundle, which was our Plus SKU, so our most advanced of the AI, and between 20% and 30% in the other packaging depending on how they bundle it. And so we're really excited about what that's going to do, not only from a consumption perspective because the more people are using AI and the more they increase their usage, the more the flywheel of consumption will continue to kick in. So it's about driving value for customers. It's about driving enormous consumption. And so, so far, so good.

Excellent. You're well on your way. Maybe we can pivot more into product. When we think about Control Tower, I mean, massive opportunity. I get asked this question a lot. I think I know the answer, but I want to ask, kind of, you because I think it would be great for everybody else to hear you describe it. The question often gets asked, what is ServiceNow's right to win the AI governance layer with Control Tower because you've got so many other vendors out there from various positions seeming to close in on it from multiple angles, including horizontal app vendors, infrastructure and even security -- stand-alone security providers, even the AI labs themselves. Make it very clear for us.

So it goes back to this incredible platform that's ubiquitous across the enterprise, right? So whether you're using us for IT, HR, finance, legal, customer service, you name it, the platform is the same, right? And the ability now to connect to any model, any hyperscaler, any software provider, any data model, any data provider and to be able to manage it. So we're agnostic, right? And by the way, our customers want to be able to move between. Most of the customers are not using only one, any of the things that I just named. And so the ability to connect to any data model, any software, any agentic AI agent and manage it all in one place. Well, that's historically what we've always been able to do. We've always been vendor-agnostic, data agnostic.

And so the ability now to manage it all in one place, no matter where the information is coming from or what underlying platform you're using, it's kind of the legacy of who ServiceNow has always been. And so you asked the question before about token maxing and these budgets. Well, the AI Control Tower -- and by the way, when I talk to CFOs, I can manage spend across every vendor, every AI vendor. And more importantly, well, as importantly, to managing the spend is actually seeing the ROI. And so the ability there and the AI Control Tower to see it all, to manage it all and then, even more importantly, govern it all, right? Kill switch if something is doing something that shouldn't do to really be able to manage that across.

I think that's unique to ServiceNow. A lot of people can do it vertically in one place, in one stack, in one area. ServiceNow can do it across the entirety of the enterprise. And so when we have those conversations with customers, when we show them the product, it's an immediate like show me more and how can I get this tomorrow.

Awesome. Gina, I want to turn next to cybersecurity. And I did just add this to my list of questions because cyber stocks are ripping, but I think people may not appreciate. ServiceNow has one of the largest cyber businesses literally in the industry. Can you just walk us through like where it's been, how Armis changes ServiceNow's strategic position with the Chief Information Security Officer and why combining asset intelligence with Control Tower creates a better-together opportunity?

Yes. So we talked about in Q3 of last year, the fact that our security and risk business had crossed $1 billion in CACV, right? So a large business to start with. Then you add Armis and Veza on top of it. We are actually a top 8 security provider in the world. I think that that's not really understood.

To your second question on how do Armis and Veza really drive even, I think, more value, it's a couple of things. So first and foremost, I think this is a great example of M&A done brilliantly, if I say so myself, and I will. I don't do that often, but I will. First quarter of owning them, they overachieved their plan significantly. But more importantly, than them just overachieving their plan, they're pulling the core, right? So our security and risk business also overachieved.

And it's not just security and risk, it's pulling our CMDB and our ITOM business as well. And why is that? It's because you have the entirety of the customer journey with security in one platform, right? Some companies detect and alert. We can now detect, alert, decision, remediate all in one place. And so the importance of security post-Mythos in an AI world is more important than ever before.

And so now our customers have one place where they can really get the alerts, understand them and then remediate them. We've always sat on top of other security providers. So it's not like we're going in and taking out. This is an incremental budget that we're seeing. And then you combine that with AI Control Tower and the ability to manage everything in one place, it's just a very compelling value proposition for our customers, especially today.

Awesome. You mentioned earlier data and analytics as another key opportunity. Not something that I was thinking to ask you about, but since you mentioned it, why don't you share for us why that's so exciting and how it's going to drive the next few years?

Well, I think if you think about what's really required in an AI world, it's a few things, right? It's data. It's AI and the reasoning and the intelligence. It's the workflow to actually drive action on that data and intelligence. And then it's the governance and security wrapped all around it. So if we're really trying to provide the full value to our customers, data is a clear piece. We've got the AI. We've got the workflow for sure and the security. Data is increasingly important. And we've talked about Workflow Data Fabric. We've talked about data action and the ability to connect to your company's data and again, agnostic of platform, right?

We've got the connectors that enable this very seamlessly and the ability to use that data no matter where it is in an organization. And this, I think, when you connect data to everything else, it not only ends up being a productivity delivering machine AI. But it's -- I think that's how you reflect top line as well. Like what's the data in the market telling you? How do you think about things? And getting at the speed of machine and then actioning it throughout your organization immediately, it's a top line and an efficiency play. And so we're really excited about our data and analytics. It's growing extremely well. And yes, the ability for our customers to connect to any data no matter where it is, is a huge selling point and something that they're very focused on right now.

Got it. I'm going to pull on one other thread that you touched on earlier, which is CRM. And I mean, there's another small company last night that coincidentally reported and put up exciting results. But -- let's make it about ServiceNow. Can you just bring us up to speed? I know you guys acquired Logik.ai. I think that's a year ago or so.

Yes, a little over a year. Yes.

Which was -- we always knew to be the best in its category in the market. But where are we in the journey? And what can we expect ahead?

Yes. Listen, I think at the end of the day, hopefully, the narrative is shifting, right? ServiceNow had really strong results. Other software companies also having strong results. The narrative is shifting, right? The value is not in the intelligence. It's important. The reasoning is important in an AI world. But the context and the domain expertise that software providers have is more relevant than ever in an AI world. So that's number one.

CRM specifically, in that acquisition of Logik.ai that we did a year ago, CPQ, phenomenal AI-first technology. And if you think about ServiceNow's, I think, history in really helping our customers manage the most complex workflows, CPQ is arguably the most complex workflow in the whole CRM stack. And so the ability to have such incredible products then connected to not only the CPQ process, but the sales and order management and servicing, you have one-stop shop on one platform where you can really -- you can quote, you can fulfill and you can service all in one place. And so what CPQ did for us was make us even more relevant in the front office conversations.

We talked about the fact that our CRM business in totality crossed $2 billion and continues to perform extremely well. So we remain extremely excited about that product portfolio, the resonance. I actually had a conversation just last week with the CFO of a great company that's looking at closing our CRM deal in the next day or so. And so again, the ability to really sell, fulfill and service all on one platform with modern architecture is a definite compelling conversation that we're having with customers every day.

I think all investors are really hungry to see AI come to life and really get their heads around tangible use cases. What are some of your early adopter Lighthouse, Now Assist customers doing with AI today? And what steps did they take in the early days that have enabled that success?

Yes. I think that the Lighthouse customers that started early with us are just -- they're in prime position, right? They cleaned their data. They have simplified their stack. And they're really leaning in on, for example, our L1 specialists. So we have the City of Raleigh that leaned in heavily. They implemented our L1 specialist with no back-end engineering big workload having to do. They're seeing 98% accuracy and they're able to autonomize -- so autonomous 65% of the request, zero-touch, 65%. And this is in a 10- to 15-week time frame. So really, really fast. And it's one use case.

And so now they're looking at going much more broadly across the platform, which is really exciting. We have another customer that we did a 10- to 12-week pilot with a few of our FDEs, and we were able to very quickly in 12 weeks, drive over $5 million of efficiency benefits with one use case with our L1 specialists, right? And now they're looking at -- and by the way, a lot of the companies, they're starting pretty small at complex but less risky use cases to get the proof points, and now they're going much more broadly.

And so it's extremely exciting. Right now, we're seeing EmployeeWorks, which is our Moveworks product portfolio, combined with our historical employee service portfolio. And we are building out now efficiency experts and productivity experts for legal, for finance, for HR, for customer service that really helps any person within that domain function drive incredible productivity. And so it's -- the use cases are endless, and it's really, really exciting to see.

And what you're seeing from a customer base is that even those customers that were slower to kind of lean into the AI moment are very, very quickly wanting to understand what they can do and how fast they can drive really incredible value. And so there's definitely a shift happening that it's not just the top 100 customers, but even the ones that historically were slower to adopt AI are really leaning in very, very fast. And so I think the next few years are really exciting time for software.

The future is bright. I agree with you.

The future is bright.

Gina, in terms of the other opportunities, if I reflect back on the past, I mean, many years ago, I think even predating your journey at ServiceNow, we were so focused on counting Global 2000 customers and what the penetration was and your track record and presence in the largest of enterprises and the largest of governments everybody is very familiar with. And more recently, if we listen to Bill, I think Bill was quoted as saying that now is the time to address the Fortune 500,000. Why? What does that mean? Why is this now the moment to maybe look a little bit further down market and address that opportunity?

Yes. I think a couple of things. So first, we talked about our legacy and where we've come from, right? And we have been very customer-centric. We're an incredible culture. If you talk to anyone who's ever even worked at ServiceNow or walk down the halls of Knowledge, the culture of ServiceNow is pretty amazing. And part of that culture has been customer first, customer obsession. And so our customers have always been the Fortune 500, like the enterprise and commercial plus, our products were built for that, right, at the end of the day. And there was so much opportunity to expand horizontally into HR, into customer service, into finance and supply chain that we were really focused there on serving our customer base across the enterprise.

Well, today, we're at an inflection point. And as we think about trying to serve other customers in other markets, it just felt like the right time, right? The ability to build a product that is much more suited for the small and medium businesses is easier than ever. And with ServiceNow's context and history and understanding of the workflow and understanding of how companies get work done, we're in prime position to do just that. And so you'll be hearing pretty soon about an incredible product that we're coming out with to serve that customer base that we are extremely excited about.

Awesome. Very, very cool. Another opportunity, I don't -- I want to make sure I don't get over my skis. As we think about U.S. Federal, am I too aggressive to think that there's an inflection point where agencies are standardizing on ServiceNow, viewing AI as a core way to modernize and capture cost savings?

You're not. So that's exactly what's happening. There's such a great opportunity because so much of the agencies have so much opportunity to modernize. And you've seen us our success in that area is because our platform and our product portfolio is so well suited for them. Add AI into it and the ability to drive even more incredible efficiencies and labor productivity, it's right in the sweet spot. And so we're very excited. We talked in Q2 about overachieving the plan in Q2. We're set up for a very successful back half. Pipeline looks good.

And then more broadly, the longer-term opportunity in Fed is enormous. And then even more broadly, public sector, right? What we've done in Fed is absolutely replicable across every other government across the world as well as within state and local in the U.S. And so you'll continue to see us push in that space, and you'll continue to see us -- you'll continue to see that vertical be a pretty significant growth vector for us.

This is the time of year, at least here in the U.S.

It's true.

So looking forward to great things ahead. We are just about out of time for this session. But Gina, what haven't we maybe talked about that investors might still be underappreciating about ServiceNow today?

Yes. I'd say a couple of things. So I mentioned it earlier, but I think it's really interesting, and I've been -- it was part of our thesis, our acquisition thesis for sure, but the fact that the acquisitions that we've been doing, not only being very successful, very early days as we've acquired them, but they're pulling the core more broadly across the board. And I think that, that is -- that was underappreciated and it still is. We're starting -- we're trying to talk about it because it's -- as people keep saying, "Oh, is the core starting to decel?" Well, actually, we're building incredible AI innovation into our core. And then we're doing, I think, really smart acquisitions that build out the product portfolio that pull the core with it.

And that, I think, is probably a little bit underappreciated.

The second thing I'd say is that we have 6 unicorn business that will be bigger than $1 billion, all built within ServiceNow, right? And so I think that's a little bit underappreciated. We talked a little bit about the security and risk being part of it. But we have 6 businesses that we've basically organically built from scratch that are over $1 billion. And I think that's pretty -- that's a testament to the DNA I talked about earlier about the organic innovation, that will always be who ServiceNow is. And then lastly, I would say I talk about Now on Now quite often, right? I like to say we drink our own champagne, and we do. We are customer zero, almost every single product we put forth.

And so our own platform and Now on Now internally has enabled us and is driving $500 million of efficiency savings this year alone which enables us to grow our top line and drive incredible efficiencies and keep headcount flat even though we're acquiring some companies this year. And that efficiency is only going to continue to expand. So when we talked about the targets we put out for FAD, it wasn't just $30 billion and $32 billion. We said we'd be a Rule of 60. And that's because we're seeing real accretion on the bottom line because of the efficiencies of our own AI products that we're using internally.

Like we are the best reference for any customer conversation, which is why when I talk to customers, when my finance teams get to talk to customers, my finance teams love that because it's another area of growth for them because they can show how even within finance, we're able to use the ServiceNow platform to drive incredible productivity. Our HR teams, they talk to customers all the time about the incredible products that we use internally and the value creation that we continue to see. And so that's just going to continue to expand. And I think it's one of the reasons why ServiceNow remains extremely relevant in an AI age, and I think a leader in the space.

That is amazing. Gina, it's always great to see you.

Likewise.

This was fantastic. And I really appreciate you being here.

Thanks so much. Thanks, everyone.

Ladies and gentlemen, thank you for standing by. My name is Krista, and I will be your conference operator today. At this time, I would like to welcome everyone to the ServiceNow Second Quarter 2026 Earnings Conference Call. [Operator Instructions]

We will now turn the conference over to Darren Yip, Senior Vice President, Investor Relations and Market Insights. Darren, please go ahead.

Good afternoon, and thank you for joining ServiceNow's Second Quarter 2026 Earnings Conference Call. Joining me are Bill McDermott, our Chairman and Chief Executive Officer; Gina Mastantuono, our President and Chief Financial Officer; and Amit Zavery, President, Chief Product Officer and Chief Operating Officer.

During today's call, we will review our second quarter results and discuss our guidance for the third quarter and full year 2026. Before we get started, we want to emphasize that the information discussed on this call, including our guidance, is based on information as of today and contains forward-looking statements that involve risks, uncertainties and assumptions. We undertake no duty or obligation to update such statements as a result of new information or future events.

Please refer to today's earnings press release and our SEC filings, including our most recent 10-Q and 10-K for factors that may cause actual results to differ materially from our forward-looking statements. We'd also like to point out that we present non-GAAP measures in addition to and not as a substitute for financial measures calculated in accordance with GAAP. Unless otherwise noted, all financial measures and related growth rates we discuss today are non-GAAP except for revenues, remaining performance obligations, or RPO, current RPO and cash and investments.

To see the reconciliation between these non-GAAP and GAAP measures, please refer to the earnings press release and investor presentation, which are both posted on our website at investors.servicenow.com. A replay of today's call will also be posted on our website.

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

Thank you very much, Darren, and thanks, everybody, for joining today's call. I looked at the transcript from an earnings call 7 years ago. And back then, we said ServiceNow would be the defining enterprise software company of the 21st century. I thought I'd give you a report out since then, we beat expectations in every quarterly report, expanded the profitability and free cash flow of the company, quintupled our total addressable market, accelerated 6 of our own unicorns to $1 billion or multibillion-dollar businesses, process billions of workflows and trillions of transactions grew the partner ecosystem globally architected the most complete AI control tower for the enterprise, maintained our best-in-class renewal rate, increased our brand value, offered our customers deep enterprise context, unlimited choice and differentiated capabilities. And of course, we set a course to $32 billion in revenue in 2030 operating at the rule of 60 and beyond.

So today, we're adding a stunning Q2 print to this track record. Subscription revenue growth was 23% in constant currency, 1.5 points above the high end of our guidance. CRPO growth was 21.5% in constant currency, more than 2 points above our guidance. Operating margin was 29.5%, 3 points above our guidance. We had 123 deals greater than $1 million in net new ACV, up 40% year-over-year.

ServiceNow AI ACV exceeded expectations again surpassing $1 billion, keeping us on track to beat our target of $1.5 billion ACV by the end of 2026. We're feeling real good about it. What does it all mean? We are who we said we were. The path to value isn't just making AI. It's deploying AI securely across the enterprise. IDC forecast spending on AI software is going to grow 53% this year, 17% faster than AI hardware whichever chip wins, whichever lab wins, which ever price per token regime prevails, the enterprise needs one governed layer of record, full work and ServiceNow offers needed certainty in an uncertain stack.

Our platform is optionality on all AI outcomes, not a bet on anyone. We're in the bull's eye of AI, cybersecurity, workflow orchestration, integration and automation. That's why we're growing fast -- it's why we're only just getting started. We are who we said we were. Over the past several months, we've addressed a number of really good questions during meetings with investors.

Today, I'd like to give every investor the professional courtesy of those exchanges. One question we regularly get is ServiceNow becoming a cybersecurity company. Here's the answer. ServiceNow already was a $1 billion plus cybersecurity business. Today, our risk and study business is the fastest-growing of the top 10 cyber companies in the enterprise. I'll make it very clear. We now have a 10 figure, cybersecurity business that's growing faster than all the other top cybersecurity companies. We're building the world's most integrated end-to-end security platform across cyber, risk and compliance, agentic incident response, exposure management, identity and access security, cyber physical security and continuous vulnerability detection.

The security stack sits on top of our ITSM and ITOM core infrastructure. So think about it. AI control tower plus Armis plus Vesa. Our customers want every AI enterprise to be visible, governed and secured in one command center. Nation third-party -- they don't want any blind spots. There's 2.2 billion agents entering the enterprise globally. That's 2.2 billion new identities, 1/4 of today's human population. Vasa maps access across human, machine and AI identities. We'll have 40 billion connected devices in the world in the next 4 years.

Armis already tracks 7 billion of those devices in real time. Many customers, especially in the public sector seek out Armis because government policies require state-of-the-art visibility. The attack surface is excluding every ungoverned asset and identity multiplies the blast radius. When you integrate awareness and identity with the actionability of the ServiceNow platform, you have a complete 360-degree capability to secure the enterprise. It's highly telling that the AI control tower is already gaining traction with our partner ecosystem.

In fact, one global services firm is leveraging this portfolio to help their clients rapidly triage their cybersecurity activity. They're hunting down problems with ServiceNow and the others are rapidly following suit. So once again, this is the eighth largest cybersecurity business in the enterprise and the fastest growing, and we are just getting started.

Another question we get is when will customer deployment of AI Mark an inflection point for ServiceNow's growth. Here's the answer. It already has. The percentage of renewal customers purchasing a genic AI for the first time, doubled quarter-over-quarter and year-over-year. So customers that weren't already on the AI journey are signing up fast. Most customers are now completely allergic to anything that looks like a project. They only want deterministic.

ServiceNow only does deterministic. That's a big reason why customers with agentic AI in production have grown 9x over the last 9 months. So here's a few of many examples. The Department of Air Force is expanding its use of the ServiceNow AI platform. The deployment will unify IT operations and enterprise visibility. Experian is using ServiceNow to automate intelligence at scale. We will also integrate our platforms, embedding experienced data and decisioning into existing ServiceNow workflows in a 5-year deal and many deals are going longer, you should see that in the CRP or in the RPO, by the way.

Maybank, Malaysia's largest bank we'll leverage ServiceNow to establish a resilient operation center to fortified security and resilience. The U.S. federal government's largest IT contractors and agencies are now consolidating asset discovery and security response on ServiceNow. One agency is using Armis to move from asset blind incident response to comprehensive threat hunting. Hitachi will standardize enterprise asset management across its global businesses on ServiceNow. Additionally, we're partnering with them to advance the Hitachi Intelligent Infrastructure monitoring solution.

The city of Raleigh became the first local government to deploy ServiceNow's L1 AI specialists in production with no in-house AI engineering bench behind it. That's right. It's on its own. The city is moving to become fully autonomous 1 ticket category at a time. Many enterprise customers are at various stages of the same journey. They are progressing from supervised to autonomous operations. a large global consumer good company partnered with ServiceNow to launch its first agentic AI use case in ITSM to triage workflows.

The customer rapidly deployed a repeatable governance first, Blueprint for future Agentic use cases, a leading global food and beverage company found itself with AI agents proliferating across 5 platforms simultaneously with no unified way to govern them. Their CTO has a mandate, no agent goes live with our clearing governance, risk, value validation and observability. AI control tower went live this spring. They can now see in real time who was building AI and whether it had been approved, the value for them was immediate.

It's worth highlighting, IT operations management continues to be a source of strength to ServiceNow extending its outperformance in Q2, with attach rates to ITSM continuing to rise year-over-year. Our CMDB gives customers a trusted system of record for their infrastructure, applications, services and dependencies. ServiceNow delivers the intelligent layer and the infrastructure it runs on. We also get asked is ServiceNow gaining traction in the CRM marketplace. Here's the answer.

The market participants in the enterprise are very good. They're really good companies. And let me be clear. They're not going away. Having said that, we're doing very well. Already, we're a $2 billion ACV business. CRM NNA CV growth accelerated again on a year-over-year and quarter-over-quarter basis. Sales CRM average deal size doubled year-over-year. We're on track to execute over 2 billion service CRM cases this year, in addition, partners are increasingly positioning ServiceNow as an operational CRM platform, opening executive conversations across the C-suite. For example, in Q2, a partner closed a full front office replacement of a major CRM deployment in just 2 months, a leading North American automotive marketplace outgrew its legacy CPQ provider. It couldn't handle the volume or complexity of the business after 5 vendors fail to deliver.

ServiceNow will help their sales teams achieve the speed and accuracy to operate at scale. An American software leader selected ServiceNow to modernize a highly customized quoting environment, our ability to connect CPQ with broader workflows, customer data and service operations was a key differentiator in the win, a leading North American telecom infrastructure provider selected us to unify commercial and field operations on a single platform.

ServiceNow will scale volume 3x with no added headcount and cut repricing from weeks to hours. A regional financial institution consolidated its loan origination workflow onto ServiceNow's unified CRM platform replacing legacy point solutions. Here's the big one. Voice is the next frontier, and we're winning it. We just proved something extraordinary. A large airline has gone all in running their customer service voice calls on ServiceNow's voice AI, CRM agents. This is live in production and handling 5 million annual voice calls in year 1 alone.

The results speak for themselves. Customer satisfaction is off the charts. We also get asked about ServiceNow's role in the HR stack. Here's the answer. Employee Works as the strategic entry point for enterprise-wide employee experiences. This combines Moveworks conversational AI with ServiceNow workflows to create a single place to search, self-serve and take action across HR, IT and all workplace services as Fortune 500 customers adopt employee works, we're seeing it pull through broader HR and employee experience opportunities, a similar pattern to what's happening in the CRM business.

We get asked about the industry dynamics in enterprise AI. Here's the answer. Innovating for the enterprises like politics, as you may have noticed, it's pretty easy to make noise, hard to make progress. One of the reasons Knowledge 2026 was the biggest we ever hosted is because customers are desperate to make real progress with a proven innovator they can trust. Sessions on ITSM, ITOM and AI control tower were all oversubscribed because the influx of AI creates more activity for IT, not less.

Customers demoed our latest product releases, including new AI specialists, specialists for IT CRM, employee service and security. They learned about ServiceNow Action Fabric. This enables any agent, Claude, copilot or homegrown to tap directly into secure, govern enterprise actions headlessly. With so much of a data mess, they wanted to understand ServiceNow's context engine and autonomous data analytics which resolved data fragmentation across systems.

With interest in ServiceNow rising, our innovation velocity is accelerating to meet the opportunity. For example, we have a big announcement coming very shortly, a business model evolution that expands our TAM with AI native products. This new offering will be a conversational service desk experience. No tickets, and AI coded automation. In a new product-led motion, we're targeting the Fortune 500,000. Many of whom we expect to replace their legacy offerings and bypass the startups, stop waste and time.

We already have several customers in beta and soon will be GA. That's generally available. This is the first of many net new AI native products we'll be bringing to market in the weeks to come. Our Dynamite engineering team is on fire. Another area of real progress for customers is the expansion of our strategic partnerships. Deeper integration is ServiceNow AI Control Tower and Microsoft Agent 365, extended agentic AI governance from desktops to data centers with Project Arc and new agents secured by the NVIDIA Open Shell run time and governed by ServiceNow AI control tower.

Enhanced collaboration between ServiceNow's AI native FTEs and industry-led Accenture FTEs. There are too many to cover here. The momentum is everywhere. Here's a rapid fire round for you. Are we worried about seed compression, not at all. Our addressable user base is growing and 50% of our net new business is already non-seat-based. We keep seat-based pricing because customers prefer it for predictability, particularly now where a lot of pricing out there has been less than predictable.

Our customer is going to build their own I've yet to meet a customer who would even consider it. The best tech leaders know it will cost 5x to 10x to build an agent versus run one on ServiceNow. Has the government business, it's never been stronger. National governments, regional governments, local governments, they're all expanding their ServiceNow deployments. There are just a few questions that I hope you found useful in answering for you over these few moments we get the spend together.

For now, I'll answer the final question, why will ServiceNow get incremental share of wallet in the enterprise. I'll explain it as plainly as I can. There are many good companies in the enterprise today, and I do have respect for them all. Some that have built very strong businesses over the years, others that are new participants. They're good companies. The established companies aren't going anywhere, and I expect them to do very well based on the years of business logic and context in their platforms.

The new companies are growing fast, and they'll be disruptive to some legacy point solutions and likely complementary to the bigger platforms. There are two major factors that should cement conviction in ServiceNow. One, if you were to assess all the players out there, which of them include a system of record, deep enterprise context, fully integrated governance and auditability, a proven global distribution channel, and a flexible pricing model that includes predictable consumption and outcome-based options. I'll save you the trouble. Only ServiceNow's completeness of vision checks all of those boxes.

The second factor is pure market fit. Which of the platforms in today's enterprise was designed from the ground up to integrate to all of these players. Again, the only answer is ServiceNow. Risk at scale is why CEOs are losing sleep right now. They read all these threat headlines. They see all these platforms and token invoices and they don't know what to do. This is the gap. ServiceNow is the bridge. We're in the control business, 1 platform, 1 system of action, any cloud, any agent, any workflow any model, govern secured and accountable. This is the AI control tower enterprise leaders now know is mission-critical, enterprise execution with cybersecurity at the core of the platform and cybersecurity growing real fast.

ServiceNow is the rules and rails of the enterprise, we're in command of the agentic enterprise from workflow to cyber. Our position is real, it is durable, it is compounding. This is the foundation for a re-rating of ServiceNow. Let's get it started today. We said defining enterprise software company in the 21st century. We are, who we said we were. Thank you for your time today, for your interest and ServiceNow and for your enduring support. We'll never take it for granted.

With that, I'll hand things over to our President and CFO, Gina Mastantuono. Gina, over to you.

Thank you, Bill. Q2 was an outstanding quarter that highlights ServiceNow's broad-based demand strong execution and operating leverage. Once again, we beat the high end of our guidance range across every top line and profitability metrics. AI net new ACV growth continues to outpace expectations. Our AI control tower is supercharging our security and risk business and ITOM is seeing strong demand tailwinds for the CMDB to serve as an essential governance and data foundation. Simply put, the momentum across the portfolio continues to build and we remain on track to deliver another exceptional year.

Q2 subscription revenues were $3.877 billion, growing 23% year-over-year in constant currency and 150 basis points above the high end of our guidance. RPO ended the quarter at approximately $29 billion, representing 22% year-over-year constant currency growth with an increase in average customer contract duration. Current RPO was $13.2 billion, representing 21.5% year-over-year constant currency growth. That's a 200 basis point beat versus our guidance. Across our workflows, we saw widespread demand.

Technology workflows had 50 deals over $1 million, including $9 million over $5 million. The combination of Armis and Vesa has had a strong pull effect on our core. ITSM was in 15 of our top 20 deals. ICON had an outstanding quarter in 18 of our top 20 deals with 14 deals over $1 million, our security and risk solutions were in 16 of our top 20 deals also with 24 deals over $1 million. CRM and industry workflows were in 16 of our top 20 deals with 15 over $1 million driven by sustained momentum in CPQ and sales and order management.

Core business workflows had 12 deals in the top 20 with a blockbuster 24 deals over $1 million, driven by strong demand for employee works and creative workflows had 18 deals in the top 20 with 14 over $1 million. From an industry perspective, business and consumer services led the way with net new ACV growing over 6x year-over-year. Education posted impressive growth, surpassing 125%, followed by telco and media or nearly 40% year-over-year.

Manufacturing also delivered strong growth in the quarter. Our renewal rate was a best-in-class 98% in Q2, underscoring the durability of our customer relationships. We ended the quarter with 658 customers generating over $5 million in ACV with 32 more customers crossing the $20 million threshold since last year. As customers scale, they are consolidating more on the ServiceNow AI platform demonstrated by 18 of our top 20 deals including 8 or more products.

ServiceNow AI continued to outperform expectations in Q2 with ACV crossing over $1 billion and net new ACV growth accelerating sequentially, growing over 40% quarter-over-quarter. Deals, including 5 or more ServiceNow AI products grew 5.5x year-over-year which drove a tripling of million-dollar-plus deals. In addition, the number of customers with agentic AI in production has increased 9x over the last 9 months a leading indicator for the future consumption opportunity. While still early, we're already tracking ahead of our target for AI to reach 30% of ACV by 2030.

As Bill noted, our new AI native SKUs are making our agentic solutions more accessible across the customer base. as evidenced by deal volume amongst first-time ServiceNow Agentic AI buyers growing over 45% year-over-year. What's more upgrades to our new AID of SKUs are driving price uplift in line with the 20% to 30% framework that we laid out at our Financial Analyst Day. Employee Works or AI front door for the enterprise workforce continued to build strong momentum with deal volume growing over 150% quarter-over-quarter.

Another good example of our acquisitions amplifying the core. The robust attach rates of AI across the platform are also driving our data and analytics business. Raptor DB Pro deal volume grew 80% year-over-year again in Q2, and workflow data fabric was in 17 of our top 20 deals.

Turning to profitability. Non-GAAP operating margin was 29.5%, 300 basis points above our guidance, driven by the revenue outperformance and timing of spend, primarily in marketing. Our free cash flow margin was 16%. Together, these results continue to demonstrate our ability to drive a strong balance of world-class growth profitability and shareholder value.

Moving to our outlook. For Q2, we saw net new ACV outperform, so we're raising our full year guidance. Part of that outperformance was due to strong U.S. federal demand, which shifted some on-prem revenue from Q3 to Q2. This is simply about timing. I'm very confident in our Q3 and full year guidance. For 2026, we are raising our subscription revenues by $15 million at the midpoint from $15.755 billion to $15.770 billion, representing 21% year-over-year growth on a constant currency basis.

We expect subscription gross margin of 81%, reflecting more customers utilizing our hyperscaler partnerships as well as accelerating AI adoption. We expect operating margin of 31.5% and free cash flow margin of 35% and GAAP diluted weighted average outstanding shares of 1.04 billion.

For Q3, we expect subscription revenues between $3.975 billion and $3.980 billion, representing 20% year-over-year growth on a constant currency basis. We expect CRPO growth of 20% on a constant currency basis. We expect operating margin of 31% and we expect 1.05 billion GAAP diluted weighted average outstanding shares for the quarter.

In closing, Q2 was another outstanding quarter in an environment where most enterprises are still searching for AI's ROI, ServiceNow is the platform delivering it. In my conversations with CFOs, the question has become simple, where is the return. They've watched budgets burn on pilots that demo beautifully and never touch the P&L.

ServiceNow doesn't just deploy AI our AI control tower provides a single view to discover, govern and secure every AI system and tie every agent to a real ROI. AI that only advises is a cost AI that completes the work is a return. On our platform, agents don't just reason they take action. And because we have the contextual data, every action is anchored in the live governed reality of the enterprise. -- turning probabilistic AI into deterministic, reliable outcomes. That's how AI moves from an operating expense to operating leverage.

Customers aren't paying us for tokens. They're paying for resolutions. That's why enterprises are choosing ServiceNow to convert AI ambition into measurable ROI.

Finally, to our teams around the world, thank you. Your execution is why the world works with ServiceNow and why we are more confident than ever in the road ahead. With that, I'll open it up for Q&A.

[Operator Instructions]

Your first question comes from Gabriela Borges with Goldman Sachs.

This is for Bill or Amit, if he's on as well. I wanted to ask you about your Level 1 ITSM product cycle. I know you talked about it at knowledge and went generally available you pilot customers, all that good stuff. My question to you is, what are your options over the last 3 months? What's working with that product cycle, what's the feedback in terms of how you can make it better.

And Gina, you already have a couple of general AI data points some monetization. For this product cycle in Brazil, any nuggets you can share with us on how much customers increase spending work ServiceNow when they go through the level automation price.

Gabriela, thank you for the question. See the Level 1 ITSM product cycle has been very accelerated for us. The thing we're solving for, which we talked about knowledge, is to really have human equivalent AI specialists, which can take on the full task end-to-end without any customer having to deal with individual pieces of technology, AI agents, orchestration, the reasoning, we take out and extract out all of that work for them and customers really benefit from the outcome. And that is what's resonating with the customers today.

So we have deployed Level 1 support AI specialists as well as 20 other AI specialists inside ServiceNow, and we're starting to do that with our customers. Today, 40-plus customers are using it already getting a lot of good benefits. We're talking about closing down close to 80% to 85% of the service request without having any human interaction. As this end-to-end service request completion, not just giving you the information but actioning on those requests as well and that reduces the time.

So for example, some of these requests might take 2 days for humans to get to our result. We're doing that in 20 minutes. So the productivity gains for employees is very, very high and very superior because now they're getting the issues resolved. Why we're reducing the volume of requests required for humans to deal with, and they can now deal with something more complex instead of having to deal with all these requests which are coming as volume-wise.

So this is a game changer. This is first in the industry, and we've seen huge success already, and you should expect a lot more continuous evolution in this space. Customer traction is excellent so far, usage goes up considerably because you do burn down a lot of analysis because you are doing full end-to-end tax resolution here and that's really where the opportunity for us exists and it's also labor arbitrage. So we also get to monetize the labor cost, which employees have to pay employees have to pay their employees. Now they can do this in a much cheaper way so we can take away the labor cost as well. So a lot of great examples happening here and great, great progress so far.

And I'll just add, Gabriela, to the monetization question because it's so very important. I'll reiterate we crossed $1 billion in AI ACV in the quarter, well on our way to the $1.5 billion. I also noted in my script that we're while early, we're already tracking ahead of our target for AI to reach 30% of ACV in 2030. And these L1 autonomous agents. If you think about the complex task that they're able to execute really drives more and more assist as we think about compounding effect of consumption. This is a great example of how we will reach our 30%, but tracking very well, and we're really excited about what we're seeing.

Your next question comes from the line of Michael Turrin with Wells Fargo Securities.

On the Q2 upside, you mentioned the Fed outperformance. And I guess the question is that strength at all prove a leading indicator for a bigger bounce back there versus last year in terms of spend? Or how should we think about the seasonality of that segment? And maybe you can also frame just how you're approaching that from a 3Q guidance perspective, if there's any prudent just given the duration or upfront impacts there for us to be thinking about in parsing Q2 and Q3?

Yes. So thanks, Michael, for the question. So clearly, a strong Q2 in Fed is good news in general. And as we move into the big Q3 quarter for FAD, it's definitely a good indicator. We called it out specifically because we did have a little bit more on-prem in Q2, which is purely timing. But I want to be clear that the beat was not all just on-prem. We had really strong net new ACV in the quarter as well, which allowed us to raise the full year guide. And so Fed business is strong as we move into Q3, pipe looks good, and we're very excited about what we're seeing.

And Michael, I would just build on what Gina is saying by simply reinforcing the message I gave you on cyber. Cyber security is going to be a massive tailwind for ServiceNow. The AI control tower for reinventing business is massive. Think about all of the assets, the incidents and the actions that have to take place to manage these large entities of government operations. Think about the Department of Defense even as 1 example and the importance of saving people's lives like medical material agencies in flight, putting things together, the devices, the coordination.

The beauty of ServiceNow is Amit said a moment ago, it doesn't just think but it acts and it closes the loop. And that, I think, is the full cycle of AI innovation and cybersecurity that we're building here at ServiceNow. And as the attack surface becomes even more dangerous by the moment, we're up for the challenge. And I think you're going to see us move up the leaderboard from a #8 company to contending for the top spot.

That's very clear. Congrats on the strong execution there.

Thanks Michael.

Your next question comes from the line of Alex Zukin with Wolfe Research. Alex?

Your next question comes from the line of Tal Liani with Bank of America.

I have 2 questions, but I'm going to combine them into one. Your pricing is token-based, assist based and competitors like Salesforce offer outcome-based that could introduce pricing pressure. On the other hand, you own the data, you own the context and competitors need to get the data out, contextualize it and pay a lot for tokens to do that.

So my question is, at the end of the day, you're launching many AI modules in the next few quarters or next few months, do you think on top of the value -- can you also offer price advantage versus competition? What happens to pricing of AI given all these differences between you and competitors?

Yes. Tal. So we've been very clear in terms of keeping our pricing very customer-friendly and thinking about how they want to adapt their products and where they see value. So we're never trying to kind of do strange things, which is very hard to manage or hard to understand. So hybrid pricing structure, which we introduced where it's a combination of license and usage directly applies to giving the customer predictability and flexibility. And it does -- when you use more, that means you are getting good outcomes, otherwise, you would not use more.

So outcome is already tied in the underlying assumption of usage, right? So it's trying to kind of define another metric, which is very hard to understand or measure and then have to go back and forth in terms of contracts and everything else else. In enterprise software doesn't work. And we've seen that for years and it's played out so well for us now because the way we address our pricing requests from customers seems to resonate with everyone, right? So that's really how we're thinking about it.

And the question you asked about tokens and things like that, it's really based on the outcome in terms of what you get the result, the full solution versus just counting each individual pieces of LLM or things like that. So customers are seeing the outcome from their usage, but they're also now been very predictable in terms of what they will pay us. And that has worked quite well.

And the second thing you asked about how we allow access to our systems in the context -- our context is for us to really get the better results for our customers and our competitors can get access to it, neither do LLMs. So that's really where the secret sauce is, and that's something which -- when we run 7 trillion workflows on our platform. We are collecting so much intelligence which can really change the game for our customers from the usage perspective and the results perspective. And that's where the differentiation comes in. And nobody else has that today.

And I would just add on your question on pricing. Our pricing uplift for our Pro Plus SKUs continues to be above 30%. And for our new AI native schools that were just launched, continue those uplifts are in line with what we talked about at bad at being 20% to 30%. So customers are absolutely understand the value is delivering to them.

Your next question comes from the line of Samik Chatterjee with JPMorgan.

Maybe if I can follow up on the AI targets here, which you're clearly exceeding already in terms of your road map and tracking ahead -- how much of the upside or can you sort of help us ballpark how the adoption is going in terms of new customers that are coming into the ecosystem as a result versus maybe you're being able to upsell more of your customers into the higher tier packages because of the people being more sort of interesting at that level? Like help us -- if you can help us break that down a bit in terms of what's the driver of the upside as you look at the road map here?

So thanks so much for the question. As we talked about, the AI-native SKUs are really making our genetic solutions more accessible to that customer base, new customers and then existing customers who haven't tried AI before, right?

So we talked about deal volume among first-time ServiceNow agentic AI buyers. So customers that haven't bought AI before grew over 45% year-over-year, and again, uplift in pricing of 20% to 30%. So the AI functionality is really resonating across the board with our customer base, existing customers and then also for new logos. So the new customers are also leaning into AI first, as you would expect.

I'll just add also the use cases across the AI is just expanding quite a lot. -- customers, of course, start with the Gen AI kind of mindset, but now doing resolution manning, incident management, triaging the whole case management around it. So once the agentic use cases get started, we're seeing a tremendous amount of interest in doing more -- and that's why you've seen the growth in is talking about with our AI adoption. And that happens for existing customers because they want to identify their workflows. They're finding new use cases in other departments.

So there's a lot of cross-sell opportunities because you do connect multiple departments and multiple systems together, you're just not doing it for one particular area and that's where we become much more of a control tower as well as the full orchestration engine versus other vendors out there. So that's really where we're seeing the exciting uptake. And we keep on learning from it.

And if you look at the innovation cycle we brought in now, really amount of new capabilities we're introducing over the last 6 to 12 months is just huge and it's very exciting for our customers and very differentiated versus all the random individual pieces of technology, which are out there in the industry today.

And then on your question specifically on adoption, we talked about a number of customers with the Genetic AI in production has grown 9x over the last 9 months. So adoption is going well on top of what we just talked about.

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

And certainly, the 200 basis point beat on the CRPO is pretty impressive. We're getting some questions just on some of the mechanics and the full year guidance raise, and I know there's then you called out in terms of Q2 to Q3 revenue recognition, but it seems like a very strong quarter.

You're tracking ahead on AI, net new ACV security business is firing on all cylinders. Just help us understand the relatively modest full year subscription revenue raise versus the Q2 outperformance? Is there more conservatism other dynamics we should be thinking about?

Yes. So thanks so much for the question, Tyler. So we talked about the fact that about half of the beat is a pull forward of on-prem for a quarter, right? So that won't impact Q3 versus Q2. From a full year revenue guide, we passed along all of the net new ACV overachievement. But yes, I'm always looking, especially in this market environment, at a conservative prudent guide, right? There's certainly upside, but we feel really good about the guide right now. And we raised for all of the net new ACV overachievement in the quarter and are being prudent for back half as most would expect.

Your next question comes from the line of Matt Hedberg with RBC Capital Markets.

Bill, obviously, a set of strong results here. And I guess with all the talk about enterprise air readiness and ethos driving increased cyber awareness, it seems to be benefiting you guys. There is a concern from investors that buying cycles may start to elongate I guess with that being said, can you talk about any changes you saw or you might expect on deal cycles or decision-making. Obviously, it seems like ServiceNow is a consolidation point when it comes to IT spending. But just any perspective on that would be helpful.

Thank you for the question, Matt. So think of it this way. The frontier companies out there are incredible. It's so exciting. The hyperscalers are incredible. It's so exciting. And what's really unique is we're in the midst of the AI revolution. So the one has to then say, where is ServiceNow's place in this AI revolution. We're in the bull's eye of it because the frontier models need to get activated in the enterprise. That's battleground. And so whoever teams up with ServiceNow wins.

And the reason for that is, as Gina and Amit were discussing the $100 billion workflows and the nearly $8 trillion transactions that we have in flight right now, there's a lot of business processes that are running on the ServiceNow platform. And what we did with the company with the CMDB, you have to go to the beginning of the company. We knew all the people. We know all the places, we know all the things. And over time, we integrated with all the systems of record.

So we're completely integrated with everything hyperscalers from tier models, data lakes, systems of record. So that workflow and how you automate that and the incredible power of AI going east to west and north to south without any clue workarounds because these clunky systems that have been in the enterprise for 6 decades doesn't let AI do what AI was born to do. We let AI do what AI is going to do. because of the data in that workflow automation platform. And if it's not in our platform, we've integrated into the other participants, and we have connectors into all of them. So those connections led AI and the magnific and power of AI really go to work.

The other thing that is so interesting right now, as you know, the attack surface is exploding -- every ungoverned asset and identity multiplies the blast radius of AI in the enterprise. So we had a leadership position in security and operations, and we integrate with all these excellent security companies that are out there. These guys are my friends. But we did something a little different. We gave the customer that 1 command center where they had a full purview of their landscape, and they had the threat areas very well known.

Now with Vesa and Armis, we're managing all the identities of the humans, the agents and the thinking machines are robots. And now we're going after the critical infrastructure the people, the networks and the devices with Armis. So the strategic relevance of ServiceNow is at the bull's eye or the epicenter of the AI revolution in the enterprise. And so -- what you're seeing here is a company before your very eyes turning into both an enterprise software market leader and a cybersecurity market leader and the fastest growing at both. And that's pretty special.

And so I think what you should take away from this is Mito was a gift to the ServiceNow company in the sense that everybody now is scrambling with all the exposure that they have to patch things up. But it's one thing to know where the threat area is. It's another thing to hunt it down, take action on it and close the loop is what the ServiceNow platform enables you to do end-to-end cybersecurity. And so I think it's just gotten very interesting right now. It shows in our numbers A lot of people like a seats going away.

No, actually, active seats are going up. Well, what about the term of the contracts, they must be going down. No, they're actually elongating and you see that in the CRPO and the RPO. And oh, by the way, the pricing oh, you must be doing something wrong on the pricing. Now actually, we're giving the customer exactly what they want, the hybrid with the seat and the consumption, so they get a great ROI on their investment. So all these pieces are coming together.

And then you say to yourself, you read the media headlines today and you're like, wow, it's pretty cool that we have a kill switch for Rogue is for any company that's running ServiceNow and you get a rogue AI, there's a kill switch, it doesn't get through. And then you think about how you use the right model and you hire for the right job. And we do that, too and people are realizing you don't need to take a Ferrari to mail a letter.

So using the right technology, the right job and then managing the budgets including all the tokens and the security of this has become pretty important. And so we're right now really seeing a new world order of things. And when one of the colleagues just asked a question, kind of about the AI and all that. I think this maneuver on what we did with the AI control tower and setting that new vision for the company for the future. I think cybersecurity will be bigger than ServiceNow is in the next few years. I think you'll be like -- could you please talk to us about your workflow automation business and your core IT because all I hear you talking about cyber.

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

So just wanted to maybe triangulate sales and marketing headcount was up quite a bit quarter-over-quarter and you've already added more sales headcount in that line this year than all of last year. I'm just curious -- is that a matter of timing? Is that some headline coming in from the M&A? Or is that the company ramping up sales distribution ahead of this -- the revised actually impact I'm just trying to understand how we're thinking about sales distribution given the large head one already and how we're thinking about that for the rest of the year?

Thanks, Samad, for the question. So it's all 3. So a little bit is from M&A as we inherited some incredible sales associates. And as Bill just talked about, security and risk really ramping. So we're certainly making sure that we're hiring ahead of that. We've always said and we've never stopped hiring quota-bearing feet-on-the-street sales exact, and we will continue to do that. And you'll continue to see us do that.

So yes, we feel bullish about back half as you would expect, you'll see more sales heads as a result. But yes, some of it is from M&A.

And may I say, Samad, Gina laid it out there beautifully. We're a growth company, and we're going to grow fast. And the one thing I also wanted to reinforce is a commitment that we made as a management team to the capital markets. We will complete this year. After having acquired 3 gorgeous companies, Moveworks, Vesa and Armis, we will complete this cycle of 2026 and start 2027 with the exact same headcount before we did the acquisitions.

So you are going to see operating margins and the free cash flow margins of this corporation scale. And you already saw the 3-point operating margin improvement in the quarter, which was way beyond expectations. We are serious about growth, growth on the top line, expanding the margin profile of the company and winning share everywhere we go in this AI revolution, especially cyber.

Your next question comes from the line of Brad Zelnick with Deutsche Bank.

Gina, I appreciate your gross margin guidance reflects more customers leveraging your hyperscaler partnerships and accelerating customer AI adoption, which both seem like really good things. But focusing on the AI side, -- how are you managing the tension between an increase in consumption mix and better token pricing going forward? And how should we think about the upside versus down risk to gross margin from here?

Thanks so much for the question, Brad. So yes, both good reasons for a little bit of short-term pressure on margins. Notably, even though we had a little pressure on gross margin, we held the operating margin flat. But with respect to gross margin guidance, as we ramp and the increasing hyperscaler is that we're ramping quicker than planned, which is a very good thing.

As we continue to ramp and more and more goes to hyperscalers, the cost per comes down. So we absolutely believe that midterm, there will be less pressure and even better pricing on the hyperscale side of things, which I also talked about at that -- the same thing with respect to AI consumption. And so if you remember at FAD, I talked about a little bit of short-term pressure, but that we absolutely think that mid and longer term, we have some opportunity to continue to increase.

All of that being said, operating margins continue to accrete. As Bill said, we will remain as disciplined as ever on driving that only best-in-class top line growth but best-in-class margins well on our way to the rule of 60 by 2030.

If I can add, Brad, on the token, how we think about using large language models. I think clearly, in the market, and we've been talking about it for years, so that large language models are getting commoditized. There is no reason for using some of the most expensive ones. So we're very smart about how we use and leverage some of the emerging technologies where use open weight to urgent, where do we have our own, where we have domain specific ones. And where we use this higher-end frontier models. And a lot of these capabilities can keep on being swapped around, and we really optimize across the board to ensure we're getting the best outcome while keeping the costs low.

So engineering team is really on top of it, and our research team really does a lot of work in the lab to keep up with it, and we work with many of them as well to optimize how this thing gets adopted. So we are not really worried about the margin impact as we keep on using more of these capabilities. Why because the way we price is really based on the solution versus individual tokens at the end of the day. So I think that should be how you should think about long term.

Your next question comes from Keith Bachman with BMO.

Bill, I wanted to direct this to you, if I could. You've talked quite a bit tonight about cyber and high aspirations for what you want to be as a cyber company. But maybe you could talk a little bit about revisit your strategy and aspirations as what the boundaries are. So you have Vesa and Armis, which are intriguing assets, but there's a lot of areas where you don't play or don't participate. You've been in the stock for a while in terms of a workflow engine.

But how do you think about your future opportunities with cyber. And related to that is there's ongoing convergence in cyber and observability with new competitors ending it from the cyber side -- you've had some presence in observability, but as these markets converge between workflow, cyber and observability, how do you think about revisiting your strategy also on the observability side?

Yes. No, no, I appreciate it. Thank you very much, Keith. We're building the world's most integrated end-to-end security platform. I think that's the way you should think about it. And think about us in the context of AI control tower, Think about us as the Agentic front door to Security 360. And of course, Armis give us an enormous start on some of the areas we didn't have, but we already had a lot of areas and a very large security business.

Now with the great engineering we have and the development commitment we have I think we're just going to build so many great things. I talked about risk and compliance, which we already have. I talked about identity and access security, which we already have. I talked about cyber physical security, which we already have. I talked about continuous vulnerability detection which arms is the best at, and we're literally hunting the vulnerabilities, not passively looking at them on a dashboard exposure management, agentic incident response. These are things that our platform does -- so what I laid out today was an organic story.

Now to the extent there might be other things we wish to do. I'll let Amit comment on some of the road mapping that we're doing. But I just want to give you great confidence that like what we have right now is awesome. And it's going to really rock the world. In fact, I'm actually pumped up because we just had a couple of days of Board meetings and I got to see the solution, the products that we have in flight and our great go-to-market leader Paul and all the work he's doing with the teams and how beautifully integrated they are in the company. Where the rare company that actually brings companies in from the outside and puts their CEOs in charge of the business.

And we did that with employee works with Moveworks, -- and now we did that with Armis and Gavin running our security business as a corporation within the corporation, and that's inclusive of Vesaasa. And so the alignment of our naturally born assets and then having these businesses run by people that are born in the security space. I mean, you've got to look at this hunger this drive, this belief this innovation road map, the way I saw it, and I think you would be as excited as I am. So Amit, do you want to add some color.

Yes. No, Bill, I think you covered a lot of the ground in there. I think, Keith, on in general, if you look at the security and the cybersecurity space, we are basically covering the pre-breach with vulnerability management and exposure management. So we complete that story in terms of any device, any asset, any kind of agents and everything else across Versand Arm is from that perspective.

Then you have the post breach, which we have been very strong at ServiceNow. We're managing all of the things for -- so across the life cycle or any breaches associated with cyber attack. And now we have a runtime security as well. So we're bringing all of these pieces into 1 platform. And really, that's the area we are playing in. There are always going to be a lot of other peripheral things in cybersecurity. And the cybersecurity space is usual, we're not going to be in every area. But where we have strength, where we have opportunity and it builds on top of what we did with CMDB, what we did with approach breach stuff and now adding the asset as well as the pre-breach things for any kind of exposure and vulnerability for devices and IT is just really changes the game and creates a big platform.

A second thing quickly on observability. As you probably saw, we launched our AI ops specialist as part of -- so we're already doing a lot of work with absorbability, bringing agent kind of use cases into a platform. So we're not trying to build this observably outside. It's really part of ITOM and then we're integrating with all the other players, which gives us signals and then you can make decisions and take actions. And that's really the foundation around ITOM and everything else we do in that ecosystem today.

And if I could, I just want to say, Keith, to my friends out there in the security business, great friends like Nikesh and George and many others. They still are great friends, and they are great partners. And we do -- we run their solutions in our company, too. And we intend to continue to partner with them and make those partnerships even deeper because it's such a surface area and so much opportunity and meet those as open up the floodgates.

So I think the new information from a shareholder value standpoint is we're in the party now. And we're not out to replace all of those excellent companies, we're building our own story on our own great foundation, and it's important that the customer gets the benefit of all of us because they're going to need it.

Your next question comes from the line of Moskowitz with Mizuho.

Bill, maybe a follow-up to an earlier question, if I may. All the commentary on this call sound very favorable, but there have been a couple of recent indications from tech vendors at organizations have become more consumed with hardware and AI spending, and this is having a knock-on effect on other aspects of IT spend. So just to ask this directly, have you seen any impact to sales cycles with ServiceNow?

I have not. In fact, the key here, Greg, is this has really become a C-suite story. You have to recognize that breadth and depth of our portfolio, having 6 unicorn businesses, a seventh on the way, by the way. So when we go in to 2027, I'll have 7 unicorn businesses that are either $1 billion or multiple billions. Keep that in mind. So the breadth and the depth covers the surface area of many aspects of a corporation, but it also covers the most important part of the corporation, which is how do you run the business? And the fact is, with AI, these customers don't have enough time to do it the old way.

So many of them have such a fragmented enterprise that they need to take advantage of our workflow automation above the mess and click in that AI engine into this unlivable platform and really begin running. So the higher you go in the C-suite, the more relevant we are and the more the C-suite realizes that we're in the bulls eye of what has to happen to fundamentally be the control tower for reinventing these businesses.

So I have not seen any change, if I've seen any changes on the positive. And I will tell you, we're ready. And our business is rocking. And when I think about what we're going to do with the new businesses that we took advantage of at the end of last year and took some criticism for. It was because we believe in our strategy, we believe in our team, we believe in our customers and what they need and now it's all about execution, and we're good at that. So what I see is a customer base waiting for us, plays that we're running to gain even more traction and a fantastic future for people who believe in ServiceNow.

We have time for one more question, and that question comes from the line of Adam Wood with Morgan Stanley.

First squeezing you mentioned in the state call around the AI control tower and controlling the enterprise control pain for customers. Obviously, that's a huge opportunity and a critical function. But obviously, also a very competitive space -- could you talk a little bit about your right to win there? Is this going to be more a departmental battle where you have the strongest presence in wind or do the enterprise wide?

And then can you talk about any customers that are going out in that review and kind of call out why they're charging you for that use case.

Yes. Maybe, Adam, I'll start to tell you about how we think about AI control tower. As Bill mentioned, our heritage has been the CMDB platform. which tracks every kind of asset out there, hardware, software and other enterprises have. We build a control tower with that kind of foundation where we would be able to discover anything an enterprise is running which includes now AI agents, any devices which are connected to it. And it's a very heterogeneous. This work across multiple domains. It's not really for ServiceNow assets, but everything else.

So we've always been doing this open ecosystem discovery management, life cycle tracking, cost management and observability around it. So it was very natural for us to get into this idea of AI. -- agents being also monitored and managed across all the different landscape customers have. And that has been very clearly resonating with the customers. We have more than 500-plus customers already like using a control now in the first 6 months when we launched this product, and it continues to grow. And we keep on adding more and more capabilities in terms of finding like Bill mentioned, kill switch, right? How do you find errors or issues with any of the reagents running around and stop them from accessing any information or any data.

With Vesa, we added a lot more around identity governance -- and with the Armis is be able to now take all the devices as well in their physical AI as well. So the breadth and the depth we have here is the reason why we have the right to win. We had the foundation and we build a solid product, which is really working for our customers, and we have tremendous amount of proof points where we are able to now really help customers to manage the whole huge AI landscape and really have control and a peace of mind and that's really where the foundation is from.

And I would say, running the business is what C-suite executives care about. How am I going to be a best run business. And when you think about it that way, and you asked for some examples also order to cash, procure to pay, designed to build, hire to retire. We can go through all the business processes and CEOs know exactly what they are for their company. And they know they have to optimize them to ring margin length out of waste and gain future market opportunities like lead to cash as an example. So they're thinking big picture, they're thinking business processes.

So in that context, our enterprise participants in the transformation of these companies. And some examples would include a Fortune 50 health care, care and retail distributor. You know this company well, believe me, they're capturing millions in annualized savings by consolidating vendor risk governance and fraud detection across 1,000 suppliers. They're using ServiceNow's AI control tower.

Tech Mahindra. You recognize that pretty quickly, strengthening through a 5-year deal, by the way, to fundamentally transform the workflow processes across HR, IT, security and they're going to govern their assets at mass scale with a genetic AI. Another one I love is Maybank. By the way, another 5-year deal, so much for deal shortening, right, a leading financial institution and what they're doing, I mean, this is Malaysia's largest bank, they're using the AI platform and control tower to establish a resilient operation center to fortify security and resilience as well as autonomous regional operations.

NTT Data is one of my favorites too, since Paul and I were very involved in that, I'll tell you. They have a governance process with us to drive AI scale for all internal use globally, and they're doing it on a single platform. and they're looking at responsible innovation done with great visibility and the control tower accelerating AI adoption, but also monitoring it, measuring it, make sure everything is done in real time the right way. And Amit about Kill Switch, we're doing many other things. So I hope that gives you a little feel for it, Adam.

And I'll now turn it back over to Darren for closing comments.

Thank you all for joining. We look forward to talking to you next quarter.

Ladies and gentlemen, this does conclude today's conference call. Thank you all for your participation, and you may now disconnect.

Thanks, everybody, for joining us. Kirk Materne with Evercore ISI. We're really excited to have ServiceNow with us this afternoon, Gaurav Rewari, who's the EVP of Global Marketing, Data and Analytics. So thanks very much for being here.

Just for some background for everybody, can you just talk about sort of your responsibilities at ServiceNow and then the elements of the Data and Analytics platform? Because I think it's something that's obviously up and coming at the company, but maybe not as familiar to everybody. So I'll let you kick off with that.

No, happy to provide some context, and thanks for having us. So yes, I'm Gaurav Rewari, I'm EVP and GM, General Manager, of the Data and Analytics business.

Relatively new business for us at ServiceNow. And we've done things in data and analytics before. We had embedded reporting, we had data integration products, but it was fairly scattered and it wasn't sort of a serious area of focus. And so Bill and Amit reached out to me to join and to stand up our next multibillion dollar business. So that was sort of the problem statement.

And I think the motivation was, on their part, was twofold. One was what they were hearing from customers, which is, look, "We'd love for you to take data seriously." And the second is just its incredible relevance to our AI success, right? And you've all probably read the reports, right, the very sobering statistics, around 95% of projects fail, the MIT study, and the other things from Gartner that are equally sobering.

And if you actually read that report, it tells you that, in most cases, the reason for that are data issues, right? So this is -- I often -- the data is all siloed, I don't know where what is. Even if I find it, I don't know what it means. There are 5 different versions of the truth. The quality of the data is suspect. If I can clean it up, how do I keep it clean? Then I derive insights from the data, but you've got one version of a definition for return on invested capital, Andrew has got another one. Which one do I believe? And on and on and on, right?

So these kinds of issues, we like to joke, it seems like the path to agentic AI heaven goes through some form of data hell, right? And so we said, okay, we looked at ourselves in the mirror and we said, look, if we are serious about driving business transformation through agentic AI, we've also got to be serious about being in the data and analytics space, and making sure that our customers have the tools and the support that they need to get their data estate to be AI-ready.

And I'm just delighted to share that sort of the product line that we've built to support that has met with a very strong reception. And we're on track to break $1 billion plus in ARR in just a few quarters here.

That's great. Very fast ramp. Can you just remind people the products involved in the data and analytics side? Obviously, RaptorDB is a big one. But what else falls within your sort of purview?

Good question. Yes. No, look, the framework with which we think about the scope of data and analytics in the new world of AI, which is fundamentally different, we believe, from yesteryear, are what we call the 4 Cs.

Your first order of business is just to connect all your data. And it's really important that you provide connections to all systems of record, all data platforms, et cetera, right? So that these AI agents can learn what they need to learn so that they can do what we want them to do, right? And they can't just be ServiceNow data. So that connect layer is hugely important.

The second layer is, okay, I've connected it, but like it's not enough to just connect the data. I need to be confident that it's trustworthy. So I need to have -- clean the data and you need to do that on an ongoing basis. So there's governance that's required. So that's the second C.

The third is you can connect your data, you can keep it clean, but you can still really not know what it means and what ties to the other. So that's context. That's a big investment area for us. That's the third C.

And then the fourth is, just think about it for a second, right? AI isn't just about assist and copilot type of -- initial copilot kind of capabilities, right? It's about actually taking action. That's where AI is today. And so how can we have a world or how can we have an architecture and an infrastructure where like the system of where you get insights is completely distinct from the system where you actually take action? You've got to bring those together. And that's the fourth C, converge.

And so our products map into that. Workflow Data Fabric is connect and control. We have a new analytics product line that we've just announced that helps with the context and the context engine. And finally, the converge is Raptor.

Okay. Out of curiosity, when Bill came up to you and offered this opportunity, why was it exciting to go to ServiceNow data? Meaning data, there's a lot of companies that are involved in data. What did you see at ServiceNow that gave you sort of -- or gives you permission to win in this area and help customers with this? I was kind of curious, because it's not a trivial task to try to build a data business. It's hard. There's a lot of companies that are trying to do this.

Yes, yes. Look, I'll just sort of speak very frankly here, I wasn't initially intending to go to ServiceNow. I've sort of, deliberately, I think, chosen in my career to alternate between big companies like Oracle, and then startups, just to sort of stay nimble. And so I was actually headed to a startup, and I spoke with Bill. And I suppose he did the old Jedi mind trick on me or whatever. But like I was so fired up at the end of that call, I got to tell you, that I basically said yes on the call and I hadn't spoken to my wife before doing that. So there was an interesting conversation that evening. Of course, she was very, very supportive.

But I'll tell you, there were 3 reasons that just compelled me like to say yes. One is I've always had a soft corner for this company, because from the Fred Luddy days, they always go back to first principles and think about how is it that we can architect our product to win, right? So we have a structural advantage.

So we're -- even when we are in the age of AI, that notion of a single codebase, a single platform, with a single security model, single user experience, the painful discipline required to just invest in that gives you leverage, right? And what did Archimedes say? "Give me a lever long enough, I will lift the moon." That's what architectural purity gives you. So I've had a soft corner for that.

And then secondly is it's a very collegial place. It's somehow managed to keep a very sort of startuppy innovative environment going even at scale. So those are the things. Plus the old Jedi mind trick, I suppose.

Yes. He's known as a pretty good [ talker ]. So you're not the first, I'm sure there's many of us. Talk to us about, as you obviously have a great customer base that has used you and trust you for managing a lot of workflow, how does the discussion about getting these data products, getting them to view the data products as something that they want to expand with you? Just walk me through maybe an example of a customer where that sort of conversation starts and what it ultimately ends up looking like as they say, "Hey, look, I like your strategy. Let's go."

Great question, and I think that gives me an opportunity to make a really important point, is I think that we are on our way to becoming a data and analytics juggernaut by, initially, and even in the midterm I would say, never really selling directly to data and analytics teams. And the way we do that is by saying, "Hey, Dear ServiceNow Platform Owner, Dear Line of Business Head, that uses ServiceNow for workflow orchestration across the board, would you like to have your operational workflows and your analytics run 10x faster?" Right? "And if you do, we'll run a POC for you. We'll show you the results. Sign up." And we would have sold RaptorDB Pro. No conversation about speeds and feeds, no conversation about columnstore indexing, no conversation about parallel processing. It is the value and the outcome that we sell.

Then the next port of call is, "Okay, so now you're embarking with us on this journey for agentic workflows, would you like to make sure that your AI agents have, for their training, right, data from not just ServiceNow, but related data, from Workday, from Snowflake, from Databricks, et cetera? If so, we've got the right thing for you. It's Workflow Data Fabric with its connect and contextualized layer," right?

And so, and lastly, we've gotten into analytics now, we are not going and saying, okay, let's talk to you about -- because I used to be at Oracle, at MicroStrategy, et cetera, I ran products for those companies, right? We're not going to have a conversation about, hey, let's talk about slowly changing dimension and ragged hierarchies, which is the DI speak. We're going to say, "You put changes into your production systems. Do you want us to help you predict which changes are likely to fail and where the incident volume is likely to spike and which businesses are likely to be impacted?" And why we can do that is because we're going to take our analytics product and bottle it up into workflow-based solution.

So fundamentally, we are actually selling solutions with data and analytics products underneath the hood. And then the phase 2 of our journey is to say, well, we've earned the right then at some moment in time to go directly to the data and analytics office.

Okay. That makes sense. RaptorDB Pro, it's positioned to run both transactional and analytical queries on the same data set. How much of an advantage is that for customers in terms of just price performance? And that alone, does that get you in the door to have the conversation, I guess, in terms of...

100%. Look, I would say that RaptorDB Pro in its first innings, and we've got a few lined up, is largely about saying, initially, was largely about, hey, if you have a certain volume of transactions that you're running, a certain number of workflows that you're orchestrating across your system, we will speed those up without you knowing, right? Like that's what RaptorDB Pro brought to the table in the initial innings.

But then this notion, as you call out, about a converged infrastructure, is profoundly important. You see most of enterprise software's history has been about saying, you have these what I call OLTP systems, online transactional processing systems, think ERP, CRM, HCM, that execute transactions and get work done. And then you have, if you have questions, you need answering, business intelligence, analytics, you would typically forklift that data out into a data warehouse or a data mart and then analyze it over there, right?

Okay. But now imagine a world where you have not thousands, but millions, if not billions, of AI agents acting and thinking on your behalf, right? How can you have a situation where they're going to be acting on stale data and stale insights? Because moving that data over introduces what's called latency. So if you can have the same workhorse database perform both operational tasks and analytical tasks, you give them real-time insights, not insights that have that latency.

So it's fundamentally that value proposition that we find that our customers are -- love. And what we have chosen to do, and this is once again how ServiceNow is distinctly different, is we've said, yes, we have an analytics tool. But if you want to point your favorite analytics tool, Tableau, Power BI, et cetera, directly against RaptorDB, we'll let you do that too. It's okay. We'll embrace the choices you've made just as we've embraced the choices they've made on the systems-of-record layer as well.

And when you think about Workflow Data Fabric, how much of the sort of early demand for that is people just trying to get ready for agentic? Meaning, I kind of wonder it's always sort of the chicken or egg, are they trying it out and then realizing the data doesn't work so they got to go back and deal with it after the fact? Like, is it just the central discussion around an agentic enterprise driving more, I guess, understanding of the need for a technology like that, that can help centralize data and basically inform the agents in a much better way?

And you're saying versus the more traditional like I want to upgrade my analytical infrastructure...

Yes.

Yes, good question. I'd say that certainly, the need to get your data estate-ready for AI is the why-now motivator. I mean I've been going to this Gartner Data & Analytics conference they have for longer than I care to admit. I had a full head of hair when I started, right? And I got to tell you, the sessions that used to be the most packed were the ones on analytics and dashboards. That's where you got the whistles from the gallery, right? No one went to data quality, master data management, like those are not sexy at all. Last 2 years, standing room only. Same people, same problem really, and they're standing room only because their CIOs and CEOs are telling them, "Listen, clean this up yesterday," right?

So that urgency is definitely tied to getting your data ready for AI. But in so doing, I honestly do feel you're solving a lot of the problems you need to solve anyway to get a more robust, semantically richer analytical infrastructure in place.

And you mentioned earlier the ServiceNow customer base, they're trying to figure out how to get to that agentic layer. When they think about sort of spending on RaptorDB Pro, does it come more from sort of the -- is it just a broader view of workflow, and so this is sort of almost a new budget for them? Or are the data people getting involved sort of after the fact? They're like, oh, ServiceNow has got a lot to go here. I'm just kind of curious who the buying audience ultimately ends up being at the end of it. It might be all of the above.

It is all of the above. But principally, I would say it's the ServiceNow platform owner and our existing e-buyer that sponsors the project around. "Okay, I have like 5,000 reports I'm running and they can run 10x as fast if I have RaptorDB Pro under the hood." So that's sort of the land motion for RaptorDB.

But we have just announced some additional capabilities, like the one I alluded to, which is, hey, what if I have Power BI or Tableau in house and I want to point it directly against RaptorDB? What does that mean? That means you don't necessarily anymore have to take out your data from Raptor, put it in Snowflake, put it in Oracle, put it in BigQuery, et cetera. So the cost of defining and maintaining those data pipelines goes away. So it self-funds itself. And guess what? Because you're hitting Raptor directly, you get live, real-time analytics, not with that latency.

We've done the same with something called Live Archive, where what we're saying is, if within Raptor you want to offload some data to lower cost storage, we'll let you do that, right? And then we'll let you actually query both the hot and cold data seamlessly. Today a lot of companies take the data out and put it in a backup and archival system. But once again, the cost of doing that goes away if you go with the Raptor option. It self-funds.

And I guess when -- you guys obviously have a lot of products like Now Assist and others that are agentic in nature. Is the data discussion fundamental in those as well now? I mean, is that when people are thinking about that? Is it sort of like, yes, if you really want to get to sort of more autonomous agentic, you're going to need to make sure that the data is set up? So are you getting pulled into those discussions essentially?

100%, and increasingly so. I mean I'll be perfectly candid, in the early days when the story was largely around connectivity of data, quality of data, governance of data, it was like, "Yes, yes, I got to do it." It's like washing my hands 5 times a day. I get it. I got to do it. But everything has changed with this context thing, where demonstrably you can show that the quality of your AI agents, reducing hallucinations and bias, is tied to how rich the context is that you can give to your AI agents. Then collect -- 3 Cs, connecting the data, controlling it and then contextualizing it, becomes crucially important. That's all large part -- in large part done through Workflow Data Fabric. So suddenly, it's like, okay, I got to know this too as a prereq.

And our vision, I would say, on context engine is quite unique. Because a lot of people may not know that like ServiceNow's initial special sauce was the CMDB and this whole Knowledge Graph that was built that powered the CMDB. And so we've been in this business forever, which is mapping the smallest IT software hardware component all the way up to a business service, right? And understanding the lineage, the impact analysis, et cetera.

And so to that, we've added context from your data platforms, like Snowflake and Databricks. We've added context from identity and about users through our Veza acquisition, about assets from our Armis acquisition. So suddenly, you've got something that is it's the graph of graphs. That's what our context graph is.

That's really interesting. If there are any questions, I got a ton more, but I'm happy to make it interactive as well. All right, I'll keep going.

The data.world acquisition, can you just talk about what you guys are doing on that front in terms of the data catalog, governance capabilities? I think it fits into what you said about the 4 Cs, obviously, but how is it for you?

Yes. No, happy to spend a minute or 2 on that. Look, I think that was the first move we made, inorganic move that we made. And it was a Knowledge Graph based company for data cataloging, which was unique. We looked at all the other companies out there in the startup venture ecosystem. And we just fell in love with this one because of the way it was architected. And it's wall-to-wall deployments at places like McKinsey, WPI, et cetera. So we spoke to a lot of customers.

Fundamentally, what we said was we need a way to organize the data or catalog it. So we understand, where did this field come from? Can it be trusted? What was the last time it was modified? What is its lineage? And ultimately, bless it. And so from that, we create data products that are really metadata and that tells any user, including an AI agent, this set of things are on this topic and can be trusted, right? So we knew that it was a seminal piece. We had not built that, so we made an inorganic move there. Happy to report, we've just fully integrated it into the ServiceNow platform and rolled it out at Knowledge in May.

So that's the sort of the big piece of the puzzle. But that's the first step in a longer journey. And that longer journey is about saying we're not just going to get your data estate AI-ready on day 1, we're going to keep it AI-ready. So data quality, data observability, MDM, data harmonization, data enrichment are all things that we will both build and partner with. So we have this notion called Workflow Data Network, which says, "Look, if you want to use ServiceNow's data quality product down the road, great. If not, if you've got your favorite data quality product, you can plug it in."

So that is once again a very different approach relative to the other players. And so that's what -- and we call it, we've given a fancy name, Autonomous Data Governance. But really, that's what it is.

Okay. And you mentioned sort of you guys have zero copy partnerships with some of the other data providers like Snowflake, Databricks. How should we think about those relationships in general? Is it all just about openness? If someone has -- most, Snowflake to be their core data repository, maybe they have you all, sort of just running under the ServiceNow stack, for example, I guess, how do you think about that from a -- there's, I'm sure, some coopetition to some degree, especially as you get into analytics. But how should an investor kind of frame your position in data versus the ones that are maybe more centralized around that area?

That's a very nice question. And I think that, honestly, it harkens back to one of the reasons I shared with you I felt compelled to join ServiceNow, which is going back to first principles and figuring out how to architect this for today's needs. And in so doing, I believe our position is unique in the market, right? We don't say you have to move all your data into our data cloud or into Raptor for the magic to happen. If you'd like to, we love it. Thank you very much. We'll be flattered. But you don't have to.

So if you want to leave your data in SAP, the ERP systems, or if you want to leave it in Snowflake, Databricks, Google BigQuery, Oracle Database, we've got all of those. You can leave it in place. You don't need to move it. We will logically represent it in Raptor. And at the moment of the question, we'll push down the query -- federate the query and push it down to these underlying data warehouses and data lakes.

They're happy because we continue to drive data processing consumption there. We are happy for another reason. It's because we say to our customers, just like we are the platform of platforms, as Bill likes to say, for system of action, we're also the platform of platforms for insights. And AI agents need insight and action.

It is our position in the stack that allows us to do what we do. And what that meant was basically looking at where the industry was. Everyone, you might remember, was talking about data gravity, data gravity. Don't play in AI if you can't get data gravity. And our position was, that's nice, but it's not necessary. What matters to us more is knowledge gravity. And we believe we can do that even if we're sitting atop the data warehouses, data lakes, the systems of record.

So that's why Zero Copy is such an exciting thing for us and it's important. And the reception has been really strong. And I think it's a distinctive architectural benefit.

I think ServiceNow has always, because you've done so well in your core ITSM, you've been sort of given permission by your customers to expand. And I'd imagine having data products allows for potentially more surface coverage for you all over time. You're not going to announce anything, but I'd imagine as customers think about building agents that are cross-functional, things like that, the data foundation sort of helps support that view or that vision for you all. Can you just talk about that a little bit?

Absolutely. I think that data and knowledge foundation, as we just talked about, gives us the framework, and the fabric, no pun intended, in place so that you can do powerful things on top. And once again, it's a logical fabric. So not all the pieces involve moving the data over. Some can stay in place. So we play nice with the other systems of record and the data platforms.

So I think it opens up avenues for us. And I think I'm personally very content, because we can blow past all our revenue targets that we have for this business and our ambition by continuing to sell into our existing e-buyer more and more data and analytics capabilities, but positioned as outcomes that matter to them, right? But the time will come.

And this was actually something we did at Oracle. We were very late to the BI platform space. So we built something called BI Apps. Basically, it was CRM analytics, ERP analytics, HCM analytics. And that's what we sold on top of PeopleSoft, Siebel, JD Edwards and E-Business Suite. The customer often didn't know that they were using a BI platform underneath. We blew that past $1 billion, $1.5 billion in revenue. And then after that, the customer is like, "I kind of like this. Can I use it for other things?" And we said, sure, you can. And that was the expand motion.

It is our belief that exactly this will happen. What Mark Twain said, "History doesn't repeat itself, but it rhymes."

Yes. How about just the go-to-market for these products? I assume, is this, from a rep perspective, they understand the benefit of bringing data into the conversation? You have specialists that just are sort of -- that come in along with the sort of account manager? How do you make sure that the assets you have in Data and Analytics are represented in conversations? Because I'm sure you're still introducing a lot of your customers to these capabilities.

No, no. Great question. And look, I think it's the latter. So what we do is we have our core AEs. And the core AEs own the relationship with the customer. They're typically more schooled in the sort of bread-and-butter products of ServiceNow that we are known for, whether it's IT service management or the like. And what they do is they know enough to be dangerous and have the first couple of conversations, and then they quickly pull in the specialists. And we've got specialist AEs and SCs as well.

But now we have to, as we go into 2027, ask ourselves. Because this business is -- it's one of the fastest-growing businesses ever in ServiceNow's history, right? Within a company that has already broken past $5 billion, $10 billion, now $15 billion, faster than anyone else. So we have to ask ourselves whether the time has come where we have a dedicated, not a specialist, but like dedicated sales force just for Data and Analytics, or do we wait a little bit? So those are the discussions that will happen back half of '26.

Interesting. Interesting. Any questions? I'll keep calling, but I can keep going too.

Analytics. What do you think the secret sauce is for you in that area, right? I mean we've all seen it, you're at Oracle, done that, we've seen analytics, I don't know, it almost takes on sort of people are like, "Oh, analytics, who cares?" But there's obviously value to that. Is the value in the analytics really just the whole stack that comes along with it from ServiceNow? It feels like it's a layer that people think is somewhat commoditized, which might not be fair, but it's the view. How do you make sure -- or I guess, how do you monetize value at that layer?

I don't think that's fair. And as in like, I think that proclamations of the death of BI are greatly exaggerated, as they say. And I think that it's never been more relevant. But there is such a thing called modern BI. And what is modern BI? Modern BI is the complete upending of a massive category. This is a $100 billion TAM category. I started my career at MicroStrategy back when the term BI was not coined, and we sort of evangelized it along with Business Objects, right?

And look, here are the 3 things that are happening. Number one is we now have a world, agentic AI world, right, where we want these AI agents to think and act on our behalf, right? And so like just as humans need trusted business metrics, you better believe that these AI agents need, not the Monday afternoon versus Monday morning definition of return on invested capital, but the official, governed, curated, best version, right? So they need authoritative business metrics just as much as humans do. That's number one.

Number two is that this separation between the world of getting insights and taking action cannot survive in a world where you've got AI agents doing both. And they need real-time analytics in the flow of work. That's the second big thing that's happening.

And then the third is I think dashboards will be greatly diminished as a consumption mechanism for BI and for analytics, and be conversational. You want to ask your questions conversationally, get results conversationally. And you want to have AI agents analyze the results for you, interpret it, spot outliers, bring them to your attention. And then because we are ServiceNow, trigger workflows. So you detect risk and you remediate, in one platform. Nobody else can do that.

And that's why analytics is deadly important for us. And it comes at a time when every single chief data officer is looking at the old analytics tools and saying their better days are behind them, like we have to think differently in the age of AI. It is a moment of profound disruption in this $100 billion TAM market, and we are positioned to go in with we're bringing insight and action together. That's the Pyramid acquisition that we made 2 months, 3 months ago, something like that.

Okay. That's super helpful. One of the conversations I think we've been having at this conference and with investors in the last few months is the sort of concept of a harness and orchestration layer at companies. And I know this might not be perfectly within your purview, but data seems to play a really important role in sort of the value of describing up these layers and what you can do with data, is sort of a differentiator versus just model intelligence getting better.

I guess how should we think about that with the data sort of offering at ServiceNow? Meaning, does it help you all have -- like does having the data platform make that sort of orchestration harness layer even more powerful to some degree as we -- because the models are going to keep getting more intelligent, that's going to happen. So the differentiation has to happen in terms of your ability to understand data, take actions on data, things like that. So I feel like it sort of feeds into that broader discussion, but I'd love your sort of take on that.

No, no, for sure. I think that we talked about this new context engine that we have, that is a graph of graphs. It combines the traditional ServiceNow Knowledge Graph that we've always had with an identity graph, a user graph. We've also built in sort of something we're calling a Decision Graph, which is because we are sitting on 20 years plus of accumulated workflows, we are able to understand, in a look-back fashion and a go-forward fashion, okay, when a decision was taken, why was it taken? When an exception was made, who made the exception? Did it go through a chain of approval, yes or no?

And so decision traces to figure out why that was done and what the outcome was is context for the AI agents to make smarter decisions in the future. Similarly, we talked about that one version of the truth for your business metrics, because in parlance -- in common parlance, that's called the semantic layer. So we got that through Pyramid. But that's going to fold into our Context Engine as well.

So these are ways in which the data products that we have become extraordinarily relevant to our AI story and to AI adoption with customers, which I think is what you were asking.

Yes. No, exactly. I think we're all asking a question of like we all know the models are getting more powerful, how do you add value on top of them? And I think, obviously...

Yes. So one is the unique context that we have and we provide. And then the second is what you were getting at, which I forgot to speak to, which is this notion of what Bill likes to call the rules and the rails, so the control paradigm and the harness. And I think that extends to data as well. That's what that Autonomous Governance piece will give us, that we're building out. And data.world, the data catalog, is the first piece of it.

So we create these data products that are blessed assets for AI agents and humans to use. And unless they're blessed, they can't be used. That's a harness. That's a control mechanism. In fact, like we -- I wanted to name that, before it got named Autonomous Data Governance, I wanted to name it the Data Control Tower. It can shut down. There's going to be only one control tower.

Only one control tower.

Yes, yes. Standing leg. So yes. But in essence, that's what it is.

Okay. And you all now have a much more fulsome stack of Data and Analytics products right now. Is there a cadence that's normal, I know it's early, is there a cadence like -- like is it RaptorDB first, then Workflow Data Fabric, then analytics? I mean how do you think about...

From a customer adoption?

Yes, from a customer adoption perspective. And maybe it's too early to know that or there's not a good sort of...

There is 1 or 2 patterns. I mean yes, there's a lot of noise in the data, but a couple of distinct patterns are, I think it's usually Workflow Data Fabric first, largely because we are already in 95% of the Fortune 500 doing the take action piece. So they are using the integration write-back capabilities. And so they're already Workflow Data Fabric customers. That's why we have more than 6,000 already.

And then it's about jumping up tiers in our pricing model with them. Would you like to also tap into true zero copy? Databricks, Snowflake, et cetera? Well, then step up to another tier. That's Workflow Data Fabric.

Raptor in the first innings was, "Hey, do I want my workflows to run 10x faster? If so, I mean" -- so the bigger companies with a lot of workload, they're the first to gravitate to it. But with Live Connect, Live Perform, some of the new capabilities I alluded to, I think we'll see more broad-based adoption of Raptor earlier. And analytics is the baby of the family, like it's only just rolling out.

Taken off.

Yes.

Okay. Maybe I got a couple of last ones. But of the data platform when you think about -- there's a lot of things, I think, bringing it in and having it to be part of ServiceNow with the change management database, things like that, is that what's durable? Meaning, I think everybody is wondering what moats are and stuff right now. When you think about your data platform and what's durable, that's very unique to ServiceNow as we think about sort of, you know, everybody is wondering about terminal value and all that in the AI world, when you think about your business in particular, the things that are going to be almost impossible for someone to sort of replicate or replicate easily, what comes to mind?

I'll give you 3 things and tell you why neither of those are the answer to your question. The first is that converge database you talked about, right, where you can do both operational execution as well as analytical execution in the same database without needing to move data, that's hugely differentiated, and which -- can you think of like which -- no one else has it, right, at our scale.

I'll ask a follow-up. Yes.

So that's number one. Number two is the ability to like federate out the process of understanding the data and taking action without necessarily having to move the data over from external sources. That's a crucial differentiation.

The third is the CMDB, which is -- I mean, it's a marvel of engineering, built over 20 years, with the accumulated workflow history that we have that allows us to do the things we can with the Context Engine, right? That, unless you've been in this business supporting 10 billion-plus workflows with trillions of transactions, how are you going to get it. That's a pretty good moat, right? That's the third piece.

But neither of these, and there's probably 2 or 3 more I could probably come up with, but neither of these are what I would put as number one. Number one is the fact that all of these gems are in a single platform. Single data model, single security model, unified user experience for everyone. No one else has that. And that's because Fred Luddy, when he founded the company, made that a defining characteristic of the company. And so that's number one. That's the true differentiation.

Yes. And is that single platform, what do you think about from a customer perspective, is it just like the simplicity of it to some degree? I mean what is -- like if I'm a customer, I'd be like, great, yes, I'm glad it's a single platform. What does that mean to me? Does it mean is it just performance based? Is it the understanding of centralization of data? Like just take it another step further. So if you're talking to a customer about it, why that would resonate with them? I understand why it resonates with ServiceNow, but why would the customers?

Lower cost of ownership. More accuracy in the results. The ability to have a core set of people within your IT department trained on using the platform that can then do, with the same skills, allow you to do magical things in HR, CRM, ERP, IT, you name it, right? So it's the gift that keeps on giving, right? And the ability to say, hey, you set up your security and like you have access to this kind of data, Andrew has access to something else, and suddenly, anything you do in HR or CRM or any of the other lines of business, inherit that.

In alternate solutions, it's all siloed, so then you've got to go buy some other product to stitch it all together. That's not the case when you have a single platform, single data model.

And I would imagine, because of that, the customers that have bought multiple products from you, whether it's ITSM plus HR Onboarding, are they the ones that almost see the value the most? Is it most obvious to them? Are those the easiest upsell customers where they are at? Okay.

100%. I think you alluded to it in one of your earlier questions, is this installed base is actually pretty happy, and it's quite refreshing actually. You go to Knowledge and you just feel the love. And I say that because if you're an installed base play, like Data and Analytics is, it matters. You're innocent until proven guilty. You're given a chance. And that's a big deal. That's a big deal.

One last chance. Any questions? All right. We've covered a lot of territory, so we'll probably end it there. But thank you very much.

My pleasure.

This is really interesting. And we'll see how data ends up in the next year or so at ServiceNow. It will be a lot to watch. Thanks a lot.

Thank you.

Appreciate it. Thanks, everybody.

I was asked to introduce myself before every session because the transcript after that doesn't know who is presenting. So my name is Tal. I'm 6 foot 3. And tomorrow is my birthday. So tell me...

Happy birthday.

Here you go. Thank you. So I introduced myself for the record.

We -- as you know, I cover software and networking, and we recently launched coverage on ServiceNow, and we launched it with a positive view. And we distinguish between -- I'm just starting with kind of 30 seconds of our views just to give a framework for our discussion.

I was just talking that's always...

We started with a positive view because we distinguish between companies that will use AI as a tailwind and companies that will be -- we will see great competition because of AI. Our biggest fear is that the AI labs, the next step for them is to launch applications because if they want to be -- especially those that are going to lose on the enterprise side, meaning they'll be behind, the natural evolution for them is to launch an application and to go into CRM, to go into -- because that's the way to penetrate to the enterprise space.

So the -- when we looked at our entire universe, whether it's Workday or ServiceNow or Salesforce, we identified ServiceNow as a company that is really entrenched, meaning it's impossible, in my view, to replace ServiceNow. It's also impossible to replace Salesforce. It's also impossible to replace Workday, but that's not the point. The point is, can you grow with new customers? Can you grow with upselling and can you grow with AI? And if you can do that, your growth could accelerate. And that's how we identified ServiceNow as a winner in the space of enterprise software. So that's kind of my introduction. I think I took a bad decision to host this in this room. We should have taken the bigger room, I apologize, but it's only 30 minutes and it's your daily workout. So Gina, thank you so much for coming.

Thanks for having me.

It's -- I want to start with kind of -- I start with a softball question, with an easy question. articulate your growth strategy in the context of my kind of initial thoughts on your company, articulate the growth strategy. And if you can speak about 2 things: growth before AI, meaning as if AI doesn't happen, how do you grow with existing customers, upselling? That's before we talk about AI driver and then growth in the context of AI.

So a couple of things. I think it's impossible in this day and age to talk about growth without AI because AI is embedded in every single product now that we offer to our customers. And so to talk about and to think about growth in enterprise technology without AI, I think, is a fallacy. So -- but what I will do is I will bifurcate AI, but it is a huge part of the growth strategy because ServiceNow is the AI control tower for business reinvention, AI built into the platform that, as you say, is entrenched in our customer base so strongly and you think about 98% average renewal rates every single quarter for over 20 quarters consecutively.

Over 20% revenue growth even at $13 billion before any acquisitions consistently at our scale. it tells you a lot before you think about the growth trend about how entrenched and how mission-critical we are in our customer space. The other great thing about us is that we are the trusted platform of the IT organization. And IT and technology is becoming the business for every -- or is the business for every single business, every single customer, every single industry.

And so as you think about growth from here, and we articulated, I think, really strongly at our Investor Day just last month, it's a few different things, right? And so we talked very, very clearly about our 3 big growth vectors being security and risk, CRM, data and analytics. And that's on top of an incredible base, core technology that even our most penetrated product set of ITSM still has so much white space if you think about customers even within U.S., outside U.S. And so it's about really embedding AI into the company, and it's part of each of the growth strategy.

So I can't talk about security risk. I can't talk about CRM. I can't talk about data and analytics without including AI in there because fundamentally, what people have to understand is that AI is the tailwind that will enable a company like ServiceNow to continue to grow at over 20% even at our scale, while at the same time, driving pretty incredible margin accretion.

And so if you think about security risk, data analytics, CRM, then think about EmmployeeWorks. So we did this incredible acquisition of Moveworks, which we integrated the technology into our employee experience within 3 weeks and launched EmployeeWorks, which is Moveworks plus our HR to really be that front door to the entirety of our entire platform.

But for customers, incredible technology, all AI-driven, that really allows their employees to self-service across the enterprise, whether they have questions about HR, IT, legal, security and then add that to -- so that's adding AI to our core. If we think about AI for our core IT, we just launched Level 1 autonomous agents, that are really there to help drive end-to-end resolution on our platform for our most prolific SKU of ITSM, that ability to build incredible Agentic AI into the platform to help our customers drive increasingly complex workflows and get great results, autonomously resolving 90% of issues, drives huge value both to the bottom line and as well to the top line because the value of an engaged employee versus an unengaged employee is tremendous.

That you can repeat -- rinse and repeat for CRM, rinse and repeat for security and risk. And if you think about what customers have been telling us for 2, 3 years now, and telling most people that the #1 barrier to scaled deployment of AI in the enterprise is all around security, risk and governance of the AI in the enterprise. How do we make sure that the AI is doing what it's supposed to be doing, is governed, is running the rules, has the right authority to do the right things.

And by the way, it needs to all be auditable. It needs to be traceable. If it's going off the rails, there needs to be a kill switch. The AI control tower enables our customers to have a bird's eye view across the enterprise of every single asset, AI asset across the enterprise and enables them to see what it's doing, how it's doing it. It gives them -- it enables identity, it enables visibility and then it enables the governance and the scalability across. And so these are just a few areas of really how we think about growth.

I fully agree with everything you said, but I have a question about it. And the question is about competition. AI enables other companies to actually try and be part of the workflow, meaning if you ask any winner, any company, a leading enterprise software company, what is your strength? They tell you we're entrenched into the workflow. Google is trying to be part of the workflow. CRM is trying to now -- because of AI, because of the availability of AI tools, they're trying to go into areas where you are strong. You are trying to go to their areas.

Do you see -- I'll ask it in 2 ways. Do you see increased competition in the areas you're trying to go to? And the other -- the flip side of this question is what makes you the winner, meaning what makes you better positioned to use AI to grow into all these areas?

Yes, yes. So would you believe me if I said the competition was not heavier? Not, right? Competition is fierce. Competition has always been fierce. But yes, competition is out there. What we've been doing and continue to do is ensure that we are staying at the cutting edge of innovation. ServiceNow has always been known as an incredible technology innovation company, organic innovation company. We will not change that.

We've been innovating. We've been building AI into our products since before 2018, right? We had our Pro SKUs that was the first kind of machine learning AI built into our SKUs. So number one, stay on the cutting edge of technology and innovation. We have done that always. We will continue to do that.

What I'd say competitive differentiation and advantage is in the context engine, 20-plus years of understanding the rules and rails of the companies, of understanding the workflows, of understanding -- context of understanding the assets. We are the CMDB of the companies, meaning that we know where all the assets are. We know what they're doing. We know how they're doing their work. The ability to continue to drive that, the large language models are driving incredible innovation and intelligence and intelligence is really important.

Our value proposition, the intelligence piece is less than 10%. Where the value is really accruing is on the context, is on the execution. Intelligence without the ability to act upon it, it's just really, really good, pretty darn expensive advice. You need to be able to do something with that advice to be able to do something with that intelligence. And that's all about scaling context execution, the action layer. And so this is why we continue to have 22% growth at our scale. While we gave an initial guide for our AI of $1 billion by 2026, we just increased that to $1.5 billion. And the conversations that we're having with customers are all about how do they use the platform? How do we build more AI into the platform to help them drive even greater efficiency?

And I'll tell you the proof point to customers when I can go in and say, we're customer 0 on all of our AI products, and I've been able to, over the course of 2025 and 2026, drive $300 million of savings to the bottom line. We have over $500 million of actual savings, some of which I've reinvested back into the company. With $300 million of real tangible savings from our AI driven to the bottom line, when we can show that to our customers, that's a compelling value proposition, and I'm probably one of the best people that they want to talk to when they look to buy.

I'm paid for expressing views, so I'll tell you my view, I believe you, by the way. The concern -- and that's a question, not a statement. The concern is that AI and agentic AI will happen, but it's not a very near-term phenomenon, meaning companies are talking about it. We see companies investing in cybersecurity now to protect for it and prepare for it. What is the risk that spending on the existing business is not related to AI, your regular customers, what you're doing with IT, what you're doing with, what's the risk that spending slows down ahead of AI, that companies invest less because they need to shift money in order to prepare for AI?

Yes. I get that question a lot. So a couple of points, right? Growth continues to be strong. Demand continues to be strong. What we're seeing -- and by the way, I just talked about $200 million in savings this year, $100 million last year, that's all from less hiring that I've had to do because of AI. So even internally, the ability to -- the savings isn't coming from IT budgets. The savings is coming from labor pool.

So the ability to utilize like the dollars -- some of it is coming from historical IT budgets, but a big chunk, C-suites, boards, CEOs, CFOs, the mandate is to really think about their AI strategy, and they need to lean into it. So -- some of the budget is coming from historical IT budgets, but not all of it, right? There are separate budgets coming because the understanding that this AI super cycle is really going to drive significant benefits, top line and bottom line to customers. They need to start building and they need to start building now.

And so we're seeing budgets come from many different places depending on the customers. And I know you have a question, I'm sure, on the demand environment and spending environment. And what we're seeing is not a slowdown in spending in IT. It's a prioritization for sure. And the core of what we do and the reason why ServiceNow is such a winner in this space is because we are a platform across the enterprise. So when you build AI into the platform and you then expand it across the enterprise, you're getting that value and those functionality and that capability, whether you're in HR, IT, finance, legal, support and the ability to really drive that platform value for customers has been significant.

So let's make an assumption. Assumptions are that budgets are not going to increase across the board, all of enterprise, budgets, if the revenues do not increase, budgets will stay the same. So that means the investment for AI will have to come from something else. And the question I have is when you combine everything, when you combine everything you're doing and you combine the AI, do you think that you can maintain the growth, meaning do you think that spending overall on what you're doing will actually expand and you will take the share of the pie from something else?

Yes. I mean if you look at a lot of the banks, a lot of the industry analysts do CIO surveys every year, right? Are you going to spend more or less on A, B, C, D, E, F, G vendor? And 90% of them will tell you that they expect to spend more on ServiceNow.

Got it. Okay. Of your target areas, you have multiple target areas, can you rank them, again, qualitatively, not in numbers, but can you rank them just to understand, where do you see bigger opportunities where -- versus where do you see more maybe later opportunities or smaller opportunities?

Yes. I mean I won't rank them because I'll get in trouble by my teams back home. But to your point, if everything is a priority, then nothing is a priority. And so the growth areas that I talked about earlier around security and risk, around data and analytics, around CRM, around employee works combined with Moveworks.

Those are -- obviously, AI baked into everything. I don't like to talk about AI separately because it is baked into everything are the key priority areas for us. Financial Analyst Day, we talked about the growth between 2026 and 2030 of security risk, CRM and data analytics being above 25%. We talked about a revenue target between $30 billion and $32 billion in 2030. And so those growth areas are probably the top where we're focused. But that doesn't mean that our core is not hugely important to us and that we continue to build AI into everything.

Just think about the launch of the L1 specialists. A lot of our L1 specialists are all about our core IT functionality. And so just because the growth is probably not as high in our more mature products, it doesn't mean that the focus is not as important. Our core is who we are, and we'll never stop investing behind it.

Another aspect of AI or deployment of AI is the question of pricing. On one hand, most of the companies I know are announcing workforce reductions. And on the other hand, your historical pricing was seat-based. How does it -- how do companies -- how do your customers make the change from seat-based to consumption-based? How do you help them to make the transition?

Yes. So the hybrid model of pricing that we've put in place over the last couple of years is a great way to help them in the transition. And by the way, help me in the transition as we think about predictability for revenue flow, right? And so the hybrid model allows a ton of predictability for the customer, but it also allows -- if they -- if them to not have to overcommit all upfront, right? As AI is in experimentation phase and is moving to scalability, they don't know what they don't know. There's articles out there right now about token budgets and people blowing through the token budgets in a quarter.

Let me tell you, every CFO I talk to is really freaking out about that right now. And so how do we think about -- the hybrid model allows them to have a much more predictable base. But if they start to really consume more, we're able to take the value from that, and they're able to consume as they go.

And so as we think about what the monetization model looks like, what I say to everyone is we were the first one to announce this hybrid pricing model. Finally, a lot of people are copying it. Fantastic. We will always be on the front end of how we think about enabling our customers to get the most value, but also for us to be able to monetize the value that we're providing.

And so for example, when seats end up being lower because AI is driving such incredible productivity, well, the only reason why they're able to lower seats is because they're using the AI. Well, we monetize the AI, right? So the more AI that's being consumed, the more value that we'll get. And then we talked earlier about accessing that labor pool of funds, right? If you're able to reduce labor by 65%, you can increase technology by a whole hell of a lot and still be driving significant value for our customers, where our customers are very happy to pay more for the technology because at the end, the value that's accruing to their bottom line is much, much greater.

How do you monetize the AI opportunity, meaning not from a pricing. We discussed the pricing, but rather what kind of products? You spoke about control tower. There are other products. Can you -- there are probably people in the room that don't really know what you're offering. So maybe this is the opportunity to explain how you go after the opportunity.

Yes. I mean it's all about innovation, right? So we talked about AI control tower. We talk about Veza being the place where you're able to have identity control over all assets, human and nonhuman. Any finance person knows that one of the big issues always in an organization from a cybersecurity perspective is identity risk. It was really, really hard to manage that with humans. Can you imagine how complex and complicated it is with nonhuman, right? And so that ability to really manage identity and then visibility across the estate of not only your physical IT assets but now you're digital, hugely important, that's Armis.

Think about the autonomous agents that we're building within our product set, the L1 specialist for technology. We're doing the same for CRM. We're doing the same for Employee Works. So Moveworks combined with our employee experience is the best of both worlds. I had this great conversation with someone internally the other day. And so the biggest competition that Moveworks had was them people not doing anything, but Moveworks combined with ServiceNow, the conversations that their salespeople are having with customers is so robust and the sales cycle is accelerating pretty dramatically. Fantastic. So it's all about continued incredible innovation.

When we went public how many years ago, right, Gartner, I think, had our TAM at $1 billion. Right? It's on $600 billion now, not because the market just expanded. Some of it is market, but we didn't sit still. Like we are known for our innovation. We moved out of IT into HR, into CSM, into legal and procurement and office of the CFO. So it's all about continued innovation and continued product launches and making sure that we're building AI into the platform and into the products, not bolted on, on top, right? So there's no integration issues. There's no complexity, right? One of the reasons why we've been so successful is our one data model, one orchestration, simplicity and not putting complexity on our customers.

Why was it important?

So I'm a cybersecurity analyst. I understand the importance of cybersecurity. But cybersecurity was around your solution for 20 years. Why is it important to get now to cybersecurity? Why did you make the acquisition? Why is it more important in AI than it was before?

Yes. So first of all, we had a security risk business before, it's over $1 billion. So this isn't like, oh, ServiceNow decided to move into here, right? Because security workflows are a big part of the enterprise, right? I'll go back to the comment I made earlier. Over the last 2 years, the biggest comment we heard from customers about the obstacle to scale deployment of AI in the enterprise is all around security and risk and governance. All of those security issues that we had with human identities with humans just got multiplied 100 times in the world of AI.

When you have Agentic AI deployed scaled within the enterprise, the attack surface just grew significantly, right? And so how do we help our customers think about secured governed AI scale deployment?

Execution and workflow is a really big part of it. Security and governance, so, so, so very important. If it was important before, it just got 100x more important because the attack surface is so much larger.

But is it the same buyer, meaning the same buyer that is buying ServiceNow also buys security? Or is it a different department and you need to develop new relationships and...

Yes. So one of the reasons why you buy an incredible cyber company like Armis, like Veza is because they are very connected to the CISO. Arguably, even our prior security and risk products, the CISO was part of that conversation already. And in most organizations, the CISO rolls up into the IT organization.

So it's definitely very adjacent to what we've historically always done. That being said, we also work with the CHRO with our HR products. We also work with the Chief Procurement Officer for our procurement products. We also work with the COO on customer service. And so our buying center over before AI has expanded much more broadly over the past 5, 10 years.

Yes. Let's talk about the numbers a little bit. You have expansion plans, AI helps on expenses. Your margins are extremely strong. Lots of opposing forces. Take us through your margin journey, your plans for margin journey for the next few years.

Yes, yes. So we have historically been on a trajectory of at least 100 basis points of expansion in margin every year, and that's before AI. And that's because of the inherent leverage in the organization, right? One platform, the ability to drive innovation into products across the platform, not siloed within specific product categories has been a huge differentiation from a leverage perspective. On the go-to-market side, the same thing.

And so there's innate leverage even in the initial model. If I think about from here to 2030, that leverage just becomes even greater because the ability of AI to help drive incredible efficiencies on the innovation and engineering side of things as well as across the enterprise. And so the ability to absorb margin dilution from the acquisitions we made within this year, all by next year pretty remarkable. But a lot of that comes from the inherent leverage in the initial platform and then AI built on top of it. I talked about the $300 million over the last 2 years built that will only continue to grow.

Right. And the hybrid pricing model, what's the impact of it on margins?

The hybrid pricing model, so at the end of the day, the hybrid pricing model doesn't have a huge impact on margins but does have an impact on margins a little bit. So you would have seen a little bit of pressure on gross margins over the last couple of years. So historically, we were like 95% our own data centers. We've been slowly migrating our strategy to use more hyperscalers. And so the hyperscaler margins, especially as you build, are our margin profile for our own data centers was best-in-class. And so there's -- it's a little bit more expensive, especially as we scale on the hyperscaler side.

As we grow bigger, that margin dilution comes down a little bit. You have a little bit of compression from AI. You also have a little bit of compression from our impact business, which is our business that provides incredible -- it's all about getting our customers to value quicker and deploy quicker. And so we have technology that helps them think about autonomous deployments. Think about also having L1 support to help drive implementation, has a little bit of impact on gross margins, but we've been able to offset all of that with the operational margins on OpEx.

And so you'll continue to see -- I think we gave Rule of 60 from a margin perspective by 2030, our margins continue to accrue. I feel really strongly that ServiceNow has been an incredible bellwether for a company that's able to continue to grow at over 20%, so best-in-class high growth and best-in-class margins at the same time, and you'll continue to see us do more of that.

Great. We only have 2 minutes left. I'm wondering if we have any questions from the audience. We have a mic to pass around. No. I'll continue, you have about 90 seconds to raise your hand.

I want to ask you about -- so it's very easy to ask managers to talk about the growth initiatives because that's what you do day-to-day. I want to ask you the flip side. What are your challenges? What are the things in your view, if you think strategically about the company, what's the challenge of the company for the next 3 years?

Good question. A couple of things. So number one, I'd say that we have a lot -- and I'll turn it around into a growth opportunity. But historically, we've been underpenetrated internationally. And so as we think about growth vectors outside of the U.S., we have a lot of white space to go after. So we've been investing there, and that's going to be a huge area for us.

And then the second piece I'll say, also part of the growth opportunity for us is deployment, like how do we get our customers. We feel so strongly, we know customers who deploy and get to value fast continue to expand even faster. So what are our opportunities to ensure that we're getting our customers deploy it as quickly as possible. We're continuing to invest in there. I talked a little bit about autonomous deployment, using AI to seamlessly help a lot of the journey upfront to really allow our customers to get the value faster because that is flywheel of consumption, right, the more they deploy, the more AI they use, the more capacity they generate, the more value they generate, the more they will buy and the more value they will get. So it's a huge area of focus for us as we think about getting our customers to value as quickly as possible.

Great. Gina, thank you so much.

Thank you so much, Tal.

All right. Perfect. Why don't we go ahead and get started. Thank you, everyone, for joining us. Amit, thank you so much for being here.

Yes, of course. Thank you for having me.

Here we go. For those who don't know, Amit is the President, COO and Chief Product Officer at ServiceNow. Before we get started, a couple of disclosures. My name is Arjun Bhatia. I'm the research analyst here at William Blair, who covers ServiceNow. I am required to inform you that I personally own shares of ServiceNow, and a complete list of disclosures and conflicts can be found at williamblair.com.

Okay. Let's go ahead and get started. So I am very much looking forward to this discussion. There -- obviously, the big debate right now that everyone is going to be focused on is the AI debate in software. And there's sort of 2 sides to this camp, right? One is sort of AI is going to disrupt incumbent software vendors and the other is it's a huge sort of opportunity. You've sort of at ServiceNow launched a lot of new AI capabilities, a lot of innovation on the AI front. So for generalist investor, which I think there's a lot of them in this room, who doesn't maybe live in this enterprise software world, just explain why workflow orchestration, the position that ServiceNow has, is a tailwind to -- or benefits from AI rather than is being disrupted by it? And maybe you can touch on your sort of moats in that answer.

No. Thanks, again. I think it's a definitely important question. And maybe for people who don't follow enterprise software or you understand how enterprises use software, it's a pretty complex environment as many of you -- whoever have been following it. There are a lot of different disparate systems, which needed to be connected, which needs to be implemented and orchestrated on a regular basis as well as there's a lot of versions management, so backward compatibility, forward-looking compatibility and very integrated in terms of how those things operate.

ServiceNow has been in this business for 20-plus years, really managing that various different environments customers have in their enterprises to make sure their business run efficiently, predictably as well as give customers the outcome they expect. So that software, which we've been building for many years, the platform we provide is very integral to every enterprise out there, all the Fortune 500, if not all the Fortune 2,000. And good thing we have done over many years with ServiceNow is that we keep on innovating on the platform. It remains ahead. It keeps up adopting latest new technologies to make sure customers don't have to worry about doing it themselves. Because what it allows them to do is as they upgrade our software, they're getting the latest IP, latest capabilities, latest innovation in the same platform without having to learn something new themselves and not having to break anything which exists today. So it keeps the business running intact.

And with AI, we're doing the same thing. AI is definitely a great technology. It's very, very helpful for automation as well as be able to do things much more efficiently. So we brought AI into our platform today for a couple of years already, and we've been delivering that as integral part of our platform. So customers, when they upgrade or when they take our latest software as part of their normal day-to-day jobs, they're getting the value of AI with the idea that it works in the existing environment, so you're not breaking anything while future-proofing you because you're getting updated versions of capabilities to make sure you're getting automation, you're getting efficiency gains, you're getting revenue growth as well as bottom line improvements as well. And it is something which everybody is used to.

So ripping and replacing those things, which is what I think the narrative out there is that you can go and build anything because software building is becoming easier. Software could be built before as well. People didn't try to build custom software after packaged software became much more better and made customers' life better long term. Similar things are happening with AI now, right? Because you can always build something, but building part is very, very small, right? It's 15% to 20% of your cost. It's the maintenance, the governance, the security, the compliance, which is very, very important for all enterprises. You can't operate something in an environment which you can't predict, you can't be secure, you can't be compliant to all the regulations.

So what we bring in our software is the value of AI, but also the value of all those different things, which people think that it is not needed when you are thinking of consumer software. In the consumer world, you probably never have to worry about it, but enterprise, you do need to care about it a lot. And that's the work we do, heavy lifting, building, as I said, is 15%, 20% of your cost, but the maintenance and upgrade as well as the compatibility, a huge amount of very hardening work required, not sexy, not exciting, but you have to do it. And that's where the moat for us comes in because we know how enterprises run. We know how they operate, all these systems which need to be connected and how do you get the effectiveness out of it, but at a very good value as well. Value creation is happening in our software as well today.

So we brought AI to our platform. We've been innovating. If you look at the technology stack we have today and the platform we have, is as modern as it gets, better than pretty much any other vendor out there, while we're preserving the value customers expect from these products without having to rip and replace. I was using an example earlier, like, just because you can grow vegetables in your backyard, it doesn't mean you become a farmer and stop doing your day-to-day job. Same thing is happening here, like people can say, you can build software, but why would you do it if it's a software which you are using today, can do all these things at the same cost, if not better, and give you the value?

And that's happening. If you look at our AI business, it is growing very fast, and it continues to accelerate because we're innovating while preserving the investment customers have made. So there are a lot of discussions we can have around it, Arjun, but I think the reality is that these enterprises do require something which gives them peace of mind, gives them control, gives them visibility as well as the innovation associated with that. And we bring all of that together for ServiceNow today in our platform. And that's why we continue to please our customers and keep on growing.

And so in that, like, you're the domain expert in all the different fields that you serve and all the departments that you serve inside the enterprise, and that's where you're able to stay a step ahead essentially of what a customer might build themselves because they're not an ESM or an ITSM or a customer service.

Yes, good point to make. I think -- no doubt, I think the other part associated with that and some of the -- set the context, one of the things in enterprises is not like everything is documented. As many of you in your businesses today, a lot of the content out there, the document about standard operating procedure is pretty partial. It's a very small amount. A lot of things happen outside the documents, right? Exceptions, who approved what, why they approved it? So our business process which we are running inside ServiceNow is collecting.

We run today 100 billion workflows on ServiceNow platform for our customers and 7 trillion transactions every year, is growing at 20-plus percent. So we're collecting a lot of context about how a business decision was made and why this business decision was made. And that data, all this related content is bringing into something called Context Engine, which goes into -- on top of all these AI systems to really enrich it, but also make a decision which is a little more guaranteed than any system can do otherwise, right? So our outcome usually 90% to 100% accurate versus all other systems are 50%, 60% because they're just depending on some documents they've read and try to run a workflow.

We are doing it with the context we brought in, the data we brought in and the domain expertise we have. So things like employee onboarding, it's a very good example. A very common thing, right? If an employee joins a company, you have to go and update maybe 20 different systems in one company. Some other company will have 17 different systems. And then it needs to be also done based on what department you're joining, what systems you require, what exceptions you require, what you need temporarily, what you need full time. So all that stuff has to come together when you want to get an employee onboarded. We can get an employee onboarded on our system in less than a day and make them productive next day. If you look at -- if you do this from build mindset or something which you don't have the domain or context, it might take you 2 weeks. It means your employees are unproductive. And half of things will not be right, so that means you go redo it again. So by the time employee gets going, it's a year -- a month or 2 months wasted for that.

That's kind of the example of things we see. That's just not employee onboarding, resetting a VPN access or giving you access to something temporarily if you go into China, for example, with the right laptop. So HR-related PTO requests, how do you resolve all this stuff? The context we bring in makes a big difference in the domain we bring in. And those systems are now AI-enabled, completely agentic and lets customers really get the efficiency of AI, but with the guardrails and the harness around it, which makes it much more realistic and valuable to our customers.

And this is sort of the system of record advantage that you have. I mean you've been serving your customers for decades, and you've sort of built this context over that time. And one of the questions that I always get from investors on this is, how much of the data inside ServiceNow is ServiceNow's versus the customers'? And when you're bringing this context in, is it your own sort of proprietary elements that you're bringing in, in addition to the customers' records? Or how does that work?

Yes. I think the customer data is usually not huge, right? I mean this is information, which is in any kind of system out there, which you can easily get access to. It's a lot of the running -- the runtime is where the data gets generated, right? So the metadata we create related to a particular process is very unique every time we run a transaction, every time we run a workflow. And that's the Context Engine. It's taking a lot of the -- it, of course, applies the customer data and the relevance to that particular information, overlays with the metadata and which is very distributed, by the way. It's not like we got one table. It's thousands of parameters constantly being updated and constantly being collected and related to all the different systems you might have.

Plus, we have a system technology called Workflow Data Fabric, which is also connected to all the different data warehouses. Today, no company has everything in one place. Everything is very distributed. And Workflow Data Fabric connects and does federated information collection, overlays that with the metadata we have, which is our IP, and makes decisions real time to get the outcome. So the data is ours. The metadata, which we create, the context is really dependent on that one. And that's not available to anyone. And that's why, as I said, a lot of time people miss this idea that you can do the work, but how effective the work has been is a really differentiator, right?

As I said, if I finish a task and you never have to reopen the task, I'm 100% effective, but if it's something you have to reopen every other time, that's really waste of time, and it's not efficient, and it's costing you a lot more money, not just the cost of software, but the business time.

Yes. Okay. So you have the context, you have the domain expertise, and you're building the agents. I want to talk about one announcement that you made at Knowledge, your customer user conference, which is basically opening up the platform to third-party agents, right? And we see a lot of agents out in the marketplace, and you've essentially made the decision that this context that we have in our system of record, we will allow customers to power third-party agents with it, something that they want to build with Anthropic or OpenAI or anybody else out there. What was -- maybe just talk about the sort of the rationale behind that decision? Because you're obviously building your own agents as well in a vertically integrated stack that you're trying to provide to customers.

No, we've been always an open ecosystem. One of the reasons we've been successful for our customers is, one, that we understand that customers have a very disparate and heterogeneous systems. We cannot say everything needs to be like us and only thing which -- everything has to be through ServiceNow. You have to work in thousands of other environments. So we've been always thoughtful about that. And openness has always been core principle of the way we build software.

On specifically in terms of the idea of that how do you get access to a system. See, in the traditional days, everybody use UX, right, UI, you log in and you try to do things. Nowadays, there are going to be also agents calling into a system. So it's not only humans interacting through a user interface, but also agents now asking you to do something, maybe asking for data, but in our case, really asking us to do something, take action. We are really a system of action. So the way we think about this is that you can also ask when a particular system is -- when a request comes in from an employee, it can come from Claude Cowork, it could come from Copilot, it could come from our own user experience or an AI agent asking for it. We need to really provide the value to our customers that you can now take that action and guarantee the outcome. So that's the experience layer on top of us through agents or UX we provide. That's the headless -- or we were going to call it -- we call it Action Fabric.

And the idea is not data access. It's really action, taking the task, finishing the task. So if you want to now onboard an employee, an agent can tell us, please onboard this employee in this -- for this particular company, and we would take the full work, and get that outcome back to the agent, right? So we're not giving them the context data. We're giving them the full work. And I'm doing that work. That's why my value to every enterprise grows considerably. On top of that, it opens up more aperture for us, not just to our UX. Now any other system can also get access to us. So now suddenly -- as you said, there's an AI tailwind, and for us, it's definitely, because now giving me ability to take the IP I've built for years, understanding of the context and the data and the integration I've built, now open it up to so many more use cases.

So I don't give them the context by itself. I'm not giving them access to like, "Hey, you can ask." The context engine, which I built, the data is so difficult for anybody to understand because it's really our unique IP and our secret sauce, they can't use it themselves. It is what we overlay on top of an agent, and we do the work for you, and that's what they pay us for. That's how we monetize it, right? So we want to open up the opportunity for us broadly with all the work we have done through UX, our UX, third-party UX, agents, whatever it is, we don't really care. End of the day, our job is to really finish the work for our customers.

Yes. And it seems like it's a TAM expansion sort of motion for you, that there's generally more agents getting created and used in the enterprise because in either way, you have -- you're sort of benefiting. And from a financial perspective, even if you are powering these other agents that are outside your platform, that is a monetization.

100%. I think you're right, we are opening it up, but also like the reason Anthropic is working with us is because the Claude Cowork, for example, when they want to have somebody to do something for them, they need someone to do the actioning part of it. The Claude Cowork integrating with Action Fabric gives that full end-to-end. Versus they would go and do something in a particular system, the security issues, compliance issues, tracking issues as well as the employees should not be going and updating things without permissions.

So we put a layer. So something we have launched, and I think you saw it at Knowledge as well, AI Control Tower. We launched it last year. Giving customers full visibility and control over every AI system they have, not just ours, but third party, right? So we understand what Claude is doing, what the OpenAI is doing, what Gemini could be doing, what SAP Joule is doing, Salesforce, and we discover all those AI systems in the company and put it into this central control plane. We were doing that for access inside the company before anyway for enterprises, right, any hardware and software. And now you have full governance layer, cost structure management in terms of how much you're spending, which department is spending what, what models you might be using, but also all the security issues you might be running into.

And then we bought this company called Veza, which does this access graph. So it's nonhuman identity is becoming a big issue. And what that Veza does is it really manages nonhuman identities and ensures they're doing nothing wrong in real time. And that goes into AI Control Tower. We have full visibility across everything now. Customers can see that real time. And then we open up a platform for all these different use cases. We have full ability to now manage the security, the compliance, but also finish the work for them. And that is where the monetization becomes much more bigger. And we believe integration with third-party systems makes sense because we have the visibility and control, but also the actioning part of it.

Right. Can we talk about just pricing model real quick because I think this is another sort of narrative that's out in the market of -- historically, you've had multiple pricing models, but a lot of it's been seat-based. And now there's concerns about whether seats go away or the seat growth algorithm changes. But you have all these AI capabilities, including powering third-party agents. What is the pricing model for that? And how do you evolve the business? And, I don't know, do you see that as a challenge? Or is it...

Yes. No, I think we've been evolving our pricing. I'd say one thing we have to be always aware of is what are the customers -- where -- how they want to use our products and what is the best way to kind of show them value and monetize, right? So we have to be balancing on that one. So we have changed our pricing over the last couple of years. We introduced something called Pro Plus and Now Assist as a higher-end tier providing AI capabilities in a hybrid pricing structure. It's a combination of seat, but with some idea of something we call Now Assist entitlements. So you burn down that Assist. It's entitlement in terms of number of volume of Assist you get, and customers have predictability in terms of what the ceiling is but also flexibility in terms of how they use it and when they use it.

So we have evolved that pricing structure for our premier, higher-end SKU a couple of years ago. And it's been very, very effective business, as we have said, $1.5 billion this year planned ACV and growing very fast. And that hybrid thing has -- hybrid pricing structure has really resonated with our customers, and it allows us to really add more and more capabilities. So what we've done now going forward is now taken that idea and apply it to all our SKUs. We have a whole full set of AI SKUs starting from the base SKU to the higher-end SKU, functionally graded. So it's a different level of AI functionality depending on the SKU and allowing customers to now use AI Now Assist fungibly across all the different tiers as well. So that is the structure we're going towards.

And if you look at our business now, and we shared earlier that net new business, 50% of our revenue is non-seat based now. It just shows you that our change in terms of how we've been monetizing is more reflective of how the world needs to be, right? So we're not completely dependent on seats. There will be seats always, but there also needs to be another consumptive element, but with predictability, not this idea that I have no idea how we're going to pay this month. That doesn't work. I mean this idea that to go away and spend as much as you want and it reward you, that's silly and doesn't make sense long term.

So we are being very careful and thoughtful about how enterprises work and how customers think about it. And this idea of Now Assist burn-down with some predictability is what we're doing now. So our pricing structure is very straightforward now. It's across all our SKUs. So our go-to-market becomes very simple. Customers get AI across all our products. There's no idea of non-AI and AI because everything needs to have AI as a base building block. But then you surround it with a lot of deterministic and core capabilities around it and give the customer outcome with some prediction.

Yes. It feels like -- yes, it makes it a lot easier for CFOs to implement AI in that way as opposed to -- I think there's been some reports of individual employees running through tens, if not hundreds of millions of AI credits.

I think it's amazing that we can get away with that.

Right?

It's illogical.

Right. And maybe just thinking about the agentic capabilities that you're building on ServiceNow, on the platform itself, what do you think is the sort of the advantage? Or how should investors kind of perceive the advantage of you providing a full sort of vertically integrated stack with agents, data, governance, compliance, all in one SKU? Like, do you think customers and enterprises are more likely to go that route? Or are they more likely to put together external agents with your sort of infrastructure?

Yes, I think there'll always be interoperability required. I don't think there's ever going to be any enterprise that uses one product ever. It will be multiple products, and everything will have unique needs associated with that. So I do believe even the orchestration layer, there will be multiple orchestrators. You will have to integrate between different systems. We do this through agent to agent, but also from the business process level. There will be some unique build you might do. If you're a manufacturer, you will build your own supply chain, which is more your IP. Sure, you'll build it in-house. You're building it before, you might build it with AI. Makes sense. But you will need to connect it to your core operational systems, which is what ServiceNow is very good at.

So if you're running your IT department, your HR systems, your finance systems, your customer service, which are more operational, there's some uniqueness, but it's usually a little more homogeneous between companies, which we can provide at a much scale, but it will integrate with your unique IP, build in-house or third party. So that's the future going forward. It's agent to agent, no doubt. But in this idea that you will have different layers combined together. So when we build this full vertical stack, it's going to make our product much more, I would say, AI native.

So the whole stack is very modern, and it has to have all the elements you require in the AI world. You can't just say that I will build pieces of it and then depend on somebody else to complete the story and not provide a solution. Eventually, customers want solution. They don't want piecemeal. They don't want the spare parts. And the spare part world in enterprise software has been done many years, many times and always has failed because nobody can keep up. And you take your best people who should be building a business, building software, which is not needed, where you can have somebody who is much more uniquely qualified to do that for you, right?

So that's, I think, going to be the future where people will still buy solutions. And that's why we introduced something we call AI specialist, this idea of autonomous workers. So eventually, what people are trying to do is reduce the amount of human labor, get automation, reduce the time to fix or fulfill some issue. And that's what we want to provide with autonomous AI agents and take out the human labor cost, but also do something which used to take 2 days, do it in 20 minutes in a predictable fashion. And that's the solution they want, then why would you take AI agents and cobble them together yourself if I can give you a higher-level solution on top of it at a better price and reduces your labor cost, right, with a much more prediction? Because everything doesn't have to be AI. You can have things where like you're updating a database record, you can do that with just normal calls through API. Why do I want to burn a token on an LLM, which pricing might be going up every year, who knows?

So you need to be smart about how you build your software stack and be understanding of what part you want to do it through a traditional software mechanism, what you need AI for, what you use ML for, where do you -- which model version also use? Everything doesn't have to be Opus 4.7, right? You have to look at tiering where you need small models, cheaper ones, while you also build IP on top of it, around it. So that's how we're building our top software stack. It's not this idea that it's fully vertical, idea that everything is owned by us, but we connect it to everything else.

Yes. And how do you -- in that, sort of, how do you view the model layer? Because you have -- you mentioned it's not one model for every use case. How are you viewing -- and you have partnerships, I think, with pretty much all the frontier labs, but you're using multiple models, I presume, and just talk about how this goes?

We have model agnostic, to be clear. I mean we provide customer choice. Just like across the whole stack, we always have this idea of you can run with any -- on top of any system of record, you can run on top of any cloud, hyperscaler or CoLo or private cloud, for sure, any model, any data layer as well as any engagement layer now, right? And any tool you can build with Claude Code on top of us. We have a build agent.

So we've been always idea that very open, but any kind of choices available to customers. On the model, it's the same thing. You can use any model underneath. Model for us, LLMs, the frontier labs, are probably 10% or 8% of the full stack. 80%, 90% of the IP -- 90-plus percent IPs we build. That's where the differentiation comes in. And a lot of these models, in some cases, are interchangeable. So whenever the pricing changes, we look at which is the best pricing. For some example, customers might choose something. They said we standardize on this. We want to use that. That's okay with us. There might be some sovereign requirement. Some models can't meet.

And there are also use cases where you can -- we do a lot of optimization. Through AI Control Tower, we know the cost structure of everything, who's using what. And then we also look at where the cost structures are to understand which model to use for a particular use case. So we're switching those things underneath the covers. Just like -- I think, if nobody cares what chip you use underneath your cloud, most of the time, same thing will happen to the models, right?

As long as the results are there.

Yes. As I said, the autonomous AI specialist, if it reduces my ticket volume, fixes something in 20 minutes versus 2 days, why do I care what I use underneath? That's, I think, over time, right now, this excitement and the FOMO going on that everybody is looking at it every day in terms of features and all this stuff, is kind of even out.

Right. And you're kind of at the forefront of at least getting AI into the enterprise and sort of top-down processes. But I think there's maybe a dispersion of how ready enterprises are actually to adopt AI. So talk about what are you seeing in terms of where are we in the adoption process today? For the customers that have adopted it, how are they thinking about ROI? Because they are at least increasing their tech spending. So where does the return come from on AI adoption?

Yes. I would just look at from -- like, last year, for example, early last year, when we were talking to a lot of -- agentic was becoming kind of what people wanted to do. And the technology was getting better. We had an agentic solution, but the customer didn't know. Whenever we used to go and talk to them about it, like, first, they don't know where to start. What use case makes sense? Second was how do I do it? Third thing of worry for them was, is it secure, is it compliant, can I have visibility? So that was the barriers last year -- early last year. That kind of was the kind of how we thought about AI Control Tower because what we wanted to give them is like, let's take out this governance, security, visibility issue off the table first.

So when we introduced AI Control Tower, our customers and the CIOs started feeling comfortable, "Hey, I can implement agentic without having agentic go haywire and break systems underneath," right? I mean you've seen some examples out there like PocketOS and all where the whole database and the production system got wiped out because you had no control. So that was one part. So we did that early -- middle of last year. We launched AI Control Tower, very successful.

Second thing we see from adoption perspective, as I mentioned, was where do I start? So what we did was we did 100 different use cases, agentic frameworks with like a point-and-click kind of mindset, right? You can get going very fast in a few weeks and give them a very prescriptive ways of getting going, right? Do you want to start with incident management? Do you want to do resolution planning? Do you want to do triaging? Do you want to do SecOps? So we need to find those use cases, say, "This is -- you're currently running this system. This is the agentic version of it, and we can get you live shortly with this control around it." And that took over the next barrier, "where do I start?"

And then third one was how do I go doing this? We also brought in some FDE mindset. This is not like armies of people every day available to customers. It's for a short amount of time, taking the first use case and getting it live.

Specialist engineers.

Specialist FDEs, yes, forward deployed engineers, which are basically black belt, very heavy understanding, deep understanding of AI and our products, and they can get our customers get going in a few weeks, so that they can take the barrier out and show them the value, show them the ROI. We do calculations and all kind of stuff. And once we saw these 1 or 2 use cases go live, it was just open gates stuff, right? Any customer like, "Oh, I want to do this for this one. This, this one." So we start seeing the volume go up, right? And that's really the adoption pattern we're seeing.

And this year, if you see it, the amount of customers now doing agentic with us is pretty high. The volume has gone up considerably. That's why we felt confident to increase our plan for Now Assist to $1.5 billion, 50% growth over what our plan was because of the volume of agentic going up and with the AI Control Tower surrounding it and the security. So we invested aggressively on the security platform to make sure customers feel comfortable adopting this thing because that's a big area of worry. So that's the, I think, the trajectory now we're seeing.

And is it -- I think you mentioned volume, which I'm trying to figure out, is it the breadth of customers increasing? Because there were -- last year, I want to say a lot of customers that were in pilots that probably moved into production this year. But then are there more customers and enterprises coming into the pilot phase and looking to expand?

So yes, we track that kind of the whole pipeline, right? There's a lot of POCs and then we do pre-prod and prod. I would say 70% of our customers now who are doing AI are in pre-prod and prod. So they are going very fast on the production environment, right? The usage, that's why it keeps on going up because now they're starting to see multiple use cases. Usually, the one use case unlocks, then you suddenly get 4 or 5, the multiple department wants to get involved. And that's where I think the production systems have gone up a lot more than last year. I think there were a lot more experimental. This year, I think most of the case discussions we're having with our customers are pre-prod and prod, pre-production and production, so that they can start seeing the value of the investment they're making in this area.

And maybe last one for us to close out on. You have a target out for -- a revenue target out for $30 billion by 2030. Just talk about -- now that you are seeing some of this traction, on AI. What role does that play in that long-term target? And where are we kind of in sort of getting to the milestones -- the interim milestones to get to 2030?

Yes. I think we are very confident about our 2030 plans. I think this is the base case we laid out based on -- we want to be also very prudent to make sure that we know what we can predict and how well we can do in that. So the $30 billion case for 2030, which doubles our business by 2030, is kind of the base case we've laid out, right? So we do believe we have all the core products, very differentiated, well liked by our customers and a TAM which keeps on increasing. There's also, I think, our expectation -- and if you ask Bill, $30 billion is definitely not even to think about. Much more opportunity in front of us, and we'll get there.

The thing which will drive this, as you said, is what, kind of, gives us the confidence. One, I think we have a lot of unique IP and very modern platform, and it's getting adopted very fast. I think if you look at -- now we combine the things we have, AI with workflow, with data. And our data business is on fire, and it continues to grow considerably. And then you combine that now with security, which we have invested aggressively, and we have -- CIOs and CISOs are 2 big buying centers: CIO #1; and CISOs, chief information security officers, #2 buyers for ServiceNow. A lot of people don't realize we are one of the largest cybersecurity provider in the market today.

So that -- so if you look at the growth engines now we have, security, which is going to be and continues to be one of the leading areas for us. You add data with the Workflow Data Fabric, the RaptorDB, which we launched just last year. $100 million ACV in less than a year, right? So very fast growth. And we are looking at $1 billion-plus kind of business growing there for sure. And then CRM, which we've been there for a few years, especially customer service, field service management, CPQ doing very, very well. And then you layer our core very solid IT business in HR business and then you layer the employee works, which we build with Moveworks, the idea of engagement layer for any employee to really -- like CVS Health, for example, uses it for 160,000 employees every day to get any kind of help they need inside the company.

So we have a very solid portfolio. And I think we feel the investments we made are lining up very well. And the AI is definitely a tailwind to let us get into a lot more conversations when you surround that with AI Control Tower and the security product. So a lot of growth opportunities, and we feel very confident where we are going, and it's been reflected in our numbers, and it continues to do better and better.

All right. Perfect. We'll wrap it up there. Amit, thank you very much.

Yes. Thank you, everyone.

All right. We'll go ahead and get started. Thank you, everybody, for joining us. We have Amit Zavery from ServiceNow, President, COO and Chief Product Officer as well. So Amit, thank you for joining us today.

Thanks for having me. Hello, everyone.

So look, originally, I think the shape of the conversation was going to maybe be a little bit different. But given the speed at which things are moving and the focus on AI, I wanted to maybe just jump right into that. And I think there's a lot of questions, some might say some debates. But can you talk about how the Now Assist platform has broadened both in flexibility and capability over time? And then I have a bunch of framing questions or follow-up questions after that.

Yes. So I think if you look at just in AI, it's just moving at a very fast pace, right? So we, of course, started with the idea of Gen AI and giving summarization, helping users get more value from the content they have or what they're doing as the day-to-day task. Over the last year, 1.5 years, we've accelerated what we've done with Now Assist, specifically becoming more of a system of action, right? So the idea of doing things with agentic and making it an agentic platform. So taking different AI agents, how you orchestrate them, how do you work with them, how do you use AI agents to finish task. And coordinating the full activity end-to-end. It's been the next phase from Gen AI to more agentic use cases.

And that has been a big game changer because now you're getting a lot more value out of the investment in AI and you're also getting a lot more efficiency associated with it and removing some of the complexity associated with that, right? And when we started doing a lot of that work, one of the big things which came up was around this idea of governance, security, compliance, visibility. And we built on top of our Now Assist platform, something we call AI Control Tower. And that was a big evolution because that removed some of the barriers customers had in terms of adopting AI, especially agentic as well as ability to have visibility across not just our platform, but third-party systems out there as well.

So our agentic platform has become more this heterogeneous connecting different agents together, but with visibility. And then over the last many months, at Knowledge, we announced this idea of AI specialist. So we have 20 different AI specialists, which do full end-to-end work. So it's really human-equivalent AI specialists, like a Level 1 support engineer, HRSD or HR Service Manager, things around FinOps, things around security ops, things like that. And 20 of these AI specialists now really driving not this idea of you have to manage all your AI agents, but we're finishing that work for them. And that is a big change, right? Because now you remove a lot of the barriers, the work you have to do, but you're getting an outcome which you can also now calculate the ROI against a human cost associated with doing that same task.

So that has been the evolution. And Now Assist has gone from -- and we use that as a term, but it's pretty much across all of our portfolio, right? So we're adding AI across our stack and making sure we have tiering in terms of functionality, but also making sure that this kind of capability becomes much easier to use as well as adopt across the different kind of use cases which are happening inside the enterprise. And we've been adding a lot of more capabilities across the board in this area now.

So there's a lot I want to unpack there, especially on the technology side. But before I jump to that, you mentioned this idea of lowering the barrier. And I think one of the big changes that happened recently was putting AI at every level of the product portfolio. So maybe help investors understand what signals drove that decision and what it unlocks for the end customer?

Yes. No, I think so if you look at -- we have this Pro Plus SKU, which is the Now Assist idea of providing a premium capability for doing automation. And we had this hybrid pricing for the last 1.5 years already. So we have got a lot of signals from a customer that they like this idea of combination of flexibility and predictability with the pricing. They like that they need AI and they can get that full end-to-end in one particular offering as well. But one of the feedback we were getting is that why do I have to always start at the top, right? There might be some other use cases. I want AI as a table stakes. So we wanted to make sure that we bring AI not only in the premium SKU, but AI capabilities, all very, I would say, factored by functionality in different tiers, but available in all of our products.

We don't want to have a non-AI and AI mindset anymore inside the company. Our customers don't want it. They want to be able to adopt AI as part of the same products they buy from us, not just one of the products. So that kind of drove this. We knew the pricing has worked. The feedback we got from our customers were very positive, how we've approached this AI capabilities in our Pro Plus. And then we tiered a functionality and gave the basic base capability in the SKU we called Foundation. And then we have Advanced SKU, which has a little more ability to act -- take action on top of it and then Autonomous at the top tier. So that's what drove it. And it allows our go-to-market to be much more simpler for our reps to go and have this conversation with our customers.

It allows us to monetize AI across our full SKUs as well. Messaging becomes much more simpler as well. And also lets me drive one integrated technology stack instead of having fragmentation in a product for no reason really. Over time, it had to get to an AI end-to-end. So we kind of took that accelerated path towards it based on the feedback we've received, it's been very positive so far. And customers like this idea that they can start anywhere and they can get the value of AI investments we're making while we let them move up as they need to. And we preserve the top capabilities only in the top tier anyway. So we're not losing any of the revenue opportunity, but we're monetizing AI in other SKUs now as well.

I think the simplification makes it a lot easier for adoption. And I think that's important. And the other thing investors are really focused on, we hear it across the different platforms and software. Who's going to be the AI control tower. Now I know at Knowledge in the Financial Analyst Day, you unveiled it to investors. But help us understand what ServiceNow's platform, what allows it uniquely to be well positioned to be the control tower for organizations?

Yes. I think you look at ServiceNow has always been this system of record for enterprises, for any kind of assets, right? With CMDB, which is the core foundation of ServiceNow, which became kind of the way companies adopted ServiceNow was to really have visibility across every asset they have inside the company, any hardware, any software, any IT asset. And if you look at what AI agents are, it's really a software asset. So we were already discovering everything a company was using from IT perspective and bringing into CMDB for many, many years. And if you ask IT departments in terms of knowing what they're using, what licenses they have, who's using how many of those licenses, what much you paid for it, all that stuff they used to go to ServiceNow CMDB to get that data typically, right?

So for us, it's a very natural extension to now say that I will also discover and track and manage and give you visibility to AI agents. We discover them just the same way in the same architecturally. We, of course, build connectors and adapters to discover a lot of the next-generation AI systems out there. But for IT managers and IT system owners, this was like, okay, I already have all the other visibility. I don't want to go to a third-party system for only AI-related stuff. I want to go to the same place where I can have full license visibility, all usage visibility, all cost visibility.

So that's what drove AI Control Tower. And second thing, we're always doing compliance management, auditing, risk management in the CMDB as well. So it was very natural for us to expand that into the AI domain as well. And the reason why we've been able to do very well is because it was not very difficult for them to implement this. It comes naturally as part of what they already have in the IT systems. And what we are thinking of it is that, one, we've always been heterogeneous. We look at everything inside a particular enterprise systems anyway. I can give you, as somebody managing the environment, full visibility control while I integrate with third party. So it's not only about ServiceNow, it's always been about the third-party systems as well.

And that's what is giving us the right to play, right to win, and we were winning in that area, right? Because we are probably as neutral as it gets from all these things. We discover all these things. We give you the cost management associated with that and really remove some of the barriers associated with the shadow AI projects or cost runaways or even security. And one of the reasons we did the acquisition of Veza was that idea of nonhuman identities, right? How do you have visibility in the nonhuman identities, the governance associated with that, any kind of security issues you run into? And what are these AI agents doing given they change identity so frequently based on the role and request they get.

So it became very natural for us to keep on expanding into it. It's been resonating. It's one of the fastest-growing products for us as we speak. And it really gives a lot of peace of mind for any operator inside an enterprise, right? So -- and our view and our vision is that we would kind of integrate with all these different things out there. And we are not just saying it has to be only about ServiceNow. And that's why our integration with Anthropic, Google, Microsoft, OpenAI, but also a lot of agents coming from Workday, Salesforce, others, we can bring that into one place. And nobody else has been able to do that today.

So earlier today to kick off, we had the CIO of Jefferies on stage. He said in multiple different ways that we're essentially a ServiceNow shop that we -- that's not something we're going to look to recreate that, we're going to continue to build on it. But he also mentioned this idea of the difficulty around on agents, right, that we didn't build for a world where you had agents, you had humans that were meant to work, right? And so you just mentioned with the acquisition, how does the recent M&A allow you to help companies monitor what agents are doing? Kind of what's the unlock there that other systems aren't designed for? And maybe speak to the M&A specifically how that adds to your capabilities?

No, I think we're hearing the same thing. I talk to CIOs and all, right? One, they do depend on ServiceNow. It works very well. And just because you can do something separate -- differently, you don't need to, right? So I think that's been pretty much the theme I talk to every customer. And then the second thing is that our view always has been we need to keep on making sure we bring the value of AI or any innovation, as a matter of fact, into our platform, the customers don't have to deal with it later, right? So we keep on modernizing. My job at the company and what we're doing with our R&D work as well is to really ensure that we remain ahead and continue to innovate to give value to our customers.

So as I look at the landscape of opportunities for us across AI and what we've been building, see the AI agents are going to be a new paradigm, and it's already starting to happen where they will interact with all the systems. So users are not only going to be going and pointing and clicking through UX, there will be also AI agents who will request some activity from third-party systems. Similarly, so one of the reasons we have opened up our platform and we launched something called Action Fabric is to allow any AI agent to call into ServiceNow and allow us to do the actioning for them, right? And we've been always a system of action irrespective of whether you come from our UX or you come from Copilot, you come from enterprise Claude or Cowork or whatever it is, we don't really care. But we also want to make sure that we also provide you the first-party experience if you want to choose to.

So our UX has been modernized drastically. I mean if you look at the experience layer is as AI native as it gets with the conversational front-first mindset. The Moveworks acquisition we did kind of led that to give this one unified modern experience across all of our products. And then we added this idea of conversational experience for voice and multimodal omnichannel into the same platform. So you don't have different stacks for different things. and it's completely modern going forward. And then underneath the covers, we're doing a lot of work around security, compliance and visibility and giving that view to our customers so they don't run into issues when they're deploying AI and they find nefarious things happening into the system.

And I don't know how many people realize we have a very large post-breach security business, $1 billion plus, and it's been growing very significantly. And when we now augment a lot of the cybersecurity, vulnerability management as well as nonhuman identity or devices, which is becoming big as well, right? Devices are accessing a lot of the system as well. That's where the acquisition of Armis and Veza fit in. Armis gives you full understanding of any devices out there in the system, be it OT, IoT, medical devices, physical AI now, which is becoming prevalent inside shop floors and manufacturing environments and hospitals. So how do you bring -- just like we were doing any asset, we need to bring every device into this. And now this idea of a platform, which has full visibility, full understanding, provided securely and then giving you the ability to interact with that through our UX, third party or any agent, you have a platform which is very robust, very end-to-end capable, very modern, but also in a very secured, governed and compliant manner, which really gives you peace of mind if somebody is going to operate it.

So I keep on modernizing while keeping the enterprise mindset always in a platform. And that's why a lot of customers love it because they can keep the same platform as we upgrade, they get new features. You don't have to replatform, right? So our platform is still one platform. We add new, new domains on top of the same platform, but it becomes very simple for customers. That's how we've been able to get into CRM and other areas because it's the same underlying technology stack. And now you have a very modern AI native stack underneath the covers.

So I want to pull on some of the newer areas that you're moving into. But before I get there, I did want to touch on the M&A question, right? And if we zoom out, there happened to be a cluster of M&A in a very short period of time. And so the follow-up question has been, is there a shift in strategy? Or how should we think about M&A going forward? So I figured as a technologist, like how are you thinking about the M&A strategy at ServiceNow? What led to the recent M&A? And then how do you think about it going forward?

We have been very careful with capital allocations in general, right? So I mean, we definitely want to make sure we feed our organic engine everywhere. I mean, everywhere we have opportunity, we need to make sure we build the best product, which are well differentiated. But AI also opens up opportunities to expand our TAM and areas where we believe we can accelerate our road map based on customer demand, where we can also build out -- continue building out differentiation and new opportunities for us. Our tuck-in -- ServiceNow has typically been doing tuck-in acquisition, and that all continues, right, where we want to find good IP or acqui-hires or good talent who can help build our teams faster and provide better delivery on the road map and new IP as well.

In some areas, as you mentioned in some of the acquisitions we did recently, cybersecurity, and I think the security space for me and for all of us is really relevant to AI. Without that capability in the platform, you really become just a feature provider without any kind of governance and security associated with that. So we saw immense opportunity with the acquisition we did of Armis to augment what we did with CMDB with any asset, now to expand. We've been talking about OT anyway. So we've been doing IT and OT work. Now adding the security layer around that changes the game. They are -- they have a lot of good IP, very domain-specific capabilities. And adding that to our security business really does 1 plus 1 is much bigger than we would be possible otherwise, right?

So that's really the kind of drivers for some of these things. I think we are at a point where we have all the assets we need at the size we're talking about. There will always be tuck-ins when we need to or where we find something unique. But beyond that, I think between what we've done with Armis and Moveworks, we cover what we need. Veza is a smaller company, but it gave us this ability to do nonhuman identities with a patented Access Graph technology, which is very critical. You talk to any large company now, they want that. We had done another smaller acquisition of Logic to really expand what we can do with CPQ because that's a more AI-driven case -- capability, so you can do accelerated configure, price and quote. So we've been always finding those things so we can really get faster at where we need to go and bring in people who have a lot of the domain expertise. And I think it has worked out well so far. But as your question in broader in terms of acquisition, I think what you should expect is the tuck-ins. And beyond that, I don't think that there's anything we really need to do drastic. That's how I summarize.

I think one of the things that underpins all of this is when the company rolled out RaptorDB, which I think allowed a lot more workload horsepower. Can you just help understand how that underpins all of this and maybe what adoption of RaptorDB Pro has looked like?

Yes. I think another area where probably a lot of people don't have understanding, like we have a very large now very fast-growing data analytics business. The core foundation -- a couple of core foundations to it. One is RaptorDB, which is a PostgreS database, but we rewrote it to be more of an HTAP. So basically hybrid, both analytic as well as transactional processing database. And all of our products now underlying that it comes automatically with RaptorDB standard, right? So that you have a good, scalable, highly performing product available to all our customers, given the size of ServiceNow deployments have grown quite a lot across our customers. We wanted to make sure we have a very foolproof and balanced database underneath the covers. Before we used to use some open source technology, we didn't scale to the level we need.

But beyond that, what we're discovering now is that customers want to do a lot more with the information they have inside ServiceNow as well as bring in other information through either Zero Copy Adapter or any other way. So what RaptorDB Pro does is, one, it is much more highly performant and scalable. Performance is like 17x of what the standard would be. Plus, we've been able to now do a lot of analytics workloads on top of that. So you could do insight to action, you can understand what your incidents happen, where happen, what you need to do with it, also connect into Databricks, Snowflake, BigQuery and really do a much more -- a very detailed analysis associated with that.

So we've been able to sell that. It went to $100 million in a very short amount of time in the last 4 quarters, ACV. And we continue to see that expansion happen because there's a whole thousands of thousands of customers, ServiceNow, who don't have that, and we can easily go and talk to them the value of going to Pro. But on top of that, what we build is the idea of Workflow Data Fabric, the connector as well as the integration into 300 different data systems. And then we are layering on top of a semantic layer and a data catalog to do analytics apps, which we can now monetize by different domains as well.

So this portfolio and the platform has grown drastically to be now providing a dual data stack. And using that stack, we did a Knowledge Graph. We have a context engine, all built on the same stack where customers can now use a lot more capability from ServiceNow than they could typically before they used to extract and move everything out. Now they can do inside ServiceNow and they get more because we are touching so many different systems anyway. So that's really the RaptorDB as well as the Workflow Data Fabric and the data analytics stack. I mean we have said openly that's our next big growth engine. It should be getting to be $1 billion plus and continue to grow beyond that because it really changes how a platform can be used end-to-end different use cases than we were monetizing before.

Helpful. And you mentioned now different growth opportunities, and you mentioned moving to different areas. I think one of the questions we get commonly is maybe around the right to win in categories like CRM. And I think it would be helpful maybe even to explain just what is ServiceNow focusing on in these newer areas? And where do you see maybe existing vendors as competition versus you're just offering something that isn't addressed. Can everybody please silence their phones? Let's just all do this at once.

Yes. No, I think -- let's say, our right to play has always been about really doing actioning across multiple different domains. And our heritage has been IT, no doubt, but case management. Like how do we resolve an issue somebody has. So that we did that for IT, we do that for HR. We do that for finance. We do that for procurement. We do it for security now. CISO is the second largest buying center for us, right? Because any incident happens, somebody needs to help you resolve it. And then you need to coordinate it across many people. There's a workflow, there's a resolution plan, there's triaging. Same thing applies to customer service.

So when we look at CRM, it's a natural extension of what we did inside the company. I can do it for outside the company for enterprise, right? Because all what we're trying to do there is like somebody has an incident with customer service. They need help. Somebody needs to answer that either on a chat or a phone or whatever other mediums is and then triage that and help other people resolve it and get the resolution back to the end user. So when we look at CRM, it's really about expansion in areas where we're good at. So it's customer service. We're not doing like full-blown SFA, marketing automation, things like that. CRM is big enough space. The largest TAM is customer service. And that's an area where we are very good at.

Naturally, we are starting to win there. We -- as you see the numbers there, one of the fastest-growing area, a couple of billion dollars now and heading forward. So that has been -- but the core of it is really the complex orchestration and with an outcome mindset, not just giving you an information, but taking action. So if you look at customer service, you're taking action by resolving something. You look at what we're doing with CPQ, same thing. You're configuring something, you're taking pricing associated with that, then you're getting a quote. So it means you're connecting various different systems together and now making some decisions for them, helping you orchestrate that, getting an outcome, which is a quote, not just like say, tell me what is my forecast because that's just information gathering.

How do you do these various steps, which we've been very good at for years and years. That's really been the heritage of ServiceNow for 20-plus years. So this idea is wherever it's applicable for us, we go. And we started with, of course, IT, but very naturally, we moved into other areas because it's the same platform. We don't have to rebuild everything. It's the same technology underneath the covers. So the customers love it because when they add new domains to us, new workflows on it, it's on the same platform. So you're not replatforming every time you want to add this particular use case versus what you find with most of the other vendors is that every domain is a different platform, different stack.

Marketing is a different stack. sales is different stack, service is different stack, IT is a different stack, which is painful. So that's why customers and IT love us because we are able to do this thing on the same way, it's very modern and able to do this thing very quickly. So that's our right to play. And that's why we win. So yes, there will be natural worry that there are a lot of other vendors in every space, but we've been multi-vendor competition for every space we've been in. It's just that we have to make sure we out-innovate, we build the best product, make our customers happy. And we've been doing that, and we feel that we will continue doing that because we have that ability to do it.

Well, I think the growth speaks for itself, right? It's been very durable because you guys have been making customers happy and adding a lot of value. As I think forward to the 2020 -- the 2030, I cannot believe it's going to be 2030 in a few years. But as I think about the 2030 targets and the growth to get there, can you maybe just help us think about what you think is going to be the biggest engine to drive to those 2030 targets? And I have a couple of follow-ups.

Yes, yes. So 2030, I mean, you saw the numbers we're talking about, our base case is $30 billion. right, and a very good growth rate as well as improvements -- continued improvement in the margins, free cash flow while absorbing some of the acquisition, plus also a lot of the innovation we're doing, right? The growth drivers are straightforward, right? One, our AI stack and the agentic is going to be what you're seeing with our already increased guidance on top of what we're doing with Now Assist this year, and that continues to grow. So a lot of the use cases we're doing in that area will drive a lot of that growth associated. Second growth driver is security space. I think security and risk is becoming a very key element of our portfolio. And the assets we have, the differentiation we brought in and the innovation we're bringing in there is a great adoption happening already, plus also solving a lot of the critical problems to remove the barriers for AI.

The third driver is Workflow Data Fabric and the data analytics stack. As I said, it's one of the big growth engine for us, and we're already starting to show that acceleration. And the more investment we make in there to continue bringing a lot of the data and the ability to do analytics on it, it drives a lot more value of our platform. And the fourth one is CRM, right, customer service, the CPQ and CPQ is leading a lot of that conversation with the customers to really improve how they deal with their end customers as well.

So those are the growth drivers, a platform broadly touching everything around IT, HR, the Employee Works, which we released recently between the combination of Moveworks and what we do for HRSD, which is bringing that thing into the platform end-to-end and then have the AI associated with it every product and then you layer the data, the security and CRM, suddenly, you have a portfolio which is very robust, very fast growth and differentiated in the market. And that's what will get us to the beyond the base case as we expect in the future.

Helpful. So I want to end on a curveball that I didn't prepare you for, which is I love asking technologists what they have found to be either -- I'll let you define it how you want as a Rorschach test, whether whatever cool means, but what has been your coolest experience using AI tools, whether that's as an employee at ServiceNow or whether that's in your personal life, what have you found to be the most interesting thing in terms of your AI utilization?

I think to me, AI should be really -- you shouldn't care it is AI. Why do you care it is AI or what it is, right? If it can help me solve my day-to-day job and make me more productive or make me better, that's how I look at AI. So I'm not really going looking for AI tools anymore. I'm seeing like how has my product improved by it using AI. So I think the AI -- I'm really excited about what we're doing inside ServiceNow with the AI specialist because it really changes -- it does what you need to do in a short amount of time with better outcome and solves the customer problem. And eventually, what you use underneath the covers, as an end user, don't care. As a technologist, I love it because I'm using a lot of this technology to learn how we can do better with our products. But end user, when I look at customers, I shouldn't worry about it at all.

Super helpful. Amit, thanks for joining us. Great to have you, and wish you the best of luck.

Thanks for having me. Thank you, everyone.

Thank you for everybody for joining here. It's a great pleasure to be here with Amit Zavery, President, Chief Product Officer and COO of ServiceNow. Amit, thank you for joining us.

Yes. Thanks for having me. Hello, everyone.

We're back here a year on after what's been a very consequential 12 months, I think, in ServiceNow's history. You guys have 3 highly strategic acquisitions, launched Autonomous Workforce, wholesale repackaging under a new kind of scheme with foundation, advanced, prime categories. You just had your Financial Analyst Day, you laid out a $30 billion subscription target by 2030. So a lot to dig into, but we can start off simply. Love to hear your introduction, yourself, your background and a little bit about what you focus on at ServiceNow.

Yes. First, it's been a busy, 12, 18 months for sure. I've been at ServiceNow for the last 18 months. As you mentioned, I run the product engineering, operations and product strategy for ServiceNow. Previously, I was at Google Cloud for 6 years, where I ran all the platform teams, including a lot of the strategic products and portfolio there. And previous to that, I was at 24 years at Oracle, ran various different groups. Before I left, I ran the cloud team as well as all the middleware and the platform team over there as well, which was a substantial part of Oracle's revenue. Very excited to be at ServiceNow. A lot of things going on, great portfolio, great product plans going forward as well as a great customer base. So really good time to be at ServiceNow.

Yes. Yes. I think we should start off with what was probably the biggest topic for me when I was talking to the partners and customers out at the Knowledge Conference, and that's AI Control Tower. A lot of traction with it. Our checks suggest that customers are deeply concerned about their AI sprawl. They don't know what these agents are doing, shadow IT, not to mention the cost side of it as well. They need something to bring this all together. You can talk about what's differentiated, kill switches, all those pieces.

But I think one thing before we get into it, that's interesting is that this is a very contested space. Everybody wants that governance and control. Customers are choosing you guys to do that. So can you describe why it's so differentiated and why you guys are the right platform for customers?

Yes. I think, see AI control tower, last year when people started talking about agentic and even when I was at Google, the amount of AI work going on, and I was building a lot of the AI technologies. It was clear that customers are going to face a lot of issues managing the AI capabilities, the usage of AI, discovering a lot of things which is going inside the enterprise and really making sure it's secured and governed. So last year, we launched AI Control Tower. One of the reasons behind that is whenever we're talking about agentic to those customers, they were really getting worried about security, governance, compliance, auditability as well as just visibility broadly. And ServiceNow has this product called CMDB as a core foundation of our product portfolio, which -- where we control -- we manage and monitor all the assets inside an enterprise, any IT asset, hardware, software.

For us to do that and extending that to AI was very natural. AI agents are software. We are discovering a lot of other things for every IT system out there anyway. And so we added the AI agents as a way for extending what we did in CMDB very quickly and easily and then giving them so much monitoring and measurement as well as the cost management associated with that. And that opened up a lot of conversations with our customers. And the reason it's kind of valuable for us as well as why we are differentiated. One is I said, we already had the foundation for managing and monitoring a lot of the systems and AI was very natural. Second is, I think we were connected to so many different systems out there. I mean, ServiceNow is kind of enterprise OS, the way you think about it, connecting various different systems East to West across different systems already, very heterogeneous, very open ecosystem.

So for us to be more of a neutral third party where we can now not just track our AI agents, but also discover things coming from any different systems out there, hyperscalers, all the large language or frontier model companies, any AI systems or system of record. And providing a full governance layer on top of that, just like we did for any asset, became -- it's much more differentiated because of that.

And the other part, which we have been doing very well is we recently did an acquisition of a company called, Veza, which has a patented technology called Access Graph. An Access Graph for nonhuman identity is becoming a very, very critical element for monitoring and managing AI agents because their use cases as well as identity changes so frequently, and you have to do that monitoring real time. They do around 30 billion different permissioning and parameters for nonhuman identities.

So we brought that into AI Control Tower, and that suddenly changed the game for a lot of our customers because they can feel more confident about AI systems not taking wrong actions or doing wrong things and giving them the visibility. So tons of stuff going on in our product portfolio and that has been really well adopted and differentiated, and we continue to invest and provide that capability with AI Control Tower now.

And maybe to double-click a little bit in there. You have this product that's answering a lot of customer needs. Your customers are in different parts of their AI journeys. At what point do they kind of hit that where they're like, "Oh, we need to do something that's like AI Control Tower?" Is it a cost function? They're like, all of a sudden we're spending more than we expect or is security the main function where they're like, hey, if we want to push this and put to production, we need to have a way to make sure that it doesn't go rogue?

Yes. I think it usually starts with when more usage of AI starts happening. Like if they want especially agentic where you have all these business processes and systems connecting various different AI agents together. And there could be a lot of shadow AI projects happening. And then you have no idea what's going on and who's spending what or who is using what. And last year, as we said, when the agentic use cases were starting to emerge, a lot of the worry customers had around was just control and visibility. And what AI Control Tower conversation started was just peace of mind, where you don't have this sprawl of AI without IT knowing what's going on, who's using what, how much they're spending.

So it really accelerates the AI adoption by having this as a central control plane and heterogeneous because a lot of the providers today, they do pieces of the technology for their own visibility. They might connect into a few other things, but the end-to-end discovery mechanism and the whole monitoring and visibility mechanism. It doesn't exist in the market other than AI Control Tower. So I think it just removes that barrier for adoption of AI because now IT team members as well as CIOs and CISOs start feeling a little more confident they can get going with AI without just random stuff happening inside the enterprise. And with enterprise anything -- I mean, you've seen a lot of examples. I mean you saw the recent PocketOS and others, where if you don't have visibility and control, things can go completely wrong, and you need to have some guardrails, and this is what it allows them to do.

Yes. Yes, it's a gating factor so they can deploy more. If we go to something you already touched on, which is acquisition, Moveworks, Armis, Veza. One thing that I noticed is, I think, investors have been kind of trying to digest what it means, why they're strategic. When I talk to the customers and partners, they seemed really clear about what it brings together, why it's such a high value. There's been a lot of companies that do acquisitions. This was one of the ones where they seem to be paying attention a lot and kind of see the vision that you have. So what do you think that they're getting that maybe investors kind of haven't wrapped their mind around?

No, I think we've been very disciplined and thoughtful about what we acquire. And over the last -- as I mentioned, with the AI growth, there's an opportunity to really innovate faster, have -- get a lot more domain expertise in some of the areas. And one of the biggest areas we've seen a need for is around security and governance, right? So the acquisition like Veza and Armis fit into this idea of how do you really monitor and manage the proliferation of AI systems, but also devices. Armis provides the ability to do OT, IoT as well as medical devices, vulnerability management and exposure management.

Today, our business in security space is $1 billion plus, which happened last quarter -- Q3 of last year. And that was an organic business we built over a few years, and it continues to grow very, very fast. What we saw from customers was that you already manage all the IT assets. Why are you not able to now do also security and asset and vulnerability management for non-IT assets like OT, IoT and specifically medical devices? So Armis fit in very well with that kind of mindset, right? We -- allows us to extend to any kind of devices out there and also extends what we have in CMDB and augment that with millions, billions of devices into that system as well.

So that as a growth with physical AI and other things come up, we see a lot of value for ServiceNow to provide that exposure management, vulnerability management on top of post-breach what we were doing already. Veza is a little much smaller than Armis is, but this idea of patented Access Graph technology, again, augments everything we do for nonhuman identities, just like we use for human identity. The identity governance specifically becomes very critical. So our security business and the product portfolio road map got accelerated by this acquisition. We're bringing a lot of good domain experts in this area who are well-versed and have been doing this for quite a few years and made our story much more powerful to customers as they think about AI adoption as well.

We continue to do the integration with third-party systems, right? So this is not like it's replacing a lot of things we were doing before -- not doing before, like we integrated into CrowdStrike, for endpoint, we integrated with Palo Alto and network-related stuff and get a lot of signals, but the whole exposure and vulnerability management with the idea of post breach. And today, CISOs is our second largest buying center for ServiceNow already, right? IT, CIOs were #1 and CISOs are #2. So this was natural for us to keep on expanding into these new areas, no doubt increased our TAM, but also accelerated our road map and bring a lot of this expertise into our product. And it has resonated very well with our customers. Our pipeline since the acquisition has grown for security portfolio very, very well. And we continue to see a lot of good traction with the product being integrated.

Similarly, the Moveworks acquisition was very much led with this idea of conversation first, AI native, experience layer on top of ServiceNow. We had a very great -- we have a great set of technologies today for doing actioning, fulfilling a task. On the requester, we wanted a very AI native experience, and Moveworks brings that. So that's now integrated into our employee EC Pro product we had, the whole employee center and bringing this thing together as employee works.

In the first quarter, we announced, I think, in the Q1 results, we did more as a combined product than what Moveworks has done by independent whole last year. So we saw acceleration because of the road map being integrated, able to deliver a lot of new AI native capabilities on our product portfolio, and it's becoming our user experience across all of the offerings we have today, right? So we've been very thoughtful about how we bring all this stuff together to really differentiate, accelerate the road map as well as continue to innovate in all those areas.

Yes. One of the debates out there obviously has been if AI is going to generate all this value, where is that value going to accrue? And where is most of that getting to get captured? I think you guys have been pretty explicit that the moat is not necessarily the LLM. You guys have the context engine, this graph of -- graph, including the CMDB layered with Veza, Armis is included in there, too. You guys have about $100 billion in annual workflow, 7 million -- excuse me, 7 trillion transactions and you guys put it pretty simply at your Analyst Day, there's no competitor that can do that, right? Help us understand in layman's terms what the technical reasons are that others can't do that. What do you provide for your platform that enables that differentiation?

Yes. I think you, remember, I mean, we have been doing this work for our customers for 20-plus years. The amount of data we collect, as we said, 100 billion workflows we run, plus 7 trillion transactions happen on our platform, which is growing at 20-plus percent -- 25%. So the Metadata we create, the context we generate around why a decision was made in the business process. Why an exception was done, who made those exceptions. Those are not available in any documents, which an LLM can read. These are all information we're collecting as you run these transactions. That's in a context engine, which is distributed across multiple areas, and Metadata is very hard for people to understand what to do with it, if it's not done by ServiceNow as a part of our workflow, right?

So we build that. The CMDB, as I said, is really kind of the enterprise database today, right, the IT system of record and used by all the Fortune 500 and pretty large number of Fortune 2000 companies. So that has become the kind of the underlying ways for large enterprises to operate on ServiceNow. All the systems today, they operate the operational part of it in terms of executing the workflows, business processes around for IT, employees, for security, what we do for customer service, FSM and other things like that. It's pretty broad and deep for many, many years.

That information allows us to now take some advantage of AI technologies like LLM, which is probably around 8% to 10% of IP in a stack, but the rest we build and operate over this information we have collected plus the efficiency we have gained. And everything doesn't require or need to be LLM driven, right? There's a lot of deterministic things we do, which requires a much more understanding of the business process is and not have to say, is lender spending money on tokens, but you can still operate that very efficiently.

So we bring this deterministic mindset to very probabilistic systems like LLMs and still give you a guaranteed outcome because you can't make mistakes in enterprise systems. If you get the wrong answer, you instead of onboarding an employee, you deboard an employee or you have the wrong financial results, it's not going to be very valuable to you as an enterprise. So the context we have gotten, the way we run the systems, the 20 years of experience plus having up stacked being very AI native now, right? So we're getting the same advantages as AI companies have in terms of technology, but then you're wrapping and providing a lot of insights into these things. Plus, we also work in a very open ecosystem, right? Customers start in many different ways. And you can't just say that there's only one way to operate today a business.

So having that opportunity to integrate into different system providers, like a system of records, integrate into any kind of hyperscaler, be able to also run -- or use any large language model, any data provider, any tool to build your workflows custom on top of our ServiceNow platform and have the whole governance and security layer. One of the biggest issues you run into when you're building the systems out there or running a business application or business process is the security and the governance. I would say most of the time, when we build our products, they have to be compliant. We spend probably 50% to 60% of our cost of engineering and R&D is around that whole security, compliance and things like that, which are very hard to replicate from scratch. It takes years and years of hardening. The life cycle maintenance around that is pretty long, and customers need a place to call when things go wrong as well.

So that's all the things we provide out of the box, working together with our customers, proven and operating at scale. And that's really what -- and the partner ecosystem associated with that, right? And the go-to-market muscle we have for years and years of building that relationship with our customers. So those things all add up to really be able to provide that comfort for our customers as well as differentiated and innovative products long term.

Yes, that 50% to 60% statistic, pretty interesting...

Yes. A lot of people forget, people think build is the only thing you have to do and build is -- itself is 20%. The rest is all around everything you have to do around it.

Yes, that's what it takes to be in the enterprise, right?

Yes. Quite boring, but painful but important, I mean.

If we go up 1 level with this AI topic, Bill broke the news on the Q1 call that the Now Assist target is being raised from $1 billion to $1.5 billion, 50%. I think in Q1, you guys were already around $750 million. You got growth in customer spending $1 million plus and Now Assist growing 130% year-over-year. That's all real acceleration. And importantly, I think, Gina, kind of emphasized the methodology hasn't changed, even as if you guys kind of repackage some of the pricing. What's given you confidence in that revised figure as you move away from this kind of sidecar AI concept to help fuel that growth and maybe even kind of go beyond that?

No, no, I think we've been monitoring, of course, our pipeline as well as a customer interest and the adoption associated with that and the renewal as well. So as Bill mentioned in Q1, we'll be going from $1 billion ACV to a $1.5 billion target this year. Our plan was $1 billion. We feel very confident in $1.5 billion ACV on that one. It's because I think, one, with the agentic use cases and some of these things go in production and people using it, we're seeing the volume of usage go up very fast. We're seeing a lot of interest to do multiple use cases than what they started with the employees -- with the enterprises.

So that gives us the ability to say, you know what, we will end up using up whatever entitlements the customers had previously. And when they renew, they will renew at a higher longer -- broader entitlements or they might buy up-specs early enough, right? So that is one vector, which we see happening.

Second thing, as we think about some of the things we're adding around our product portfolio. Our product portfolio has grown drastically, right? So we've added things like AI Control Tower, what we're doing with employee works in terms of amount of requests coming into a system, which will end up burning down a lot of Now Assist and the request volume will continue to go up. What we're doing with security portfolio is pulling a lot of this conversation for monitoring and managing a lot of AI systems as well.

So suddenly, we are in more conversations about AI than maybe previously we were. So I expect our renewal sizes to be higher as well as we're seeing expansion into a lot of new cross-sell areas, which we didn't have. We simplified the packaging as well. So we're bringing AI across all of our product portfolio, and that will drive a lot more conversations with our customers going forward as well. So I think in general, just the demand is there. We're seeing a lot of adoption. We're seeing a lot of interest. And then I think the innovation cycle continues to grow, and we see a lot more capabilities now continue to be introduced into our portfolio, which will help our customers with their AI use cases as well.

Yes. And touching on the -- some of the pricing and repackaging that you're doing. I know it's early days and it's going to get phased over time. But what has the customer reception been to that? Do they understand this new schema? Does it help them with that adoption friction?

Yes. For those who are not aware of what we did, we had a product we have called Pro Plus, which is the Now Assist the premium SKU, which was AI-driven, which we've been in the market for a couple of years, and that has done very well. The pricing structure we had, which was a hybrid pricing structure, licensing-based, but combination of seat, but also consumption, right? And that has been in the market for some time, and we've seen customers understand that hybrid pricing structure, gives them predictability as well as flexibility. They're not going to get sticker shock or any kind of billing shock, but also they know what they're using and that they're using it and seeing value, they will renew it -- also they have predictability in that regard. But we also account for revenue upfront as well as we use that just like any subscription. So the model has worked very well.

So what we decided was based on what we're seeing from our customers to bring that same kind of structure to all of our SKUs, not just to the premium SKU. And the idea is that every SKU will have some AI capabilities tiered by different functionality level. The top tier always remains most differentiated. The bottom tier will have some basic capabilities, but customers can start with AI as they choose to, and they can use a consumption model to see value and use it while that we still have a licensing kind of mechanism. And given how successful we've been with Now Assist and the Pro Plus kind of combination, we are now introducing that across the product portfolio and also removing this nickel and diming where we structure where you have to buy every feature separately.

We're bringing it together into much more structured across ServiceNow product portfolio, giving them the AI Control Tower capabilities, the experience layer, the data connectivity in this kind of a tiered structure. And every customer I've spoken to so far really like it because this gives them the ability to take AI if they choose to in all the SKUs, but they do it by consumption, so they only use it if they choose to, and they will have associated entitlement. And it simplifies our go-to-market. Our sales teams can really pitch this very simply and easily. And customers can move up the tiers as they choose to, based on functionality they like as well as the adoption they see value from.

So no, I think, it's very well liked so far. The hybrid model has worked already. So we're not experimenting with new pricing structure. It's just now adding the same pricing structure, which has worked into all of our SKUs and simplifying our go-to-market as well as customer conversation. So we're very excited about how this has evolved. We announced it at Knowledge, which was just a few weeks ago, which is our large customer event. And everybody seems to be feeling comfortable with the way we are thinking about this and how we will go ahead. And there's no force migration. They can do this at renewal. And the Pro Plus and the Prime, which is the new version, the top version of this new structure is equivalent. So there's no pricing change for those customers. The rest will go through the license changes whenever they renew if they choose to. So customers like that message. And so far, we feel good about where we are.

If we touch on the less positive aspects of AI, I think, it's created a lot of confusion out there. I think you guys said in your last earnings call that customers don't know what to do, they're somewhat confused. We kind of hear the same thing. I've heard more people than usual, who aren't in finance, talk about terminal value risk. So it's getting out into the ether a little bit and probably creating a little bit of reluctance, right? So when we think about that what does that look like? How is that impacting decision-making from your perspective? And maybe the other important piece is, is this an issue that's going to persist for 3, 4, 5 quarters? Is it something that will be resolved in a few quarters? How should we frame it that way?

I guess maybe if I understand your question. One, there's definitely AI -- there's a volume of message in AI and the market is large. The customers don't know in many cases, what is real, what is not real, what to go and where to do things, who to work with and how to get going, right? That's why I think our goal always has been about talking to customers about how to get started and where to get started, right? Some of the -- most of the times, the conversation is the use cases, what makes sense. And we are very prescriptive now than maybe a year ago about which use cases for a particular customer makes sense. We provide them POC capabilities. We provide them the FDE help, engineering capabilities as well as needed in a short amount of time, but get them the right use cases identified so they can get going. And that has removed a lot of the barriers for us at least.

Having said that, I think customers also are cautious about security and risk and the whole visibility as we talked about earlier. So that's why I think the investment we're making with the AI Control Tower again resonates, even if they don't mind wanting to use anything from AI from us, they can still use the AI Control Tower to have the central control plane. So suddenly we have a conversation even if they're thinking about something else from an AI perspective. Similarly, the security around devices are all becoming very real because there is a proliferation of physical AI and other things coming up.

So we now suddenly have many at-bats than probably what we had before, right? If you look at where we were at 2 years ago and where we are now, the volume of conversations we can have with the customer, we can start from so many different angles. The employee works is a very good example as well. Any kind of conversational interface you want to provide to customers to use things across their enterprise, find information, ask for tasks or getting work done, again, we provide an option. Same thing with what we're doing with AI-driven omni-channel intake with CSM or FSM.

So I think that is really opening up a lot more senior level conversations for ServiceNow. IT always loved us and they continue to love and invest in what we're doing going beyond with autonomous AI and other things like that. Same thing with CISO. So suddenly, you have a lot of supporting structures inside the company for ServiceNow. And AI, irrespective whether you use AI or not from us, there's always a product available to you, right? And the AI part, I mean, again, we'll see in many years. I don't think you use large language models or frontier models for everything. Because it's very costly over time probably or some things you don't even make sense to use.

We give you this flexibility and the ability to really do the right thing to run and operate your business because eventually you want outcome, cost savings and a lot more efficiency. And that's what we are driving towards. So the idea of autonomous AI and AI specialist is that, that I'm giving you an agent -- the whole autonomous worker who will replace a human worker at a much cheaper alternative, but guaranteed outcomes. Instead of just having this thing do something, which might not be really productive and then have to redo every time, right? So we're trying to improve that situation with outcome-driven mindset, place.

Let's follow that thought of the LLMs out there. We've seen a little bit of a leapfrogging, right? One day, ChatGPT is going to take over everything then it's Gemini and it's Claude, who knows what will be next. What is your view on that? I mean do you expect that cycle of the leapfrogging to continue? And then from the customer perspective, are they dedicated themselves to one or the other? Or they just want whatever gets the job done the best?

Yes. I think it's still early days. I mean you're right. I mean there is a huge amount of leapfrogging as well as, I would say, equivalence of commoditization. So there's a lot of -- between the large language models. And we work with all of them and we work with a lot of open source models as well. We try to be more effective about what will give us the right result, irrespective of which one is the model. I think customers, same thing, right? Underneath, as we said, we also have a large language model in our stack. Customers get to choose, but a lot of time, they just take the default. Most of them don't care.

A lot of them wanted to get a guaranteed outcome as well as secured environment. As long as we can guarantee that, we can choose and change the models underneath the covers, they would not even know or care most of the time. There's some who will because they might have standardized on one or something like that or they might have a license or committed agreement, which they might want to burn down. They've been trying to do -- large language models are trying to do something similar to what clouds do. Where you commit model, you can burn down different of your AR usage.

But over time, I think, there will be a lot more commoditization going on there as well. There will be tiering. I would expect in some of the use cases you want to use an older or cheaper or even nondifferentiated model. In some very complicated use cases, you might use the most latest one, but over time, it just becomes like chips. I mean you don't really care what chip you are using in your application. I think it will be the same thing in this infrastructure layer. It's going to be cost-driven, less differentiation. And how many times you want to keep on testing them. See what happens with every version you have to do prompt engineering again, you have to redo your work. And that's the problem, I think, a lot of customers are realizing when they say you want to build something completely brand new on a large language model. Because every time the new version comes out, you have to retest. It's not backward compatible. It's not feature, forward-look -- feature -- it is not future-proofed.

So a lot of those issues we have to take away and that's what we're trying to do with our software stack is to remove that barrier of usage without customers having to deal with it. We deal with it for them. We extract it out enough but then we give you the value and outcome or a solution on top of it. So I expect a lot of these things to change over time. And many of these model companies will start having to figure out how to solve some of those problems.

Yes. Let's look at a few years. You guys laid out the $30 billion to $32 billion 2030 subscription revenue target. A lot of pieces in that, but what people noticed was it's like high teens 20%-plus CAGR between now and then, AI, 30% of ACV at that same time frame. This last quarter, you guys kind of -- if you think about the CRPO kind of growth curve, it's kind of in that high teens area as well. So it kind of implies that you guys are going to be able to sustain that level of growth, maybe even inch up a little bit between now and then. Help us kind of frame some of those components that are in them. You guys have talked about it and what gives you guys confidence? I mean, Bill, obviously, sounded very confident about it, but help us maybe kind of get closer to where he is maybe?

Yes. I think at Financial Analyst Day, we wanted to lay out our plan for -- until 2030. And I think there are base cases, and I think there's a lot of upside cases, right? So I think Bill is definitely -- and we all see there's a huge amount of headroom available for us to grow. What we already have, and we want to make sure that there's a clarity in terms of where we will definitely be there. The $30 billion to $32 billion is our base case, and we'll continue to focus on accelerating more of that going forward. But the reason we feel very confident, one, I think our innovation cycle, the product we're building is resonating with our customers. We are still the proven and most adopted enterprise kind of workflow as well as the whole idea of bringing AI workflow data and security into one platform. I don't think anybody does that today end-to-end, right? So we give you that confidence level for our enterprise customers. And also unlocking a lot of new things for us.

I think if you look at the growth engines we have, security and risk growing at a very significant rate. As we said, we kind of crossed $1 billion, and we'll talk about where it's going, but it is one of the fast-growing areas and then the road map has been accelerated.

Second, if you look at data platform, data and analytics, the Workflow Data Fabric. We talked about RaptorDB, which is our Postgres HTAP database, $100 million ACV in less than a year, right? So it's like a very fast acceleration path. And this is just untapped market. It's all available to us. Then you add the Workflow Data Fabric, the connectivity with the zero-copy adapter, the data analytics and the data platform we're building out. That's one of the fastest-growing areas, and we talked about a potentially very fast $1 billion business for us, right?

Similarly, if you look at what CRM is, customer service, one of the fastest business to $1 billion plus. We're on target for $2 billion, I think, what we shared at the financial analyst days. So that is getting -- continue to accelerate. We've done a lot of modern work with AI, voice and capabilities on SFM. CPQ acquisition of Logik is really driving a lot more conversations with the customers, customers like NVIDIA and others who are using that for CPQ today.

So we have large growth engines which are all substantially invested in innovated, differentiated, while we have a very good base platform, right? It's completely AI driven, but also it's very deterministic in terms of it can get the work done. Guaranteeing an outcome. And then our -- the domain expertise in IT, HR, CRM, security allows us to really go into a lot of those conversations and give us the confidence that we can really accelerate growth in each of these areas. And all these technologies are pulling in more and more of our products, whether you look at it with ITOM, ITAM, ITSM, what we're doing with portfolio management, what we have capabilities in our enterprise architecture, I mean it's just a source to pay.

So we have a very substantial capability, but it's on this one platform. So you don't have to keep on replicating every time you want to add new features. That's why we're able to innovate faster, which is very hard for many other vendors out there where they have to keep on rebuilding a lot of things because they're not built on the same platform. So that's why we feel very bullish about the headroom we have in front of us, and the pipeline and the customer traction is proving it out so far. And I think our base case is laid out, which we feel very confident and I think Bill mentioned at FAD that he has a lot more expectation and I think we all know we will be there, so.

Bill seems like he has very high expectations. Very quickly, just on CRM, you hit on it a little bit. I think the quote you guys had was going to blow through $2 billion. When you're seeing success with that product, what does that look like? Is -- are you displacing other CRM systems out there? Or are you kind of coming in, in areas where there's a little bit of greenfield and growing from there, what does that look like? Because a lot of enterprises have a pretty robust CRM solution?

I think CRM is a broad market. So just to be very clear, we are -- the space which we have been seeing a lot of, the investment we've been doing and seeing growth is customer service, which is very logical for ServiceNow, right? Because if you're doing case management, we understand incidents, we understand issues and how we resolve it. And that has driven the early growth of CRM business for us. Associated with that is Field Service Management in terms of how you operate all the people who want to help you. Then you add layer on top of that. All this complex orchestration work. Like CPQ is a very complex orchestration. It's not just asking for information. You're going to do something, which is, again, very much action-oriented like ServiceNow has been always. Same thing with some of the things we're doing around distribution like order management.

So the portfolio we built is in areas where we know we have expertise, differentiation and the credibility and the capability building the platform. And that's why we feel very confident of blowing through $2 billion, as you heard at financial, it's a pretty large number already in a very short amount of time. And we are displacing people in some cases. I think in customer service, there are many incumbents. But I think a lot of what's happening in customer service, given that most of customer service products out there, customer has been very fragmented and very old architecture. So people are rethinking voice, for example. They're rethinking how omnichannel intake happens. People are not just calling people on the phone for support. They're doing it in multiple mediums.

So for us to build that in a platform because AI platform is what is supporting our CSM product is very quick. And today, we have customers who now are using this multichannel way of interacting with our systems and replacing what they had or sometimes consolidating because the opportunity is to really modernize, make it more efficient and get into this technology stack, which allows them to get into many more areas for customers to do much more efficiently. So that's where we're displacing or interoperating in many cases. And it's just a modern stack and proven capability -- allowing -- and a lot of people who are running CSM, are also running the IT systems. So they're used to our platform for them now extending that into CSM, becomes much more natural because you're not redeploying a completely new stack. It's very easy for them to now add CSM from us or CPQ and other things like that, given it's built on the same platform.

Yes. Very insightful. Thank you for coming here and giving us your wisdom. I think we'll all be watching ServiceNow very closely.

Thank you all for your interest and support as well. Thank you.

Welcome to ServiceNow's Financial Analyst Day 2026. Thank you for joining us today. Before we begin, I want to remind everyone that today's event will be webcast and recorded for future playback. Information pertaining to our forward-looking statements and a reconciliation of our GAAP and non-GAAP results are available on our Investor Relations website at investors.servicenow.com. .

As you can see, we have an exciting agenda for you all. Bill and Nick will kick us off and discuss our vision and opportunity. Amit and team will present the Blueprint for Agentic business, including deeper dives into the key growth areas that unlock AI transformation.

We'll have a 10-minute break, then Paul will go over our go-to-market strategy and lead a panel to showcase the tremendous value customers are getting from ServiceNow. Finally, Gina will close with a financial overview of the company's performance and outlook. So with that, let's get started.

[Presentation]

Please welcome to the stage, Chairman and Chief Executive Officer, Bill McDermott; and Vice Chairman, Nick Tzitzon.

Wow, nice turnout. Thank you.

It's always great to come out to a video where the Nick character is a useless corporate bureaucrat.

Well, you should tell them the real story.

No, I'm not going to. Nice to see everybody. Anything you want to say before we dig into the content?

Just no place I'd rather be than right here right now with you, Nick and all of you, thank you very much for coming. We're going to give you a lot of insight on the company. The company is in great shape, and we're ready to roll. So let's get it started.

Sounds good. Well, why don't I bring up a few things one by one and ask you to comment on them. So we'll go first to this. I think very few people here in this room, Bill, on either side, on our side or on their side are interested in the past. But sometimes, it's worth reminding everybody where the company's come from. So when you look at the trajectory of the company over the past several years, what comes to mind when you look at this traffic?

Well, Churchill said, the further back you look, the further forward, you can see. We came in, in 2019, building on a great company terrific founder, very good CEOs, excellent board and good culture. And we said we want to be the defining enterprise software company in the 21st century and that we would be the first to get to $5 billion to get to $10 billion.

And then many of you included weren't so sure we'd get to $15 billion in 2026, and we're blowing through $15 billion in 2026. And so the first thing I'd like to say is promises made, promises kept the fastest enterprise software company at scale to hit $15 billion in the time frame we did it and organically.

Right now, this is the hottest brand in the enterprise. We're pursuing a gigantic TAM. We'll talk about that a little bit later. The tailwind is at our back. We have the products. You're going to see the products today. And you're going to see the best team in the industry today. We have the revenue and scale matters because it builds ecosystems and networks.

We have the users and the loyalty of them, our attendance is up double digits. This is the biggest knowledge ever. You'll feel it, I -- who's going to knowledge tomorrow? Great. You're going to love it. And the ecosystem, I mean, the show floor is just amazing. I encourage you to walk through it. You'll see the control tower. It's stunning, and we'll talk about that today. I said we were the platform of platforms in 2019.

And now I'm telling you we're the AI of the AIs. So this is a company that has the loyalty of its customers. It has the inspiration of the most satisfied workforce in our industry, and it's the trusted brand. And I'm not the only one to say it. Fortune says it, Forbes say it. The customer says it with their wallet and you actually know it. So what better time has there ever been than right now for ServiceNow and ServiceNow shareholders.

You mentioned an aligned Board. I see our Lead Director, Sue Bostrom is here; Paul Chamberlain is here from our Board, Larry Quinlan, is here from our Board. So it's great to see the Board...

Yes. I mean you've got a lead director, Sue Bostrom, Larry Quinlan, Paul Chamberlain. These are individuals that have been with me through thick and thin. So too is our founder. We still have our founder on the Board, which is awesome. And our Board is a really great board, very committed to the company, very inspired by what we're building and how we're executing. And hopefully, you feel that the entry point you're getting in at today is just like never going to happen again.

So let's shift gears. The portfolio has obviously evolved substantially in the years that you mentioned. This is the representation that customers will see at knowledge. When you look at this AI control tower for business reinvention, what are the important things for investors to understand?

Well, let's start with the AI control tower for business reinvention. So does GPS signals that will come from language models and other things. but there is only one air traffic control tower for business software in the enterprise at ServiceNow. And so what you'll see today, as you'll hear from our colleagues a lot about the Agentic front door with auto. So any channel you come into, you now have one single agentic experience with ServiceNow.

So if you enjoy ChatGPT or you enjoy Claude or other language models that same simplicity is being brought to you for the enterprise. If you think about industry, we're in all the industries that are featured in this slide. Why that really matters is the moat and industry domain expertise is unmatched by ServiceNow in the enterprise. It also creates more loyalty and net new ACV opportunity, particularly in CRM, and we're going to talk quite a bit about that today.

Autonomous workflows. This is super cool because now ServiceNow goes across the entire enterprise, east to west. So years ago, you knew us for IT. That's okay. We need to remind people that we are the ERP of IT, we are the system of record of IT. And no place has greater permission to grow in this world of AI than IT. And of course, CRM on its way to being a couple of billion business. By the way, we have six of them. And security and risk. We're now in the biggest growth TAM I see in the next decade, especially when you think about the world's third largest economy is actually cyber crime.

So when we made our bold moves, we knew what we were doing, and we'll cover that today. And naturally, when you look at the autonomy of workflows to be able to coalesce all of the clouds, all of the language models, all of the systems of record and all of the data sources into an autonomous workflow that can close an action out. Not give you a recommendation that's probabilistic, but a deterministic outcome achieved.

That's where the world wants to go. And you're going to see something today on employee experience that is second to none. And also app development, not only is it a big business, but we all know, lots of code is getting written by us and by others. The more that AI is generated in the world the more it has to come through the ServiceNow platform. We are the gateway to the enterprise. So more AI is great for shareholders. So we're going to sense and that's any data, we're going to decide that's any model. We love them all, and we have deals with all of them to either build software together, put it in our software or help them get into the enterprise with our unique attributes and then obviously act on any workflow.

And it could be ours. It could be someone else's. It all comes through ServiceNow. So we welcome everybody. And to do this securely. And I think you're going to hear today that we're in the security business. And we think this is a gigantic opportunity for ServiceNow. And you say, "Well, why do you think that Bill?" Well, it's already $1.5 billion business, and we weren't trying real hard. And now you're going to have IT, IoT, any device, critical infrastructure, networks, devices, all coming from one platform that fuses IT and OT, the only one in the world.

And I really think that any system is just like so stunning because, everybody else wants to, I'm reading an article say they want to shut the world out. They want to protect their moat. We're welcoming everybody in because we know we have the winning hand. So when you look at all the hyperscalers and all those systems of record that you know so well, they all integrate with ServiceNow.

So we're still the platform of platforms, that is the foundation, and we're nice. There's no reason to waste time. having skirmishes because we want everybody coming into ServiceNow with their AI, and we're going to grow, grow, grow, and we got a bold ambition for 2030 we'll lay out there today.

So one of the things that Colin and his team have done, acknowledge is the customer's voice is really out there. And I know you're personally inspired by several of those stories. Any that you would pull out just for this crowd as a preview.

Well, I think FedEx to me is one that I'd really like to pull out. Raj will be on stage with me tomorrow, the CEO of FedEx. When you think about FedEx, it's a great company. And Fred Smith was a great innovator, an unbelievable entrepreneur. And he used to talk about the package itself and how it moves throughout the world is as important as what's in the package.

So to think about FedEx teaming up with ServiceNow and Raj coming here on stage, knowing that they're moving 18 million packages a day through over 200 countries around the world and every key business process, things that would sound like core ERP to you is now running on our agentic platform. I mean that's pretty stunning. And then if you want to take something just really interesting, Chipotle is doing great. Everybody likes Chipotle. I like Chipotle anyway. And now they can change in their 4,000 locations, all their menus on the fly. They can be highly creative with their associates.

And you're just changing everything to real-time enterprises. And so whether it's rethinking CRM or whether it's driving a new approach to supply chains, everything now is real-time business processes on the ServiceNow platform. So I think this control tower idea has now manifested itself into a complete portfolio of products.

Love that. Let me do a couple more just to set the stage. So, you mentioned we're nice, and we've taken this posture in an environment where it seems like there's more coming into the enterprise than ever before. You always say trust is the ultimate human currency. What does that mean in practical terms?

Yes. Well, trust is the ultimate human currency. It's the one thing you can't trade on. You could trade on just about everything else in life, but not trust. You earn it and drops and you lose it in buckets. So we don't lose it. We want to win more and more every day. So I think we all know that the net present value of a loyal customer is every business's greatest asset, which is why I think you should all be excited that we have the highest retention rate in the enterprise.

And we are continuing that push to make sure it stays that way. And we're transforming our company to make sure of it more on adoption go-lives and the use of AI. And that's really where that hockey stick formation is going to kick in big time. We're open. And when I say trust, open AI, Anthropic, Google, NVIDIA, Microsoft, Amazon, we have deals with every one of them. They like us. We make a lot of money together.

The language models are coming to us because they know what they do is very important and so do we. But they also know the context that we bring to the unique data position that we have in the enterprise and the process position and the relationships and the ecosystem is going to be a gateway for them to prosper and grow and bring their amazing intelligence to the enterprise, and we warmly welcome them.

I also think you should know that we're getting really good at AI. And now we're even going to make a guarantee. A total satisfaction guarantee on AI go-lives in less than 100 days. Some of them could be a few days, but all of them are going to be less than 100 days. And we're going to make that commitment on stage. You're getting the first preview. We're excited about it. We have the forward deployed engineers, we have the customer excellence group and we have partners that are lined up and ready to roll with us to make that happen. And so we're going to make that offer and make that offer tomorrow on center stage.

I think customers are going to like it a lot because the pipeline is huge. And if they see, we're going to now offer them something on the control tower. That's a pretty special offering as well to get them started, getting them using it, landing and expanding with is something you know we're good at I think you'll know that we're well on our way to being a truly gigantic enterprise software company.

We're not slipping. We're growing. And I also want to make it clear that we are also using our own platform. So if you think about the positioning that we have right now, we have our own AI running on Now on Now, and we're achieving enormous productivity gains. What do I mean by that? Gina has already told you in earnings calls that it's been good for $0.5 billion and overachievement on the productivity curve.

But I'm telling you that we took a couple of really smart moves with what I call tuck-ins based upon the size of our company and the fact that we never bought anything for revenue. If we did, we would have bought companies that you would have recognized a lot better with a lot more revenue. No, we bought the future. And the beauty of that is, we're going to leave this year with the exact headcount that we entered this year.

And what you can take away from that is that our platform is resonating in the way we run our company, the fact that everybody has AI in their pocket to take care of customers, run their business and run our company. That's why 9 out of 10 customer cases are now managed by agents in our company. The same is true for HR and all the questions around running a business that used to be done by people are now being done by agents with people still in the process only when it's absolutely necessary or when it's a high-touch minute where you have to really touch an employee and make the heart of a human come through or in the case of a customer, a white glove treatment because they're exceptionally special. Other than that, the agents are doing the work.

Let's see if we can do two more in two minutes. So you've talked a lot about the growing opportunity. It's not controversial to say there's some skepticism about is the opportunity in fact, bigger. I don't want to litigate the entire thing, but when you look at the prize in front of us, what is your takeaway about the trajectory ServiceNow is on?

When I started in my career at Xerox Corporation, it was a great CEO named David Kearns, and he always said, "I can absolutely handle and empathize -- I can absolutely handle and empathize the folks that are a little skeptical, but not to cynics."

And I think what's cool about people in this room and around the world, they like ServiceNow a lot, and they're rooting for ServiceNow. So you might have a certain skepticism, let me take that away from you real quick so we can get back on to track that we belong on with the rules and rails of today's corporation. We have clarity around the TAM. I think we've taken you through this ride together from IT to multi-workflows to an enterprise platform.

Obviously, the AI platform we brought in and Now Assist across the enterprise. But now we took you some place very, very special. And I empathize with you because we waited 9 months for Moveworks to close the regulatory process. And then on the back of that, Veza came in okay? And Armis came in like within 3 days. So it's probably like, hey, what are they doing? Are they buying growth? What are they doing? No, we weren't.

We were buying a ticket to a bright future. And so now you have an AI control tower for business reinvention where you have your agentic front door and you have your identity management. Now this is key. Does anybody here actually think that the working population of corporations around the world is going up? Well, it's not. It's flat.

And the birth rates around the world are actually going down. And the good news is at that moment in time, here comes the agents. And here comes the robots to make the lives of people better and to increase the productivity of every company around the world. 2.2 billion agents in the next few years, robots, and we own the identity of not just our agents, but the agents that come from other companies in the flow of work, they'll come through our control tower. And then ultimately, we will coalesce all the clouds, all the language models, all the data, and we'll do it all in a highly secure IT and OT environment. You never heard that before because there's only one company in the world that's built to do it and it's ServiceNow. $600 billion TAM, we're going for it.

Maybe we'll have a robot moderate this conversation next year.

Maybe have a robotic CEO.

No, I don't think so. So let's leave it here. So I don't want you to steal Gina's thunder, but she did review this slide, so she knows we're going to show it. It's not about rhetoric, it's about results. We've heard that before. What's the promise we're making about the results trajectory of the company over the next several years.

Okay. Very clear. This is a sub revenue $30 billion plus commit between now and 2030. I want to be very clear. This is not the bill ambitious number. They wouldn't let me put that up there. Do you know what I mean? That is the one that you can say, okay, like the whole management team bottoms up across the board believes in that number. 60-plus is the revenue growth plus the free cash flow margin is going to be a 60-plus number.

Right now, it's 56, it's going to 60-plus, and we're not taking our foot off the accelerator. We're going to grow the top line and you'll see the acceleration of that, and we're going to expand the margin profile of the company and, we're going to take down stock-based compensation down around the 10% mark in 2029. So you'll be dealing with a 50-plus GAAP company, GAAP, G-A-A-P. So I know what you want and we're going to give it to you.

So bottom line, high level, we're going to double the company. We're going to be masterful on our execution across the world globally and through industry. The verticals are really good. We're actually also going to take a platform down market a bit because we have 90% of the Fortune 500 now. It's not a marketing slogan. I actually have people go through the math 9 out of 10 Fortune 500 now, fact, and so we know that we are going to expand with the Global 2000, but we're also going to take it down a little bit, where we could go into new markets in the upper mid-market and take care of business on folks that really aren't in our league.

It's time for that now. And so we're going to run a very efficient ship. And when I started telling these stories to you a while ago, we were climbing a mountain and it was tough, and we are climbing and climbing and climbing. And there's three things that stand out in the core values of this company. Number one, we're hungry and humble. And we're hungrier than ever. The chip on our shoulder is tougher than it's ever been, yet there's a humility and a kindness and an openness about us that never will be in question.

We're here to wow our customers. Customer satisfaction and loyalty is job one at ServiceNow. And ultimately, you're going to see a team today. When I tell the Board about this team, I tell them this is the absolute best team I've ever run with in my career, and I mean it. And so I don't have a second story. We got the best team in the business. So win as a team is the way we roll. And so what you're going to see today is unbelievable leadership.

Amit, our great engineering leader. Obviously, the COO of the company as well, has done some extraordinary things in architecting the product portfolio. It's really amazing. It's so exciting. And Paul Fipps, on the go-to-market side has engineered the AI control tower for business reinvention across the world. And Gina, obviously, is going to give you what she always does, right from the heart, the truth and the belief in this franchise. But I also want to call out the folks that report to these individuals and how great they are.

Too many in name, but I do want to call out one in particular. When we acquired Moveworks, we also acquired a great management team. And instead of having a great leader like Bhavin report into somebody at ServiceNow, we actually said, we think you should be the boss and let the people at ServiceNow report into you. So we're really making account given big businesses to people we believe and trust. So we wouldn't have acquired it if it wasn't a cultural fit in the first place, oh, we didn't believe in the leaders and they believe in this mission as much as we do.

So we now have a great team. We're going to win as a team and you're going to see the best days to ServiceNow are now and in the future.

He'll be back for questions, but that's a great way to that.

Thank you very much, everybody. Thank you.

Please welcome to the picture President, Chief Product Officer and Chief Operating Officer, Amit Zavery.

Great vision by Bill. I'm here to talk to you about how we're going to execute against it. It's great to be back to my -- for my second Financial Analyst Day since joining ServiceNow. During FAD last year, I shared our vision and plans for an enterprise agentic platform, and I'm really excited about to show you what we have accomplished so far. The last 12 months for us have been marked by innovation and growth.

Our autonomous workforce of AI specialists are already delivering impact with customers like FedEx. EmployeeWorks launched just two months after acquisition of Moveworks, beat Q1 expectations by 5x. One of our data analytics products exceeded $100 million in ACV in its first full year of availability and data analytics is on track to be a billion-dollar business for us.

The next evolution of our CRM products expanded into omnichannel, intake, sales order management and CPQ, which will help our CRM business cross $2 billion in ACV. And our security and risk business crossed $1 billion and expanded further into our AI identity governance and OT cybersecurity, helping to differentiate our core. Our AI products are nearing $1 billion in ACV, and the momentum only continues.

And the AI control Tower became a marketing -- market-defining solution. So all this innovation and level execution enabled us to beat and raise our guidance in all the quarterly results last year. We also stayed true to our principles by continuing to expand our open ecosystem and the platform by partnering with partners across the tech stack and all industries. And we have taken also an AI-native approach to transforming every corner of our own business as well as building AI into every product.

And we delivered a new conversational experience across our workflows, launched monthly releases and automate automatic upgrades as well as powered more innovation by using AI tools and AI-native approaches across all of our portfolio. But let's talk about today and fast forward to what we're going to be delivering as we go forward.

Every analyst, including all of you probably are covering as you cover software is asking if AI is going to replace the platform or AI needs the platform. A recent headlines are answering that question better than I could. At Meta, for example, an AI agent exposed sensitive data, which is an enormous security incident with no external attacker. The own AI agent was the failure more here. An AI agent at PocketOS hit a credential error and delayered the entire production database and all the backups of customer data in just 9 seconds.

And the industry has been trying to put Band-Aid on all these issues using agents and spawning more and more agents. But none of these stand-alone AI products can solve the core fundamental issues because none of them can govern the system as a whole. And there's an important distinction here to think through. Autonomous work is not just powered by one new innovation. It's really two essential capabilities coming together, working together to drive real outcomes. It's probabilistic AI, which is what generates the answers and deterministic execution is what runs the enterprises.

And every enterprise needs both of those. That is what it means for AI to be an operating system with enterprise context. And thanks to our CMDB and context engine, we know why a particular decision was made, we can encode the real-time relationship between every asset, person, service dependency and policy. I know many will say nowadays, I'll just build it myself. I'll stitch together the frontier models, take some open source models as well because I've been told that the next best SaaS application is just a prompt away.

But that idea falls apart when you test against three things. First, time-to-value is drastically underestimated. What should save a customer, time and effort only ends up costing them more. Second, the total cost of ownership is very complicated. They compare a build versus buy decision with the cost of API, typically and an engineer's salary.

But that misses the point. You have to add model selection and the constant updates, which happens with the new and new releases from the model companies, prompt engineering, security and compliance validation, managing new requirements by also not breaking the hundreds of systems, which you are already connected to, which run the business itself. And that's just the start.

Go back, please.

The third failed test for build versus buy is the security and governance gap. Autonomous AI agents that take action inside enterprise system without a harness will create an infinite risk surface. One compliance error from a homegrown agent would cost millions for a business. And we'll be also looking at research around this. customers building their own LLM-based solution, typically spend 5 to 10x more than using ServiceNow, depending on the complexity of the business they have and the different systems they have to connect.

And all of the solution will take longer to build and it's usually less secure. So the ROI and the TCO is not even proven if you want to do it -- go down this path. And the ultimate trap of build versus buy is this. The building an app is definitely not the same as running a business. And that is why we made it possible for customers to both build and buy full solutions on our governed platform. At the core of that platform are four integrated pillars that create a complete sense, decide, act, secure loop for AI, which is built on a modern AI native stack.

And this gives customers visibility, context, intelligence, automation -- automated actions, governance, all on one platform. The Gartner projects that 40% of agenetic AI projects will fail by 2027. But not because AI is incapable, just because the AI is in governed. And that's what we are here to fix.

Our platform is about more than helping customers, not just fail. It's about powering the success and growth. And we have proven that we can do this at scale. Today, ServiceNow runs 100 billion workflows and 7 trillion transactions annually, growing at 25% year-over-year. And that scale creates a flywheel. Every Action on our platform deepens our operational context and enriches our CMDB and context that makes our AI better. Our new UI has higher repeat usage, and we only grow more with the launch of auto. Unified AI experience, you will hear more about later.

So basically, actions which creates outcomes, outcomes which create new actions. The flywheel continues to accelerate. And every step makes our ITAM, ITOM, SPM, ITSM and all of our core products more valuable than ever, which is triggering more customer conversations and continue to expand our IT business as well. And humans usually need nowadays agents and agents definitely need guardrails.

You get both through the platform we have delivered. And this is a durable advantage we built first in IT and now expanding even further into many new domains. And if customer is also feeling this compounding value in real time, I'll give you an example, like CVS has taken hundreds of millions of actions now on ServiceNow supporting our 170,000 colleagues of theirs across 9,000 stores. Robinhood is deflecting 70% of employee requests before human intervention, saving over 2,000 hours a month.

TridentCare achieved 96% scheduling automation with our AI-powered CRM, improving care for millions of patients while also increasing revenue. So the question becomes what does it take to enable and govern autonomous work for the enterprise. Today, my team will show you how it's done through the four pillars of sense, act, decide and secure. But the first, let's start with the AI platform that everything is built upon.

Jon, over to you.

Thank you, Amit. As Amit said, we're going to spend the next hour or so talking about five sections. I'm going to start with the ServiceNow AI platform. And we have reimagined and reinvented our platform. And you're going to see a lot today. You're going to see autonomous workers. You're going to see the power of AI control tower. You're going to see new AI native experiences, conversational experience. And we have reinvented our entire platform for the agentic era.

Now to be clear, we're still a system of action. We are the workflow platform. And things are evolving. We're seeing patterns in the market that I'm going to address as we go through this presentation. But what I want to talk about first is that we have reimagined the platform from the bottom up. And what that means is that we have recreated the AI stack, and it allows us to do things like innovate at the speed of innovation, which -- or at the speed of AI, which is very, very important because the expectations of our customers is changing rapidly.

They want to see these innovations come very, very quickly and want new experiences very, very quickly. Now the things that you're going to see around multi-modality, and voice, and new conversational experiences, those are all part of the native platform. They're not bolted on. And the first area that I want to dive into that Amit talked about is this idea of context. And the context is extremely important to any agentic system. It drives the AI.

But The first, I want to play a video of Boris, who is the creator of Claude Code at Anthropic. And Boris is going to talk about how important context is to an AI system. And why the ServiceNow platform is uniquely positioned for context, could we roll the video, please?

[Presentation]

So as Boris said, context is the driver of AI. And we have a context engine inside the AI platform at ServiceNow. But what is context? Well, context is not data. Context is not a decision. It's not an outcome. Context is actually the history behind an outcome. It is the decisions and what made up those decisions that are important to context and that important to the AI system. That's what our context engine delivers.

Now it doesn't just stop there, though. Because there are new outcomes and new decisions that are created every day inside of our system. And so the context engine gets better over time and in turn, the entire agentic system at ServiceNow gets better.

Amit talked a little bit about this earlier. And some of the industry would have you believe that every single process inside of the enterprise should be an LLM call. There's no need for structured workflows anymore. It's all about the LLM. Well, that's not very smart, it's not very efficient. And it is not the way that we want to drive our platform.

Now you're going to see a lot on agenic AI and generative AI today because it's extremely powerful. It's extremely flexible. So things like our -- and our AI agents and the things that you're going to see today are based off of that. However, all the context in the world doesn't fix the predictability of AI, meaning the power comes from the idea that you could ask the same question twice and get two different answers.

On the right-hand side is structured workflows. We've been doing this for decades. These are things like flows and approvals and catalog items. And they are what drive the enterprise today. And the trick here is not to offer one or the other. You need to offer both. And what we're going to do in the reimagined platform is to harmonize those two things together. So that agenetic systems and activities call into structured workflows and structured workflows can call into AI agents, and we bring them together in a way that nobody else can do to provide the most efficient, effective outcomes.

Now as I was saying upfront, things are changing around us very, very rapidly. And our customers want broad access to our system. And we're seeing others in the industry, exposing their system of records through APIs and through MCP to allow for reading and writing of their system essentially becoming a database, a system of record. And while that's very exciting, that's not what we're going to do.

We're going to expose the system of action. And we're going to do that by opening up this layer to the Cluades and the OpenAI's and the Gemini of the world. What is the system of action? Well, that's where the true power of our platform comes from. That is our workflows, our flows, our processes, our skills, the context engine, playbooks. All of those things that is the system of action that is ServiceNow.

But we're not just going to expose that. We're going to monetize it. And we're going to do that by introducing something called the action fabric. And there are a few things you should take away from this it is any protocol, any tool. So you can use your tool of choice and you can talk to the action fabric headlessly and kick off the autonomous work that is so powerful within our platform and it's governed.

So all of the business rules and everything that's happening, you can call into it and those actions are taken and workflows are triggered. But we're not going to stop there because we are now going to monetize that process. And as Amit said, we have a monetization model today for generative AI. It's called NowAssist. It's a $1 billion business. This will be $1.5 billion by the end of the year. And what we're going to do is plug directly into that system.

So now that any time that an outside human being, machine, AI agent, third-party agent calls into the action fabric, we're going to burn assist, the flywheel is going to spin faster. And this is a tremendous TAM opportunity for our company because now anything and any one and anybody can call into the action fabric and take advantage of what ServiceNow is known for. Automation.

And what's going to end up happening is we're going to have this universal action layer, where all of these systems are calling directly into our action fabric and spinning our flywheel even faster than it does today. Now there are other things that are going on in the market and that we want to address with our platform, one of them is autonomous agents, these long-running agents. And they work on your desktop and they help you do things.

They write code, they will handle your schedule. They will monitor your e-mail. They're great. They're assistants. And we wanted to build one of those and we did. And the first stop was talking to CISOs and security, and they said, "Absolutely not." You're not going to be able to deploy those things, they're unsafe. They're not governable, we don't want them.

So we started [ Project ARC ] with NVIDIA. Our partners and friends from NVIDIA, we got together and we said, well, how do we fix this? And what we ended up doing is using one of their technologies to secure these agents in essentially a sandbox mode. What that did was give us the ability to tell these agents what they can do, what they can't do, please don't delete my entire inbox, what systems they have access to. And it gave us the control to allow us CISO to say yes. But we are the automation company, so we wanted to expose our agent and many, many others.

I think today, we just have signed a partnership with Anthropic for Co-work to talk directly to the action fabric. And what that does is it allows your assistant now not just to manage your calendar or plan a trip for you. But it can also ask for time off and kick off these headless workflows that are going on in the background. So I can do things like take time off and change my HR or my benefits and request a new laptop, all from these agents that are running on the desktop.

Now there's going to be a lot of these agents. You might have 4 or 5 running on a desktop, you might have tens of thousands of desktops across your enterprise. So the last thing we wanted to do with [ Project ARC ] was plug it all back into the AI control tower. Each and every one of our agents is talking directly to AI Control Tower telling you exactly what actions is taking, what system is trying to get to and allowing somebody in the enterprise now to look holistically across the enterprise, not only at our agents that are running on the desktop, but at all agents, giving you that holistic view.

Now the last piece of this puzzle for the action fabric is build anywhere. And again, our customers, the ecosystem, our partners are saying, "Look, we want to use the tool of our choice, but we love your platform. We want to build net new applications. We want to build primitives that run in your action fabric. " And in turn, what that does is it makes us a system of action. It gives us a tremendous consumption opportunity across the board, and it drives the flywheel in ways that we couldn't have imagined before Action Fabric.

And so what we want to do today is show you how easy it is to use your tool of choice and build net new applications, net new workflows on our platform. And to do that, Jithin is going to show us an awesome demo.

Thank you, Jon.

Super excited to be here. Some of the incredible innovations Jon just spoke about, I really want to show you how it all comes together on a demo. AI and vibe coding has fundamentally changed how applications are built and how agents gets imagined into existence as autonomous specialists in the app. I'm a developer. My HR team -- that's the job I'm going to do today in front of you. My HR team asked me for a brand-new addition to our employee benefits app.

So typically, I have few tool choices. I could be using Cursor, Codex, Gemini. Today, I'm in the mood for Claude Code. Here I am getting on to the next screen, which is the clock code, and what I'm about to do is in the cloud, I'm going to ask to help me build a pet insurance module for the Employee Benefits app. And the first thing I would do is in simple natural language, I'm going to say, add pet insurance enrollment to the Extra Care benefits app, which I just spoke about, tap. And what you're seeing right now is Claude is starting to get to work. You are seeing something called Fluent. It's our ServiceNow's AI-ready platform language.

We have open-sourced our build agent skills and platform knowledge directly to agents like a Claude Code via our SDK. That means the whole thing, the UI, metadata, access controls, business rules, all of it. And the last screen you saw was the app is almost built by the Claude. Now I'm going to actually jump in and show you how it actually lives in our own native ID, which is actually ServiceNow studio.

Now let's jump over. Right here, you can see on the top of the list, the benefits app. Let's go ahead and click into it. And the moment any application, which lands on our platform, like Amit was talking about and John was talking about, it elevates the app to an AI-native application. Automatically, when an application is built on our platform, our platform will actually recommend a set of agents who will live and breathe every day with the humans in the loop day-to-day 24/7.

You can see our application has already recommended that we create an enrollment agent, right? Let's take a look at the agent. And in that you can see the enrollment agent, it's all set up. It can qualify, understand and manage the end-to-end enrollment with minimal human intervention. Insights like this are possible only with the CMDB, the context engine, and the action graph, which John spoke about earlier.

And you can see I'm already on my way to actually create an agent and every assist which is delivered in the app is a run-time assist for the user. Imagine every application, having 3 to 4 agents living in it, every interaction is a monetization moment every day, 24/7. And now we'll jump into the actual building of the agent.

Let's go ahead and build it. You can see with the click now the Claude Code with the ServiceNow Studio and the SDK skills, the agent is already getting built. And once the built complete, it's ready, it has its own roles, instructions, autonomy, it can actually sense, decide and act every day within the application, but we are not shipping it just blind.

Let's make sure we run the right automated testing and scanning so that it's ready for production and overall. Now it's actually running through the scan process. It's going to come up with the readiness score. This is how our platform is built. It has run through its own evals, come up with the score. Great score, 90%. Now I am ready to actually submit for deployment.

Now what are you seeing is App Engine Management Center. This is the product or the platform where every application goes through to make sure it has the right security controls and the access controls, everything built in. And by default, any app, which runs through any agent or an asset, AI asset would run through, it automatically gets registered as a part of the AI-control tower. Let's do -- this is where we do one more last review of the application. Everything looks good. And let me make sure I have the right readiness, which comes through with a release note and all of it you can see. I'm ready to now deploy the application right here.

Now this is the actual app, which is live, ready for you to prompt. Now I'm going to switch my hat a little bit. I'm an employee, and I would like to actually understand what are my benefits from my pet insurance point of view. Right here, I'm going to actually prompt and type in. You can see it's pulling a massive amount of user awareness and context at the back end. It looks very simple, but in order to qualify and make sure this agent delivers the right accurate information, it's actually bringing in CMDB context engine every one of those process mining capability you can think of.

The last point I have a 2-year-old frankie, which I want to make sure I can actually get the insurance set up, right? There you go. It's now going towards making sure I have my frankie getting access to the coverage, what it needs to be. beautiful, isn't it? So what you just saw is the actual agent is live in action.

Every app built on our platform will get autonomous agent embedded within, and that's how we are fundamentally changing the way AI apps and agents are built within our platform. I'll say it one more time. It's like Jon shared earlier, it's about you can build in anywhere, any tools and any choice, what do you have run and govern in ServiceNow with the enterprise-grade controls and security. Every app sits with an autonomous agent embedded and running the AI assist meter at scale. So that's the end of my demo. And I would like to now bring in Gaurav, who's going to talk about the sense part of the overall value prop.

Thank you, Jon and Jithin. So you just saw why the ServiceNow AI platform is the system of action for autonomous work. And now I'm going to show you and talk to you about how we bring the sense and decide pillars to life on that same platform. We do that by helping our customers achieve four things. First, connect all their data wherever it lives; the second, control it with enterprise-grade governance; third, contextualize it with enterprise-wide intelligence; and then converge that contextualized intelligence right into the flow of work.

And our customers are responding strongly to the strategy, making it one of the fastest-growing product businesses in ServiceNow history. Workflow Data Fabric now has over 4,000 customers, driving more than 3 billion monthly data transactions. And we've recently added consumption-based pricing and more than 700 customers have already consumed more than 0.5 billion credits. And then there's RaptorDB, where our new premium Pro SKU has seen explosive growth. We've gone from 0 to $100 million ACV in 5 quarters flat, with an ASP well north of $0.5 million.

Okay. So let me step you through the four Cs of our strategy. First, Connect. Workflow Data Fabric is fundamentally architected for the agentic era. See, most data fabrics are primarily built for decision support for insights. Workflow Data Fabric, on the other hand, is built for insight and action with read and right capabilities, and it supports all types of data wherever it lives. And that's another crucial distinction. You see we embrace the system of record and the data platform choices our customers have already made.

You Can, but you don't have to move the data into ServiceNow. I know the others who are playing for data gravity. But for us, what really, really matters is knowledge gravity. And Workflow Data Fabric already offers 250-plus connectors and we are expanding our reach even further. With 100-plus new zero-copy connectors, so customers can access data wherever it resides, no replication required. With full support for MCP clients. So our AI agents can work with any MCP-enabled source. And with auto for Workflow Data Fabric, our customers can describe what they want in plain English and let AI build the new integration.

But look, connected data is not the same as AI-ready data. Today, teams spend more time finding, cleaning and preparing data, rather than using it, slowing down AI adoption, limiting AI accuracy, and it's leading to some pretty frustrated data analysts.

I can't imagine the AI agents are too thrilled about it either. So to ensure AI decision accuracy, you need data that is fully visible and governed throughout its entire life cycle. You need tight control of your data. And this truly needs to be non-negotiable. So that's why we're introducing the ServiceNow data catalog, which delivers native metadata management, data lineage, privacy and ultimately, trust. So humans and AI agents alike can now instantly discover and use curated data products, safe in the knowledge that these data products have their enterprise's seal of approved.

That's great. But getting your data AI ready isn't a one-time activity. Enterprises have to keep it AI ready. And so to ensure the ongoing AI readiness of data, we'll be taking our data control capabilities even further with a complete AI-driven autonomous data governance solution. And we'll be delivering data quality, observability, enrichment and policy management. All unified inside the ServiceNow AI platform.

We'll deliver this through a combination of ServiceNow products and partner products in our massive workflow data network, which now spans data quality, observability, MDM security and integration partner products. Because just like we do with the data lakes, we want to embrace and extend what our customers already have. And that's how our strategy is fundamentally different. We're going to take that a step further by introducing partner passport. So customers can procure and consume select partner products using ServiceNow consumption credits.

On to contextualize. With more than 100 billion workflows a year running on our platform, no one is better able to understand our customers' business context than us. And as Jon mentioned, we bottle that magic up into something we're calling the context engine. So the platform of platforms, as Bill referred to, now has a living graph of graphs. A graph that brings together our knowledge, action, access, asset and decision graphs, all anchored on our powerful CMDB.

Built right into this context engine is our market-leading analytical semantic layer. And we've used that as a foundation for a new product that we're announcing called Autonomous Data Analytics. And so I think conversational analytics to guide the -- what happened, what will happen, what should I do type of decisions that need to be made by both humans and AI? And it's fully autonomous.

So think embedded, think always on, AI analysts working tirelessly on your behalf, surfacing insights, interpreting enterprise-wide data in context, spotting outliers and issues, providing recommendations. Even taking action. And soon we'll be packaging this capability into autonomous data apps, easy button solutions to bring the power of this insight to action, capability right into our technology, customer and employee workflow areas.

And so as an example of such a data app, customers will be able to combine product usage, support, contract engagement data from ServiceNow and let's say, Snowflake or Databricks, data lakes and then identify churn risk to then trigger autonomous customer retention actions in ServiceNow immediately. Finally, converge. Today, enterprises typically analyzed in one system, act in another. We decided to unify both at the database level with RaptorDB. We have RaptorDB standard, which is freely available to everyone and a premium version called RaptorDB Pro that delivers even greater scalability and performance through advanced database features.

Now we're adding 2 important new capabilities to RaptorDB Pro based on feedback from our large customers as well as those in regulated industries. So the first is Live Archive, which is a cost-effective archival solution for ServiceNow that then also allows you to seamlessly query across hot and cold data; and second, Live Connect, which allows you to point your existing BI tool against RaptorPro for real-time analytics with no ETL or data movement. Together, we feel these expand RaptorDB Pro's addressable market in our installed base by tenfold. So there you have it. Four foundational capabilities to power and deeply differentiate ServiceNow's autonomous AI strategy by bringing data and intelligence right into the flow of work.

Next, I'll hand it to Bhavin Shah to cover employee experience.

Thank you, Gaurav. I see a few familiar faces. I know some of us have connected over the years. I'm Bhavin, and I'm responsible for ServiceNow's employee experience products and AI Front Door. I want to cover the third part of this, chart here that you see or the fourth part, where we're talking about this employee experience and the acting upon different systems on behalf of employees.

And essentially, what we're doing is building on the ServiceNow Data Fabric to drive this employee experience and drive values on top of that for our customers. When Moveworks was acquired, Bill, Amit and I got together, and we felt that we were uniquely positioned to take ownership of the AI Front Door for the entire workforce. The reason for that was by combining the Moveworks employee experience with the ServiceNow workflows and Data Fabric, we are creating a powerful front door for work across every system and every employee.

Now we've been busy. My kids call it integration maxing at home. But we've rolled out Moveworks to every ServiceNow employee. We've launched the Front Door to called ServiceNow Employee Works, and we've integrated that Front Door into our new commercial model in just four months. So lots of activity, lots of work going on there. And we're moving fast because there's actually a gap in the market.

Consumers are validating this in every conversation I'm having and in every deal now that we're winning. Now in the past 2.5 months alone, we've seen a 10x pipeline build for our go-to-market efforts, right? That means that demand is here, and we're now so ready to capture it given the two companies and what we both afford and it can produce together.

And I'd say this, if there was an M&A award, I think Bill and Amit deserve it because both of our teams are on fire right now. The AI Front Door is also moving fast. And the frontier is moving fast as well, not just with the models but with enterprises, too. I'm sure you guys know this talking to customers, talking to different organizations. And to build an effective experience across all employees, you need the ability to execute. And this is really critical and hard to do. Now we started off with everyone being sort of captivated by AI Smart and generative capabilities. But then we transitioned in 2024 into what I'd call co-pilot chaos. And this is when every sort of functional AI was being introduced every platform, every offering with no real large-scale enterprise impact. When we saw these various studies come out, people were wondering where is the real value going to hit.

And so today, what business leaders are looking for is what we characterize as enterprise AI. That means it works across the business, right? End to end, not just middle to middle, right, east to west, not just north to south. So I think the differentiation here is that ServiceNow and us together have been able to execute so fast because we can bring these capabilities end-to-end, east to west, all to these enterprise customers.

Now the thing to understand is that for an enterprise customer, a user isn't just a user, they're actually an employee. And this is where our differentiation goes even deeper. Employees have to navigate a complex journey, right, spanning peers, managers, executives, countless systems and unique business contacts, right? This is what it takes when you're running a large organization.

And so these employees have a need that sort of expands beyond just the end users that a lot of the sort of offerings think of people [ as ]. Now we have a deep understanding of the workflows, the context and the action. And we're the only platform really that meets these demands of the enterprise with the employees in mind to get work done. And this is really resonating. In these meetings, we're having in the conversations and the deals we're winning. They understand that we can see this as a lens of actually an employee throughout the year, throughout their month or throughout a week.

And in order to execute this end-to-end obviously requires another formula, right? The fully probabilistic Yolo model of personal AI isn't sufficient, right? We've tried that, we've talked about it earlier. And there's parts of the business that are not open for negotiation. They demand reliability. Right? Think about payroll adjustment, HR investigation and escalation. These are all things that have to be done in a certain way based on the company's policies, based on the company's culture, based on how the company was created over the years that it's been around.

And so not everything will be agentified immediately. And frankly, some processes, according to our customers, will never be agentified because they always wants -- they always want to make sure there's a human in the loop. And so that need for human loop is something that ServiceNow does a really good job of unifying across for these organizations. Now my personal conviction of joining ServiceNow comes down to this, right?

Personal AI gives you outputs. But EmployeeWorks and this new product that we've now rolled out really delivers outcomes end-to-end. And ServiceNow and like harnesses this and executes these plans in a way that gets work done for a company. Let me give you an example here, right? Sending you to this conference becomes less labor intensive for your company. And that is what real enterprise ROI is. Businesses want AI that can deliver outcomes similar to human labor.

And to do that, you have to go end to end. You have to go across all of these systems very effectively. And so in a world where everyone's token-maxing and that's seen as a flex, right? Enterprise AI is actually maximizing token efficiency. And that's on everyone's mind, as you know. And so what customers are really seeking is how can companies do this. And this is ultimately how they will pocket the benefits.

Now this brings us to a unified experience. It's something that I spend every day working on thinking about the whole team is rallied around this. And with EmployeeWorks, we're able to deliver a seamless experience across the patchwork enterprise. We deeply understand the company, its employees. We bring together different platforms and workflows and that's what transformation for a real business comes down to.

That's how we deliver real outcomes. But there's more. So if we actually have an AI marketplace that allows you to build deep into the ServiceNow platform but also along with thousands of prebuilt agents, popular apps like Workday, SAP, Coupa and more. And this actually lowers the cost of ownership, right? The old model of expensive implementations, specialized developers, long time lines, it's gone.

The new model is vibe coding, customized experience in minutes. And so this is how AI scales, not by adding more tools, but by empowering more people to build on a governed platform. Let me give you an example here, CVS Health, Fortune 10 company, you guys know well, 220,000 active users, 2 million conversations, 0.25 million [ fewer ] calls and chats to IT and store service centers. This is real money to the bottom line, 40% year-over-year live Agent chat reduction.

And so this is just one example. I'll use another one Honeywell, they're an industrial giant, 80% of the inbound requests and work, the deflection, if go to service desk has been handled by the AI. The human mediated workflows are actually happening 60x faster because the AI is doing the intermediation and we're seeing -- they're seeing about equivalent reduction in labor costs.

Now in closing, like, I've been selling to this market for about 8 years to the ServiceNow install base. And one thing that we've seen and that was revealed each time we would roll this out was that when you roll this out to all employees, there's actually an impact on the number of workflows and automations that get consumed because you lower the friction to get help. You lower the fiction to find what you need. You lowered the friction to do an action. And what that does is causes usage to climb.

On top of that, what makes us really excited is that ServiceNow has 25 million active users on their employee center. And this becomes the install base in which we're going to be building the future of EmployeeWorks. So I think it's going to be a really great year. And we have a lot of other exciting product announcements and releases coming up for the rest of this year. And so real quick, I just want to give you a quick preview into what you'll hear more tomorrow with regard to ServiceNow Auto.

So you'll see this and you'll learn more about it at the keynote that we'll have in the morning. But ServiceNow Auto is really the combined intelligence of Moveworks and now assist coming together in a new unified experience. You'll be seeing this, obviously, in action shortly as we talk through it a little bit here. But also, I want you to understand that we'll be handing this off to Pat to tell you more about autonomous IT. And from there, we can show you some more.

All right. Well, thank you very much.

Good afternoon, folks. And thank you for coming to this. Like I know we're hoping to educate, share some information here, but hopefully, I can add to that. Bhavin mentioned, I'm going to talk a bit about autonomous IT. I'm going to take a bit of a general statement up at the beginning. We're going to talk a little about just workforce automation, and then I'm going to dive more specifically on how we're applying that to the world of IT because that's kind of relevant to us because it's still the biggest part of our TAM right now.

It's the biggest part of our current revenue base. This has been an automation company really since the get-go. I was one of the founders of the company. I worked with Fred Luddy in the early days. That was always his mental model. He wanted to build a general case workforce automation platform. And that's what's been driving value for our customers for 20 years. You take a process, you put it on service now. It's more efficient. And that efficiency and that productivity is we've been paying us for. That's the fundamental deal here. We make you more productive, if you pay us. There has been a big change in the tools we have available to solve that problem though.

AI gives us a new tool in the toolbox to apply. We do think, though, that we have a bit of a different take on how to apply that to the world of workflows than the traditional enterprise. And I'll start by saying that we absolutely believe there's a value in what I'll call horizontal AI. Bhavin just talked to you a lot about our Moveworks and EmployeeWorks product. We bought a company here because we think it's a real value for our customers and for us.

But fundamentally, horizontal AI is about interacting with you as a requester of services. It's your unified place to ask for things to get information, to kick things off to check on statuses, it makes you more productive as an employee. Behind the scenes though, you still have a variety of, what I'll call vertical processes. If the thing you actually requested is a pallet of steel for a factory in Milwaukee, there is still a purchasing process, which goes through before that pallet of steel actually shows up in Milwaukee.

Those vertical processes are where the actual black letter savings are for AI because that's where people have a job. I'm a purchasing specialist. I'm a sourcer, I'm going to work cases for a living. That's where the big value is for our customer base. It's in the verticals. If you can solve the verticals, it lets you get out of the game of reporting things and asking for things and interacting with things and into the game of actually solving a problem, actually resolving something executing a business process.

So you're not reporting that your e-mail is broken. We actually fixed your e-mail for you. You're not asking for a pallet of steel. You may ask for some automation, we'll actually make sure the right steel, from the right vendor, show up at the right factory, right day and you can build a car. Fundamentally, that's a business process. This, however, is hard. It's hard because most of these processes today are human mediated and many of them will probably remain human into the foreseeable future.

Human beings take part in these processes and a lot of them span multiple systems as well. There's various steps, there are state changes, there's technology shifts in there. And our industry has tried to work around this complexity by frankly, throwing bodies at it. We will throw FTEs at your project, and we will try to wire up your purchasing process with some little sim here and some duct tape here and a little bit of bailing wire here, and we probably get it working. But we've done one of your many business processes at a big investment of FTEs.

We fundamentally believe there's a better way to do this. We want to get out of the game of one-off bespoke process automation and into the game of giving our customers autonomous workers. This is a new paradigm. You saw Bill mentioned it. You're going to see all over the stages here. We are rolling out autonomous workers first inside our IT departments, but also inside other workflows and ultimately beyond ServiceNow.

The idea behind an autonomous worker is very straightforward. It's just like a human being. You assign it work, it approves things. It produces the same audit rules. It follows the same logs. It lives in your user record. You don't have to do business process re-engineering do one of these autonomous workers. It gets us out of the game of saving 5 minutes for a customer here and 10 minutes here and 20 minutes here and into the game of going to a customer and saying, "Hey, you've got 100 people doing that job. I can help you do it with 50 or maybe even 80, whatever the number is, it's less than 100. Let's talk." That's the real value behind the automation and the age of AI.

If you look at where we're going more specifically, we have got a path to zero touch. You will see about 20 of these in the hopper, but 4 of these we want to talk to you about today, Level 1 service desk specialists. I'll dig into this one a little bit more in one slide, so hold your questions. junior IT operators, asset analysts and product managers for PMO. The idea is these are all jobs that our customers have that we feel like we can do some subset of that work with automation. So we can go to our customers and offer them that value.

And the first one we have, which is -- this is live. This is not hypothetical. I've got 6 live pilot customers now. I've got about 50 customers in the hopper, who want to get live with this very quickly. We've actually had to turn people away because the oversubscription is so high here. But IT specialists. You put them in your user record. If you've already bought ServiceNow, you assign to a team, just like you onboard a new human being, and they do stuff. They answer questions. They take basic actions. They solve cases. And they do so in lieu of a human being, but they follow the same rules the human being would.

And this is important for our customers because it will help them get value, and it will help them get more efficient, and it will help them, frankly, save headcount. Fundamentally, that is the game they are in. It's important for us because that's how we grow as a company, as we offer that value to our customers. And fundamentally, it is important to all of us here because this is the productivity that AI is bringing beyond just the technology industry and the society as a whole. This is the promise of AI. We will help make the overall economy more productive. We're going to start with IT, but it's not the end of it.

With that said, enough of me talking about this, let's bring Amy up, she can show it to you.

All right. Great. I'm already here. Thank you, Pat. It's fantastic. Okay. I am incredibly excited to be here and share the product with you and share how -- what Bhavin and Pat talked about really come to life. And we're talking about both individual employee productivity, which then transitions to the productivity of a team, which then goes into the productivity of entire workforce when you look at autonomous workers. So with that, I'll show you how this all works.

Okay. So I'm going to start off here with EmployeeWorks. This is our new unified front door to work. And imagine I'm an ITSM manager at [ Electri ], and I've got a lot on my mind as I start my day. First off, I just moved from California to Washington. I've been getting some physical therapy for my knee, and I don't know if I'm going to get covered for that in my new state and if my current plan will do that for me. And I don't know who to ask because the kind of -- it's the kind of question that might stump us all at work. Do we go to our insurance provider, our benefits, our doctor? We don't know.

So today, I'm going to go in and ask Auto what to do here. So I'm going to type in this prompt and see if I get coverage in Washington. So Auto immediately gets to work. It's checking my plan, verifying that this life event qualifies me to change my benefits, and it's summarizing the answer for me. But not just that, Auto tells me what I need to do to kick off the process. And apparently, I have not changed my address yet. So I'm going to go ahead and put in my new address and enter that in. And now Auto gets to work, updating my address across various systems that work like Workday, which just saved me a huge headache. You didn't have to go in there and change my address. And it's also telling me everything I need to know to change my benefits based on the policy, based on the context of who I am and what's available to me.

So I can assess it's a minimal change in coverage. This looks like it makes a ton of sense for me. So I'll go ahead and enroll in this plan. So Auto can go ahead and finish the process for me. Everything is done. So in about a minute, I went from a complex benefits question to a completed solution, which is amazing. So it's not just about me, though, I'm also thinking about my team at work and what they need. So I'm going to start a new conversation. And I want to see if there's anything I need to do to unblock my team, if there's anything kind of pending my approval. So Auto can go through all the different requests and things sitting in multitudes of systems and pull that together for me at a glance, looking across any tickets that might be open or things that need my review. I see that summarized for me here and also prioritized, which is really helpful. And I can see that Alex is asking for a hardware refresh. And this is actually stalling his productivity because it's gone for quite a while without my action taken.

So I'm going to dig into that and ask a little bit more before I approve this new computer, I want to understand what's going on here. So Auto can bring up his request, and then I can go in and actually click into that request and have it surfaced right here. This is a really cool part of our new AI experience. We can bring the information to you. You no longer need to hunt, navigate, go other places. I can see everything I need to know like Alex's machine is clearly out of date. Everything is maxed out on it. I'm going to go ahead and approve this for Alex. Fantastic. Always feels really good to unblock the team.

Now from there, there's another pending conversation, something that I've been asking about recently that has an update that I can jump back into. In this case, I have a couple of my engineers that provide VIP exec coverage and they have a shift that I need to give them specific access for. Now one of these team members, Jordan, I have to go in and actually review the access. But before I do that, I want to make sure that I can also revoke that access when their shift is over. So I'm going to ask a couple of questions here. When does the shift start? When will this access be revoked? Can we do that automatically?

And Auto goes to work one more time. And so the first support engineer is provisioned automatically, but the second one, Auto can go through and provision and also make sure that their access will be revoked at the appropriate time, which is super cool. And so let's go in there. I'll go ahead and improve it. Everything looks great. Okay. So I just did stuff for my own personal productivity as well as the productivity of my team, which is fantastic. And it's a totally new employee experience, which is so exciting. So we're really excited to have this in our customers' hands and get that available to everyone, as we have so much demand for it right now, which is super exciting.

So next up, though, although that was a lot about employee productivity, we also know that sometimes despite everything we do, a team can get swamped. There's too many inbound requests. So I'm going to go over to my ServiceOps work desk and see how my team is performing overall and go into my ServiceOps dashboard. So unfortunately, even though I did all that great work for my team, there's still some bad news here. Our backlog is up, CSAT is dropping down, and we're still overwhelmed by the volume of work coming in. And like Pat talked about, that's where an L1 IT service desk AI specialist can come in.

I'm still learning about what this can do for my team. So I'll ask Auto what I need to know about it. Auto, again, goes to work summarizing everything that this IT agent can do for my team. It's reviewing specialized capabilities. It's also projecting how many incidents this could solve for my team, brings up an entire profile right here on how well this AI specialist will perform, including the eval score, which gives me high confidence that this will perform at a level that I need for my team. I can look through and see everything set up, including the skills that this AI agent will use and also escalation path. So in case there's a really complex issue, it can get routed to a human.

So this looks pretty fantastic. And based on what it's going to do for the CSAT of my team, there's no question, I'm going to activate this AI specialist. All right. And just like that, it was added to my team. That's incredibly easy for any manager, who's feeling swamped or that they don't have enough resources, they can activate these AI agents and add them to their team. No admin, no configuration, no deployment, just a few clicks, and it's there. So we'll fast forward in time. And I come back to that same dashboard and I see, great, everything is tracking on time now. We've got our AI specialists on the team. Things are progressing well. CSAT is back up. But I also want to audit how this AI specialist is performing.

So I'll go in and ask Auto to give you an analysis on this AI specialist. Go through, it looks at all the past activity, looks at the metrics, CSAT scores for this individual. And it pulls together again, an awesome comprehensive briefing for me. I can see that the specialist is handling 52% of all requests, CSAT of 4.6. This is fantastic. But I also want to audit exactly what it's doing in a particular incident. So I'll click into one. And I can see a full record here of exactly every step that, that AI specialist took. So I have no doubts about how it's doing this work, how it's resolving these incidents and the effectiveness it has, not only for my team, but for those that it's helping.

Great. So everything is working really well. This combined team of both humans and AI specialists working together. This is truly the future of work, not just AI that assists, but AI that acts and resolves, delivering real business outcomes. So very excited to share that with you. Next up, John Ball will be joining us to talk about our innovation in CRM. Thank you.

So I'm going to be covering the fourth key step to unlocking AI transformation, Act, and I'm going to do it through autonomous CRM. And so let's get straight to it and start by recapping just how far and fast we've come in CRM. In 2023, I was up here and telling you that we have become the fastest CRM player ever in the history of the industry to get to $1 billion in ACV. And now just 3 years later, we're going to blow through that -- double it and blow through $2 billion. So we've massively expanded our functional footprint to deliver awesome experiences across the entire customer life cycle from lead and opportunity management to configure price quote and order management, all the way back to where we started in customer service and field service.

And we're doing this at scale, managing over 1 billion cases per year, over 1 billion order and work order tasks. And at peak times in CPQ, we're configuring 100 times a second, every single second at peak times. We're recognized as a leader in CRM by analysts like Gartner, Forrester and IDC. And last, we have industry-specific IP that speeds time to value across multiple verticals. And this growth and success is driven by our deep understanding of how to solve real challenges in delivering great customer experiences. And I'll give you a hint folks, it's not about tracking interactions in the database.

In service, you have to provide great omnichannel intake of requests and you have to make resolving those requests easy and efficient. In sales, you have to go beyond just tracking leads and opportunities. You have to make it fast and easy for sales reps to configure, price and quote those opportunities. And all of that, you need workflow, powerful workflow. You need the ability to model the products and services a company sells as well as the types of requests, orders and changes their customers are entitled to because without workflows and without the ability to model this declaratively or you're just writing a bunch of custom code.

And a Vibe-coded app on top of a shaky foundation doesn't resolve the requests. It just makes disappointment happen faster. So whether it's handling a warranty claim, disputing the Visa transaction or ordering a new telecom service, all of these examples require powerful deterministic workflow at the core. Now what AI does change is how customers, sales reps and customer service reps interact with these systems to get the job done. With conversational AI, you can talk and chat with the system using natural language. So that's cool, but it kind of reminds me of some great Elvis lyrics, a little less conversation, a little more action please because you don't reach out to a contact center or a customer service center to have a conversation.

You reach out because you want action taken to resolve your request. And understanding this point is crucial because the vast, vast majority of customer service requests are not how-tos, the web and YouTube solve that. And I'll use a simple example to illustrate my point. Say you want to change an existing order. This seems simple and straightforward, but to deliver this, you need to understand the intent request order change. Then you need to understand all the specifics. Is it a change of the delivery date or of the quantity or of the actual product being ordered.

Conversational AI is great at capturing all those intents, but then workflow is required. If it's a change in quantity, do we have enough inventory? Or if it's a change in the product being ordered, you've got to rerun the CPQ process to check for compatibility and then generate a new quote. That's CRM workflow logic, and that can't be solved with AI alone. And here's my most fundamental point. You have to get it right every single time. You're certainly not going to run refunds, disputes, orders or anything else mission-critical in the stochastic process that might hallucinate.

In sales CRM, CPQ is a great example where AI can really turbocharge productivity. So imagine sending a draft quote to a prospect just minutes after a Zoom call with that prospect that is tailored to the specific requirements they described in the Zoom call. That's now possible with AI-powered CPQ as long as you have headless and speed of thought CPQ engine that enforces all the compatibility rules, bundling, discount policies, et cetera. Luckily, we do. Now this is not theoretical. We're live in production with sales, service and CPU use cases with amazing customers like you see here, driving better customer experiences and millions of dollars of savings. And several of these customers are presenting here at Knowledge, so you can hear their stories firsthand, not from me, from them. From NVIDIA, who reduced time to quote from 5 days to 5 minutes. It's just an amazing stat, 5 days to 5 minutes or Rossmann, a large European retailer, who deployed our Agentic CRM for retail store support, saving a massive amount of time and allowing store associates to focus on the customer, which is their real job.

Now there's no better way to understand this all than through a demo. So please welcome Chris Shutts, CEO and Founder of Logik.ai, who now runs all of sales CRM for us. Chris, take it away.

[Technical Difficulty] Pretty complex generator. It's got dozens of options, dozens of different pricing rules. It's a pretty complex piece of equipment, and he wants to change his order. So what he's going to do is he's going to call into [ Electri ] generators, and he's going to interact with one of our CRM voice agents and see if he can get his order changed. So let's see how Marcus does.

[Presentation]

Okay. So here, you can see Marcus has interacted with our voice agent. She's asked a couple of questions about his order. And behind the scenes, the AI agent querying our order management system and finding possible orders that might be for Marcus that he placed a month ago. She then clarifies the correct order and then finds it. And let's see what Marcus wants to change on this order.

[Presentation]

Okay. So what's happening here is the AI agents interpreting what Marcus is saying in the large language model and then mapping it to options in our configure price quote application. So this is what John was just talking about with this concept of speed of thought and 100% accuracy. So we've got an agent that's querying the option availability in CPQ and then making sure that all of these options fit together real time. In this case, Marcus needs an automated transfer switch in a maintenance plan and the agent is making sure that all that will work for his order.

[Presentation]

This is a pretty typical case for a complex expensive order like this, where there's a lot of back and forth dialogue with the customer, especially when you're doing order edits and order changes in manufacturing systems typically. So not only do we have the voice agent interacting with CPQ to make sure all the options fit together, the performance is really important. So we put a lot of work into our solving engine that runs inside of our CPQ app to make sure that, to John's point, we can get answers that are speed of thought so that Marcus has a good interaction with the AI agent real time.

[Presentation]

So now that we know exactly what Marcus wants, the AI agent can take all those options and then rerun the manufacturing bill of material rules because this is an engineered piece of equipment, so the bill of material is dynamic based on the options. She also needs to run all the pricing rules and then perhaps most importantly, figure out when they can actually produce it and manufacture it and she needs to give that information to Marcus before she can close out the order.

[Presentation]

So now that we have the product configuration, the bill of material correct, the sales bill of material that goes with this machine. Now the agent is taking all that information, putting it into a customer-facing document that she can then send to Marcus real time so we can confirm like billing address, shipping address, payment terms and things like that.

[Presentation]

So now Marcus has the e-mail on his phone.

[Presentation]

Great. So now you can see Marcus in a couple of minutes was able to interact with a voice agent and actually make some pretty complicated order management changes using the agent interacting with our configure price quote and order management applications real time. So thank you.

All right. Great job, as always, Chris. So hopefully, for those in the audience, that demo helps you understand how we're combining AI, data and workflows to really change the game in CRM. We're delivering better customer experiences, while improving our customers' cost structure, which is really something that every company on the planet wants. And so that's just a huge tailwind for our business. And with that, it's time to pass to my colleague, John Aisien. John should be coming up here. Take it away.

Thanks so much, JB and Chris. As JB mentioned, my name is John Aisien, and I'm responsible for our risk and security products. And what I'm here to do is to walk you through the fifth layer of the 5-layer cake that Amit and my colleagues have stepped you all through. I'd like to start by making a bit of a bold claim. ServiceNow is a security leader. We spent the last 5 years already establishing significant preeminence in the governance, risk and compliance market, growing that business tremendously, nearly 4x greater growth over the last 5 years than the market itself is growing.

My primary goal of the next 10 minutes is to essentially provide you with the proof points that back the claim that I'm making on this slide. Let's start by grounding you on the foundations. As Gina and team shared at the end of Q3 last year, our Security and Risk business, a bit of an unsung hero within our portfolio, surpassed $1 billion of CACV at the end of Q3. We grew our business, Security and Risk organically 40%, 4-0 percent, in 2025 versus 2024. What has this growth been powered by? Two foundational anchors that have enabled us to achieve the results that we've achieved.

First, our IT asset data gravity, right? For 20 years, we've been the preeminent even provider of IT asset insights and the workflows built on those assets that enable compounding in terms of the asset gravity that we have for a typical enterprise. You combine that with the east-to-west coverage that we have across so many buyer persona and user persona, back office, human resources, supply chain, source to pay. I promise I won't go through all of them, but essentially 10 primary persona that we address across the enterprise. And if you believe, like I do, that all enterprise data is ultimately security and risk data, you could see how that provides us with both the right and the responsibility to achieve the preeminence that we've already achieved.

But what we realized is as we're building the next-generation architecture for this platform shift that we're going through, the agentic AI platform shift, we needed to add to the IT asset data gravity that we already have. So over the course of the last 2 quarters, as you probably have heard, we've been a bit busy inorganically. So one of the first things we did was acquire Armis. In one sentence, what is Armis to a CISO? Armis is a cyber asset graph. It enables us to take our IT asset dominance and provide a comparable view of that same data to the CISO, while adding incremental attributes and asset types that we previously did not cover exceedingly well.

Code, unbelievably powerful in this age of AI, OT, IoT, medical devices. But all of that is our cyber asset graph. You combine that with what we did in March by closing on our transaction of Veza. And at its bare essence, Veza is an access graph. It's a way for a typical enterprise to gain insight into who and what has access to what. And then you build extremely high-value applications on top of that. Agentic or not, that is extracting insight from that data play. And of course, the third dimension in the multidimensional core that ServiceNow Risk and Security is our Knowledge Graph, essentially the enterprise context that can take the exact same set of assets and access in Deutsche Bank, and that will generate a different outcome from the exact same set of assets and access in Allianz because the context of both organizations are different, different policies, procedures, rules, regulatory frameworks, people, et cetera.

So it's this combination. If you want to leave with anything from this presentation, our core in ServiceNow Risk and Security is powered by cyber assets, the things, access to those assets by humans and other things and enterprise context. All of this furnished across all of the platform building blocks that my colleagues have been talking about. And this combination is already meeting at the customer. We're not the only bright folks that have this insight. As an example, a global international financial services leader, whom I might add, has a representative in this room, is using ServiceNow Risk and security today, has combined that with Armis for capturing connected asset information across their building management systems and then able to extract potential vulnerabilities from those BMSs and essentially automatically remediate prior to any incident occurring.

This same customer also uses Veza to enable visibility and intelligence by both humans, systems and agents across the 50 or 60 AWS services that power a subset of the cloud estate. And it's a comparable story that we see across an international consumer packaged goods leader whose story I won't step through for brevity. What are the growth drivers, both current and future, that are powering this business? There's 4 that I'd love to leave you with. As we become a full-blown workflow to use the ServiceNow parlance, I expect my colleagues in finance to begin to share insights about this business over time.

Here's 3 leading indicators that I want you to remember. One, how is this business doing organically? How are we growing usage as a key leading indicator to then growing ACV? That's one. Two, as many of you saw in our April 9 announcement around our AI native packaging, we did something super interesting. We enable the entirety of our customer and our partner base with the rights to AI Control Tower, the delivery mechanism for all of this IP. So one of the additional leading indicators that you should watch for is our effectiveness in building net new IP and driving our existing IP to market as an attach to AI Control Tower.

The third. I've been in the cyber industry directly and indirectly for about 26 years with Brad. I remember him from 25 years ago. And one of the dreams of the CISO ecosystem through this time is collective defense. The attackers are actually collaborating on the deep dark web, as you all know. The economic and the architectural prerequisites, enabling the defenders to actually collaborate, have been, shall we say, lacking. I believe that the machine speed by which agentic workloads can identify code defects, change them into vulnerabilities and do [indiscernible] with that requires a next-generation architecture.

And the Action Fabric that Sig talked about earlier is the enabler for collective defense in the enterprise all up. And I'll describe why in a bit more detail in a minute. This is the architecture by which everything comes together. The data plane I described earlier, powered by assets, access and knowledge, manifested through the context engine and delivered through the Action Fabric to both ServiceNow Risk and Security workloads and third-party workloads.

So imagine a circumstance where even though we're now a fully-fledged provider of exposure management solutions post Armis, a customer is already using CrowdStrike for exposure management. They're using Microsoft for endpoint, but they want incremental value arising from that 3-axis core that I described, powered by ServiceNow. We can serve that up in Action Fabric and CrowdStrike agents, Microsoft agents can take advantage of that derived insight for both decisioning and for action. That's the next-generation architecture that we're making real, all of which spin meters for ServiceNow, as we're delivering value to our customers.

So to wrap, our enterprise data intelligence layer that's unparalleled in its coverage of buyer and user persona in a typical enterprise requires us, provides us with a responsibility to enter this market in a material way in the way that we have and to become a participant in the primary table by which the next-generation architecture gets built, as this platform shift becomes increasingly mainstream. Action Fabric is the collaboration layer, the enabling architectural building block that enables all custom risk and security workloads and third party ISV workloads to collaborate with ServiceNow workloads to reduce security -- increase security outcomes, increase risk outcomes and generate business outcomes as a result.

And the last thing I'd like to wrap with, remember the role that Zero Trust played as an architectural north star for the cloud world as workloads moved on mass outside of the firewall. A comparable next-generation architecture is needed for the agentic world. And I will posit that the notion of permanent access privileges in systems is going the way of the dodo. It just doesn't make any sense. And so we're going to play a role in making that vision a reality by taking the IP that we have, the IP that we've acquired and the people that we've assembled to contribute to this zero privileged architecture becoming a reality.

So to provide you with some insight into why I believe this claim continues to have credence, I'm going to have Nenshad Bardoliwalla, our AI platform product leader, demonstrate this through a simple demo scenario. Nenshad?

Thanks very much, John. You've seen a glimpse of what the AI Control Tower can do. But today, we're going to dive into the secure, risk and compliance capabilities. So first off, let's look at CVS Health. They serve over 185 million people a year, and AI powers all of their operations. With hundreds of models, agents, tools and prompts, the greatest unmanaged exposure for CVS' security team is the speed at which AI is increasing their attack surface.

Today, I'm going to be the security admin in CVS' AI center of excellence, focused on securing our AI investments. The AI Control Tower gives me a single view of our AI security posture. Now the moment I log in, I'm going to go ahead and check out the governance page, look at security and what I see is that AI asset security score has dropped overnight to 28%. Now I just need to figure out why. And sure enough, a new alert gets flagged up here that the Aetna Benefits AI agent has anomalous privileges. This agent helps millions of members understand their coverage in plain natural language, and it's at risk of leaking PII, member names, addresses, phone numbers. They can all be inadvertently leaked to other members.

So let's go ahead and start the remediation process. I click remediate and immediately, Armis' early warning flags agent vulnerabilities and active exploitations targeting health care. And while this agent was built with good intentions, Varonis detects it's gained elevated permissions and can share PII with other agents, requiring immediate action to stop a potential data leak. In addition, our asset intelligence here on the right shows how this information can be shared between other systems and agents.

So going back to this overprivileged state of the agent, I'm going to approve the recommended access permission adjustment and multiple things are going to happen simultaneously as a result. Let's go ahead and do that. Yes, please reduce my agent access. So we're going to temporarily disable the Aetna Benefits agent. We're going to work with Veza to remove permissions. We're going to update the AI Control Tower inventory and then the exposure record is automatically created in the unified security exposure management application created for my team to review when debriefing.

Now this agent's elevated permissions and its connection to other critical assets were caught because it was under continuous monitoring. So I ask myself, what other risk, vulnerability or active threat may be out there that we don't know about. Let's go take a look. So I can see here that I've already gotten my score up to 78%, which is exciting. But I can go ahead and use the power of Armis' shadow AI detection and find that there are 3 other AI agents running in CVS Health's business units. This is shadow AI without any visibility or governance.

Each one could be the next compromised or overprivileged agent. So I'm going to change these to managed. And AI Control Tower opens up 4 new use cases in USEM, 1 for the original agent and 3 for the additional shadow AI agents that our asset discovery capabilities identified. I mark them and once they're managed, now continuous security, governance and controls, monitoring happens across every managed agent. So here's what I just showed. We caught an agent with elevated permissions serving 37 million members, and we contained it with a full audit trail in a single operation. Number two, we uncovered shadow AI agents that no one previously knew even existed. And number three, we created incidents for all of these findings with audit-ready documentation.

In this representative example, I am firmly the human in the loop as CVS' current policy for agentic execution requires. But the AI Control Tower can also operate fully autonomously from continuous monitoring to anomaly identification to remediation. And with that, we're going to hand it back over to Amit to take us home in the product section. Thank you.

All right. Thank you, Nenshad. Thank you, John, and to all the speakers. That was just amazing, I think. I'm sure you can see how proud we all are of what we have built and our strong innovation road map. The world-leading analysts also make it clear that they agree. In the last few years, our analyst recognition has grown from 6 -- just in 6 categories to leading in 39 categories, and that number continues to grow. And our recognition isn't just limited to our traditional products. Across the new categories, especially agentic AI, ServiceNow is now consistently recognized as a leader.

And our future road map is also accelerating. That's partially because AI is not just empowering our customers to build and work faster, we also are leveraging the same AI technology to speed up our innovation as well. What you see behind me is the breadth and depth of what's coming in 2026 alone. Across every area, we're shipping AI native capabilities and autonomous workflows to power our customers' agentic enterprises. And underneath all of this is a platform that continues getting stronger and more powerful every day.

And the one key piece of our road map strategy is acquiring specific features and functions that accelerate how we deliver value to our customers. I know there are a lot of questions about our M&A and the investments we recently made. So let's talk about it directly. Bill also alluded to you earlier that we're making strategic decisions to acquire both tech and talent that strengthen our platform and also further differentiate our core. And we already have proof that, that is already working. You heard that in terms of the big bets we have made from Bhavin, Amy and John Ball in terms of how successful our products have grown and how well we are getting differentiated in the market because of those acquisitions getting integrated into our product portfolio.

For us, these acquisitions are not just about buying growth, they're also -- they are about delivering the critical pieces to power our customer agentic capabilities and agentic enterprises. They fit right into our platform, making it stronger and more relevant. We've also taken the same AI native mindset that has reimagined our products and our road map to evolve our commercial model as well. As many of you know, seat-based pricing does not reflect the value of AI. So we have moved beyond it. AI is now embedded in every tier of our products from foundation to advance, to prime.

Another shift is how we meter value. The unit of value is the work that gets done in real time. And we now have hybrid as well as consumptive meters across all of our entire portfolio today. And this gives customers something predictable like a subscription commitment and something which is flexible, so it scales with their actual adoption. And we're using different meters across the whole portfolio now. AI Assist, for example, for AI and data-related products, human and nonhuman identities for Veza, assets for ITAM and Armis.

And over the last year, hybrid and consumptive meters accounted for more than 50% of our net new business, and that number will only grow. Innovation in our commercial model and our products also go hand-in-hand. For example, we're building an AI native service management product designed for the mid-market. It will be entirely consumption-based and conversation first. This will be one of the first of many ways we're taking the strengths of our platform to entirely new customers through new channels as well.

And with our shift towards autonomous workforce, we're also going beyond traditional software budgets and tapping into the labor market. Our customers can now hire, manage the performance and retire digital equivalent of human workers for a fraction of the cost. And these autonomous workers can be added or removed on demand and are constantly expanding their skill sets, as they learn more and more as part of our platform. And this is the hybrid workforce of the future, which we are now making it available today.

Our AI specialists capture at least 6.5x more value, while saving the customers over 80% compared to the cost of human fulfillers, which it replaces. And beyond the numbers and beyond the market recognition, at the end of the day, customers are the biggest proof points of our success. The enterprises that run the world have trusted us with their most critical operations at one of the highest renewal rates in the industry today. So we have covered a lot of innovation in the session today. So I want to come back to our 4 pillars of everything we do: sense, decide, act and secure. And of course, the AI platform that everything is built upon.

Here's what we know to be true. We are in the midst of the most significant enterprise transformation ever. Every company in the world will leverage autonomous work. The only question is how and who helps them get there safely. We have the platform, the architecture and the track record. We have the customer relationships, the partner ecosystem and the talent. We know how to execute it at speed and scale. And we have a commercial model, as you heard before, to capture the true value of AI. And we have done this before. We know what it takes to lead a market through a generational shift, not just participate in one.

Thank you for joining us today. I hope you are as excited as I am for what's ahead. Now I know you guys noticed that we're running a little late, so we're going to take a short 5 minutes break before Paul walks you -- go through the go-to-market strategy. Thank you all.

[Break]

Please welcome President, Global Customer Operations, Paul Fipps.

Okay. Welcome back, all the great innovation from Amit and the team. That was fantastic to see. Now the last time when we were together, we laid out a strategic thesis, platform, industry and global scale. And today, that thesis is working. First, AI platform-led. AI data, workflow, all united on one enterprise platform. Not theory, but real execution. Customers are live, partners are building and the platform is delivering. Now just as important, deeper industry relevance, solving complex mission-critical challenges across financial services, health care, manufacturing, retail and public sector.

And third, global expansion. We said we would invest with intention internationally. And today, Europe, APAC and Latin America are proving that strategy right. We have made real progress. But the bigger signal is where the market is going next. Across every boardroom, in every industry, in every geography, the market is converging around 3 realities. Enterprises want to identify workflows. They don't just want to automate tasks. They want AI that can reason, they can decide and they can act. Critically, they want speed. They don't want value in 18 months. They want value now. And to do that, they need orchestration and control, one platform to govern AI across every model, every workflow and every function.

This is no longer about experimenting with artificial intelligence. It is about operationalizing AI at scale securely. And at ServiceNow, we were made for this moment. So today, I'm going to focus on 4 ways that we are driving agentic growth: one, workflow identification; two, autonomous implementation; three, AI-powered ecosystem and four, our strategic expansion. So let's get started with identification. Now let me show you what this looks like at one of the most advanced technology companies in the world, NVIDIA. So NVIDIA didn't come to us with a single point solution or challenge. They came to us because scaling AI inside the enterprise requires orchestrating multiple complex systems simultaneously.

So let's take a look at all 4 areas. In field engineering, AI agents now triage and troubleshoot in minutes instead of hours. Configure price and quote, those times for some of the world's most complex AI infrastructure quotes dropped from 5 days to 5 minutes. In customer success, AI is enabling proactive management at scale and in knowledge management, altering agents continuously create and maintain critical documents. So here's the punchline. This is not isolated automation. This is platform-level agentic AI, multiple AI agents operating simultaneously across multiple business functions. And NVIDIA isn't the only place this is happening.

Across our customers, our 4 deployed engineers -- our elite 4 deployed engineers that you saw before are powering the Now Next AI program that I spoke about last year. They are doing the work of business reinvention, identifying workflows on-site, inside customer production environments. I'll give you an example. NTT Data. Our 4 deployed engineers are shoulder to shoulder using AI to ensure 70,000 configuration items are fully under compliance. At PayPal, we're helping process trillions of payments faster. And at Robinhood, we're ensuring seamless onboarding, as they scale headcount 26% year-over-year while integrating all of their acquisitions. Workflow identification, that is only what ServiceNow can do.

Let's turn to agentic implementations. Deployment velocity is no longer a services differentiator. It is now a strategic growth lever. And we now have 2 paths: self-implementation, AI-guided deployment built directly into the platform or services-led implementation, AI agents embedded in ServiceNow's delivery process. This dramatically compresses implementation time lines and time to value. So the result is some customers are going live up to 2x faster.

Let's take the State of Hawaii. In one of the most regulated environments imaginable, we move from workshops to go-live readiness in just 6 weeks, 6 weeks. Historically, this could take many months. Now that's not incremental improvement, that's enterprise deployment velocity that's completely redefined. Now let's talk about one of our most important stakeholders, our partners. Partners are no longer just extending reach. They are accelerating implementations, they are expanding category adoption, and they are compounding platform value for ServiceNow. Here's some data points.

Consulting and implementation, 34% year-over-year increase. Managed service providers, 43% year-over-year increase. Resellers, 35% year-over-year increase in sales certification growth. Why do I talk about that? Because it's a powerful increase in the number of sellers positioning ServiceNow with our customers across the globe. Our hyperscalers. This year, we were Partner of the Year in 5 categories of the hyperscalers. Microsoft's Partner of the Year for ISV Innovation, Google's Partner of the Year in not 1, not 2, not 3, but 4 different categories. And the first one was agentic innovation. Second one, business applications, platform and then financial services.

So hyperscalers are important partners for us because they accelerate revenue across all segments, particularly net new logo acquisition. If you think about it, they give us access to millions of pre-committed cloud buyers, faster procurement cycles and a co-sell motion that's at scale across the globe. And our tech partners and builders, we now have 2,500 applications in the App Store for ServiceNow. These apps are built across CRM, risk and security, technology and EmployeeWorks.

Okay. Let's move to the fourth bullet and talk strategic expansion. This is not adjacency for adjacency's sake. This is disciplined category expansion from system of action to system of autonomous enterprise execution. Starting with ServiceNow EmployeeWorks. You heard earlier from Bhavin. The power of Moveworks and ServiceNow completely unified. Let me give you a customer example. At a customer I talked to recently, the CHRO told me she said, "Look, I have mandated a 10% year-over-year reduction in operational cost through 2028." She said, to get there, I have to have AI handle routine HR inquiries, employee self-service and ticket deflection.

Now ServiceNow EmployeeWorks then became the conversational AI front door for that project with auto identifying the workflows in the background. Result, $55 million in projected annual cost savings, 3.5 million productivity hours returned annually. That's business reinvention. Now the same is true for risk and security with Veza and Armis. Our customers now can see every asset, govern every identity, both human and nonhuman and secure all assets and agents through one platform. ServiceNow AI Control Tower is complete.

Finally, our customers are no longer buying AI as separate solutions. And as many of you know, there's a lot of conversations in the marketplace around seat-based pricing versus consumption. But the future of enterprise monetization is not binary. It's hybrid. Customers want the predictability of platform commitments with the flexibility of consumption where agentic scales and creates asymmetric value for them. ServiceNow's new commercial model ensures AI is built into every offering from day 1. And this model is designed exactly like our platform, predictability where it needs to be, flexibility where it should be and scalability where it matters.

So when I back up and I just kind of take a step and look at the whole landscape, here's what I see. We help customers sense what's happening. We help customers decide with intelligence grounded in enterprise context. We help them act through agentic workflows, and we help them secure everything through AI Control Tower. So now I have the privilege, and I'm super excited to bring out 2 fantastic customers, who are visionaries in their industries, Vishal Talwar, who is the EVP and CBIO at FedEx Corporation and the President of FedEx Dataworks; and Oliver de Wilde, who is the Head of ServiceNow COE for Hitachi. Gentlemen?

Right. Well, thank you both for joining us. Oliver, I'm going to start with you. So you're modernizing Hitachi's IT operations globally. Maybe you could just share with us what's so hard about deploying AI at the enterprise scale of Hitachi. I mean it's a massive complex organization.

So it might be a bit of a controversial start, but the problem isn't just in the technology. That's not the hard part. The problem is in changing the organization. And when I talk about the organization, we're talking about the people, we're talking about the governance and we're talking about the processes. So all of these parts really is where companies struggle because they have to get all of those pieces in line and then the technology actually comes quite naturally and quite easily.

You can always find very smart people to build something, to find a workaround to make it work. We've had those problems in our deployments, and we work through them. That was okay. But really, the harder part was getting all the stakeholders on board, working out what processes you wanted to keep, what data you wanted to keep and how it needed to operate. So I'd say those are the harder things. The technology actually, you guys have made it quite easy for us. The technology is there.

On that change management and basically the operational capabilities of the people...

Absolutely.

So Vishal, I mean, we all know FedEx. FedEx moves 18 million shipments per day across 220 countries and territories. I mean it's an amazing operation, an amazing company. The operational complexity is extraordinary. But from your perspective, what's hard about deploying AI at scale?

The stakes are just significantly higher. I mean if there's -- to put that in context, and you just said it, right? So we operate in 220 countries. We move about 18 million packages daily. And we manage that through multiples of tens of millions of workflows. It's very different if you're playing a 1-person band or a 2-person band. You can sort of get the music right. But now if you're playing an orchestra, you have to get that right across 50, 100. Take that at the scale of an enterprise, for every decision, every workflow, every task to be seamlessly coordinated, to be seamlessly executed, takes a lot of precision.

And to have the right data available at the point of insight and action that it's needed, that data you can trust and then try and bring the entire organization, along to the point that Oliver just made, around talent and change management. It's an entirely different operating mindset for the enterprise. You can't do that with a 1 or 2-person experiment on the side. You can't do that when you know that on the receiving end of your execution is life that is waiting for that parcel to get delivered on time. I mean, health care is our largest segment. Aerospace is a pretty big vertical that we serve. These are high-stake businesses.

You can't introduce risk in an environment. You have to be able to trust that anything that you're doing, whether it's AI or otherwise, you can introduce it responsibly across the breadth and the depth of those workflows. That's the hard part.

Great point. And you often refer to us as the digital backbone, which I think is a really great analogy. So Oliver, Hitachi and ServiceNow have been -- we've been collaborating for multiple years, particularly early on in the AI side. And together, we've seen some incredible outcomes from strong user satisfaction to rapid adoption. But what do you think has made that success possible?

So I think it's always been a partnership. I think we met sort of 4, 5 years ago. And I think the partnership started really there with customer success, and then we were invited to participate in the Lighthouse program. And that was really where we and Hitachi Energy specifically got to help design and build some of the components that we're now seeing today. And really, that allowed us to help you shape it. It didn't come without its road bumps, and there were definitely some technological challenges that we had to overcome, working with the customer success teams, working with the product teams to actually get these things fixed then deployed at scale because as Vishal just said, this isn't just about 1 or 2 people. We deployed it to 60,000 people overnight.

And when we did that deployment last year, we saw like the real benefits instantly. We saw a 25% reduction in our service desk in people contacting it. We saw a 10x like increase in self-service on the service desk that just was not there before. So we saw like market changes, but actually being able to work with you and partner with you to help develop it and change it. And one of the biggest areas that we really, I think, helped with is on the whole value creation. And this is, I think, something that we're seeing in elements of control tower, but really then the value sort of estimation and generation because it's something that I was always getting challenged by my CFO on is, how are you proving that the investment that we're making in the time and in the licenses is actually returning a positive value for me.

So being able now to see that and to quantify and you have all the data in the system, you can see what is being done faster, what's being done slower, what's even not being done at all. And that now you can see it a lot more easily. We went through the spreadsheets, the Power BIs, the manual ways of calculating, and now we have tools and products to do it. So I think that part of the partnership, and I do treat it like a partnership, has always been there, and it's really helped us become successful and see those sort of results that we've had.

I would say you really drove a vision early on of a value-based almost zero-touch IT organization. So incredible partnership.

It should be something that we could all strive towards. And we're definitely not there yet. We're not finished.

Yes. So Vishal, FedEx has a bold vision to make supply chain smarter with everyone. I mean this is one of the most exciting things you and I have done, I would say, over the past year. But maybe share with how your team is unlocking the new value with FedEx Dataworks, which I know you run as well and our strategic collaboration around AI-powered automation across the enterprise.

Sure, Paul. As we just outlined, FedEx operates one of the most complex supply chains in the world. And we've been doing that for about 50 years. And the one thing that we've come to acutely understand is the amount of fragmentation that exists in supply chains. And that amounts to about $1.8 trillion of value that's leaked annually because of that fragmentation. So what we want to do now through FedEx Dataworks is make sure that we bring solutions to market that allows for that inefficiency to be trapped. We want to make sure that we bring orchestration solutions that fill the void and connect all the elements of this fragmentation inside the supply chain.

So starting with Source-to-Pay announcement that we just made, we want to make sure that the insights that we generate -- the first-party data that FedEx network generates, which is about 2 petabytes of data, we want to release those into signals that is -- that benefits our customers so that they can go from a reactive to more a predictive posture in the interventions that they want to drive inside their environment. Source-to-Pay is one example. We want to then extend that to building workflow solutions that allow our customers to more seamlessly orchestrate supply chains inside their enterprise. And that's where the partnership with ServiceNow and FedEx gets pretty exciting.

It's super exciting. You'll see more of that tomorrow with you and Raj on stage. So very excited to see that. Okay. So I think we're going to get to probably one of the harder questions here. And one thing we constantly hear from boards and CFOs right now, I know you all hear it, is why can't we just build this ourselves? The whole build versus buy, particularly with all of the large language models. So Vishal, I'll start with you. What's the build versus buy conversation look like on the inside of FedEx?

Just because I can, doesn't mean I should. I mean, for me, it boils down to that. I said the stakes are high. And it doesn't mean that we will not build stuff. You have to take a more nuanced approach. We are very keen on making sure that the core of our value chain, where we want to have the differentiation, where we want to go and help our customers more deeply are areas where we will want to own IP and we will want to build. But I don't want to be known as the best HR system company in the world, the best IT system company in the world or the best finance system company in the world.

I will shamelessly take that from folks that have much more experience than FedEx will ever have in this enterprise and bring best practices inside and build the digital backbone that you can help bring with speed and channel my energy instead into the core parts of our value chain. So for me, it boils down to just because I can build, I go back to 1 or 2-person band, it doesn't mean I should. There are areas where we will build and there are areas where we will partner and increase our speed to market.

It's a great answer. Just because I can doesn't mean I should. So Oliver, how about you? I know -- I'm sure you've had these debates inside of Hitachi.

Of course, I mean, Hitachi is an engineering company. We're not short of people who want to build stuff, which is a great thing. But I think as Vishal said, it's like just because you can build it, does it mean you should build it. And I think I completely agree with that sentiment. Take the best fits from everywhere else. We're not a software sort of predominant house. We build -- in Hitachi Energy, we build huge transformers. We build switchgear. We build trains. There's loads of stuff that Hitachi builds. Let's keep building that. Let's keep building what we're good at. Let's buy what we haven't and what we don't build ourselves and then integrate it together.

So I think it's maybe slightly less of a build versus buy comment and actually more of a build versus orchestrate and how you assemble this into your digital backbone or your digital core, whatever your company sort of refers to it as, but how do you bring the pieces of the jigsaw together into something that then works for your organization and helps drive your organization forward. And you can buy things from ServiceNow, from Salesforce, from Microsoft, from Google, like pick, whoever it is, but you've got to bring the best parts of that together for your enterprise.

And every enterprise is different. Your needs are different to my needs. I'm not shipping hundreds of thousands of packages around today. But then we do have mission-critical infrastructure that operates in a different way. So we have different needs. So take the best parts that other people make and build it into your best solution.

Fantastic. I know we could -- I could probably keep asking you questions for the next 30 minutes, but I know you guys are both on time. So thank you for joining us. Thanks for coming and sharing how we collaborate together with ServiceNow and FedEx and Hitachi. And maybe everyone give a great round of applause for Vishal and for Oliver.

Please welcome to the stage President and Chief Financial Officer, Gina Mastantuono.

Thank you, Paul. What incredible customers, and hello, everyone. I've been really waiting backstage for a while to get out here, and I can't tell you how excited I am. So not only am I excited to be here, but I'm really excited not only about where ServiceNow is today, but about the scale of the opportunity that we see in front of us. Listen, I know there's questions swirling out there in the market, and that's healthy. Great companies to be able to answer hard questions such as, will the growth of the foundational models come at the expense of budgets for the incumbents? Will seat compression shrink revenue? Do software stocks become only margin stories. These are questions I get all the time.

In ServiceNow's case, the answer to each of these questions is an emphatic no. We are a unique platform company. We're the AI Control Tower for business reinvention. And as you've heard throughout today's presentation, ServiceNow is not a traditional SaaS company. We're the orchestration layer, AI agents run on, not software they replace. We're the AI operating system for the enterprise. We are truly in a category of one, where AI makes us both more competitive and more profitable simultaneously.

We have a clear path to grow the top line and drive continued margin expansion to deliver durable shareholder value. We'll look at this next. But first, I want you to walk away remembering 3 things: one, our structural advantage is ours and ours alone. AI only reinforces it. The AI super cycle is a revenue tailwind for ServiceNow. Two, ServiceNow is the AI platform enterprises are already buying. It's not a bet on future potential, but a flywheel that's already spinning. We're the best-in-class workflow and governance layer where enterprise AI value accrues.

And three, margin expansion and AI growth are not at odds. They're the same story. AI-driven internal efficiencies fund the innovation and bring focus to our growth investments. Let's dig deeper into the growth opportunity. Our core business is strong.

It comes down to execution. As Bill talked earlier, this is a company that executes. In 2025, we grew 20% year-over-year to nearly $13 billion in subscription revenue. We're looking at a 5-year CAGR of 24%. And we added more than $2 billion in revenue in 2025 alone, which is more than the entirety of our subscription base in 2017. Now Assist ACV crossed $600 million last year, more than doubling year-over-year. That momentum carried into Q1 with ACV crossing $750 million.

Now Assist isn't separate or distinct from our core workflows. They are our core workflows. This kind of organic innovation is a powerful growth catalyst for it, much like how AI fueled customer demand in the upgrade cycle from Standard to Pro. Our Better Together story continues to strengthen. In 2025, 91% of our net new ACV came from deals with 5 or more products, up from 86 the year before. This includes a 7.5x increase in Now Assist deals with 5 or more products.

Customers are not experimenting with one AI solution in one corner of their business. They're deploying AI across the enterprise. Customers are going all in, in our core technology workflows, where we saw over 50% growth in deals with 5 or more tech products.

Also, we have three key growth accelerants. Security and risk is the next growth vector for technology workflows. In 2025, net new ACV grew 40% year-on-year, and at less than 20% penetration from the base, there's plenty of room for expansion. With AI control tower, customers govern AI across the enterprise. Its ACV has quadrupled since launch. Armis and Veza further extend the TAM. CRM represents a massive market opportunity, crossing $1.8 billion in ACV in 2025. Sales CRM is leading the way with ACV more than doubling year-over-year.

We win because of our single platform across the entire customer life cycle connected natively to service and operations. Data and analytics is a multiplier, which more than doubled net new ACV year-over-year. As you heard Gaurav say earlier, RaptorDB has already surpassed $100 million in ACV in just its first year. Every AI agent deployed and every custom workflow built pulls demand for data connectivity and performance. All of these growth vectors also have underlying tailwinds created by the proliferation of AI, data and assets. More agents deployed means more governance, more data connectivity, more platform usage.

That's why half of our net new ACV has already shifted to non-seat-based pricing models as they catch those tailwinds. Those underlying units, including assets, infrastructure, platform usage are seeing significant growth. We don't count seats here. We count dollars. With the strength of AI adoption, we're also seeing a growing mix shift towards consumption. That's why we're democratizing access to AI with our new AI native packaging. Every new SKU has a bundle of tiered capabilities across the core product AI, Workflow Data Fabric, Moveworks and/or AI Control Tower. As our customers purchase those higher-value bundles, we expect to see an average price lift of 20% to 30%. This new packaging also unlocks customers' AI consumption journey earlier. Now at every level, consumption becomes an incremental growth driver as enterprises scale usage of Assist, connectors and the underlying assets being governed. Then as customers look for more advanced capabilities, they upgrade to Prime for our most premier offering.

AI consumption is already showing up. Existing Now Assist customers who renewed in 2025 expanded their ACV by an average of over 3x. It's not just about Assist packs. Every cross-sell, every subscription purchased is adding Assist and is part of the consumption story.

As I'm walking you throughout my growth story, you may be asking, where will the budget come from to pay for these incremental consumption costs? AI spend is expanding budgets for ServiceNow. Customer conversations we're having today are focused on reducing labor costs to fund ServiceNow's advanced AI capabilities. Let's play this out. If you had a team of 20 support analysts today, the team would cost over $1 million annually. About 90% of that is labor, 2% is ServiceNow. Now what happens when you move into an agentic AI world, as enterprises look for efficiency, they'll naturally target their largest cost center, labor. ServiceNow's autonomous AI agents can resolve 75% of the team's work, reducing the necessary headcount to just 5.

The customer wins. Their total cost to get that work done drops 65% and resolutions happen in a fraction of the time. At the same time, these 15 freed-up seats convert into 6.5x more in AI agent consumption, just like Amit talked about earlier. Even after accounting for license reduction, total ServiceNow spend grows over 5x. Lower cost for the customer, better experience, faster outcomes, that's the definition of a compelling value proposition, and it's driving the shift we're seeing today. AI consumption compounds as workloads get more complex.

Generative AI laid the foundation with each task consuming 1 to 10 assists. Agentic AI deepens the value curve by completing multistep tasks, consuming significantly more tokens. Autonomous AI specialists represent the next step change, purpose built to perform specific job functions end-to-end with the two layers combined consuming over 15x the assists of generative AI. As AI solves more complex workloads, usage rates climb and so does the value we capture. This is just the beginning. Our autonomous workers will cover all corners of the enterprise as the platform scales.

DocuSign is a customer exemplifying this journey from GenAI to their first agentic use case and, now, to zero-touch service desk, their first step towards autonomous workforce. Using ServiceNow, DocuSign has a target of autonomously handling 90% of all IT tickets so human agents can focus on the most critical work. They expect to save millions, and the opportunity is massive. DocuSign is realizing their vision of true workflow transformation and creating a playbook that they can replicate across their entire business.

This is just one great customer example. You've already heard directly from FedEx and Hitachi earlier about their incredible AI journeys with ServiceNow.

What does it mean for ServiceNow at a larger scale? Let's look at IT incident management, just one use case within ITSM. We see over 100 million incidents per month on the ServiceNow platform today. If 75% of those incidents can be processed by an autonomous workforce, this translates into a $3.5 billion ACV opportunity net of any seat licenses that go away. Multiply that across other ITM use cases and then across the entirety of our platform, we power 100 billion workflows and 7 trillion transactions annually. And you can see the incredible opportunity in front of us.

How long does it take for a customer to realize autonomous outcomes at scale? With all new technologies in the enterprise, it takes time. But as you heard from Paul and others, we're finding every possible way to help our customers accelerate that journey. Let's look at an example. When a customer purchases agentic capabilities, they receive a generous Assist allocation, meaning Assist coverage tends to be relatively more limited in the first couple of years. What starts as a strategic deployment across ITSM, CSM, HRSD becomes a foundation for enterprise-wide AI transformation. By year 3, they're taking on more complex agentic use cases, inflecting consumption. Year-over-year AI ACV compounds, driven by the deepening adoption across the enterprise as the customer naturally graduates up the value chain to autonomous workflows.

The result is a fundamentally different revenue model with fewer seats, but far greater value. We anticipate by year 5, this AI customer would be spending 4.5x the initial Assist entitlement. These journeys have already begun. As Bill teased it earnings, we're raising our 2026 AI ACV target from $1 billion to $1.5 billion. The demand we're seeing is real. These are not features bolted on to existing products. They are built in. They're solutions with strong adoption and measurable outcomes already. When AI attaches to existing workflows, it doesn't just add revenue today. It makes the platform stickier and expand the ACV opportunity for each and every customer. This is a flywheel that's already spinning, not one just being built.

And looking further out, by 2030, we expect 30% of our ACV from ServiceNow AI. When the unit economics work, when trust builds, when complexity scales, this is what happens. And I really just love that math.

Okay. That should give you a sense of our growth story and trajectory. Now let's turn to profitability. AI is structurally expanding ServiceNow's margins. I'm going to repeat that. AI is structurally expanding ServiceNow's margins. I'm often asked whether AI inference costs will compress our gross margins. That framing doesn't apply to us. AI reasoning is less than 10% of our cost to serve. If inference costs rise, the margin impact remains modest. Customers aren't paying us for tokens. They're paying for a resolved outcome. Reasoning is one input. Workflow orchestration, governance, context, cross-system action, that's where the other 90% of the value and costs sit. We're differentiated and our pricing reflects the full platform, the CMDB, the workflow engine, the governance layer, the business service map, 20-plus years of operational context.

That competitive positioning is what sets us apart from the stand-alone AI providers and why our gross margin profile holds. This allows ServiceNow AI to continue to ramp with subscription gross margins remaining above 80%. While our move to hyperscalers is impacting gross margins in the short term, the ROI on that strategy has paid off as net new ACV from public cloud partners nearly tripled year-over-year. We're also not just selling AI solutions. We're using them ourselves. AI is driving meaningful year-over-year gains in output from our fully ramped reps. We're growing the top line while getting more efficient with every sales dollar invested.

We're also seeing an acceleration in the incremental savings from agentic AI flattening the hiring curve, with $200 million in savings in 2026, that's on top of $100 million that we saw in 2025, for a total of $300 million in expected annualized cost savings from agentic AI flowing to the bottom line in 2026. AI agents are doing 90% of the monotonous work. ServiceNow's own support and service operations have been rebuilt on our agentic AI. This margin expansion is structural, not cyclical. We are the proof of concept. Every customer is being shown what ServiceNow has already built at enterprise scale.

All of this allows us to return to normalized margin expansion in 2027. We expect 100 basis points of non-GAAP operating margin expansion and 100 basis points of free cash flow margin expansion in 2027, inclusive of Armis. We can commit to this because operational discipline is a core muscle. And now AI is compounding that discipline with $300 million of hard savings flowing directly to the bottom line. The message is simple. We are not trading TAM expansion for margin expansion. The model enables both, and you'll see that in our numbers in 2027 and beyond.

Turning to our long-term targets. I know you're all waiting for this. All day, we keep you here for this part, right? Okay. Bill gave you a little preview, but I've got a little surprise, so hold, wait, please. In 2021, we established a long-term target to achieve $15 billion in subscription revenue in 2026. Many were skeptical then. I see a few of you in the room. Fast forward to today, we're on track to beat that target by $0.5 billion organically. I know the guide is higher than $15.5 billion. Organically, we're beating that by $0.5 billion. Not many executive teams can say that about their long-term targets. I know you all know that, too.

Our momentum puts us on pace to double that target in 2030. That's $30 billion plus in subscription revenue, and it's not blue sky scenario. It's what a durable platform growth story delivers. As you heard from Amit, though, we haven't been standing still, we've accelerated organic innovation to catch the tailwinds from emerging opportunities made possible by AI. We've expanded the TAM with recent acquisitions. And while we're not asking you to underwrite this upside today, we see a strong path to it, a higher 20% CAGR from our current 2026 guidance and $32 billion of subscription revenue in 2030. Pretty impressed that I got to say that number, right? And he didn't take it.

But this is not blue sky. There's a road map of real defensible growth engines, and they are not heroic assumptions. Security, supercharged by our demand for AI Control Tower and the new TAM unlocked by our acquisitions of Armis and Veza. Data becomes even more critical as enterprises deep in their AI investments. You heard that from customers today. AI has upended the market and we are taking share. Together, these three vectors compound at over 25% growth year-over-year through 2030. Most importantly, cutting across all of it is AI, agentic workflows, autonomous workers, unlocking value in ways that simply did not exist 2 years ago. And I would note this does prudently bake in a deceleration in some of our more mature products.

In this environment, it's a show-me story. I get that. We get that. That's why we're ensuring your top line growth option with a commitment to continued strong profitability. Combining top line growth and profitability at a level a few companies achieve at any size, let alone ours, puts us on a trajectory of achieving the Rule of 60+ by 2030. This is what we're building, a business that delivers accelerating value for customers and shareholders simultaneously year after year.

That means focusing on GAAP profitability as well. Two years ago, we committed to getting stock-based comp below 15% of revenue by 2026. We did it in 2025. We also told you that sub-10% is the longer-term destination. Today we'll tell you when, 2029. It's the same playbook: revenue scale, disciplined equity practices, a comp philosophy that allows us to attract the best talent, but doesn't over-index on stock. Let me put a finer point on how we're returning capital to shareholders. We doubled our share repurchases in 2025. In Q1 alone, the $2 billion ASR represented nearly double the shares we repurchased in 2025, all in 1 quarter. The results? We expect to be dilution net neutral for 2026. We still have $4.2 billion in authorization remaining, so we have plenty of capacity to keep managing dilution going forward.

We're always evaluating the best use of capital to maximize shareholder value. Our framework is clear. First, we reinvest in organic growth at high incremental returns, products like AI Control Tower, Now Assist, workflow Data Fabric show what strategic internal investment delivers. Second, we deploy capital into acquisitions of technology and talent with a focus on tuck-ins that open new TAMs or meaningfully accelerate our product road map. Third, we are committed to returning capital to shareholders, balanced against the significant growth opportunities we see ahead. We will continue to be thoughtful about that trade-off. With the sizable free cash flow generation that will come with our significant margin expansion, we'll also have tremendous flexibility as we think about capital allocation in the future.

So let's end where we started. I know there's questions swirling in the software industry, and it's easier for some people to put us in a box with others. The fact is we are in a category of one. ServiceNow is the orchestration and governance platform that AI requires more of, not less. The AI supercycle is a revenue tailwind for ServiceNow. We showed you the math today. It works. The margin expansion is structural and we are living proof. Our own AI transformation is the strongest customer reference we have. We bring growth and profitability, two engines of shareholder value, both powered by AI. That's how you get to the Rule of 60+ at more than $30 billion in revenue.

Thank you all for joining us today. And now we're going to welcome back Bill, Amit and Paul to the stage for Q&A. Just give us a minute.

Kirk Materne from Evercore ISI. Thanks for a great presentation, both the technology depth and the long-term vision. It was great to see. I think my question is somewhat maybe for everybody on there on the panel. But I think one of the debates going forward is going to be at sort of the orchestration or at the agent control plane. I think every big enterprise, the LMs all understand that a lot of the value might accrete to that layer. It's also super early days in terms of agent deployment for most big companies.

So as investors, what should we watch for? What are the milestones that we can see from you all to know that you're hitting on that strategy? Because right now, I think, everybody it's sort of a land grab and I think everybody is asking the question. I think most people understand you have the right to win there, but what are the metrics, the KPIs we should be watching for to understand your strategies playing out?

Yes. No, thanks for the question. So I think the way I see it, there will be a lot of pieces being orchestrated by different, different parts of the technology providers. But the idea of an autonomous worker takes away this requirement to do individual work by each of the vendors. So what we're doing with autonomous worker is taking away the effort you have to put in to create individual agents, manage them yourself, figure out orchestration, the reasoning and all that thing, which is not really very conducive to a long-term way to manage a business.

So the metric I would look at is how many people are now going to start adopting autonomous worker and how we see that kind of proliferation of AI specialist inside the enterprises so that they can now get away from their dealing with individual pieces themselves, but getting the full value of a solution. So what we're seeing now with the AI specialist, for example, what we introduced is 20 AI specialists, especially the L1 support specialist, we're seeing a lot of customers who don't want to do that building and managing and taking care of the spare parts themselves. They want to elevate that and get a full solution. So I think that, that will be a trend over the next few years versus what is happening now.

Same thing happened with cloud. If you remember, everybody used to buy -- get to the LAMP stack, they wouldn't want to build themselves. Then eventually, they realize keeping and maintaining that stuff is not easy. Dealing with changes in the technology is not easy. And they line up going to hyperscalers, somebody who provided the full stack. And then you can build an application with it, and you don't have to deal with all the different pieces. And I think the same thing will happen with us now. And that's what the metric I'm watching for, and I'm seeing that already play out with a lot of customer conversations I'm having.

Obviously, very impressive to see all the progress you guys have been making and the targets coming out. I think seeing that ACV target of 30% coming from AI out just a few years is really amazing. But I guess on the other side of that is kind of implicitly, it would suggest the non-AI components are going to be growing much slower. Back of the envelope, I did was 10% or less CAGR during that same time period. I think I've had an argument to investors about how that's the wrong way of looking at this.

But I'd love to hear from you all as you receive that question of like, but what about the rest of the business and that seems to be growing slowly? Is that a worrisome sign? Help back me up on like why that's maybe the wrong way to ask the question?

You love that one.

So AI is the core. You're exactly right. Customers want to buy products with AI built in. And that's why we introduced our AI native pricing and packaging. It's why even if people don't want to go full in automatically all the way up to Pro Plus, which is now Prime, they can start with foundation. They can taste it. They can start to about working because who really wants to buy any software today that doesn't have AI embedded in it? So it's 100% the wrong way to be thinking about it.

And remember, you all remember when we first launched Pro, right? No one said, well, the core standard is declining and Pro is doing so well. They said, oh, my goodness, Pro adoption is fantastic. This is wonderful. And you get 25% price uplift. Show me more. That's exactly what's happening today. Only now, it's 30% on top of Pro and now we're embedding actually AI into even the foundational pieces so not everyone has to go full stack right away, but they can really start utilizing the AI, understanding the benefits.

We firmly believe that once they start seeing the benefits in a small scale, they're going to much more rapidly proliferate and grow with us, and that's when the consumption wheel continues to fly. But you're already seeing pretty incredible growth in $750 million in Q1, up to $1.5 billion. This is remarkable growth and we are just getting started. And so it's wrong to think about, well, if AI is doing so well, it must mean the core is not. It means AI is pulling the core. And that's what we continue to see. We're driving all of our customers to be wanting to consume more AI. That is what the benefit of the ServiceNow Platform. It's going to help our customers, and we really see the value accrue over the next year 2, 3, 5 years.

Alex Zukin with Wolfe Research. Wonderful presentation, obviously, would expect nothing less. A couple of competitors out there are saying, hey, we're taking some share from ServiceNow. You have two targets out there, and I would say none of your competitors have the security angle. And it seems like the kind of variability of the upside is kind of partially driven by executing on this new I think, Bill, you called it the largest new TAM is cybercrime. So maybe just talk about how do you see the competitive narrative and the landscape evolving. And how does the security component of your portfolio drive that maybe higher target that you laid out there?

Go ahead, guys.

Maybe I'll start, Alex, on that one. I think on the competitive side, some of those competitors have been loud in the marketplace. We just don't see them in the competitive stack. Now it might be in a different segment that's much smaller than a ServiceNow customer, our target market. There might be some edge case areas. But I think for us, we're very focused on the segments that we serve and innovating and delivering great value for those segments. And any time that comes out, we dive into the research and look at the data and figure out what's working? Are we missing something? So we're very cognizant of what they're talking about.

I think on the security side, just from a pure customer and go-to-market standpoint, we really think about Veza. I've never seen anything like it. Well, I shouldn't say that. I think CPQ is like it. I think when we bought Logik, it just started to really take off because it actually filled out an entire part of the stack with CRM, and John Ball and the team have done an amazing job there. I think with Veza, just the identity, securing human and nonhuman agents and understanding the identity, of course, has given us an incredible extension of AI Control Tower. So I thought the AI Control Tower is complete.

And then with Armis, every customer that we talk to around operational technology, where we're discovering, managing and securing operational technology assets and bringing that back into the CMDB, it is just like a very compelling story. And whatever industry I tell that story in, they need it because they don't have it right now. So I think it's a very close fit with ServiceNow, SecOps, vulnerability response. It's a beautiful extension.

I'll just add one thing. The other part, which is also important is the data part. So the stack we have built, having an AI platform, which as you saw today, is very deep, has very, very critical functionality required to run any kind of AI systems out there, including all the workflows we've been talking about. Now having a data platform, which can bring all the information together to do the context engine work we talked about and be able to make decisions very quickly and predict a better outcome really drives our workflows and outcomes much better than anybody else can do today.

And you bring security on top of that where you ensure no nefarious things will happen in your platform, really changes the game when you go and talk to the customers. They don't have to bolt on all these things separately. They don't have to bring all the signals from separate areas and manage all that stuff in a different environment. So when we bring security and data on the same platform and then you have workflows, gigentic workflows, the autonomous worker, it's really -- I don't think there's anything out there in the market today. There's no competitor who can do that. They can talk about pieces of it. So if you hear the noise out there, they're talking about pieces of technology and maybe mid-market or somewhere else.

In the enterprise space, there's nobody like us. And when I talked about earlier about bringing the same technology now to mid-market, that also takes that business away for them, right? So you'll see a lot more of our capabilities being delivered, AI native, completely consumption-driven, right, and conversational experience now delivered for AI native -- for mid-market with AI native mindset and bringing ITSM and other capabilities to mid-market, which we didn't do before. That gives us another opportunity we've not talked about earlier.

Keith Weiss from Morgan Stanley. Two questions. One real quick question on timing. Gina, you mentioned the Pro SKU, and we saw a really nice adoption of the Pro SKU. Can we expect Now Assist or Prime or I'm not quite sure what we're calling it now, to ramp similarly to what we saw from the Pro SKU? Number one.

And number two, more strategically, you guys are bringing agents to your customers. You're bringing the autonomous worker. You're bringing the AI specialist. But you also have to open up your platform for your customers to build their own agents or let other people bring their agents. So when we're thinking about like the 5x uplift from autonomous worker, what's the uplift when you're just opening up your platform and letting other people build agents on top of your platform like they're going to request?

I'll take the first one and then I'll hand it over to Amit. So on the first one, actually, we're conservatively building in a similar ramp with our AI that we had with Pro. I actually think -- and so far, it's actually been slightly accelerated to what we saw with Pro, but our numbers that I showed are building in the conservative estimate of similar penetration glideway as we saw with Pro.

Yes. On the agent stuff, I mean, I think there is the architectural evolution, which is happening where there are going to be agents interfacing into applications. They're not just going to be users or humans just interfacing. So having an ability for us to provide that access in a governed manner with monetization is the right way going forward. So I do expect more and more of that kind of use cases emerging. And what we have done is we've been very careful about how we expose it. So we have an MCP server. We allow agent-to-agent capabilities as well communication. But we heard about Action Fabric. The idea is that we will wrap this thing with a set of APIs, which are governed, but also monetizable.

So we measure every assist -- using the Assist kind of metric, measure any access, and we meter that and people can burn down. So it makes our Assist more fungible, not just be able to do Now Assist kind of use cases, but also now accessing data. But we can get to manage it and make sure that you register for it, you have what kind of requirements, the SLA, the security. So we're bringing all that stuff into this thing. And one of the announcements we did is with Anthropic to be able to also do things with their cowork, but it's also in the governed and measured and measured capability so that it doesn't allow people to just get access to it without any kind of permissions.

Arjun Bhatia with William Blair. Actually, I wanted to follow up on Keith's question about Action Fabric. And I'm curious if you worry that customers might push back that you're essentially introducing a gate for their data. And I'm curious how much of it is theirs versus yours? Or does this all not matter at all because the ROI is going to be high enough that they are going to come out -- customers are going to come out winning on top of this?

And then one question for Gina. I'm curious when the pricing model evolution might take place such that most of your revenue, not net new ACV, is consumption or non-seat-based. How do you see that playing out throughout 2030?

Yes. I'll address that. I think we have been talking to customers about how they want to access our environment and what ways they want to -- one, what the volume they would need, what is the different kind of metering we would require for that and what would that metric cost would look like. And so far, it's been pretty well understood by them. They realized they used to access things, but there was no guarantee of SLA. There was no way to know who was accessing and what security issues you would run into.

So when we provide a much more governed platform, they seem to be very comfortable with it so far. And when we've been introducing this concept, we've talked to many customers already, and there's never been an issue in terms of worry about having this kind of metric being delivered. And given that it gives a fungibility within Now Assist, it also makes it much easier for them to think. It's not a separate thing, which we're introducing or creating a new kind of metric, which would be confusing otherwise.

On your question with respect to non-seat-based when we think net new ACV would be more -- listen, I was really thinking that you all would be pretty impressed that we're already at 50% so far. And by the way, it's been increasing pretty rapidly over the past couple of years as Now Assist has been driving a flywheel. And so we haven't given time lines for what we expect that to look like long term.

I do expect the 50% will continue to increase. I don't think it'll ever be 100%. I think some of our business will always be seat-based. And if you think about kind of the new AI native pricing and packaging, just by virtue of the initial subscription, you're getting a large chunk of assists in there. So there is consumption already baked into that initial seat. And so consumption will continue to be a bigger portion as we go forward.

I think it's probably also worth noting that nobody buys software from a major enterprise market leader because they have seats or consumption or based on the value. It's always based on the value. And then it's how you back into the value in the way the customer is most interested in it. In our case, we have no problem with seats one way or the other because we have consumption, but it just so happens that our active users aren't going down because we go east to west. And so if you think about the 2019 ServiceNow, around $3.5 billion, we pretty much add a new ServiceNow every year.

And I would just -- sorry, were you finished?

No, I was just going to say, and the active users because now you've gone from IT to the employee, to the customer, to the creator, to the data, to the Control Tower, to the security, the number of human beings and machines and robots are all going to expand. So however we mix the formula, it's a great formula for shareholders. .

I was just going to add, the hybrid pricing model of subscription plus consumption has been really resonating with customers. They like a bit of predictability as well as if they exceed, being able to understand how much consumption is coming through. And so we'll stay on the forefront of where the customers and where the market is leading. And hopefully, what you're seeing in all of the announcements here is that we're always on the front foot of how customers are really thinking and how they're thinking about driving value from the platform.

I think this is such a hot and important topic. I think, Paul, you would agree that a lot of customers are getting a little bit surprised on the tokenization of models and how that is surprising their budget landscape, which is forcing them into more predictability with enterprise leaders like ourselves, where they want the seats. They want to be able to predict their budgets and they're getting highly surprised in some cases. So as Gina said, this hybrid model seems to be like the Goldilocks formula right now, but we're open to anything.

We're seeing a lot of vendors copy that now, right? I think it's becoming the industry standard where we introduced last year -- a couple of years ago.

Yes.

Exactly.

Brad Zelnick, Deutsche Bank. Really appreciate the very compelling presentation today. Bill, I wanted to follow up on your comments about now being the right time to go further down market. Why now? And why might it be different? Because in the past, it seemed the medium-sized enterprises didn't really value the platform the way that large enterprises did. And I'd be curious as well what your view is on AI readiness in kind of medium enterprise? And relatedly, what does this mean for partner leverage? Does this create an opportunity for a whole new set of partners?

Brad, first of all, thank you for your kind remarks. The team really put a lot into it, and I'm glad you saw the innovation today. Thank you so much. I'll give my color on it. And then, of course, Paul is very close to this each and every day. But we have a more complete story now than we've ever had before. And with AI, the autonomous implementation, because if you think about implementation risk and the time to get things off the shelf for mid-market customers who generally don't have the staffs of a large customer, if we can do that through autonomous implementation, all of a sudden, that's a much more attractive conversation.

And I'm not suggesting that we're going too far down because we want to be where the money is and we want to be where the retention is. So it's not just the number of new logos you get. It's being thoughtful in getting the right one so they stay with you and you don't lose your retention leadership. But the offering can be lighter weight. It can be autonomously implemented. And when you think about all the things we have now, we have so many different ways to come into the mid-market customer that we didn't have 2019 to, let's say, even 2024. So I think we're a new company. We're transforming even as we roll.

Paul, anything you want to add?

I think it's great, Bill. And I think during my presentation, I talked about autonomous built into the product. So Amit and his team are really innovating on self-implementation there, but then also leveraging AI on our services implementation standard, which we'll be launching tomorrow and really compressing that time to value. I mean, we see a massive opportunity.

On the AI readiness part, what I would say is these mid-market companies, which I think is where you're going, Brad, in that segment of the business, I think the innovation that we've done over the past couple of years really lends -- enables them to be AI ready with their data. So things like RaptorDB Pro, Workflow Data Fabric, all the things that the teams have innovated on that we didn't have even 2 years ago. Now you can go in, you can kind of plug that in and get the data ready because we know AI success is going to be all about the data and grounding these models inside of that data.

So the new innovation capability, combined with what Bill is talking about on the self-implementation, but also just the autonomous implementation work, we think is right.

Brad, if I just could finish, just as one further comment. We have built quite a network now in the ecosystem of resellers and partners that care a lot about the platform. And some of them were born for the mid-market. We have one that's a $23 billion market cap company that actually serves the mid-market with great expertise. So if you talk to a large-scale account executive that's managing General Motors, the likelihood of them calling on a $300 million mid-market company is pretty low. They're going to spend their time at GM. So it's important to have the channel and the indirect partnerships, both from an integration and a sales perspective to make a lighter weight implementation, especially if it's autonomous, really rock for the mid-market.

And frankly, we're getting a little annoyed. Alex brought up a question about the competition. I made a promise to myself this morning. I was only going to say nice things today, and I wasn't going to get into it. But I have to just tell you, we've had some people say some things, a lot of people say things. But then when we do the research on these things, we find out that it doesn't necessarily tie with what they said. So please be advised that what they say in a certain way is a complement because if we're the target, we must be the leader.

The other thing is I want to thank some of you who sent me letters how you always know what's really going on. And you send me letters, "Hey, Bill, can you believe this that or the other one is now copying Control Tower? Hey, Bill, can you believe -- so we're always like one step ahead of them anyway. And so we'll come up with a new idea next month, and we'll always be one step ahead of them. But in the case of the smaller ones that have the loudest microphone, I think we've got some ideas for them. We want to meet them.

Gabriela Borges from Goldman Sachs. Back right. I wanted to ask Paul a follow-up to some of the case studies that you showed earlier, like the Level 1 ITSM case study. So it strikes me that the outputs of some of these case studies are really beautiful. But when we actually think about what a complex enterprise environment looks like, it can actually be pretty heterogeneous in practice. And you're coming out with this 100-day guarantee on ROI.

So maybe I think, Paul, for you, and Amit, maybe, how are you able to bridge that gap? Tell us a little bit more about what the AI FDEs are doing in practice because it seems like there's a lot of technical milestones to go from garbage in, garbage out to something that looks like the case studies that you're showing us here today.

No, thank you. It's a great question. And the way we think about it is really kind of twofold. One is, and I talked about it a little bit during the presentation, but our 4 deployed engineers, truly led by John Aisien in the front row here are truly elite. And they work with customers on really the high value, I'll call them high-value workflows. So things like massive usage outages at a huge bank and the cost per outage is incredible. The volume is not that high, but super critical and important to that bank. Then we think about how do we actually agentify the existing workflows that they have.

In some cases, customers want to redesign those entirely. You may have a process like an incident management process if we're talking about ITSM that you've just had for years, and you now want to redesign it, optimize it and then agentify it. So that's the high-volume part. And that actually, the high-volume part drives a lot of the assist consumption and drives that asymmetric scale from a value standpoint that I talked about during the presentation, the high-volume use cases are where that comes from.

Now the great news is the product team is innovated across the autonomous workforce now, which you saw a little bit of today, you'll see a lot more over the next 2 days. So we now have autonomous workers that you kind of plug in based on the products that you own, and they work side-by-side the human workers. So autonomous workers actually help us drive the high-volume use cases much faster while the FDEs look at the high-value use cases. And so we're attacking it from both angles. And the receptivity from the customers has just been incredible.

Don, do you want to add anything on the FDE model we have? Today, I think the FDE model is only for very selected. What we do with FDE is to identify very high-value use cases, as Paul was mentioning, but also kind of help customers reimagine the business process for those complex use cases and understanding where the integrations are required, what changes you need to make. And then really, the product takes over and then lands up being what you implement and the FDEs usually move on. So it's not a continuous FDA engagement like many other vendors have typically.

If I can add one more thing beyond on what Paul and Amit described. I think two other benefits of this FDE motion that we're seeing, and we're super excited to scale out these benefits into our field organization as we rearchitect and refine our go-to-market. But the two benefits are, a, kind of accelerating the innovation flywheel itself. And even when you go in with a completely comprehensive kind of basket of IP, you're going to find stuff that you didn't predict.

Let me give you one example. Unfortunately, I can't use the customer by name. But we deployed a sort of investment management, user and portfolio management agentification in 12 weeks for a Northeast-based customer. That customer actually had their own AI guardrails, like no kidding. They actually had a customer implementation of AI guardrails. So Now Assist Guardian did not support the ability to plug in a third-party guardrail in the same way we support any model or any identity, et cetera. So the FDE team literally extended Now Assist Guardian to support BYOG, so bring your own guardrails.

And now as an example, Palo with the Protect AI acquisition, which is essentially an AI guardrail, has plugged into that BYOG, extending TAM across both joint customers and prospects. So I'd say it's a virtuous flywheel that we're seeing, where the FDEs are building that last mile, but adding it to core product, which, in turn, is lighting up incremental capabilities and many of them sort of partner-driven as we meet with the customer with that IP.

Samad Samana from Jefferies. Thank you for spending time with us today. If It's great to hear from you as always. I could maybe dig into 30% AI ACV that implies roughly like $9 billion, right, in 2030, plus or minus. If you think about unpacking that, how much of that is from the portfolio as it exists today versus what you think you have on the road map? And I guess the related question in that is how much does the change in the pricing and packaging influence that? And does that require any changes for the existing installed base when they come up for renewal? I know it's a several-part question, but I'm just trying to learn from Alex.

So a couple of things. So first and foremost, I want to be clear on the new pricing model. So Prime is basically the same pricing as Now Assist Pro Plus, right? So we're not increasing pricing in our most premier offering. The customers who are all in our Now Assist are not going to expect to see increased pricing. Where the increased pricing comes is when people in lower tiers and lower levels continue to adopt and grow their AI usage by bundling products or by going from standard to foundation, foundation to advance.

And so what I'd say is that, obviously, the pricing model is baked into that 30%, but it's not a huge differential from where we are today. It will mean that it's really about penetration, how many more customers are driving upwards to those higher level pricing packages. And what I said earlier is that we're expecting a similar penetration trend as we saw from standard to Pro, which I think is actually quite conservative as you think going forward. So that was the first part of your question. You had a few in there. Is there something else that I need to answer?

Sorry. I think you kind of answered it already. But just for customers that renew, it sounds like if they're already on Pro or Pro Plus, it would be the same migration no matter what, but it doesn't require any changes. That's all I was kind of curious about, that there wouldn't be anything on renewal, any impact.

No.

Probably this came across, but just in case, there are no options at ServiceNow that are not AI. It's just degrees of the offering and how advanced it becomes with the autonomous prime. But everything is AI-enabled. So there's only one ServiceNow, and it's an AI ServiceNow. So I think you probably already knew that. But just in case customers have asked that question, we only have AI.

But to be clear, we're not counting every single dollar of revenue as AI as some others are.

Right.

We are only counting that incremental. We are being very consistent with how we've always been and how we've always treated it. There's AI in everything, but base subscriptions, we're not counting in that AI revenue. That's why it's only 30% and not 100%.

It's Tyler Radke from Citi. Continuing on the theme of multipart questions, I'll try to keep it to two. But Bill, for you, just on M&A given that's been a huge topic I guess, first, clarification. There's no M&A in those $30 billion and $32 billion targets. But philosophically, how do you think about what you have today? Do you need to do similar size or larger deals compared to Armis and Veza and whatnot?

And then, Gina, I think this is the first time we've seen two different kind of scenarios for the revenue. As we think about 2030, like why is there two? Can you help us understand kind of the differences between the upside and the base case?

You're lucky, I didn't give you the real, real upside numbers. That would have really confused you. I'll let Bill start.

I think we're trying to be respectful of this environment we're in, and I appreciate everything you guys got to deal with. But we're stronger than ever and feeling fantastic about the company. As it relates to M&A, first of all, I think you should know in the $30 billion and the $32 billion or however many 30s, we did not put large-scale M&A in there. So we typically do these little tuck-ins or aqui-hires and very small companies for us. I recognize it was new for you to think about the Moveworks and the Vezas and the Armis.

But believe me, if you had a management team that doesn't have the courage to do smart stuff, that's the ones you short. And when we did Armis, it was at a time when the market was most confused as to what was going. And our conviction never wavered down and it still isn't wavering now. We know we got our version of Instagram. So I want you to know, like we put a lot of thought into all those things. And all those leaders that were running those companies as independent companies, and you saw Chris and the sensation he brings to us with CPQ or Bhavan on Moveworks or Tarun on Veza, all of these leaders Yevgeny on Armis, are running big pieces of ServiceNow, and they wanted to be here in this culture to build this masterpiece.

So that's real important to us. And it was never about the revenue, and none of it hit the revenue line in our last report. So let's just make sure we square up on that. Right now, our position is organic. It has always been organic. Those were very unique opportunities to get us to a $600 billion TAM. If you asked us, do we think we have what we need to achieve what we said we would today? The answer is absolutely. And I don't think there's anybody on this stage that does not believe that.

And on the question on the $30 billion to $32 billion, given the uncertainty in the market, we felt that it was prudent to give a range in not just one number. We feel highly confident in that $32 billion, but also are taking into account just market sentiment at the moment and wanted to assure you that there's a real strong glide path. And we presented it to you, 25% plus CAGR on our growth engines, really driving to that $32 billion. But if you're a little hesitant in this market, you want to tie your number to $30 billion, I'm okay with that, too.

And that will actually conclude our Q&A session today and our webcast. We invite all of you to join our executives at Chica for a drinks reception after that, and you can ask them any additional questions there. Thank you.

Thanks, everyone.

Thank you, everybody.

Thank you.

Hello, and thank you for standing by. My name is Tiffany, and I will be your conference operator today. At this time, I would like to welcome everyone to the First Quarter 2026 ServiceNow Earnings Conference Call. [Operator Instructions]

I would now like to turn the call over to Darren Yip, Vice President of Investor Relations and Market Insights. Darren, please go ahead.

Good afternoon, and thank you for joining ServiceNow's First Quarter 2026 Earnings Conference Call. Joining me are Bill McDermott, our Chairman and Chief Executive Officer; Gina Mastantuono, our President and Chief Financial Officer; and Amit Zavery, President, Chief Product Officer and Chief Operating Officer. During today's call, we will review our first quarter 2026 results and discuss our guidance for the second quarter and full year 2026.

Before we get started, we want to emphasize that the information discussed on this call, including our guidance is based on information as of today and contains forward-looking statements that involve risks, uncertainties and assumptions. We undertake no duty or obligation to update such statements as a result of new information or future events. Please refer to today's earnings press release and our SEC filings, including our most recent 10-Q and 10-K for factors that may cause actual results to differ materially from our forward-looking statements.

We'd also like to point out that we present non-GAAP measures in addition to, and not as a substitute for, financial measures calculated in accordance with GAAP. Unless otherwise noted, all financial measures and related growth rates we discuss today are non-GAAP except for revenues, remaining performance obligations, or RPO, current RPO and cash and investments. To see the reconciliation between these non-GAAP and GAAP measures, please refer to our press release and investor presentation, which are both posted on our website at investors.servicenow.com. A replay of today's call will also be posted on our website.

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

Thank you very much, Darren, and welcome, everybody, to today's call. There's a lot of noise out there, so let's get straight to the point. Here's the ServiceNow update with the AI control tower for business reinvention in the center of a growing $600 billion plus total addressable market. We have a $28 billion RPO business that's growing at 23.5% year-over-year, the most open enterprise platform that protects customer choice with active users on our platform continuing to grow thousands of partnerships around the platform expanding daily. AI, native packaging and pricing on our fully autonomous platform, -- our AI at ServiceNow, a world-class team with a proven track record of building truly global businesses at scale.

Our first quarter results are consistent with a company of this stature once again exceeding our guidance metrics across the board. Subscription revenue grew 19% in constant currency, above the high end of our guidance. CRPO constant currency was a robust 21% growth, 1 point above our guidance. Operating margin was 32%, 0.5 point above our guidance and free cash flow margin was 44%. We had 16 deals greater than $5 million in NNACV and 5 deals greater than $10 million in NNACV.

Now Assist NNACV to date continues to outperform even our expectations. The number of customers spending $1 million plus grew over 130% year-over-year. Deals over $1 million grew more than 30% year-on-year in Q1.

Moveworks closed 7-figure deals in Q1. They closed more deals than they did the entire year last year. Now has merged with our employee experience business and rebranded as employee works. So Bob the former CEO of Moveworks, now runs the whole show there, and that business grew 5x year-over-year. So we have a great story in Moveworks coming into ServiceNow.

Our sales CRM NNACV grew more than 5x year-over-year. That's quintupled with deal count growing over 80% year-over-year. With the surface area so broad, our goals for ServiceNow are clear. Here they are. Fast time to value for our customers, revenue growth acceleration, margin expansion, reduced stock-based compensation and outperforming our own rule of 55-plus standard.

To say we're excited for knowledge and Financial Analyst Day on May 4 in Las Vegas would be an understatement. We have a lot to share with you. And the Board of Directors are very proud to ServiceNow in the way it's performing. and the company is on track for our best year ever.

Since our last print, speculation about enterprise AI has persisted, and that's okay. That's what earnings calls for to clear things up. My answer is always the same. There has never been a tailwind for ServiceNow like AI. Since Fred Luddy started the company, we've always focused our platform on the jobs our customers need it done.

Let me bring this to life for you in 5 hyper growth areas. The first, our core IT business. There has never been a more compelling moment to be the CIO's system of record, were often described as the ERP for IT. When an enterprise fully deploys ServiceNow, it's not just software. It's an end-to-end operating system. And today, an average Fortune 500 company has 100 million lines of custom code to manage their business. And this excludes the code and other systems of record where there are billions and billions of lines of code.

As code volume increases 20x by 2030, the complexity of managing this explosion of code will increase exponentially. The volume of tickets generated by this complexity will also explode. In this scenario, the number of tickets hitting an ITSM system will increase by 50x compared to today. The biggest IT buyer in the enterprise was is and will continue to be the CIO. His remit will substantially expand by the complexity of the Agentic business. ServiceNow's relevance grows in direct correlation with the expansion of innovation across the AI ecosystem. Think of us as the workhorse for workflow.

The second is AI security. We're thrilled that the Armis acquisition closed earlier than expected, which as you'll hear from Gina gives us some nice acceleration in full year subscription revenue growth. You have Genny Debra, the excellent CEO of Armis will run our security business, building on ServiceNow's outstanding foundation. And here's the problem. Companies employing agents with 0 visibility. Therefore, they're unable to see the unmanaged IoT, OT and medical devices, lacking unified access control with no coordinated way to remediate vulnerabilities before they become breaches. Today's ServiceNow addresses this challenge holistically.

As the Asset Intelligence Foundation for the AI control tower, Armis solves visibility, real-time agentless discovery of every asset, IT, OT, IoT, medical devices, shadow IT, a continuously updated map that traditional tools can never achieve, 9 out of 10 Fortune 10 companies already rely on Armis. We're excited to deploy it throughout the Top 2000 and beyond.

Veza solves the identity governance. Patented access graft technology maps access across people, machines and AI agents in real time, dynamic context aware permissions that are governed continuously not set once and forgotten. This is the active directory for AI agent identities. This business will continue to be run by the excellent CEO of Veza, Tarun Thakar.

ServiceNow is the biggest piece of the puzzle. Our existing $1 billion plus security business ties everything together as the action layer for the Armis' asset visibility plus Veza's identity governance plus ServiceNow's business context, CMDB, equals a unified end-to-end security stack that could see, decide and act across the entire technology footprint. Nothing else in the market does this nothing.

With Mythos as one example, Security activity is skyrocketing. The actions run through this platform, alerts, tickets, actions, resolutions, they're all revenue drivers for ServiceNow. Enterprises can't afford experiments in today's risk environment they need ServiceNow as the strategic defense shield for the enterprise.

The third is AI native CRM. We say AI control tower for business reinvention because there's no more immediate need for reinvention than legacy CRM. It's a little ironic that a category promising a 360-degree view of the customer has left most enterprises spinning around in circles. Best-run businesses need a dramatically different and better way. Customers tell the story better than we can. A multi-market European telco faced 85-plus fragmented applications, no standard quoting process and a CPQ setup, where introducing a single new product took 3 months. ServiceNow sales CRM with CPQ collapsed this to 1 week. A global power technology leader across 190 countries has gone live with Phase 3 of its ServiceNow deployment, replacing legacy CPQ. Using AI-driven Blueprint automation, the company is reducing new product introduction time from 6 months to 6 weeks.

A regional Latin American bank is live with ServiceNow, building a full front office experience for relationship managers. Agentic AI is scanning portfolios and auto generating leads using propensity logic tied to their data lake. Because legacy CRM represents such a significant expense line for enterprises, the demand for an AI alternative is immediate. ServiceNow is not only bringing a technology superior solution, we help customers swap out legacy SaaS vendors and go live fast with AI.

The fourth area is AI native front door and the employee experience. As people use more of their AI tools like ChatGPT, enterprise leaders urgently want their employees to enjoy a clean conversational experience. ServiceNow introduced employee works, combining Moveworks, conversational AI and enterprise search with ServiceNow's unified portal and autonomous Agentic AI workflows. This is available in Teams, Slack, or any browser to turn natural language requests into govern multisystem execution for nearly 200 million employees so far.

We launched midway through Q1 and it's already closed many deals above $1 million. You'll also see some exciting new experiences, and we will announce this in a big way at Financial Analyst Day in Vegas. As more employees converge on our conversational experience, ServiceNow will deliver intelligence from any source, putting AI to work for people.

The fifth area is workflow Data Fabric. We all know that AI is only as valuable as the data itself. Enterprises are frantically organizing and cleansing data from countless disparate sources. Workflow Data Fabric connects data across systems. It adds business context via a unified data catalog and applies policy-based governance controls. With ServiceNow, AI understands how an enterprise actually works so they can take trusted action. I explained the 5 areas for 1 good reason. All of them have the capacity to eclipse the size and growth trajectory of ServiceNow as it stands today itself. And for years, we've strengthened a common platform architecture for these businesses and for others, we're incubating to harness enterprise AI.

ServiceNow has thousands of system connections, a live knowledge graph and real enterprise context. We accommodate any model aligned to customers' policies, permissions and rules, and every decision in ServiceNow is auditable end to end. Our platform delivers workflow execution across IT, HR, CRM and security. It's not recommendations, it's outcomes that matter. Our AI control tower provides real-time visibility across every agent and every workflow because governance has to be foundational, not retrofitted.

This architecture is a big reason why we recently announced the entire ServiceNow portfolio is AI native. AI, data, security and governance are now built into every product and package, not a separate purchase. This is a deliberate break from sidecar AI. We're not bolting intelligence onto disconnected systems. We're combining context with execution on a single platform. ServiceNow's context engine is the differentiated capability here. It learns from every decision ever made in the company, grounding each action in live context, approval chains, asset dependencies, identity relationships and business rules. We've now trained over 95 billion annual workflows and more than 7 trillion transactions and our 22 years at the center of the world's most sophisticated enterprises is really showing up because it brings unmatched intelligence to every decision. And this compounds with every workflow we run, making the platform smarter over time. In fact, in every millisecond.

For example, it knows which asset is tied to a compliance process, which approval chain applies to a given cost threshold and which vendors history should inform how a request should be handled. So when people ask, what's the difference between ServiceNow AI and the foundation models, you can boil it down to one word, context.

I read that one of our customers referred to ServiceNow this way. The control tower is the quarterback. It figures out which agent or LLM to use, merge that with a quote from the Hall of Fame Coach Real Walsh. Chaos is the natural environment.

Ladies and gentlemen, there's plenty of chaos in today's enterprises. You have hyperscalers, systems of record, foundation models, data lakes, homegrown tools and agents coming at you from everywhere. That's why our platform is totally open. We integrate with all of them. Because ServiceNow is the only enterprise AI platform that converts that chaos to control, we would not trade positions with anyone.

Let me give you a quick overview of a couple of announcements we just recently rolled out. ServiceNow launched autonomous workforce. Teams of AI specialists with the defined roles that execute enterprise work end to end with built-in governance auditability and human escalation. Our own deployment in ServiceNow is resolving 90% of employee IT requests with the specialist resolving assigned cases 99% faster than human agents. That's an AI specialist. In the AI native platform announcement, you might have missed build agent, which gives us developer openness another meaningful unlock developers can build from any integrated developer environment, Claude code, cursor, Codex, Windset and deploy them directly to ServiceNow. This expands the addressable builder community significantly. Build agent skills isn't just a developer tool. It's the on-ramp to an ecosystem where every custom agent is automatically governed, data connected and workflow integrated from the moment it deploys. With enterprise service management foundation, we are expanding our opportunity in the mid-market as well. with deployment in weeks, not months, this is the direct expansion of our addressable customer base.

One early example is Robin Hood. Robin Hood is deflecting 70% of employee requests before human intervention, they've already eliminated 2,200 hours of manual effort monthly, and the success just continues. I know many are interested in the progress of our hybrid business model, especially with regard to consumption pricing. You'll be happy to note that 50% of net new business now comes from a non-seat-based pricing model, including tokens and other assets, such as infrastructure, hardware, and connectors. Our hybrid pricing model gives customers the best of both worlds, predictable, foundational seat licenses combined with usage-based scalability. It's the freedom to scale AI adoption without a friction that the customers love.

We continue to see the hockey stick taking shape. One example is British engineering and technology company, 45,000 employees, 50 countries, they're using ServiceNow autonomous workflows, employee self-service and has jumped the usability and the outcome by 3x with 38,000 tickets now deflected, resolution time is down by 2 entire days. A leading online travel company is using ServiceNow agentic AI to deliver 11 million autonomous AI resolutions annually for HR and IT alone. They freed employees to focus on strategic work processes that once took days, now take minutes, the results are transformational. Over 230% ROI, 45,000 hours back to their people and millions saved annually. These and many stories like them validate our hybrid thesis as the business value emerges, refresh upgrades follows. We'll have more on this at FAD. We really can't wait.

We're seeing continued meaningful acceleration in the partner ecosystem. There is deep technical collaboration between ServiceNow engineers and OpenAI technical advisers. OpenAI native voice and text models are integrated directly into the ServiceNow AI platform, and they're using us as a gateway into the enterprise.

If you think about it, ServiceNow AI specialists are working side-by-side with Google Gemini, AI agents. They're doing this across 5G networks, retail and IT operations with 0 data movement and 0 gaps in governance. Claude models are also deeply integrated into ServiceNow AI platform for developers and employees. ServiceNow, NTT, Docomo and StarHub are developing the industry's first inter-carrier autonomous roaming resolution model on the ServiceNow AI platform. ServiceNow and Cohesity announced a partnership to deliver agent resilience by combining ServiceNow's AI agent control tower with Cohesity immutable point-in-time data recovery. ServiceNow and Carisoft expanded our partnership to extend ServiceNow AI platform availability. This opens all Carasoft's commercial channels in addition to its established government network of 10,000-plus resellers.

There's so much to talk about. I want to leave some for Q&A. But a colleague today reminded me of something Warren Buffett often quotes from Benjamin Graham. In the short run, markets of voting machines. And right now, uncertainty is winning the vote, but don't worry. In the long run, they are weighing machines. And I'll tell you, I'll get on that scale with that ServiceNow brand on my chest any day. We look at it. We studied it. We dare anyone to bring a best solution to the market in ServiceNow. We are the rules and the rails of business. When you're faced with these results, trust what you see. You have every reason to believe your own eyes. Don't fall for the that one touch button can replace 22 years of excellence. This is not a company that shrinks from challenges, rises to every opportunity.

To all our shareholders, thank you, for your continued belief in ServiceNow, we will never let you down. I'll leave you with this. There's a perfect correlation between enterprise AI from any source and ServiceNow's expansion. We're letting it whether it's built or bought, ServiceNow will unlock more value out of every dollar spent on AI in the enterprise. That's a guarantee. There are a lot of things AI can do for your business, and we love them all. There's also a lot of things AI can do to your business, and we want to protect it. We have comported this in how we've composed this company organically and with the integration of Moveworks, Veza and Armis. Our platform has gone from land and expand to control and compound AI that thinks workflows that act, all production grade enterprise scaled, ServiceNow is the AI defining enterprise software company in the 21st century. We're just getting started.

I'll hand things over to our President and Chief Financial Officer, Gina Mastantuono. Gina, over to you.

Thank you, Bill. Q1 was another quarter of outstanding execution. The team delivered strong results beating the high end of our guidance across all top line and profitability metrics. Now Assist continues to see incredible demand, which has had a nice pull effect and driven outperformances across emerging products like AI control tower and Raptor DB Pro. Q1 subscription revenues were $3.671 billion, growing 19% year-over-year in constant currency and above the high end of our guidance. This includes about a 75 basis point headwind from delayed closings of several large on-premise deals in the Middle East due to the ongoing conflict in the region.

RPO ended the quarter at approximately $27.7 billion, representing 23.5% year-over-year constant currency growth. Current RPO was $12.64 billion, representing 21% year-over-year constant currency growth, a 100 basis point beat versus our guidance. Across our workflows, we saw broad-based demand Technology workflows had 33 deals over $1 million, including 5 over $5 million. Service Ops and ITAM were each in 17 of our top 20 deals and security and risk was in 15.

CRM and industry workflows were in 16 of our top 20 deals with 16 over $1 million, driven by strength in CPQ and sales and order management. Core business workflows had 13 deals in the top 20 with 12 over 1 million. And creative workflows had 16 deals in the Top 20 with 11 over $1 million.

From an industry perspective, transportation and logistics continued to lead the way with net new ACV growing over 280% year-over-year. Financial Services posted impressive growth surpassing 65%, followed by energy and utilities growing up 45% year-over-year. Telecom & Media also delivered robust growth in the quarter and U.S. public sector outperformed in Q1, including 10 deals over $1 million. Our renewal rate, inclusive of Moveworks, was a strong 97% in the quarter. We ended Q1 with 630 customers generating over $5 million in ACV. Furthermore, we had 5 more customers cross the $50 million threshold versus last year.

We closed 16 deals greater than $5 million in net new ACV in the quarter, including 5 deals over $10 million. The power of our Better Together platform model was evident as 17 of our Top 20 deals included 7 or more products.

Our strategic focus on landing the right new customers also continues to see success. New logo ACV growth accelerated to over 50% year-over-year in Q1, which included our largest net new logo deal ever at over $15 million.

Now Assist continues to outperform expectations, putting it on a trajectory to exceed our $1 billion target for 2026. In Q1, deals including 3 or more Now Assist products grew nearly 70% year-over-year, including 36 deals with 5 or more products.

The signal is clear. Customers are moving past experimentation into full-scale enterprise-wide AI investment. We'll provide further details about these trends next month in Las Vegas. I would note that with our new AI native packages are now with this ACV target will continue to capture only the incremental contribution from our AI capabilities.

Turning to Moveworks. We took their great conversational AI and enterprise search capabilities, integrated them with employee Pro in under 3 weeks and drove it through our incredible go-to-market distribution network, launching employee works as a unified AI front door in February. The results speak for themselves. As Bill mentioned, we've already closed 6 deals above $1 million in net new ACV. We're just getting started. AI control tower also continues to build momentum, with average deal sizes more than doubling quarter-over-quarter in Q1. Customers recognize that as AI agents growing capability, a governed platform to run them isn't optional. It's essential.

With the proliferation of AI across the enterprise, we're also seeing increasing adoption of Raptor DB Pro. Deal volume grew 80% year-over-year in Q1 and included 5 deals over $1 million.

Turning to profitability. Non-GAAP operating margin was 32%, 50 basis points above our guidance, driven by AI OpEx efficiencies. Our free cash flow margin was 44%. In Q1, we executed a $2 billion accelerated share repurchase and bought back approximately 20.2 million shares, double the amount we repurchased in all of 2025. As of the end of the quarter, we had approximately $4.2 billion of authorization remaining. Together, these results continue to demonstrate our ability to drive a strong balance of world-class growth, profitability and shareholder value.

Moving to our outlook. I'm thrilled to announce the early close of our acquisition of Armis, which would significantly expand our TAM and accelerate our subscription revenue growth. While we expect some near-term headwinds to margins as we integrate the business this year, strong AI efficiencies internally from now on now and our underlying platform leverage will normalize our operating and free cash flow margin expansion trajectory in 2027 and beyond.

Our guidance captures that momentum while taking a prudent view of the geopolitical environment, particularly the conflict in the Middle East and its potential impact to deal timing.

With that in mind, for 2026, we are raising our subscription revenues by $205 million at the midpoint to $15.735 billion to $15.775 billion, representing 20.5% to 21% year-over-year growth on a constant currency basis. This includes a 125 basis point contribution from Armis. We now expect subscription gross margin of 81.5% and operating margin of 31.5%, which included 25 basis points and 75 basis point headwind from Armis, respectively.

We expect free cash flow margin of 35%. This includes a 200 basis point headwind from Armis and GAAP diluted weighted average outstanding shares of $1.04 billion. For Q2, we expect subscription revenues between $3.815 billion and $3.820 billion, representing 21% to 21.5% year-over-year growth on a constant currency basis. We expect the RPO growth of 19.5% on a constant currency basis. Both subscription revenue and CRPO include 125 basis point contribution from Armis. We expect an operating margin of 26.5%, which includes a 125 basis point headwind from Armis, and we expect 1.04 billion GAAP diluted weighted average outstanding shares for the quarter.

In conclusion, Q1 was another proof point of what this business is built to do. We exceeded the high end of our top line and profitability guidance metrics, continue to grow free cash flow and return substantial capital to shareholders, all while accelerating platform innovation that will define the next decade of enterprise reinvention for an AI enterprise. I've had a front row seat to one of the most remarkable growth trajectories in enterprise software, and I'll tell you what we are building right now, the combination of agentic AI, workflow orchestration, security and data fabric, all on one platform. This is the chapter that makes everything else look like the preamble. You're all invited to hear more about it at our upcoming Financial Analyst Day on May 4, which will be webcast on our Investor Relations -- Investor Relations website.

Finally, Bill and I would like to thank all of our employees for their continued hard work and dedication. I also want to extend a big welcome to the Armis and Veza teams to the ServiceNow family.

With that, I'll open it up for Q&A.

[Operator Instructions] Your first question comes from the line of Mark Murphy with JPMorgan.

So Bill, you had mentioned 90 days ago that the global business was performing well. And at that time, it had included the Middle East during Q4. Can you double click on what exactly you saw during Q1 amidst the Iran war? I'm just curious, are the deferrals related to governments or sovereign-backed or private sector entities -- you mentioned these are on-prem. And where the AI or non-AI? And then just finally, do you think that these would snap back relatively quickly if the conflict is resolved here during Q2?

Yes. First of all, Mark, thank you very much for the question. And let me, first of all, begin the answer with we just beat and raised. So it was a beat and raise, not an excuse that there happens to be a conflict or a war in Iran. We're not making any excuses. Our results are great. What we did explain is that there is a slight impact to the guide in going forward in Q2 as a result of the war because you have to remember, when you're dealing with a sovereign cloud in the Middle East, everything that happens in the Middle East is recognized as on-premise revenue. So it's not linear or ratable. It happens all at once. So when there's a delay, it has a natural impact. And we just mentioned that as a statement of fact that impacts slightly the guide. But I want to be clear, like everything is activated properly the conversations are going on, people are back in their offices now, and we don't have any long-term matter for the shareholders to be concerned with.

And Mark, I would just add, right, that we kept the full year guide. We didn't reduce it for any potential conflict, right? So it's a few on-prem deals that slipped in the quarter, and you know on-prem as a larger impact to revenue. But we feel very confident in the results we feel very confident in the guide.

And just as a quick follow-up, it's great to see the very clear AI traction that the business is carrying. Could you just comment on with the pricing changes and AI -- less, I think Bill's term was not a sidecar and embedded natively with the shift to the foundation in advance of time per -- how will you measure and kind of derive that assist AI revenue stream? Just going forward under the new methodology. Is it simple and straightforward? Or do you have to make some new assumptions?

Yes. I'm going to just give you one headline, Mark, at a respect for your great company and you personally that you might find interesting. Gina will be mad at me because it's something we were hoping for FAD. But in the circumstances we operate in, I think disclosure is a good thing. We had a goal to be $1 billion on our AI commit this year, as you know. And I think we might have understated that a little bit. We're already talking about $1.5 billion now, and it's on a run.

So to specifically answer your question, I think it's appropriate for Amit to give you some G2 on how we structured it and why we know it's a winner. Amit?

Thanks, Bill. Mark, so the way we're thinking about this, and we've announced our pricing capabilities is that, AI capabilities are in each of the SKUs now. And what we did with Pro Plus, which was a higher-end SKU with Assist are now available also for the Foundation and Advanced SKUs. So all of our products now have AI built in. And the incremental assist part of it was going to be counted as our AI revenue. So it's pretty straightforward, very easy to measure, easy to track. There's no confusion there. And we're very clear that it's only going to be AI part, which will count towards the AI revenue that we discuss going forward.

So to be very clear, Mark, we have the exact same methodology, and we will continue to capture only the incremental contribution from the AI capabilities. And so that $1.5 billion that Bill talked about, we're measuring the exact same way as we always measured. We're just hitting our goals a lot quicker than we ever thought we would.

Okay. Great to hear about a $500 million increase on that number.

Your next question comes from the line of Brad Zelnick with Deutsche Bank.

Great. Bill, we've been really impressed hearing from early adopters of Control Tower and how strategic it's seen for enabling the deployment of agentic apps. But we also realized that the agentic orchestration is emerging as a very noisy and competitive space. How do you see ServiceNow's differentiation evolving from here amidst all the noise?

Yes. I'll start and then Amit, by all means feel free to join in. We have data, and that data has been built over 22 years in this "ERP for IT" or that system of record. And as you know, we've expanded the boundaries end-to-end of what this platform can do. So think now about 95 billion workflows and more than 7 trillion transactions, getting trained at sub-second speed for everything that happens in an enterprise to that data. So the context and the context engine that we have built to be that AI control tower for business reinvention managing the humans and the agents and coalescing that in this unbelievable platform is what gives us the context advantage that nobody can match. And I just want to give you one sidecar. Yesterday, we had the Board of Directors in, and we had one of the really great CIOs in the world. And she basically said, we are the control rail for all the key business processes that run through our global corporation. And she said that she would never even think about it. But if you think about the fractional cost that ServiceNow is to her IT budget. She would never even think about addressing that line item because it's so important. But if you did, it would have to be at least 10x more expensive to even try to fix or change it. So there you have it. And Amit, please give some color on the differentiation.

Thanks, Bill. So -- Brad, the way we think about this is that, one, we're going beyond just orchestration. There's a lot of context, as Bill mentioned, and we introduced something called Context Engine, which tracks not what decision was -- what the decision was made, but why it was done. So it brings in a lot of information from the workflows and the systems we've been running for many, many years already. Second, we're also building out this idea of autonomous workforce. You have a full AI specialist, which do the full task of which humans do today and replaces that with end-to-end capabilities. So you don't have to worry about orchestration, AI agent management, figuring out how to integrate them and do the whole heavy lift of security, compliance and control around it, right? With the iControl tower, you have the full visibility across an enterprise-wide while we give you the full capability of doing the actioning end to end, which is very different than just saying take pieces of technologies and build it yourself and figure out a way to orchestrate it. We do provide our orchestration engine, which is very, very comparable to everybody else and very differentiated with the contact data. But we're also up leveling that with a solution, an outcome-driven mindset. So it changes the game for a lot of our customers because they don't have to worry about the heavy lift they have to do otherwise.

Your next question comes from the line of Gabriela Borges with Goldman Sachs.

Bill and Gina, I appreciate all of the detail on the new products. What I wanted to ask you about is the risk that customers start to negotiate you down on the more classic purpose ServiceNow But in order to essentially free up budget or some of the new products. I'd love to hear a perspective on how you're navigating some of those conversations when customers say we're going so much value from the AI part of the stack which means while the topic part of the stack may actually be less valuable to us, therefore, give us more of a discount on that...

Yes. Thank you, Gabriela. The one thing I can tell you from being in the industry for quite some time in running another global corporation that was the biggest in the world. One thing that I've learned is when you innovate on the platform, whatever the platform is, it reinvigorates the core. And when you do smart M&A, it also doubled down, reinvigorates the core. And if you look at any company of size, scale and significance, that's always true. So no, we're not getting negotiated down on the core. Actually, we're redoubling our focus on it because that system of record for IT, where we started and founded the company has now become more important than ever. So there's a higher appreciation for it because of AI, because it's the pivot point by which we extend to all the other functions of a company. It's also the pivot point to our workflow data fabric and the context engine that Amit just discussed.

So there is no great autonomous AI platform end to end. There is no great control tower. There is no great workflow data fabric. There is no great integration layer that ties into the hyperscale is the language models and systems of record without that and the liveable core that Fred Luddy built into the company 22 years ago. And from that, that genesis of strength, everything else has been built. So actually, I see the core having a major resurgence as a result of AI. And remember what I said in this group. It's all about also this increase in code and this increase in AI activity, and I'll finish it with Armis.

Armis is going to be our Instagram, and I'll tell you why. The #3 economy in the world is cyber crime. It's 1 trillion a month. We now have a situation where on the IT and the OT landscape of every major corporation. We are managing the agents and the humans and we are managing the landscape of the threat actors. And if you think about a single intrusion from an AI agent will cost a commercial customer of $5 million and a public sector customer $10 million, you have to look to ServiceNow quickly, and you'll need that core to illuminate the power of Armis. So those are issues that have not even happened yet. We just got Armis on Monday. So you're looking at a tailwind here that has -- I've never seen it. So get ready for major revenue acceleration.

Yes. If I can add to what Bill mentioned about the stack. So we have redone everything in our platform to be AI native. So everything which we do in terms of how we orchestrate, how we manage workflows, how we bring resolution and action out of it, as well as all the things we do with data, it's all been rewritten with AI-native mindset. So that is available today. So existing customers are getting that capability as part of the upgrades. They don't have to do anything. And a platform becomes AI-native for all of our customers. So now there's not really a pressure in terms of any of the discussions. They all want to modernize. And they're getting it very, very quickly and simply and they're getting the benefit of all the new innovations we're bringing into our platform and all the customers get that instantly as we deliver this AI-native products.

Your next question comes from the line of Peter Weed with AllianceBernstein.

I appreciate all the detail on the latest releases. I guess I've got a follow-up there. You announced the autonomous workforce in February, which was really exciting, including the GA of the Level 1 service desk coming here in quarter 2 on with employee works. Help us kind of understand that long-term strategy and vision and how does that complement the existing now assisted products, maybe narrowing in on like one example here, kind of help us understand the richness of where you're going?

Yes. Peter, thanks for that question. So our vision here is pretty ambitious and kind of game changer in the market. What we're doing with autonomous workforce is to really provide an end-to-end resolution for different functions, company run inside their enterprise today. So taking this example of Level 1 support engineer. Today, a lot of tickets get deflected of course, when somebody has an issue or question they asked for. And we help that with our employee works, where we give them self-service and help them resolve that issue a customer or employee might have. But some things they do need to require help and they usually go to human to get that thing resolved. And what we're doing is taking that pain and the burden away from human and putting that into this level 1 support, specialist AI specialists, which you'll now understand the intent and the question and figure out how to resolve it based on the learning they've had for many of the data we provide underneath the covers. And then get that resolution in a very short amount of time. Typically, a human requires around 2 days based on the case volume to resolve it, we are now able to do that in less than 20 minutes.

So the employee or customer is getting their information quickly and the issue resolved immediately without having to wait on a human agent to really do this. And that changes the game for every enterprise, right? Because now you're reducing the workload on the employees themselves. You're getting them -- moving on with the job very fast, as well as now we are just taking away also the human labor cost, which now we can also monetize beyond what we used to charge for just the issue management before. So it opens up and expands our TAM considerably, plus it becomes much more value-driven than just being able to provide your software. So that's really the vision we have, and we have around 20 different roles like this been delivered by May. You'll see that at our Knowledge event. And all the discussions we've been having with customers and quite a few of them are live right now, and they're seeing this immediate value-add by taking this kind of a technology without having to build all the AI underpinnings, doing all the security work, the compliance work and training the models and doing the spare part work and then working about upgrades and maintenance to kind of take all that pain point while giving the outcome of AI completely out of the box in our products today. So that's really the vision. It's really playing out very well and very, very bullish about what we can do here based on the context and the information we've had, which you can't just do with the large language model or any of the technology by itself. Given our historical experience in this thing, we are able to bring that knowledge and resolve it for our customers.

And one thing that's interesting, Peter, just to use ServiceNow as a benchmark. Gina has captured $0.5 billion in productivity on the back of what Amit just said. So the agents are 99% faster than the human. 90% of our cases on employee and customer issues are now resolved by the agents, the Level 1 agents Amit is talking about. And if you think about a company of our size and scale, we're able to go in a year and exit the year into a new year with the same headcount. And that's a company that's growing at the rule of 56 between free cash flow and revenue. There's not too many of them out there. I want to invest in some of the I'm on the lookout.

That's a pretty bullish outcome. Help us understand the pricing that you're able to achieve as a result of the value you're bringing?

Yes. So Peter, the way we -- this is part of our current AI-native pricing, right? So more you use -- it's more Assist you end up using -- consuming based on the Intel wins you have. So over time, we can look at beyond what we do today from the pricing perspective, but today, it kind of becomes much simpler for customers. When they see this issue been resolved or questions been handled and us helping them manage their problems inside the enterprise, we can now easily now monetize that through our assist pricing structure we have. And now it's available across all our product tiers, so we could start any of they want to.

Your next question comes from the line of Keith Weiss with Morgan Stanley.

Excellent. I want to directly go sort of at, I think, a topic that a lot of us are passing around and sort of our initial questions. I'm excited about the opportunity of ServiceNow. You guys are obviously excited about the opportunity for ServiceNow. The stock is down 12% after hours. So something is not getting through to investors. And I would say there's probably 2 parts of that equation. Like one is a lack of clarity on the inorganic contribution to Q1. There was a resin there. There's pyramid analytics in there. And don't quite know how much of a contribution it is. I think investors are wondering whether it really was the Q1 beat on an organic basis.

And then for the full year, outside of adding Armis and currency, the full year number doesn't really move at all. And we're wondering when, like when are we going to see this acceleration? When are we going to see the benefits of ServiceNow's positioning for this generated AI opportunity because we are seeing it in the AI Labs, right? AI Labs added $5 billion in net new ARR in Q1 alone each one, right? And we're talking about $1.5 billion for analysis when we get to the end of the year. It seems like they're getting an outsized proportion of the game. So when does ServiceNow participate in the way that's more analogous to the AI labs that we were actually getting organic positive revisions. Thank you.

So Keith, there's a lot of questions there. I'll talk to them one by one. So -- Veza closed in the middle of March and at a small tuck-in. Pyramid's even smaller. So they had very, very, very tiny contribution, which is why we're not calling it out. So we would have beat regardless. We did talk about 75 basis points of on-prem -- pushouts for Q2. So on-prem year-over-year is a little bit more than 1 point lower in Q1 of this year versus last year. So if you just exclude the on-prem -- and by the way, we want hosted, we love hosted. And so on-prem being lower is not a bad thing, but it does impact the numbers.

We actually have seen a couple of those on-prem deals already closed in Q2, but it was a timing issue. So that's the answer on Q1. We feel very good and strong that we continue to have strong organic growth on top of these great acquisitions that we've added. And so we've been very, very clear on the impact of Armis. I spelled it out across the board in every single metric. So you can see that, yes, we didn't increase the revenue guide, excluding Armis, but we didn't take it down either despite some ongoing conflict. So we held -- and we never really -- even in the best of times, we really increased our revenue guide for the full year after just Q1. It's the smallest quarter that we have. And so we held the guide, increased with Armis. So we're seeing accelerating revenue growth. And I think -- the example we gave of Moveworks of being able to integrate it into employee works within 3 weeks and then very quickly hit it into our distribution network and have more revenue or more deals in Q1 than they had all year last year is a great example of M&A done extremely well. So that's number two.

To the question on acceleration of revenue growth, we've basically said historically that our guide for 2026 was $1 billion. We just told you now that it's 50% higher than that, $1.5 billion in 2026, which is, I think, pretty darn good for a software company that's building AI into our platform, and enables our customers to get the value of AI within our platform with all the guardrail security and governance that they love. I'm hoping that you'll be at Financial Analyst Day in a couple of weeks' time because we will lay out our long-range plan and when we expect to see that flywheel of AI consumption that you're talking about, and I can promise you, I think you'll be very excited about what you're going to see.

I will definitely be there.

Yes. And Keith, I do want to mention, we didn't buy anything with a whole bunch of revenue, okay? We didn't buy what's been on the market for 10 or 15 or 20 years to plug a revenue gap. We bought companies that are adding to the AI control tower for business reinvention. So they are not in a meaningful way and never were intended to be a plug for a revenue gap. We just got them and we're building out the story with them and they're going to set the world on fire with reaccelerating revenue growth.

The other thing we're doing as we're reaccelerating revenue growth. And by the way, above 20% isn't too bad, right, on a $15 billion company. And in terms of accelerating margins, who accelerates margins at the rate that we have. So we're a 56-rule company going up. And we're obviously taking SBC down at the same time because we know the shareholders. I think the bigger argument for the shareholders is something like what's the terminal value of a software company? Is the seat-based pricing going to last? Well, when you have many more seats because the surface area you cover is 80% greater than what you used to cover, you're going to do fine on seats, but nobody cares about seats. We had a CIO from one of the biggest companies in the world, Telesta. She never bought a pricing plan one way or the other. She buys the return on the investment. And so in our case, we give you the goldilocks model, you're going to have it any way you want. You like, see it's great. You like consumption, great. You like a blended a 2, great. You want to split the value with us even greater. We'd love that. But as soon as you show them how big the value is they say, "I'll take the seats."

So we got you covered there. And in terms of the terminal value, see with your eyes, it's kind of a parlor trick. If you think you're going to touch a button from a language model company, and it's going to do everything we just discussed and the complexity of a global corporation. So I think having a sustained growth, a predictable growth and expanding margin company on fire on the global economy [indiscernible]

And yes, we love the language model companies. That's why we partner with all of them the same way we did the hyperscalers and even the systems of record and some of them compete with us vigorously, but that has nothing to do with the fact that we know the customer wants everybody to work nice, and that's why we opened it up to any system. So we're very confident in our position, and we're also mindful that customers are spending a lot on AI, but that is incremental. It is not replacing what they're spending on us.

Your next question comes from the line of Alex Zukin with Wolfe Research.

Bill, maybe start for you, just -- maybe just give us a characterization of the overall enterprise spending environment right now, and not just in the Middle East, but globally, there is a pervasive sense of at least from investors of this AI anxiety where customers are a bit more hesitant to maybe make bigger purchases because of some of the uncertainty, maybe not of what's available now, but what's kind of coming given the rapid pace of innovation. And then Gina, I've got a quick follow-up for you.

No, Alex, you're right. I think the big thing -- and one of our great executives discuss this with the Board. He spends a lot of time especially with the CIO community, CTO, digital officers and so on, AI offices, too. The environment is very excited about AI. These language model companies are great companies. They're very exciting. So they're very excited about AI. The problem is they don't exactly know what to do, so they're somewhat confused. I put together along with our great team here, an agentic business, white paper, that has cleared things up for a lot of customers because we're highly respectful of the great companies and what they do, but we're also well aware of what they don't do. So the customer just wants the truth. And they want to know what they do, meaning it could be a language company, it could be another type of company and what we do. And I think our positioning is really resonating with the customer because they tell us -- the fact that you're so open, yes, you're competitive, yes, you want to win, but you're still open. It's an autonomous platform. You give me the control tower, all the language models are welcome. All the hyperscalers welcome.

All the systems of records are welcome. All the data lakes are welcome because that's the environment, this heterogeneous environment that the customer is operating in. And it's also a chaotic world. If you look at the geopolitical landscape or even wars around the world, it's hectic out there. So I think what you have to do is be highly clarifying very thoughtful with the customer. The customer, in the end, determines who wins or loses. We're not so caught up in the short-term things. We just want to really double down on that customer relationship. When they see our road map to great innovation, that our dear Amit and his team are building into the company. They love the M&As we did. It's a settling effect. It's like, yes, wait here. And we'll be in 22 more years from now taking good care of you. That's really what it is. I tell people there was once the United Airlines commercial where the CEO, walks into the boardroom and start handing our plane tickets and said, go visit our customers. That's what you got to do. You got to get in front of them, you got to help them understand and it's not a time to be anything less than totally empathetic because these customers, just like the shareholders. They have so much coming at them. We just want to give you a solid clean story and then let you make the best decision you can based on the facts.

And then I would just add, Alex, on the numbers and the proof points, right? I talked about 16 deals greater than $5 million in the quarter, 5 deals over $10 million. talked about, again, second quarter in a row, our largest net new logo land at $15 million, right? So customers are spending, they are understanding the value proposition that we're driving and that we're delivering, and it is showing up in the numbers.

For sure. And if you guys knowledge, which I hope you do, and please come to the fab -- our knowledge attendance, okay? This is a live attendance, live audience. They must be interested because we're totally sold out and the seats are up 11% year-over-year already, and we have late sign-ons. The fab, the Financial Analyst Day, we already have Darren telling us yesterday, we're going to have to have a second and third room because the fire Marshall said, you can't put any more people in that room. And so if you get there, and it's not packed, you'll hold it on me, right? It's packed. Everybody cares about the story, whether it's a customer or it's an investor and they know ServiceNow has a good heart. And we also know that you're rooting for us. So we're working hard.

Nobody packs the room like you guys do, Bill.

Gina, maybe just on the numbers for you. Actually, a $10 million beat in the quarter and then reiterating the full year, given the $23 million headwind on Q1 actually seems to be impressive. Maybe what gives you the confidence to be that prudent in the guide? And then just any -- maybe a little bit more specificity on the headwinds from the CRPO dynamics with Armis?