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[indiscernible] And if you have joined via the webinar, please use the raise hand icon now, which can be found at the bottom of your webinar application. At this time, I would like to turn the call over to Mike Rowshandel, Head of Investor Relations.

Good morning, everyone, and thank you for joining us today on our second quarter 2026 earnings announcement. I'm Mike Rowshandel, Head of Investor Relations. We hope you've had an opportunity to review our earnings release we issued earlier today. If you have not, copies are available on epam.com in the Investors section. With me on today's call are Balazs Fejes, CEO and President; and Jason Peterson, Chief Financial Officer.

I would like to remind those listening that some of the comments made on today's call may contain forward-looking statements. These statements are subject to risks and uncertainties as described in the company's earnings release and SEC filings. Additionally, all references to reported results that are non-GAAP measures have been reconciled to the comparable GAAP measures and are available in our quarterly earnings materials located in the Investors section of our website. With that said, I will now turn the call over to FB.

Thank you, Mike, and good morning, everyone. It's a pleasure to be with you all again. Since we last spoke, I've spent a quarter with clients, partners and our own teams across global delivery centers, and one team keeps sharpening. AI is transforming everything we do while adding more complexity across the enterprise.

The gap between AI experimentation, adoption and optimization is EPAM's opportunity. Revenue growth in the second quarter came in the high end of our outlook range with continued improvement in profitability and strong adjusted earnings per share. Our pure AI native revenues accelerated, reaching more than $160 million in the quarter.

Our operating momentum remains solid, and we will be direct today about the growth gaps we are experiencing, particularly in significant parts of the North American business and what we are already doing about it. We are executing the strategy we set out at the Investor Day back in March. And this quarter is more evidence that we are progressing in the right direction. It's been a noisy and volatile few months, both broadly and for our sector, especially, and that volatility in itself a reflection of how disruptive AI and the technology continues to be.

Our results this quarter support what we have been saying, AI accelerates demand for specialized talent and new ranges of capability, and we are executing against 3 strategic pillars to capitalize on these new demands. Starting with the first pillar, leading in AI native software engineering, we are rebuilding how we engineer software from the inside out by taking clients beyond traditional SDLC into fully integrated Agentic enterprise harnesses, real-time data modernization, cyber resilience and token cost engineering.

Today, our advanced tools like AI Run, dial and MF Lens are running complex use cases deployed by thousands of specially trained EPAM engineers across hundreds of client engagements. Whenever I sat down with clients this quarter, the same question came up, how to deliver value from AI and generate a positive return on investment. My response is that this is a complex question in which AI does not offer a simple answer. The reason is that AI does not decrease complexity. It adds to it across talent, architecture, process, governance and models. Coding gets automated, engineering doesn't. The better AI gets at writing code, the more the last mile solution engineering and successful deployments matter.

Every successful AI deployment we deliver surfaces new use cases and new scope, which is exactly why the foundational work of modernization, data engineering and retiring technical debt clients have carried for years presents the biggest opportunity for us. and one that is finally addressable because of AI. And yet, we know that we are still early in this cycle, and it isn't linear. Some programs are starting, some are stopping and some are converting into a new ways of engaging, changing the mix and altering the market.

On the second pillar, turning EPAM into a full stack AI native organization, we continue to accelerate and expand our strategic partnership. These partnerships, along with others are on badges. They are how we build a multimodal bench that's already feeding name pipeline and many of our larger multiyear deals. This quarter, we joined the OpenAI Partner Network as an OpenAI advanced partner with a path to Elite status. Together, we are building forward deployed engineering, cyber resilience and customer experience capabilities on OpenAI's frontier models with a first year commitment to certify more than 5,000 OpenAI consultants and train over 10,000 EPAM specialists.

Beyond creating the expert force, we are extending into security, managed services and industry-specific solutions across our main geographies. With Google, we have certified more than 2,000 of our 5,000 by Q3 target under the Gemini Certified Partner Specialist program, building our capabilities on Google's Gemini enterprise ecosystem for building, running and governing multistep AI agents. This is on top of our multiyear GCP relationship with over 2,000 certified Google Cloud practitioners, agentic GCP marketplace solutions and award-winning offerings.

With Anthropic, we are now among the top 5 globally certified partners with more than 5,700 certified engineers already ahead of the 5,000 by Q3 milestone we set out. We are building toward more than 10,000 closed certified [indiscernible] OrTxs by the year-end with over half of our delivery organization already through the Anthropic Academic coursework, backed by a dedicated group of 250 forward deployed engineering Blacklabs. Notably, the practice now extends beyond the team enablement into security and into specific verticals and key accounts.

And finally, on the third pillar, our go-to-market transformation, we are using our AI native structure to open new go-to-market motions with a special focus right now in North America. Over the past quarter, we have launched a structured multi-quarter commercial transformation, standardizing how we prioritize and pursue our largest accounts, building more disciplined new logo pipeline management and investing in sales capabilities and training across the organization.

This is a forward investment in commercial discipline and the back to fundamentals execution focus we are applying across the whole business. Now let's turn to some quick Q2 highlights. Revenue grew 4.5% year-over-year on a reported basis with organic constant currency growth of 3.4%. 4 of our 6 verticals grew year-over-year, led by Financial Services and Life Sciences and Healthcare. Our emerging verticals and consumer goods and retail and travel businesses both contributed to growth. Software and Hi-Tech and Business Information & Media both declined in the quarter.

Business Information & Media's decline was driven by the completion of several client projects. Software and Hi-Tech experienced project ramp downs concentrated in non-AI services, which outweighed growth in AI, cloud and cybersecurity work within the same vertical. Across geographies, EMEA continued to lead our growth with strong double-digit performance, while in contrast, Americas delivered significantly lower growth.

Now turning to the demand environment. From a macro perspective, client sentiment and budget behavior are sitting in roughly the same zone as last quarter. The environment has not materially improved nor worsened, and we continue to see prolonged decision-making as the war in the Middle East persists. Against this background, we continue to see some real areas of strength. Let me share some specifics. EMEA continues to drive strong revenue growth, driven by an active pipeline created by proactive go-to-market sales motions that we have already implemented. Financial services were our fastest-growing vertical again this quarter, delivering growth across both EMEA and the Americas.

A key driver for growth has been AI-led deployment of use cases, including mainframe modernization using APAM IP to reverse engineer, automate and rebuild with new forward deployed capabilities. Life Sciences and Healthcare was our second fastest-growing vertical this quarter, picking up momentum over the past 2 quarters, led by pharma R&D and clinical trials paired with AI and continued momentum in med tech products and services. In Energy, our book of business is significantly larger than it was 12 months ago, primarily driven by expanding scope of services across our existing client base as well as new logo revenues. While we historically focused on upstream, we are now expanding our book of business into midstream, downstream and data center work for this vertical.

Now some of the offsetting factors. Let me be direct. North America is not growing fast enough. We now expect it to operate below our expectations in the second half. Based on where business sits today, I want to be clear that this is not a story about waiting for the macro to turn. we own it. Two things are driving conditions. First, there's a genuine shift in what North American clients are buying. Demand is moving away from tax-based services like manual testing, user experience, Javasky front-end engineering and shifting towards AI-led modernization. This transition is happening faster than the replacement work is ramping, creating a growth gap that needs to be filled even faster.

Separately, Software and Hi-Tech pulled back this quarter, primarily due to project ramp downs and while the underlying client relationships remain solid, the timing is creating a drag in this part of the portfolio. Second, our own go-to-market in the region has not been operating at the level it needs to, and this is squarely within our control. That's exactly what the multi-quarter commercial transformation I described earlier is going to address by building forward selling momentum into subsequent quarters. But for now, we would rather set expectations honestly, than ask you to wait on a recovery we haven't yet earned.

Jason will take you through what this means for the numbers. Now turning to the new big deals pipeline. We are seeing good progress here. These AI-led opportunities are exclusively with existing clients, not new logos, and they continue to actively move through our pipeline. All of them are AI related, specifically Agentic managed services and application maintenance. To be clear, none of them are signed yet, and we are deliberately not getting ahead of ourselves in factoring them in. The potential is real, and it's one of the things we are most encouraged by this quarter.

What makes these deals notable is their composition, size and multiyear structure. We are using our AI native capabilities to compete for portions of existing clients' business for which EPAMS hasn't been historically positioned, thereby expanding our footprint and impact. It's complementary growth on top of our core business, and we are focused on executing it. At the same time, the natural procurement cycle runs longer than our typical deals. Based on our best view today, the likelihood of closing and ramp timing, we now expect more meaningful revenue contribution starting in the first half of 2027 versus the second half of 2026.

Now turning to AI. Our data business grew faster than the rest of the business this quarter. And that foundational demand is exactly what continues to feed our AI native pipeline, underscoring our thesis of the largely untouched backlog underneath AI, technical depth, legacy modernization and foundational data and cloud work of all of which has to happen before AI can drive value for the enterprise. And yet, while AI native revenue growth is compounding nicely, extending its run of consecutive quarters of double-digit sequential growth, now representing over 11% of our business, getting it to a more sizable share of the business is going to take some time. The constraint we see isn't our ability to deliver.

Our FTE teams, or AI Run platform and our partners can absorb considerably more than the backlog we see today. What is needed for reliable traction within complex enterprises is a motion to bring AI from enablement to business change and impact. Compared to a year ago, our progress is real and meaningful, but the industry overall is still relatively early in the process and set against a backdrop of rapidly changing and complex industry trade wins. Let me share a few client examples to help illustrate. For a leading financial services wealth management firm, we are modernizing with AI and accelerating mainframe transformation with reverse engineering over 10 million lines of code, delivering 60% time savings in reverse engineering effort while inserting new forward deployed engineering capabilities into fundamentally new engagement modalities.

For a multinational beverage manufacturing company, we built a unified data platform to consolidate the fragmented enterprise data into a trusted AI foundation, enabling scale deliver more than 80 data and AI initiatives. Now live, the company has seen over EUR 30 million in business operational impact over the past 12 months. For a global energy commodity company, EPAM helped migrate more than 1,000 workloads to AWS with 0 downtime for users, resulting in a 40% reduction in infrastructure and operational costs and a 30% improvement in operational efficiency. The project came at a sensitive time after an acquisition when the company did extract a critical application from its legacy environment and consolidate hundreds of aging on-premises servers.

Since we spoke last, we have been honored to receive several key leadership distinctions. Databricks named EPAM its 2026 Consulting and Systems Integrator AI Partner of the Year, recognizing EPAM's work helping clients across industries operationalize AI and turn fragmented data into production-grade AI applications and agents. EPAM won the 2026 Fortress Cybersecurity Award in cloud security for migrating a Swiss private bank's entire IT landscape, hundreds of applications to Microsoft Azure while meeting strict FINMA requirements. Gartner positioned EPAM as a specialist in its emerging market quadrant for physical AI services, spending out among established vendors.

IDC MarketScape named EPAM a major player in its first worldwide Life Services R&D Strategic Consulting Services 2026 vendor Assessment. Forrester included EPAM among the 28 most important vendors in the customer experience strategic consulting services landscape. And finally, the Wall Street Journal named EPAM one of its best companies for the future. These recognitions continue to reflect the hard work and dedication of our global teams and our unwavering commitment to delivering tangible results and outcomes for our clients.

In summary, our strong second quarter reflects real progress against our multiyear strategy and AI-specific goals. We outperformed despite the macro backdrop, made tangible headways on each of our 3 strategic pillars and took deliberate early steps on the areas that need it most, particularly in North America. We remain confident in our long-term strategy to become a global leader in AI transformation services, serving as a trusted AI accelerator and a partner for our clients.

Our AI native and AI foundational momentum continues to build. And over time, these revenues will continue to make up a larger share of our overall business. We see this as a quarter as a solid step in that direction. We are clear eyed that the second half will be uneven, particularly in North America. But our conviction in the strategy, the team and the commercial transformation is high. The work ahead of us over the next couple of quarters is to keep converting focus into results with the same discipline that got us here. Lastly, I want to thank you all for your continued commitment, trust and support.

Jason, over to you.

Thank you, FB, and good morning, everyone. In Q2, we delivered strong quarterly results, outperforming the high end of our guidance ranges for organic constant currency revenue growth, profitability and EPS. Revenue was $1.415 billion, delivering year-over-year growth of 4.5%. On an organic constant currency basis, revenue grew 3.4% compared to the second quarter of 2025. GAAP and non-GAAP gross margins both improved year-over-year and exceeded our expectations for the quarter.

With solid revenue growth and improved year-over-year profitability, GAAP income from operations grew by more than 20% and non-GAAP income from operations grew by 14.7%. GAAP diluted EPS grew by 26.3% and non-GAAP diluted EPS grew by 22%. AI native and AI foundational revenues continue to contribute to year-over-year growth. With more than $160 million in AI native revenues in the quarter, this is the sixth consecutive quarter of sequential double-digit growth.

Moving on to our Q2 industry performance. We delivered year-over-year growth across the majority of our verticals. Financial services delivered strong growth and was our fastest-growing vertical in the quarter, up 11.5% year-over-year, driven significantly by insurance and asset management clients across both EMEA and the Americas. We continue to generate double-digit revenue growth in the vertical with significant contribution from AI modernization programs.

Consumer goods, retail and travel delivered 2.3% year-over-year growth, notably driven by retail and consumer goods. Life Sciences and Healthcare delivered solid growth and was our second fastest-growing vertical in the quarter with growth of 8% on a year-over-year basis. Revenue growth in the vertical continues to be driven primarily by clients in life sciences and MedTech. Notably, year-over-year revenue growth in this vertical continues to accelerate. Software and Hi-Tech declined 1.3% year-over-year, driven significantly by the expected ramp down of a large client program as well as the shift in priorities that FD mentioned earlier.

Business Information and Media decreased 2.1% year-over-year, driven primarily by the completion of several client projects. Our emerging verticals delivered year-over-year growth of 4.9%, primarily driven by ongoing strength in energy and manufacturing. From a geographic perspective, Americas, our largest region, representing 57% of our Q2 revenues, grew 0.5% year-over-year with strong growth in financial services revenue offset substantially by declines in the software and High-Tech and Business information and media verticals. EMEA comprising 41% of our Q2 revenues increased 10.9% year-over-year and 9.4% in constant currency, with strong growth in financial services as well as contributions from travel and consumer goods and energy.

And finally, APAC, making up 2% of our revenues, decreased 0.3% year-over-year. Lastly, in Q2, revenues from our top 20 clients grew 3.1% year-over-year, while revenues from clients outside our top 20 increased 5.2% -- now as we move down the income statement, our GAAP gross margin for the quarter was 30.4% compared to 28.8% in Q2 of last year. Non-GAAP gross margin for the quarter was 32% compared to 30.1% for the same period a year ago, demonstrating our ability to improve profitability while continuing to invest in our AI capabilities and grow our AI native revenues.

GAAP SG&A was 17.3% of revenues compared to 17.1% in Q2 of last year. Non-GAAP SG&A in Q2 2026 came in at 14.5% of revenue compared to 14.1% in the same period last year. GAAP income from operations was $152 million or 10.8% of revenue compared to $126 million or 9.3% of revenue in Q2 of last year and grew by 20.4% year-over-year. Non-GAAP income from operations was $233 million or 16.4% of revenue compared to $203 million or 15% of revenue in Q2 of the previous year and grew by 14.7% year-over-year. Our GAAP effective tax rate, which includes a higher level of tax shortfalls related to stock-based compensation, came in at 26.7% and our non-GAAP effective tax rate was 24%.

Diluted earnings per share on a GAAP basis was $1.97 compared to $1.56 in Q2 of last year, a $0.41 increase year-over-year, reflecting growth of 26.3%. Our non-GAAP diluted EPS was $3.38 compared to $2.77 in Q2 of last year, a $0.61 increase year-over-year, reflecting growth of 22%. In Q2, there were approximately 52.3 million diluted shares outstanding. Turning to our cash flow and balance sheet. Cash flow from operations for Q2 was negative $2 million compared to a positive $53 million in the same quarter of 2025. Q2 cash flow was negatively impacted by higher variable compensation payments related to 2025 performance as well as an increase in DSO in the quarter.

Free cash flow was negative $18 million compared to positive free cash flow of $43 million in the same quarter last year. Cash and cash equivalents were approximately $800 million as of the end of the quarter. At the end of Q2, DSO was 82 days and compares to 76 days for Q1 2026 and 78 days for the same quarter last year. During the quarter, we repurchased approximately 1.3 million shares, which included open market purchases of approximately 800,000 shares for $80 million and approximately 0.5 million shares from the final settlement of our accelerated share repurchase that was paid in the first quarter. To date, since the initiation of our share repurchase program, we've returned approximately $1.6 billion in cash to shareholders.

Moving on to operational metrics. We ended Q2 with more than 56,650 delivery professionals, reflecting total growth of 1.5% compared to Q2 2025. Our total headcount at quarter end was more than 62,850 employees. Utilization was 78.3% compared to 78.1% in Q2 of last year and 77% in Q1 2026. Now let's turn to guidance. Before moving to the specifics of our 2026 and Q3 outlook, I'd like to provide some thoughts to help frame our guidance. We're encouraged by our performance in the second quarter and by the continued momentum in our pure AI native revenues, keeping us on track to meet our goal of $600 million in AI native revenues in 2026. We have also been able to improve company profitability and most notably gross margin while continuing to invest in our expanding AI capabilities.

However, we are now expecting a slowdown in our revenue growth rate in the second half of the year. I'll try to be clear about the underpinnings of our updated outlook. As FB indicated, we delivered modest growth from North America in Q2 and now expect to continue to see very slow revenue growth from this geography for the remainder of the year. We believe our lower growth in North America is largely idiosyncratic to EPAM and something we are working to address. At the same time, our emerging pipeline of larger opportunities continues to develop, and we remain encouraged by the size of this pipeline and the progress we're making in client negotiations. However, none of these deals have been closed.

As a result, we are not expecting meaningful revenues from these deals to contribute to growth until early in 2027. We now expect modest sequential growth in Q3 as well as flattish revenues as we move from Q3 to Q4. Therefore, we will be lowering our revenue guidance for 2026. At the same time, based on our solid profitability in the first half of the year and updated forecast for the second half, we now expect to operate at the high end of our previous adjusted IFO range of 15% to 16% and have updated our guidance to reflect this.

Compared to 90 days ago, we see no material improvement or worsening in the broader macro environment. And we're not assuming any change, better or worse for the remainder of the year. Client budgets remain intact for AI and other strategic priorities. Non-AI discretionary spending continues to be muted. As in past years, we expect to generate significant free cash flows in the second half of the year with our free cash flow conversion rate forecasted to be above 100% in both Q3 and Q4.

However, with the lower free cash generation in the first half of the year, we are now expecting our free cash flow conversion rate in 2026 to be around 70%, below our typical 80% to 90% conversion rate. As usual, our guidance assumes we can continue to deliver from our Ukraine delivery centers at productivity levels similar to those achieved in 2025. Moving to our full year outlook. Revenue growth will now be in the range of 3.2% to 4.2%. Foreign exchange is expected to have a positive impact of approximately 1.2%.

Therefore, the organic constant currency growth is now expected to be in the range of 2% to 3% -- we now expect GAAP income from operations to be in the range of 10.5% to 11% and non-GAAP income from operations to be in the range of 15.5% to 16%. We continue to expect our GAAP effective tax rate to be 27%. Our non-GAAP effective tax rate will continue to be 24%. For earnings per share, we now expect that GAAP diluted EPS will be in the range of $8.22 to $8.38 for the full year. And non-GAAP diluted EPS will now be in the range of $13.08 to $13.24 for the full year, producing year-over-year growth of over 14% at the midpoint of the range. We now expect weighted average share count of 52.2 million fully diluted shares outstanding. Moving to our Q3 2026 outlook.

We expect revenue to be in the range of $1.410 billion to $1.425 billion, producing year-over-year growth of 1.7% at the midpoint of the range. Our guidance reflects a 0.1% negative foreign exchange impact during the quarter, producing organic constant currency growth of 1.8% at the midpoint of the range. For the third quarter, we expect GAAP income from operations to be in the range of 11% to 12% and non-GAAP income from operations to be in the range of 15.5% to 16.5%.

We expect our GAAP effective tax rate to be approximately 25% and our non-GAAP effective tax rate to be approximately 24% -- for earnings per share, we expect GAAP diluted EPS to be in the range of $2.33 to $2.41 for the quarter and non-GAAP diluted EPS to be in the range of $3.38 to $3.46 for the quarter, producing year-over-year growth of over 11% at the midpoint of the range. We expect a weighted average share count of 51.4 million diluted shares outstanding. Finally, a few key assumptions that support our GAAP to non-GAAP measurements for Q3 and the remainder of the year.

Stock-based compensation expense is expected to be approximately $44 million for Q3 and $45 million for Q4. Amortization of intangibles is expected to be approximately $17 million for each of the remaining quarters. The impact of foreign exchange is expected to be an approximate $3 million loss in Q3 and a $1 million loss in Q4. We completed our 2025 cost optimization program in the second quarter.

As a result, for the remainder of the year, the company will no longer adjust for severance-related expenditures and those expenses will be recognized as part of the company's GAAP and non-GAAP results. Tax effect of non-GAAP adjustments is expected to be around $14 million for Q3 and $14 million for Q4. We expect negligible tax shortfall related to stock compensation in Q3 and $2 million tax shortfall in Q4. And one more assumption outside of our GAAP to non-GAAP items. We now expect interest and other income to be $1 million in Q3 and $0.5 million in Q4. Lastly, my continued thanks to all our EPAMers for their dedication and focus on serving our clients and driving results throughout 2026.

Operator, let's open the call for questions.

[Operator Instructions]

The first question is from Bryan Bergin at TD Cowen.

So maybe I just wanted to start with unpacking fiscal '26 guide and maybe the demand here and dig in on the primary headwinds in this reduced outlook. Just based on the Biz info and the high-tech vertical slowdown, it does seem to be more than something macro related. And I think you owned up to that with some of the [indiscernible] pressures. Just curious what you saw there specifically in decision-making cycles? And then on the North American Iideo weakness, can you talk about what you're specifically changing to restart that growth? What's near term versus kind of long-term fixes?

Brian, how are you doing? So let's start with the hard questions. So overall, the demand environment didn't really change, but we are still in the same macro space. What started to change somewhere in July, and first of all, really explain it, I need to remind everybody that most of our business is time and material contracts, right? It's not annuity-based. So you need to resell or renew the contracts quite regularly. And somewhere in July, we started to see that clients are prioritizing AI budgets, reprioritizing away from cost-based services like manual testing, user experience, and as I mentioned, from Javascript front-end engineering.

And they're shifting towards modernization. -- they -- and this shift is happening faster than the replacement work is ramping, right, creating a growth gap for us. And the clients are planning to do the ramp-ups of the AI native services, mainly from savings from what AI is delivering. At the same time, they are funding tokens, hardware and infrastructure. So as the savings are realizing or appearing slower than as expected, this creates a gap. So this is what we are seeing. This is actually very much impacted in North America, and it's mostly confined in our SaaS client base, which is largely confined inside the software and high tech.

Clearly, they have others in other places, but most of the SaaS clients are in the software and high-tech sector. In this sector also, we are seeing some level of project ramp downs and outside of AI areas. And this is being -- the ramp downs are outweighing our growth in AI cloud or cybersecurity. So that's kind of the demand environment as we see it right now. Your second -- the second question was what are we going to do about the sales, right? I think already in our Q1 earnings call, we started to talk about the structural changes which we are making in how we go to market.

And we kicked this off. It takes time. It's a process, but our clients, what we're seeing that they are increasingly want to see business cases, commercial proposals rather than just engineering go-to-market motions, which was the priority in the past. I think already we talked about this in our Investor Analyst Day. This is a part of our transformation. We are building this depth and domain and consulting capability, which allows us to actually respond to these demands. This has worked before and the evidence is in the EMEA growth rate where we actually made this investment in the past and made the transformation.

So we put a multi-quarter program in place where we're changing how we're going to market from marketing all the way to the sales motions, how we prioritize clients, how we create proposals. And we are building out hiring and building a bigger sales force in the North America, especially focused in North America.

Got it. Okay. Makes sense. And then, Jason, on free cash flow, can you just unpack some of the moving pieces there as far as the added working capital headwind? And was there anything kind of onetime in contracting? I want to just understand that and your confidence in the second half free cash flow improvement and whether anything maybe beyond this year changes as you think about conversion?

No. The -- we would still have -- or I have high confidence in the 80% to 90% as we move past 2026 into 2027 and 2028. What we did see at the end of Q2 was we had clients who were expected to make payments in the last 2 days of the quarter, and those payments ended up being made in the first 2 days of the next quarter in Q3. And so effectively, it was a fairly significant amount of money that supposedly required an additional level of review before they made payment. And so that was really what sort of drove the less-than-expected sort of free cash flow in Q2. We are seeing a somewhat higher level of DSO. I do think that probably is going to continue throughout the year. It's not going to stay at the level it was at Q2.

But I think as you compare each quarter, Q1, Q2, Q3, Q4 to the corresponding quarter in 2025, DSO is probably going to be a bit higher, and that's probably a cost. We also have some additional sort of tax-related expenses. But again, I think it's very much kind of confined to 2027 and again, to 2026. And I expect beyond 2026, you'll see a return to the 80% to 90% conversion range.

The next question is from Maggie Nolan at William Blair. Thank you. .

So it sounds like there's also a bit of a timing gap in North America. And so I'm wondering if you're talking about this go-to-market transformation. I'm wondering if you can draw some parallels between what you've done in EMEA and what you're doing in North America and maybe help us understand how long the rebuild phase is when you can see maybe an inflection point in North America? Any information on maybe some of those large deals and TCV there and ability to see contribution from those in '27 would be helpful.

Maggie, so I think we already started to talk about this during Investor Analyst Day that EPAM was very focused on fulfillment, very much focused on delivering engineering excellence and selling to the Head of Engineering or Head of Products. And it was especially true in North America, where we have a large concentration of our Software and Hi-Tech business. And very much we were focused on fulfilling that demand instead of focusing and formulating business solutions, which was more predominant in the European portfolio. You have to address different buyers.

You have to have different propositions in place and engineering excellence is just not enough in the current environment as clients are looking to receive ROIs or actually realizing business goals. So this is actually what we've done in Europe, and we invested into it is we are actually created very specific domain-led go-to-market motions, pairing it with a larger seller capabilities, which is in terms of numbers and processes and methods and go-to-market motions.

We are bringing this investment which we've done into North America, expanding and starting to build it out. We start a transformation programs of how we are approaching the big deals and building out a new growth movement inside EPAM, which is focused differently than in the past, which was very much focused on purely engineering excellence. We need to pair it with business development excellence. How much time it will take? I think it's hard to say it's actually taking probably longer than we anticipated, but we are making big strides during this year.

In terms of big deals, I think Jason updated and also that it is progressing very well. We actually -- a number of big deals are increasing. We are very, very optimistic about it. And we're seeing that as they go through the pipeline. But as we have less experience in some of these things, that's why we are still reluctant to include that into our guidance or into our -- really into our forecast. but they are going through the pipeline, and we have emphasis to actually continue building this pipeline for the future, and this is going to be part of our normal go-to-market motions going forward. Expect to see results of it in 2027 in terms of significant revenue contribution.

Okay. And then, Jason, maybe can you comment a little bit on the margin durability? Maybe what is foreign currency and cost optimization and whether or not you can sort of hold these margin levels into 2027 if the organic growth is in sort of the low single digits range here?

Yes. I'm probably going to stay away from commenting on 2027, but happy to talk about 2026 and gross margin levels. We're actually not getting a lot of benefit from foreign exchange. So despite the fact that we've got a significant India workforce, India as a percentage of our total cost is not near as significant as it is for many of our competitors. So we still have very significant costs in places like Poland and Hungary and Mexico and even Colombia, where those currencies have all appreciated. And so actually, foreign exchange has not been a contributor. It actually has been somewhat negative. What we did get is the price -- some of the price increases that we got at the beginning of the year, which has been helpful. We also have been working to improve our fixed fee profitability or our non-T&M profitability.

So that's improved nicely on a year-over-year basis. And then we continue to do all the work that we've been doing to continue to improve the cost efficiency in places like India. So I feel good about the gross margin performance in the first half. I also expect that we'll continue to see gross margin in excess of 32% for each of the quarters, Q3 and Q4. Again, we're trying to do the right things to sort of preserve profitability and EPS for the remainder of the year.

Yes. I'

The next question is from Puneet Jain at JPMorgan.

I wanted to follow up on earlier question on go-to-market. Would you say like it's a capability gap versus like the more business use cases and outcomes that clients are looking for? Or would you say it's merely an issue around messaging, positioning, account coverage in North America?

I think it's a capability gap, Puneet, in business development. It's not a capability gap in terms of delivery. We can actually deliver it because we are delivering from a global workforce, and it's proven that in Europe with a different go-to-market motion and different business development capability, you can actually deliver double-digit growth, which we delivered this quarter.

So I am actually very optimistic if we fix our go-to-market notion in North America, if we increase the -- our growth organization, if we retarget them, equip them with other tools, then the capabilities, the product, which we're bringing to the market, that product resonates with our clients. And we are serving global organizations. So I think what works in Europe in terms of the product what we are selling will be also delivering the same type of growth or similar growth figures in North America if we bring it to the market in a correct way.

Got it. And then your financial services vertical was up double digits, growing at rapid clip relative to the rest of the business. What's driving higher growth there? And could that vertical be a precursor to better growth rates in the rest of the business?

We were successful, Puneet, in financial services to actually combine our domain knowledge with our AI native capabilities and actually driving large transformation programs in this case. Also, we are modernizing using AI, utilizing with EPA IP, which I actually called out MF lens or clients' legacy systems. And actually, all of them is a precursor and what we call AI foundation elements. We've just been more successful packaging it and bringing to our clients and our clients who have a large legacy -- they are responding to that. They're also building out the data platforms and data products, which they need to ground the AI models when they get implemented.

The next question is from Jonathan Lee at Guggenheim Partners.

The fact that the demand shift happened in July after you'd set the 2Q framework in early May raises questions about forward visibility. Given most of your business is T&M rather than annuity-based and clients can reprioritize budgets relatively quickly, how should we think about the durability of the revised calendar '26 outlook? And what gives you the confidence that a similar dynamic doesn't play out in August or September within a different client cohort?

No, it's a fair question, Jonathan. When we look at the guide that we have for the full year, the midpoint of the guide is going to give you, as we said in the prepared remarks, a 1.8% year-over-year growth. And then midpoint just requires that we kind of remain flat. We continue to see growth, as we discussed in Europe. We continue to see growth, particularly in financial services and life sciences.

So we think we do have a strong series of kind of growers in the business, while we will probably see some ongoing underperformance in both North America and in the high-tech portion of the portfolio. But again, I feel very confident that the ability to sort of operate in this midpoint of the range or higher and then to be able to operate with a flat execution as we move from Q3 to Q4. I don't -- you would need a material sequential decline from Q3 to Q4 to end up in the low end of this range. So again, I really do feel quite confident that this one is derisked.

I appreciate that color. And just as a follow-up, to what extent is the growth gap in North America a function of clients gravitating toward more diversified peers who can bundle AI-led savings on infrastructure or managed services with the transformation work effectively self-funding the ramp within a single commercial construct. I mean EPAM's more concentrated engineering services model doesn't necessarily naturally offer the same savings pool to redeploy. So if that's the case, how are you thinking about the commercial response?

I mean I think it's a good question. We haven't seen that, that actually demand actually migrated to our peers. What we are seeing is that it's -- some of the spend is migrated to tokens, which we can also offer, but it's -- most of our clients buying them directly or migrated towards infrastructure or into GPUs. I think with our larger deal go-to-market motion, we are actually want to transform the savings what our clients are going to achieve with AI-driven services into reinvest them to grow themselves. But what you are asking, I haven't seen that one yet. So we're not losing to competitors, if that's what you're asking.

The next question is from Tyler DuPont at Wells Fargo.

This is Tyler on for Jason Kupferberg. I want to start within North America. There are a few moving pieces, any updated outlook. So I just wanted to ask about some of the drivers there, mentioned macro is largely unchanged. So if we just put that to one side, how much of this updated outlook is due to your current go-to-market capability set versus clients actually shifting spend away from services altogether towards other tech priorities like tokens and memory, as you mentioned in a previous response. .

I think it's both, right, happening in the same time, right? The clients are trying to buy different things, different ways, right? We are -- and we have a large concentration of -- which is -- so I think -- so number one, it's both, right? But I think each of them is in a different bucket. The clients who are really shifting away the spend from us is very much comprised in our SaaS client portfolio, which is predominantly inside our software and high-tech sector. Those are the clients who are shifting their spend towards tokens, towards GPUs, which we clearly are not delivering. The rest of the portfolio and the clients, their demand is shifting, right? And I called out shifting from, let's say, manual testing, front-end capabilities, more from task-based setups towards AI native AI-driven solution.

And here, our capability around driving the business is lagging. That's where the business development strengthening our go-to-market motions or growth community is what's needed to actually push through and actually see the same results because we have that type of capability available. We have that knowledge. We have the certified engineers. We actually know how to make it work for our clients. We just need to make sure that we are able to sell it to.

Okay. That's helpful. And then I guess just an update on the pricing environment right now would be pretty helpful. Some of your peers have recently mentioned more, let's call it, competitive pricing dynamics to win work with challenges is getting as much net pricing realization as they had hoped due to increasing levels of productivity savings. Are you guys seeing any of that at this moment or not so much?

Yes. As we've talked about, we did see price improvement at the beginning of the year. We are seeing ongoing sort of vendor consolidation exercises across certain customers. Generally, those are done where a client obviously expects to see some economic advantage from those consolidations. They obviously do give upside kind of revenue potential as well. I think whenever we've talked about these larger deals, what we are talking about using Agentic solutions to produce a more cost-effective offering.

The advantage for us is that we currently don't really participate in the market for Agentic managed services. So it is a significant revenue opportunity at what we believe can be appropriate solid and good profits. profitability, it may look like a price haircut if you're sitting there delivering managed services today. And so I could understand why some competitors might refer to that. Again, for us, it's an incremental opportunity and as a result, doesn't represent the reduction in price.

The next question is from Jamie Friedman at Susquehanna

Consecutive quarter of double-digit sequential AI native revenue growth. Wondering if you can roughly size what percentage of revenue is AI native today? And when can we expect it to lift total consolidated company growth? How you're thinking about that?

So I think we already mentioned it's 11% of our business right now, it's AI. And it continues to grow. It's a very fast-growing segment, right? I think once it's crossing a certain threshold, we think 5%, that's when it's going to start seeing that it's going to lift the growth of itself. And remember, this is a very narrow definition, how we call this out. It's very narrow what we are calling AI native. We're not including what we call -- what others would call AI-assisted revenue.

The next question is from Jim Schneider at Goldman Sachs.

I was wondering if you can maybe just follow up on the last response. I may have missed it, but with the $160 million of AI native revenue you reported in Q2, do you still expect to hit the $600 million target you talked about earlier?

So clearly, that's -- $600 million is our declared goal in 2026. If we over blew it, then we actually went toward one of the KPIs we set ourselves, right?

Yes. So I think with that set piece what you're saying, absolutely.

Okay, fine. That makes sense. And then are there -- as you look at the vertical performance, would you expect financial services to sort of maintain the stronger growth rates heading into 2027? And maybe with respect to the larger deals, you see kind of pushing into '27, if you could address where are those verticals? Or is it broadly dispersed across a bunch of verticals? Maybe just talk a little bit about the vertical composition of those.

Yes. I think we are going to stay away from talking about 2027, although maybe we'll talk a little bit about the large deals. I will say throughout the remainder of this year, we are continuing to see strong growth in financial services all of the AI supported modernization, including programs, which use EPAM IP, continue to deliver nice revenue growth for the company. And then we're also continuing and expecting to see good growth in life sciences. I don't know, FB, you want to talk about some of the color around the big deal? .

So I think in the big deals bucket, we have quite a few from regulated industries, which for us is financial services, banking and insurance. So there's a large portion of that. So I think once we see that, how it's converged, we're going to update you, but we do expect some of them is going to convert and some of the large deals becoming -- coming from the financial services sector.

And the final question is from Paul Obrecht at Wolf Research.. .

This is Paul Obrecht on for Darrin Peller. FB, Outside of the new large deals emerging in areas such as BPO and agent managed services, your guide also included some larger deals in your traditional markets. Just curious, as the year has progressed, how these deals have evolved relative to your initial expectations? .

So we didn't close them. They are progressing. They are progressing to our pipeline. And some of these deals are actually in the smaller phases started to convert, but I think what's more interesting for us is that even if it's more traditional vendor consolidation, for example, larger deals, they are also triggering other type of deals, which is agnetic BPO or, let's say, legacy mainframe transformation. So we are seeing it that it's progressing. We are not losing them. They are still in the pipeline, and we will update you in, I think, on the next earnings call, how successful we have been in closing them and converting them.

Yes. And Paul, some of the deals were AI-specific and you're clearly seeing wins with those, including the ones that use EPAM IP. And then you also have had some vendor consolidation exercises, where we've had some wins. And so those would be outside of the agentic managed services, and we've made progress there. But as we pointed out, it's been somewhat uneven with good growth in Europe, as we talked about, financial services, life science and less so in some of the other verticals and geographies.

Right. That makes sense. That's helpful color. And then just as a follow-up, FB, can you provide a bit more detail on the path forward to develop full-stack agentic engineers. Just curious how much of that would be coming from internal training versus external hiring and for the internal what level of training is really required to get there relative to current talent? .

So forward FTEs are actually part of our sales motion. That's what we are partnering with our AI partners and also with the hyperscalers to actually build this -- EPAM is building it. We're building it from internally. There's a clear deliberate motion to ramp up, and it's part of how we go to market and how we sell solutions with our new partners. We are expecting to build it inside. So we set up a training programs, academy around it. This is a big part of our effort in 2026. I think as we updated you on the certifications, what we've done around Anthropic with Google also what we actually announced around open AI, you're clearly going to see that EPAM will have the largest concentration of certified engineering software engine professionals in the industry.

And we aim to be the source and the solution for all our partners to solve and get their needs around FD sold and not just sold, but we want to be the source and the supplier to work with them and solve their clients' problems using FTEs. So that's kind of what's our aim and this is what we are pushing for. This is what we are aiming for in 2026.

There are no more questions at this time. I now would like to turn the call over to Balazs Fejes for closing remarks.

Thank you very much for joining us in our Q2 earnings calls. Clearly, we have a work cut out for us. And on the next earnings call, we're going to update you how we're progressing in transforming our go-to-market notion and also around the big deals which we all talk about and also what progress we're going to make around transforming EPAM to an AI native engineering services organization. Thank you much. See you next time.

Good day, everyone. My name is Michael, and I'll be your conference operator today. At this time, I would like to welcome you to EPAM's first quarter earnings release conference call. [Operator Instructions] At this time, I would like to turn the call over to Mike Shandel, Head of Investor Relations.

Good morning, everyone, and thank you for joining us today on our first quarter 2026 earnings call. As the operator just mentioned, I'm Mike Shandel, Head of Investor Relations. We hope you've had an opportunity to review our earnings release we issued earlier today. If you have not, copies are available on epam.com in the Investors section. With me on today's call are Balazs Fejes, CEO and President; and Jason Peterson, Chief Financial Officer. I would like to remind those listening that some of the comments made on today's call may contain forward-looking statements.

These statements are subject to risks and uncertainties as described in the company's earnings release and SEC filings. Additionally, all references to reported results that are non-GAAP measures have been reconciled to the comparable GAAP measures and are available in our quarterly earnings materials located in the Investors section of our website. With that said, I will now turn the call over to FB.

Thank you, Mike, and good morning, everyone. It's a pleasure to be here with all of you. We delivered a solid first quarter with revenue growth at the high end of our outlook range, year-over-year improvement in adjusted profitability and gross margins and strong adjusted earnings per share pure AI revenues exceeded $125 million in Q1, up nearly 20% sequentially from Q4. This momentum gives us a strong line of sight to our $600 million target for the full year, even with the broader macro variability we have factored into our outlook.

We also just announced a strategic multiyear applied AI partnership with Ontic to accelerate the delivery of safe, reliable enterprise-grade AI for our clients. As an Anthropic services partner, EPAM is building a dedicated practice for more than 10,000 cloud-certified architects, including the specialized cadre of 250 forward deployed engineering Black Belts. To date, over 20,000 EPAMers have completed training via entropic economy and more than 1,300 are already Claude certified. We expect to reach 5,000 certifications by end of Q3 with 10,000 by year-end.

This is a further proof of our engineering expertise for adaptability, advanced learning and education programs and readiness for Claude within the enterprise. As we outlined at our recent Investor Day, we have a clear multiyear strategy to drive our next phase of profitable growth and further capitalize on the global AI transformation opportunities. Our aspiration is to become the go-to partner for enterprise a transformation with a focus on 3 strategic pillars, which are helping reshape the company.

These pillars include establishing ourselves as a leading AI delivery software engineering services provider, transforming ourselves into an AI-native organization and capitalizing on our AIT structure to expand go-to-market offerings. For 30-plus years of engineering DNA and heritage expanding domain and vertical expertise, advanced IP and platforms and deepening strategic partnerships continue to differentiate us and provide a durable advantage.

Our mission is to win the build opportunity of our lifetime. The gap between the rapidly developing foundational AI capabilities and the ability of enterprises and societies to adopt AI safely, reliably and with sustainable growing volume will drive some of the largest technological investments humanity has ever made. This view was recently validated by our new partner Anthropic and also by NVIDIA's CEO, Jensen during his interview with Vorkesh Patel.

Today, we are moving beyond traditional IT services with a sharp focus on AI native engineering and AI native business transformation, which both continue to gain traction. At the same time, EPAM is fundamentally retaining how the company operates, which goes beyond scaling AI adoption across 60,000 people. With our Client Zero mentality, we are engineering an entirely new operating model one that dynamically blends human talent, AI capabilities and advanced agentic systems to run the business foster better and lower cost across all geographies. The early stage of this new blend reflected in the number and the shape of AI-native projects that we are starting with clients. AI/Run, then from being an SDLC transformation pay book to powering a series of AI/Run transform motions that bring significant structure and volume to our clients' own adoption apertures.

ROI-driven Playbook uniquely brings together our engineering excellence with AI native delivery, coupled with strategic consulting and advisory teams, deep technical expertise and partner ecosystem technologies. Online traditional consulting roads and deployments, EPAM's AI run transform integrates blueprints, talent and tools into a single proven, repeatable and scalable transformation platform for our clients. We continue to create global go-to-market playbook using proven methods across the globe.

The larger number of our AI programs are scaled into deployments, tonic and implication for our engagement is becoming more significant. This is a generally new and consequential commercial construct and presents both challenges and opportunities for us and services companies in general. As the industry works through the models, we intend to be ahead of the curve as we continue to evolve our approach to AI investment pricing, client engagement and delivery models for some quarters to come.

One additional element of our strategy worth highlighting is the fact that we are now accelerating our deliberate go-to-market investments in our largest market in North America. These investments are modeled on what has proven to be successful in EMAR, evidenced by their industry-leading growth rate in Q1.

Now let's turn to some quick Q1 highlights. In Q1, revenues grew 7.6% year-over-year with constant organic currency revenue growth of 3.7%. The 5 of our 6 verticals grew year-over-year, led by Financial Services and Software and Hi-Tech, followed by Consumer Goods, Retail and Travel, emerging verticals and Life Sciences and Health Care. Across geographies, growth was led by email, delivered strong double-digit year-over-year growth. We are continual balancing our delivery locations and scale mix, adding new certification, domain specialization and additional roles across our global pet.

We also continue to proactively manage our commercial engagement types, driving new fixed price and other service deals while proactively managing localized banks. Now turning to the demand environment. Overall, client sentiment remained stable through the end of Q1 and with continued shift in spend towards AI native and strategic deployments.

Clients continue to turn to EPAM for help in addressing the widening adoption gap. The need to modernize and build out a foundation readiness remains critically important. Technical debt continues to mount and the latest AI capabilities are making backlog of required work evident, further underscoring our confidence that the build opportunity is a long-term win.

As we look ahead, there's a more macro uncertainty today compared to 90 days ago. And our outlook reflects the broader variability we are seeing in the client decision-making. We are particularly seeing underperformance in North America, and this is contributing to lower visibility in the second half. At the same time, our underlying momentum, particularly across our AI native business continues to build. However, macro volatility has introduced some additional caution in client decision-making, particularly on certain larger discretionary programs.

While Q1 was not impacted, we are expecting some impact in Q2. Importantly, our client pipeline of AI programs and fundings remain strong. What we see is a temporary shift in timing and direction as clients respond with caution and reprioritize the short-term actions against the bigger transformation opportunity.

Now turning to AI. As we have all seen in the news, AI capabilities continue to advance extremely fast. The pace of technological change and digestion is unprecedented for enterprises as they face the challenge of balancing cost optimization and productivity with real business outcomes at scale. Further token usage and the associated economics are only becoming a more integral part of the investment thesis and business case.

All this just increases complexity, which, as we stated at our Investor Day on less new sets of requirements across all 8 dimensions of AI enterprise. EPAM remains in the sweet spot of helping enterprises close the AI adoption gap, solve their most complex challenges and deliver quality AI-native enterprise-grade solutions at scale. We are working hard to further build and create high velocity performance teams within our AI native delivery engine to take advantage of larger growth opportunities.

By design, our teams will bridge strategy to execution with a more consultative approach, all with deep domain and verticalization expertise.

Looking across our top 100 clients, traction remains strong as more than 80% of our engaged in AI initiatives. Our AI frameworks and tools continue to support hundreds of active AI-native projects. Note, we had more than 100 new AI-native project launched in Q1, illustrating our active pipeline and healthy replenishment of new opportunities.

In terms of new deals, or since we shared our updated at our AI Day. EPAM is seeing an oxalating large-deal pipeline focused on AI-enabled vendor consolidations, where EPAM has significant opportunity to gain market share. These multiyear deals are larger than our historical norm are expected to scale over time and include a range of commercial models.

The trajectory of this pipeline marks a meaningful step in EPAM's evolution as a strategic partner to enterprise clients. However, the full potential of these deals is not yet reflected in our outlook. Across our pure AI native revenues, our momentum continues and fundamentals remain intact with another quarter of double-digit sequential growth.

Demand across our AI foundational services remains solid with faster growth in both our data and cloud practices as compared to the rest of the business. Importantly, we believe we can further accelerate capturing AI foundation demand with the deployment of more domain capabilities and forward deployed engineers to engagement. This motion will take some time to scale, but we see this as a critical unlock to being able to deliver true business transformation to clients.

Beyond transforming EPAM's business and go-to-market approach towards more outcome-based models, we are building not just an engineering moat, but a domain and context-based mode and court in playbook built on successful engagements over time. Capturing expertise at the source of these engagements further develops our playbooks into differentiated IP and ways of working.

Here are some client example to illustrate the shift. one, PDLC transformation for Nelnet, a global company specializing in consumer finance, student loan servicing, telecommunications and education to explore the potential of GenAI tools to boost PDLC efficiency. To do that, EPAM developed a program to identify baselines and performance productivity benchmarks based on EPAM's AI/Run transform, Nelnet achieved a 31% productivity increase, accelerated back-end development by nearly 2x and empowered its teams to scale AI-driven innovation across the organization. We continue working with Nelnet to expand the PDLC program across the organization and continued building an enterprise governance model that scales.

Two, modernize and upgrade global streaming infrastructure for a leading streaming platform client within the media entertainment, serving 10-plus million concurrent users across 50-plus countries. With our partner, AWS, we successfully transformed a fragile single-region platform into a self-healing global system sustaining 99% uptime without manual interaction. The solution deployed active, active ES across more than 6 regions with automated IAC governance and standardized site reliability engineering practices. Together, we helped our client achieve 70% less configuration drift and 0 downtime deployments.

Three, bring the right AI and GenAI programs from use case concepts to full-scale production deployment for a large global insurance company. Here, our DI platforms serve us both domain playbook and a significant accelerator, integrating both upstream and downstream systems to ensure seamless end-to-end automation to assist the reinsurance clean department in first order of loss processing.

EPAM automated billing reconciliation and streamlined reinsurance treaty analysis proving the real-world potential of AI in a highly regulated industry. After implementation, time to process first order of loss events decreased by 75%. Our efforts continue to be recognized validating our strategy and the quality of our execution.

So far, in 2026, we have been honored to receive several key leadership distinctions. We earned two 2026 Google Cloud Partner of the Year awards for helping clients achieve measurable business outcomes through advanced AI and cloud technologies. The sustainable award highlighted our use of AI and geospatial technology to address environmental challenges, while databases, ML awards celebrated or scalable methodologies for enterprise cloud migrations including our work with Deutsche Bank.

EPAM was included in the Forrester Customer Experience strategy consulting services landscape, featuring providers that supports end-to-end CX transformation from visions through execution. EPAM named a leader in the IDC Marketscape worldwide data modernization services provider for retail and restaurants. And finally, EPAM was ranked among the top 3 companies in Glassdoor's inaugural best companies in tech and AI 2026 list, recognized for its culture of belonging, innovation and leadership.

These recognitions continue to reflect the hard work and dedication of global teams and riveting commitment to delivering tangible, high-volume outcomes for our clients.

In summary, we are pleased with our first quarter results, which delivered the high end of our revenue outlook despite more uncertain macro environment, a solid foundation we intend to build upon throughout the year. We remain confident in our long-term strategy and vision in transforming ourselves into a global leader in AI transformation services working to further capitalize on faster-growing parts of the total IT and AI services market.

Our underlining AI native and AI foundational readiness momentum remains strong and continues to resonate with our existing client portfolio. while we transform our go-to-market motions over the coming quarters to further expand our new client portfolio, while the economic environment impacted visibility and added some vulnerability. We feel good about our pipeline, including the larger strategic opportunities I described earlier, which represent a meaningful step in our evolution.

Lastly, I want to thank you all for your continued commitment, trust and support. Jason, over to you.

Thank you, FB, and good morning, everyone. In the first quarter, EPAM generated revenue of $1.4 billion at the high end of Q1 revenue outlook, delivering year-over-year growth of 7.6%. On an organic constant currency basis, revenue grew 3.7% compared to the first quarter of 2025. With improved year-over-year profitability in the quarter. GAAP income from operations grew by approximately 18% and non-GAAP income from operations grew by over 14%.

AI native and AI foundational revenues continued to contribute to year-over-year growth with more than $125 million AI native revenues in the quarter. This is the fifth consecutive quarter of sequential double-digit growth.

Moving to our Q1 industry performance. We delivered broad-based year-over-year growth across the majority of our verticals. Financial Services delivered strong growth, up 11.5% year-over-year, driven by asset management and insurance clients. Software and Hi-Tech grew 10.9% year-over-year, driven by strong execution across existing clients and contributions from new logos.

Consumer Goods, Retail and Travel delivered 7.2% year-over-year growth, notably driven by retail and consumer goods. Life Sciences and Health Care increased 5.9% on a year-over-year basis. Revenue growth in the vertical continues to be driven primarily by clients in life science and med tech. Business Information Media decreased by 0.7% year-over-year, and our emerging verticals delivered year-over-year growth of 6% and 8%, primarily driven by ongoing strength in energy and government.

From a geographic perspective, Americas, our largest region, represented 57% of our Q1 revenues, grew 2.5% year-over-year. EMEA comprised 41% of our Q1 revenues, grew 15.9% year-over-year and 8.4% in constant currency. And finally, APAC making up 2% of our revenues grew 1.2% year-over-year. Lastly, in Q1, revenues from our top 20 clients grew 4.4% year-over-year, while revenues from clients outside our top 20 increased [ 9.1% ]

Moving down the income statement. Our GAAP gross margin for the quarter was 27.7% compared to 26.9% in Q1 of last year. Non-GAAP gross margin for the quarter was 29.4%, compared to 28.7% for the same period a year ago, demonstrating our commitment to improving profitability and gross margin during the fiscal year. GAAP SG&A was 17.1% of revenue compared to $0.168 in Q1 of last year. Non-GAAP SG&A in Q1 2016 came in at 14.1% of revenue, compared to 14.2% in the same period last year.

GAAP income from operations was $117 million or 8.3% of revenue compared to $99 million or 7.6% of revenue in Q1 of last year, and grew by 18% year-over-year. Non-GAAP income from operations was $201 million or 14.3% of revenue compared to $176 million or 13.5% revenue in Q1 of the previous year, and grew over 14% year-over-year.

Our GAAP effective tax rate, which includes a higher level of tax shortfalls related to stock-based compensation, came in at 31.6%. And our non-GAAP effective tax rate was 23.6%. Diluted earnings per share on a GAAP basis was $1.52 compared to $1.28 in Q1 of last year, a $0.24 increase year-over-year, reflecting growth of 18.8%. Our non-GAAP diluted EPS was $2.86 compared to $2.41 in Q1 of last year, a $0.45 increase year-over-year, reflecting growth of 18.7%.

In Q1, there were approximately 54.2 million diluted shares outstanding. Turning to our cash flow and balance sheet. Cash flow from operations for Q1 was negative $36 million compared to $24 million in the same quarter of 2025. Q1 cash flow was negatively impacted in the quarter by higher variable compensation payments related to 2025 performance as well as timing of certain vendor payments.

Free cash flow was negative $54 million, compared to free cash flow of $15 million in the same quarter last year. Cash and cash equivalents were just over $1 billion as of the end of the quarter. At the end of Q1, DSO was 76 days and compares to 72 days for Q4 2025 and 75 days for the same quarter last year. Share repurchases in the first quarter were approximately 1.8 million shares for [ $264 million ] at an average price of $143.84 per share. To date, since the initiation of our share repurchase program, we've returned approximately $1.5 billion in cash to shareholders.

Moving on to operational metrics. We ended Q1 with more than 56,500 delivery professionals, reflecting total growth of 1.6% compared to Q1 2025. Our total head count at quarter end was more than 62,750 employees. During the quarter, the company reduced head count in Mexico. Additionally, there were targeted reductions in certain geographies as part of our cost optimization program. These actions produced a modest sequential decline in production head count during the quarter.

Utilization was 77% compared to 77.5% in Q1 of last year, and 75.4% in Q4 2025. Q1 2026 utilization was impacted by the ongoing introduction of juniors, who initially operate at lower levels of utilization. The addition of juniors is intended to improve our seniority index over time.

Now let's turn to guidance. Before moving to the specifics of our 2026 and Q2 outlook, I'd like to [indiscernible] and are beginning to modestly delay decisions. This behavior became more apparent early in [indiscernible] opportunities and are looking to close these in Q3 and Q4, driving higher levels of growth in the second half of the year. At the same time, we are now expecting that higher energy prices and global economic uncertainty will have an impact on our revenue growth rate for the year.

As a result, we are lowering our full year revenue growth outlook. We remain committed to improving overall profitability and gross margins. As usual, our guidance assumes that we'll be able to continue to deliver from our Ukraine delivery centers at productivity levels similar to those achieved in 2025.

Moving to our full year outlook. Revenue growth will now be in the range of 4% to 6.5%. Foreign exchange is expected to have a positive impact of approximately 1.5%. Therefore, the organic constant currency growth is now expected to be in the range of 2.5% to 5%. We expect GAAP income from operations to continue to be in the range of 10% to 11% and non-GAAP income from operations will continue to be in the range of 15% to 16%.

We expect our GAAP effective tax rate to be 27%. Our non-GAAP effective tax rate, which excludes the impact of benefits in shortfalls related to stock-based compensation will continue to be 24%. For earnings per share, we expect that GAAP diluted EPS will now be in the range of $8.29 to $8.59 for the full year, and non-GAAP diluted EPS will now be in the range of $12.98 to $13.28 for the full year. We now expect weighted average share count of 52.7 million fully diluted shares outstanding.

Moving on to our Q2 2026 outlook. We expect revenue to be in the range of $1.4 billion to $1.415 billion, producing year-over-year growth of 4% at the midpoint of the range. Our guidance reflects a 1.3% positive foreign exchange impact during the quarter, producing organic constant currency growth of 2.7% at the midpoint of the range. For the second quarter, we expect GAAP income from operations to be in the range of 9% to 10% and non-GAAP income from operations to be in the range of 15% to 16%.

We expect our GAAP effective tax rate to be approximately 27% and our non-GAAP effective tax rate to be approximately 24%. Earnings per share, we expect GAAP diluted EPS to be in the range of $1.79 to $1.87 for the quarter, and non-GAAP diluted EPS to be in the range of $3.10 to $3.18 for the quarter. We expect a weighted average share count of 52.4 million diluted shares outstanding.

Finally, a few key assumptions that support our GAAP to non-GAAP measurements for Q2 and the remainder of the year. Stock-based compensation expense is expected to be approximately $50 million for Q2 and $44 million for each of the remaining quarters. Amortization of intangibles is expected to be approximately $70 million for each of the remaining quarters. The impact of foreign exchange is expected to be an approximate $3 million loss each quarter. Tax effect of non-GAAP adjustments is expected to be around $19 million for Q2 and $14 million for each of the remaining quarters.

We expect $2 million excess tax shortfall and negligible in Q3 and $1 million in Q4. Expenses associated with the 2025 cost optimization program are expected to be $13 million in Q2. And 1 more assumption outside of our GAAP to non-GAAP items. We now expect interest and other income to be $1 million in Q2, $2 million in Q3 and $4 million in Q4. Lastly, my continued thanks to all our EPAMers for their dedication and focus on serving our clients and driving results throughout 2026. Operator, let's open the call for questions.

[Operator Instructions] Our first question comes from Bryan Bergin from TD Cohen.

On the 2026 guide on the organic growth guide revision. So is this a handful of large engagements that are just moving slower or a broader portfolio dynamic, and what gives you the confidence on the second half implied sequential growth, just given where the 2Q number is. Are you assuming geopolitical volatility moderates to hit that revised target? Do you have things in hand? Maybe a little detail on that.

Yes. I guess I'll talk a little bit about the impact that we're seeing as we look at Q2. And I would say it's probably more of a handful of customers where decision-making does seem to be somewhat delayed. And again, we began to see that probably more so in April and May. And then I think Jeff probably could update us on some of the larger deal opportunities in the second half. .

Number one, in our estimate, we are not kind of considering that the geopolitical environment changes significantly. So we are guiding as we see it right now. So we're not assuming anything significantly changing in the current geopolitical setup. At the same time, we have quite a bit of -- as I in the prepared remarks, I highlighted large, unusually large opportunities, which we are targeting. We are currently not really sure yet how fast they're going to ramp, how fast they're going to close. But we are actually went after a piece of market, which was previously was not open to us, but I already became available due to our AI native and AI/Run capabilities, which opened us for large vendor consolidation, large transformation deals, which is for us was outside of our normal norm. So that's what's included in our current guide.

And then my follow-up on the Anthropic relationship. So good to see that come through. Can you talk about how different that model is relative to your heritage delivery approach? I'm trying to understand how difficult of a pivot that may be for you. And do you see that relationship potentially driving an inflection in your AI native revenue growth mix? .

I think Anthropic is going to be a very important relationship for -- we are -- I think we are following a playbook, which we've done before. We are -- we prepared preprepared engineers with our internal development. Once commercial products became available and certification quickly. We pivoted towards uncertified or engineering team. I just checked this morning, we are over 1,400 certified cloud architects as of this moment. So it's ramping up pretty nicely. And we will be going to the market together with Anthropic and bring to the market applied AI solutions. .

I think it will be similar to the go-to-market movements like what we've done previously. But clearly, this is in the AI era. We will be focusing on AI native AI transformation to bring safe AI capabilities to the enterprise. I don't think it's a pivot, it's an expansion, and we are hoping to see acceleration from this partnership.

Our next question comes from Maggie Nolan from William Blair.

Maybe to follow up on that subset of clients that are seeing a little bit of fitness there. Does the full year guidance range consider any broadening of this weakness beyond that subset of clients that are currently affected, and maybe can you help us understand if that's a specific vertical or why or why not you wouldn't see that broadening?

Yes. So I think the reflection in the -- lowering the bottom end of the range, obviously, would sort of -- if we were to end up closer to that portion of the growth range that clearly maybe would reflect that we saw a somewhat broadening of the delayed decision-making. So again, we took the top down because we are sort of have a less rapid entry into the second half. We still feel good, as FB said, about some of the larger opportunities that we're looking to close here in the second half, but the bottom end of the range clearly reflect that there's some broadening of the delayed decision-making.

And talking about impacts. I think clearly, already, we see some of these impacts coming in from travel and consumer sector. It's well understood for the reason. And right now, clearly, our Financial Services or in our Hi-Tech environment, we continue to see strong demand.

Okay. And then, Jason, can you sort of bridge the gap for us between the non-GAAP operating margin that you saw in the quarter, a 14.3% to kind of the full year target range in the kind of 15% to 16% range?

Yes. So I think probably the best way to look at profitability is really to compare kind of year-over-year. And so we always have seasonal factors where Q1 is lower from a profitability standpoint. You've got the reset of the social security clocks. You also generally have that slow January that we talked about. And those things usually sort of result in sort of lower profitability in Q1.

I think if I -- where I feel actually very positive, if I compare Q1 to Q1, we've got improvement in gross margin, which is the first time that we've seen that in quite a long period of time. And it's consistent with the expectations that we said that we would be working on improving profitability throughout the year. What you should see, Maggie is improved gross margin as we go from Q1 to Q2. Some of that is seasonal, but again, we continue to sort of focus on profit improvement while trying to drive top line revenue growth and certainly being successful with the transformation opportunities.

Our next question comes from Jason Kupferberg from Wells Fargo.

Just wanted to see if we can put a finer point on quarter-over-quarter revenue growth expectations for Q3 and Q4. I mean we know what typical seasonal patterns look like, but would be curious what your base case looks like there, just given the moving parts in the macro.

Yes. I'll talk to, I guess, maybe just about what my model looks like, and I'll let FB sort of provide more color as to the client opportunities. I mean, usually, what we would see is stronger sequential growth between Q2 and Q3 driven seasonal factors, the additional available bill days. And then we're also factoring in some subset of the deals that we're working on that those would then begin to ramp.

We clearly have a higher grade in the second half than we have in the first half and again, that's driven by the opportunities that are within our line of sight at this time.

And what brings us this confidence and what we're counting on. We have quite a few deals which we already know is going to start in the Q3. We also had a pipeline of large opportunities, which we're working to close and start to ramp in Q3 and Q4.

So yes, sorry, that's why I wanted to follow up on the. So those large opportunities. There's vendor consolidation deals. It sounds like there is -- I don't know if there's 2 or 3 of them, maybe you can clarify that, but it sounds like that you do have something in your back half guide for those, I guess, maybe on a risk-adjusted basis. If you can just clarify that? And then just say a little bit more about the nature of the work that is comprising those large pipeline opportunities for the second half.

So it's no longer just 3 or 4. We're actually talking about close to 10 opportunities at this point of time. These opportunities are outsized in terms of range, all of them are non-T&M, so different commercial models, combining AI, token in the picture themselves. They are -- it's a variation of business transformation, vendor consolidation and the size is really outside of EPAM's norm, what we typically do.

And then, Jason, clearly, there's a number of opportunities. And from a risk-adjusted standpoint, obviously, we're not assuming that we control all of those. We're just capturing a small subset and then that helps contribute to the growth in the second half of the year.

Our next question comes from Jamie Friedman from Susquehanna.

I'll just ask my 2 together in the interest of time. Jason, I want to get your perspective on the outlook that you had provided longer term at the Analyst Day for -- for the period 2027, 2028. There were assumptions about the improvement in gross margins, which you delivered in the first quarter and then SG&A efficiency, I think, 20 to 30 basis points. So wondering if you could share that -- I think it was 16% objective in the margin?

And then FB, I'd be interested, so in your prepared remarks, you were mentioning that you're seeing opportunities in AI-enabled vendor consolidation. So I was hoping you could elaborate on that. What's that about?

Yes. It's quickly on profitability. So there's a -- we did get price in Q1. We're focused on improving some utilization. I think we've done a nice job with our cost optimization program and kind of getting us into good shape. The cost of our bench is somewhat lower. So all the things that we talked about doing, including improving the seniority index, all of that's in process. And as a result, you see better gross margin, Q1 of 2026 to Q1 of 2025. I also expect you will see better gross margin Q2 2026 to Q2 2025.

So I think that whole journey of improved profitability, we're certainly, I would say, on our way. We're not expecting so much SG&A optimization this year that would come more in those out years. In this year, I think you'll see us do more with sort of go-to-market investments as we talked about during the IA Day. Then, I guess, I will turn it over to FB.

Absolutely. Thanks, Jason. So during IA Day, we kind of talked about and demonstrated our AI capabilities, we talked to you about Level 1, Level 2, Level 3 level of AI capabilities and SDLC maturity. In these larger deals, in vendor consolidations and also in enterprise AI transformation, we're deploying the best of EPAM or AI/Run Transform playbook. And this is a combination of our global capabilities augmented with AI, where we are able to bring a very differentiated and I would call, and a challenging proposition to our clients, which very much challenges the status quo in the vendor landscape. And that's what we are doing right now with our larger clients. .

Our next question comes from David Grossman from Stifel.

So I know this has come up in a couple of the previous questions, just about the visibility on the back half of the year and the guide. But historically, you've done a really good job of framing the low versus the high end and what needs to happen. So perhaps you can take some of the data points that you shared already and maybe put that in the context of the range, what happens at the end, what happens at the midpoint versus the high end?

Yes. So I think probably the first thing is that we're not assuming an improvement in the economic environment. So on the lower end of the range, you probably have maybe some further worsening you also have maybe more of what we referred to earlier, where you do have some clients sort of delaying sort of spending decisions. And so again, that would probably just be incremental kind of uncertainty and incremental kind of delays in decision-making.

On the higher end of the range, it's both sort of solid execution in the traditional book of business, and then probably a somewhat higher share of wins in these larger deals that FB have been talking about. Again, we have throughout the year and even when we guided during our Q4 call, we always expected a stronger growth rate in our second half, in part driven by these deals that we've kind of been focused on in developing over the last sort of quarter or two. Is that sufficient David or anything else? .

Well, I was just curious, can you still hit the midpoint of the range if we see a continuation of the environment where these larger deals continue to get pushed out?

I think the question, David, is where the environment is the current for the mid range, I don't think we need to win too many of those deals. So actually, we're not that much counting on them on the midrange. I think -- but if the environment continues to get worse, that's clearly challenging for the mid range. So the midrange is steady execution, the usual conversion, typical EPAM style deal structures in order to achieve the midrange.

And then if I heard you right, I think you said that North America was where you were seeing the most incremental weakness and you also said that that's where you're focusing your go-to-market investments. So Dakota market investments were similar to some of the prior cycles we've been through. So I don't know, did I get that right? And if I did, could you maybe at least provide some clarity around that dynamic and where those investments are going? .

David, absolutely. I mean already in IA Day, we called out the go-to-market investments, although we were not that specific, but actually highlighted that we are -- we brought in a new Chief Marketing Officer, who started and focusing on performance marketing. We talked to you about how the market changed moving away from a seller to a much more of a buyers market. We didn't highlight it, but we already at that point of time was thinking about the North American market itself. So what we're going to start doing is applying all the learnings and the investments, what we've done and understanding what we've done in the EMEA market and bring it to the North American market. Clearly, it's going to be investment in personnel, investment in process, investment in changes and transformation of our go-to-market motions in North America.

Our next question comes from Jonathan Lee from Guggenheim.

You highlighted large multiyear deals in the pipeline that are larger in scale than what EPAM has historically pursued. What gives you confidence in your ability to close and execute on those agents do you have the sales muscle, governance frameworks and delivery infrastructure to manage those programs and that magnitude? And how should we think about the profile of these deals as it relates to competitive dynamics in deal size and margin profiles relative to what you currently see?

Jonathan, great question. I think Clearly, I think it was also kind of a surprise, how successful our offering has been with our clients. We didn't expect this amount of pipeline be built with these differentiated offerings. I think do we have the sales muscle to close them, to convert them to run them up. That's why we are risk-adjusting the pipeline itself. And we are not fully including them the same way as we include other deals because we actually -- we are not sure that how fast they're going to convert and how fast they're going to ramp. So that's been all honesty, right?

So yes, we have the sales muscle to actually get into these opportunities. I think the offering is differentiated enough and resonates really, really well with our clients because we bring AI native capabilities to these deals, and we are disrupting the status quo.

In terms of scaling these opportunities and to governance in place, we, EPAM has an experience running large programs, but in the past, those programs were built bid by bed, not as one big opportunity. So yes, we were running these opportunities before as an aggregate, but we never really wanted us won't go. So that's the difference.

At the same time, I think what you asked about profitability. Clearly, what we can tell you is that our current AI native business or portfolio, which is over $125 million per quarter is run higher profitability than EPAM average. So that's what we see.

Got it. And just as a follow-up, where do we stand on the large network client? Did revenue stabilize in Q1 as expected? Or are you seeing incremental deterioration there? And what does this imply for the remainder of the year? .

Yes. So the client did stabilize revenue as expected. I think we would see probably some very modest sequential decline over the next quarter or two. But again, something I would still put very much in a stable camp. And then in terms of the rest of the book of business there we are seeing solid growth in their book of business in the Iberian Peninsula. We're also seeing growth throughout South America. And so we feel generally good about the book of business there with the exception of some slowness in Mexico and with that large customer. .

Question comes from Jim Schneider from Goldman Sachs.

I was wondering if you could maybe comment on the extent that the large deals convert into revenue beginning in the back half and heading into 2027, what would be the impact, do you think, on margins? Or would they be coming in at or below sort of your corporate average?

Yes, we're still looking at improved gross margin on a year-over-year basis. There's always seasonal impacts. And so again, Q3 would have generally higher profitability just because it's got higher billl days. And so I think what we'll all have to be looking at is just Q1 to Q2, Q2 to Q3. Sometimes, as you bring in deals, there is a modest kind of impact as you sort of do the transition or what's called KT our knowledge transfer. But I think what you'll find is that with our focus on improving profitability. In India, reducing the cost of the bench, improving utilization and focus on sort of improving fixed fee profitability. I feel comfortable that we can continue to improve profitability. .

Yes. And then maybe as a follow-up. On capital allocation, given what the stock has done, can you give us a kind of a refresher on your latest thoughts on the relative uses of cash between buybacks at this point and incremental M&A new capabilities?

Yes. So we did the accelerated share repurchase. There's kind of a true-up piece of that, that will show up in Q2, and we will also be probably doing incremental repurchases when the market opens again next week. At the same time, I think we are looking ahead to sort of the second half of the year. You might see us begin to again prioritize sort of M&A-related investments. But certainly, with the share price at this level, you continue to see some amount of generally open market purchases of the stock. .

Our next question comes from Bryan Keane from Citi.

FB, can you talk a little bit about contract pricing and how those dynamics have changed over the last year or so, in particular, something like the Anthropic deal the partnership there. How does that -- how are you going to recognize revenues in that contract in that partnership? Is it any different than the model has been over the last few years? .

Bryan, it's a good question. I think it's a moving target. As we highlighted, the economics is -- continues to be a subject which we are exploring. At this point of time, we are in most client relationships or clients are bearing the cost of the tokens. I don't know how it's going to change. We are in discussion with quite a few clients, how would that transition. So Anthropic in this sense, it's not different. We -- our relationship, we will be expecting to develop software using the Anthropic stack, the models, the tools themselves. .

And right now, we are in various cases. We're exploring different commercial models, how we can actually charge the tokens or the client pays for the tokens or what is the commercial model going forward. It's complicated in a sense because it's impacting certain security considerations. And it's -- I think it's an open subject, which we continue to work with our partners, with our clients, and with Anthropic themselves.

In terms of, I think, pricing, I think Jason is actually -- was very pleased to see even rate increases in the first quarter. So we are actually not seeing what we call rate compression at this point of time. We're quite successful for minority -- small minority of our clients to negotiate rate increases. So overall, we are not seeing that type of market pressure.

And then just as a follow-up, Jason, I saw that sequentially, head count was down, and then obviously, revenue per head was up in the first quarter. How do we think about the rest of the year to hit the guidance maybe sequentially? How should we think about the head count cadence and the revenue per head?

Yes. So I think with Q1, clearly, we've talked about the lead customer in ours, and so we did see some reduction in the head count in Mexico. And we continue to make some adjustments in different locations that kind of improve utilization and decrease the cost of our bench. I do think you'll see head count additions throughout the remainder of the year. The revenue per head count is usually not a calculation that I do, and you always have to remember the foreign exchange also plays a role in that, but as FB that be indicated, we did get rate in Q1, and so that was positive and did help with profitability and throughout the remainder of the year, I think you'll see ongoing head count to support business growth. But I think you'll also see some adjustment in sort of contract structures.

And so I think the whole calculation of revenue per head is probably a conversation we'll be having kind of later in the year. But again, we feel good about the growth associated with some of these larger revenue opportunities.

Our next question comes from Arvind Ramnani from Truist.

I just wanted to ask, right, like I mean it looks like you kind of lowered the guidance on sort of existing customer weakness, and I think what you have described as sort of in order to hit your guidance for the full year, there's some, I guess, prospective clients or pipeline, or some of the pipeline needs to convert. It seems like it's kind of like visibility at existing clients wasn't like kind of properly accounted for how are you getting confidence that the prospect of clients will actually convert to revenue on time in order for you to hit your guidance numbers?

Yes. I think maybe the first thing just remember is I don't think any of us thought that what happened in the Middle East was going to happen and it was going to go on for as long as it's gone on for. So we are seeing some impacts from that. And then from a deal standpoint, there are a significant number of opportunities, Arvind, and we're just running on a modest share of those to convert. And so again, that's why we think that it's an appropriate guidance and why we also think that there's also opportunity to get to the higher end of the range.

And then just on the topic of AI, right? I mean, certainly kind of -- you are seeing kind of good traction out there. I mean, is there any sort of like revenue cannibalization or workflow cannibalization or displacement of some of the legacy work as some of the AI work ramps up?

Arvind, mean clearly, there is some impact. clients shifting some of the IT budgets towards AI spending and also the increasingly automating parts of the SDLC, for example, testing itself. And probably, they are diverting investments away from digital platform, e-commerce platform build-outs towards new AI native products or a native platforms construction. So that's the shift what we are seeing right now.

And just last question. Just with these advancements and model capabilities we have seen both across Anthropic and open AI just in the most recent model releases. Are you all proactively going to some of your clients and saying, like, hey, we can use some of these of improvements in sort of AI to kind of lower head count on certain projects? Are you offering that a few clients or not really seeing the dynamic?

So we are going to the clients with very advanced engagement model. This is what I highlighted when you were in the IA Day, we demonstrated dark factory capabilities. And yes, we are proactively talking to our clients, how we can introduce them how we can actually provide them a dark factory based for the autonomous applicable maintenance and support capabilities, how we can automate a large part of the testing flows. So this is all part of the go-to-market movement, which we launched earlier this year.

Our final question today comes from James Faucette from Morgan Stanley.

Thank you very much. Just a couple of quick follow-up questions. On margins, I think you -- Jason, you've talked about like what you're planning to do, but especially on these longer duration projects and if we're starting to factor in tokenization or token costs, excuse me, how do you think about like the levers that you need to control or what kinds of relationships and that kind of thing do you need to develop?

And then I'll just throw in my second question simultaneously. I heard loud and clear, your potential interest in revisiting M&A, especially in the latter part of this year. Can you give us a little bit of view on in terms of what you might be looking at what makes sense and what valuations are doing in the types of acquisitions you could be looking at.

James, I think it's -- this is a great question, and it's so funny that so few people actually ask about economics. What you need to do is you need to control multiple aspects. You need to, first of all, control the model usage, what task, which model you are using what is the frequency of that model. You need to have the right blend of model. So what we are building out is this blending capability, which is which where for each particle task, you need to select the right model, which is able to execute, but cheap enough to deliver the ROI.

At the same time, you also have to recognize that you can buy the same token from the same model from multiple sources. So you need to have the multi-sourcing capability, someone came to a trading desk, which allows you to purchase the same model, same capability from various sources. And this is -- we need to develop this capability to manage these contracts, how to manage our consumption and how to buy the same tokens related to price, availability, cash hit limits. All of these are influencing the pricing at the end. You can achieve differentiation or different in terms of pricing and profit levels, if you correctly control the sourcing and the usage of models themselves. In terms of M&A, I turn over to Jason.

Yes. So I think that we continue to focus on domain capabilities, probably data assets and then some of the geographic opportunities that we talked about in the past, allowing us to expand our position, most likely in Asia Pac. And so kind of similar to what we've talked about in the past, again, I think you're not likely to see anything in the very near future, but maybe later in the year. And then just quickly from a valuation standpoint, I think we continue to see what in our eye is still a little bit of a disconnect between private market expectations and kind of public market valuations, but we continue to be engaged with the potential targets and I guess, kind of stay tuned. .

This concludes the question-and-answer session. I'd now like to turn the call over to Balazs Fejes for closing remarks. .

Thank you for joining us this morning, and we're going to see you guys in 3 months. Thank you. .

Good morning, everyone. Thank you for joining us today. I'm Mike Rowshandel, Head of Investor Relations. Whether you're joining us live here in Boston or dialed in through the webcast, we appreciate you joining us today. We've been planning and preparing for this day for quite some time now. And I can tell you the energy in the backstage is buzzing. Our entire leadership team is here. eager to take you inside our story, what we've built over the past 3 decades and more importantly, the how and why we're positioned to be successful in the AI era. But here's the thing. Saying we're positioned to win is easy, showing you is what today is all about. And that brings me to our theme for the day. AI made real. Through today's presentations, you'll hear real client testimonials, providing a deep sense of the unique value we can continue to deliver each and every day.

Before we begin, I would like to remind that today's presentation contains forward-looking statements, which are subject to risks and uncertainties. Please refer to the safe harbor statement in our presentation materials and SEC filings for a discussion of factors that could cause actual results to differ. We'll also reference certain non-GAAP financial measures. Reconciliations to the most comparable GAAP measures can be found in the appendix of today's presentation.

Now let me walk you through what to expect over the next few hours. First, some context. Our last major update was nearly 4 years ago. And to say a lot has changed would be an understatement. The macro geopolitics, competitive dynamics, AI disruption, the evolution of IT services and EPAM itself. All look very different than back then. And that's why a key objective of today's presentation is to provide important clarity on where we are today and where we're headed over the next few years.

Let me quickly walk you through the agenda. The day is organized into 2 parts. In the first section, we'll provide an important update on our strategy, how we're transforming our go-to-market motions, and then we'll dive into a key AI section where we'll talk about AI native engineering and AI native business transformation. In the second section, we'll focus on our engineering DNA, our AI talent, global delivery engine, and then we'll have an engaging panel discussion with several of our geographic leaders. We'll then dive into our financial imperatives and then finally close with a Q&A session.

Finally, for those that are joined us live here in Boston, we invite you to please stick around after our main presentation. There's a highly interactive hour of client demonstrations and industry-led tours. These client demos and tours should give you a real sense of the AI capabilities we're delivering today.

With that said, let's get kicked off with a quick video.

[Presentation]

And with that, I would like to warmly welcome our Chief Executive Officer and President, Balazs Fejes or better known as FB. Thank you.

Mike, thank you very much. Good morning, good afternoon and good evening, everybody. Thanks for joining us here in Boston. in our 2026 Investor and Analyst Day. My name is Balazs Fejes, but just please call me as Bev. I'm not going to force you to learn how to pronounce Hungarian names. Mike probably spent 2 hours practicing how to pronounce it. You don't have to go through that.

In the next probably 20 minutes I would like to give you a strategic overview of EPAM, the market itself, how we are positioning ourselves to win in the AI native era. But the first most important thing for me is that you have 4 things to take away from here. We are reinventing ourselves as a global leader in the AI transformation services space. We are using leveraging industry's best engineering talent in the industry such as sold or clients Harries, most complex business and technology problems. We are strengthening our internal and client-facing AI capabilities to capitalize on the global air transformation. And we are executing a clear strategy to drive our next phase of profitable growth.

But before we start, I think we need to really address the elephant in the room. We are reading the same headlines, same substack, I think watching the same Instagram, TikTok, YouTube shorts or YouTube videos. And even just today there are some news popping out from everywhere. It tells a story. It tells a story that AI capabilities are growing really, really fast. And this is true, but it's only one side of the story. It only talks about AI capabilities growth, but it's not talking about the adoption rate in our societies and in our enterprise.

The 2 is very different. Whereas AI capabilities are growing really fast, the adoption rate, the way people are changing how work is done is growing much, much slower. There's a gap between those. And this gap is the opportunity for EPAM. EPAM is operating on the AI frontier. We transitioned into the air front here. And today, we're going to show you how we've done that and how we planning to stay there. And how are we going to help our clients to catch up using the learnings, what we gained in the last 3 years. This is the opportunity of our lifetime.

Just a month ago, we are talking most of you and updated your 2025 results, delivering almost $5.46 billion revenue. This is our sixth consecutive quarterly revenue growth on a reported basis, and we are really proud of it. We are delivering across 55 countries with 62,000 EPAMers with 56,000 delivery professionals. And it took us 30 years to get here. We have been around. We've seen a lot. And in 2025, we really delivered this growth across all the industries, across all the different geographies with a wide and very distributed presence. We don't have real concentration on this, which is, we feel, it's very important given the current economics and go the situation.

But let me remind you who we are. EPAM, we are a build and change organization. In the last 30 years, that's what we've done. We honed our engineering heritage to actually build solutions for our clients. We are builders. We are delivering results, relentlessly to our clients, helping them to navigate technology, geopolitical and economic changes with our hybrid teams. That's what we are. And that's I think it's very important because we just entered the age of building. We are seeing that AI enables us to build new solutions, and that's our advantage, and that's our heritage.

We are serving clients and diverse and global client list across 11 industries, 345 of our clients are part of Forbes Global 2000, 64 out of 100 are part of S&P 500 and to the Global 2000 at the same time. And the top 20 clients of ours on average had 13 years of tenure. We have deep relationships. 80-plus of our top 100 clients are executing AI-native projects with us. actually be delivering for them new transformation projects. And at the same time, we're winning new opportunities, winning new deals and expanding our wallet share.

We are positioned to harness the volume of AI internally and also to capitalize on the growth opportunities. And I think that's very important as a key takeaway for us. Already in 2025, our results have benefited from AI. We delivered a very strong AI native and AI foundation momentum, which was built on 5 different foundations or pillars. We have the client closed the adaption gap with our skilled talent capabilities. We help them optimize their delivery using AIS DLC, which we later on launch part of AI RON. We have them modernize their legacy system using AI, where we launched MF lens, which is a modernization toolkit. And we also help our clients adapt physics, AI and robotics. And at the same time, we're helping clients globally to roll out [indiscernible] AI, which is becoming more and more important in our increasingly more complex geopolitical space where we are operating in.

TAM is very, very complex. And I'm sure all of you guys came here to understand how do we see TAM. So myself and nor EPAM, we don't have a crystal ball. So we just don't have that. So we decided to borrow one from Gartner, I think. So I'm going to use Gartner's crystal ball to try to explain to you where the market is growing. Market predicts -- so Gartner predicts that the total market of IT services is going to grow to $1.8 trillion by 2029, which is a CAGR of 5%. We are operating in a subsegment traditionally delivering solutions in business consulting, technology conservative application implementation. This part of the segment is expected to grow at 6.5% CAGR. It's a growing market. and continues to grow. At same time, we took another report also from Gartner, which presented a very different picture. This really talks about the AI market itself. They are predicting that the total market of AI by 2029 will grow to $4.7 trillion. That includes all the GPUs, all the data center investments people need to make in order to make it work and the software and the AI services, too.

The AI services part, which we are really looking is we compromise multiple sectors, and we actually took just one slice of it, what we call AI services plus AI cybersecurity. It's a very fast-growing sector. It's actually growing by double-digit CAGR, strong -- or sometimes strong or very strong to budget CAGR until 2029. Now what's important to take away is that the Gartner's definition, what's AI services and our definition of AI native doesn't really match because they do include some parts, which is what we call [indiscernible]. But still, very important takeaway, it's a fast-growing segment of the market. Now I'm not going to be able to square off what's going to be replaced by AI or how much IT services is going to be impacted by itself because nobody can. And we don't have the data for that. But I'm just using this as an information to demonstrate to you that it's a vast growing market, which we're trying to tackle.

On the other hand, I would like to really focus on why we are positioned ideally to win in this $1.3 trillion opportunity, which we call AI services. EPAM has a client zero mentality. We spent 3 years building or capabilities, holding our capabilities, how to harness the power of AI on ourselves. This gives us credibility. We have an engineering heritage. And in the age of building and actually applying AI, it's a very difficult thing to do, and you need real engineering power or near engineering capabilities to make it really work. We understand how to manage talent, how to create the next-generation talent, which is so important in the next couple of years. We have deep industry expertise because without industry expertise you don't know what to automate. You don't know what to change and how to really take advantage of AI. And the only thing you keep talking about is how to take cost out, and that has a limit.

And we have long-standing client relationships. Clients who trust us and you're going to see demonstrations of that to actually experiment with them how to use and how to roll out AI using our expertise, what we gained in the last 3 years internally. We have an aspiration. Our aspiration is we want to become the go-to partner for enterprises for AI transformation, which is built on 3 strategic pillars. Number one, we want to position and establish EPAM as a leading software engineering services provider. We want to transform ourselves to be an AI-native organization. and we want to launch new AI native offerings, which we're going to talk about.

The key enable us to make this happen is talent, skills, which we talked about. strategic partnership, extending strategic partnerships, which we just very recently entered a partnership with Cursor, which is a very important part of the puzzle. Domain and vertical expertise, and continuous investments into internal products, internal IP. We have been accelerating our internal transformation. We are true to our values of being client zero. So we spent 3 years implementing and changing how to run our business, how to run recruitment, project staffing, talent management, how we can do management reporting and finance and legal using AI. We got some recognition due to that in best use of AI or the best competence and skills development using AI. We have been recognized for this effort.

And using all the knowledge what we gained in the last 3 years, back in autumn last year, we launched a codified go-to-market strategy under the brand name AI Run, which really addresses how to do AI native software engineering and how to do business transformation, which become an AI innovation-based business transformation. This consists of playbooks, blueprint, how to manage talent and also tools platforms behind it. This is based on real credible evidence based on the 3-year experiments, which we're doing on ourselves. And we're going to demonstrate it to you if you are in person in Boston with all the different shows around you and also later on -- later today, we're going to actually show you how we implemented this tooling into our internal systems.

We're creating new AI native business models and services. These are net new services, net new revenue for EPAM. These services are Agentic intelligent operations. AI native experiences. Just a couple of months ago, we launched [indiscernible] Lab in North America, which is the AI native services experiences launch and brand name under this. AI native agent operations and Agentic factories and Agentic security. We are doubling down on our growth drivers, talent, skills and capabilities. Extending on our 30 years of heritage, Sandro and Alexa will be updating you how we are creating the new talent, how we're creating the new road map to actually create the new talent and how we sensing who has the capability to get there. We are verticalizing and actually deepening our industry experience. We are pushed our consultancy teams into our verticalized industries. We're building continue to build out internal platforms and IT assets and of course, strategic partnerships where we need to strengthen and we will double down our footprint.

I think if you were following us in the last years, you heard a lot about our telescope AI. We invested decades in developing an enterprise backbone, digital backbone, which allowed us to manage our organization, manage us through crisis, manage us through different disruption and continue allowing us to deliver with high quality. Now we actually put an Agentic backbone on top of it, which allows us for teams and agents to interact with each other and actually take real-time data to drive better decision-making with a higher quality output.

Our leadership team has changed. We realigned our leadership structure around industries, brought in new members. You have the chance to interact with them throughout today. Some of them is going to come on stage and present. But this is the team who is going to take us to the next level.

So why invest in EPAM? We are the best positioned growth leader for enterprise AI transformation. where AI native and foundational work is expanding, driving significant growth in markets. We are the strongest solution builders in the industry with a proven track record of solving our clients' most complex problems. We have a clear strategy. We are focused on accelerating organic growth while driving margin expansion.

Let's drive into the details. I would like to invite Elaina Shekhter, our Chief Strategy Office and Transformation Officer on stage and to tell us how to transform our go to market. Thank you very much.

Thank you, Bev. Good morning, everyone. I'm Elaina Shekhter. And as of 2 weeks ago, I'm the Chief Strategy and Transformation Officer. Before that, I was the Chief Marketing Officer. But today, we have our brand-new Chief Marketing Officer here, encourage everyone to meet Phil Walsh, who's going to be walking around. Today, I want to talk to you about what we're doing to transform our go-to-market approach. Over the years, EPAM has been particularly interested and really honestly obsessed with building the right kind of supply and addressing our customer needs in an overwhelming demand environment. Over the last few years, we've been investing significantly in our go-to-market approach and the transformation of all of our selling motions.

And so today -- sorry for the clicker. Three key takeaways. We are transforming everything in the company. As BJ shared, our digital platforms, our talent ecosystem, how we think about delivery, everything is being built around an AI-native blueprint. The same is true with our go-to-market approach. We are responding to an AI-centric environment with changing everything that we do in order to more effectively meet our customers where they are. That means that we're building domain and vertical expertise into every motion. Every sales engagement, every capability is driven around deep knowledge of our customers and their domains. And we're adapting the way we go to market through our programs that address customer reach to our engagement and commercial models, and we're doing it in sync with -- or sometimes ahead of emerging industry trends.

EPAM predominantly serves the enterprise. We've been doing so for years. And although we have a significant footprint in ISVs and helping high tech and software companies build, they themselves are large enterprises. And so our primary segment today are large companies. And their service needs and their landscape of service needs has changed significantly with the rise of AI. And it has never been more complex. So between market conditions, that demand addressing new competition, rising customer expectations and all of the AI hype, all the technology trends, which are constantly shifting on a daily basis. and our demand to meet expectations for advancing the transformations with AI and the demand of the enterprises themselves, which are shifting also on a daily basis. demanding more strategy, more growth, better optimization programs and overall better performance and, of course, a better use of capital, we are operating in a more complex enterprise environment than ever before.

And the market depends more flexibility, more capability and more results delivered more relentlessly than ever before. And so to address these changing conditions, we are elevating our entire game and our go-to-market strategy with 3 key motions. Number one, we're shifting and extending our focus from building geographic capability to building full-scale capabilities. Think about a full stack of capabilities that includes domain, vertical and effectively forward deploying those capabilities to our client engagements.

Secondly, we're integrating a consultative approach around the whole of the go-to-market strategy. So no more is a consulting over here, engineering over there. Our goal with our go-to-market transformation is to bridge strategy and execution. -- and in doing so, create a consulting moat in addition to the engineering mode, which my colleagues will be talking about right after this. And we're accelerating our motions, starting with partnerships, but not only. we are changing the way we address the market in total, direct-to-client motions, sales and marketing transformation and of course, the work that we do continuously with our partners.

What this means for us is that we are future-proofing an organization by creating a forward momentum that's bringing capabilities to clients to meet them where they are today. So our evolving focus areas are necessarily about value creation. As BJ mentioned, our hybrid teams, we have a long-standing history of building hybrid engineering teams. Today, our job for our customers is to build high velocity performance teams that include consultants and engineers. We are prioritizing developing critical industry-specific skills. This could be vertical, this could be horizontal. And we're doing that not only around AI, we're doing it with AI. More on this to come.

Finally, we're creating a global delivery value creation network that's optimized, not just across locations and Larry will talk more about that, but also around specific services and skills and capabilities of individual people and high-performing teams. Part of this integration is not only to build consulting into everything that we do, but it's actually to open EPAM up to alternative and additional buyers in order to capture new market share. Earlier this year, we announced the expansion of Empathy Lab into North America, having had a very successful launch last year in Europe. Empathy is our AI native agency. And it offers choice to CMOs who increasingly have their own budgets for technology and yes, also AI to engage with an EPAM that is ready to meet them where they are and driving key transformation programs in a way that is not encumbered by traditional agency dynamics.

We also continue to invest and integrate EPAM Continuum, which is our consulting brand. and the changes there are material. We are upgrading the entire consultancy workflow with and around AI. And so in doing so, we're expanding our addressable market. And we believe not only are we serving our existing clients better, but we're expanding our opportunities to attract and build new client relationships.

EPAM has always been known as a technology solutions expert. This is everything we've been doing for the past 30 years. Across all 3 brands and across all of our front doors, we're adopting and adapting our solutions proposition around AI. By integrating consulting, what we can deliver is end-to-end enterprise-grade scaled solutions in the absolute most complex environment. And for those of you who are staying with us for the afternoon, as you walk around the space, you'll see just how complex complexity is. And so we're driving consulting to be in locked up with technology. And in doing so, we can guide our clients on where and how AI should be used. We're helping to determine not only the right technology platforms, but the right operating models. We're identifying critical constraints and blockers around compliance, governance, security, very material, especially these days. And we're actually starting to run AI native work streams and business models end-to-end. This is part of our engagement model transformation.

And so we believe we are the absolute best partner to scale solutions around AI and build for the future in the most complex enterprise environments. So what about how we sell to reach as many clients as possible with the most relevant propositions. We are transforming our full stack of sales and marketing motions in 2026. Everything that we've been doing for the last several years has been "digital". We were focused exclusively on driving optimization, modernization and AI foundational work streams, and this continues today. In 2026, our value proposition includes the full digitization mix, but it is also driving optimization and Agentic operations. into both the growth agenda and the optimization agenda of our enterprise clients.

How we manage sales is changing from account relationship management focus to really creating a hybrid seller, someone who was a forward deployed relationship manager who was once a consultant, an engineer and a relationship manager. We are adapting our pricing models. Of course, much of our business continues to be very much focused around T&M as much of the foundational work we continue to do is built around high-performance teams, but we're adding output-based, ROI-based and business outcome-based models to our engagement mix successfully. Our sales cycle is changing from a more linear sort of traditional sales cycle to one that is continuous. This is definitely a work in progress, and it will continue to evolve very quickly as we introduce Agentic motions into both the top and the middle and the bottom of the funnel.

Finally, marketing is transforming, and I'm very happy about that. So from sequential brand through funnel activities, we are introducing a performance optimized marketing motion. With Phil on board, we're going to be sharing a lot more with you on what that looks like. So beyond investing, we are transforming our sales motions and our approach to market in order to capture additional market share.

And nowhere is this more evident in the acceleration of our partnering motions. So we've been making announcements over the last few months, and there will be many more to come, and quite quickly, I might add. But today, our ecosystem of partners includes over 160 different partners. These include the platforms, AI Native players, industry partners, universities, research labs and such. This ecosystem is constantly being built out and adjusted to suit our solutions and consulting propositions. With our partners, our motion has changed from a partner-centric channel motion to one that accelerates our propositions and our value to clients. We are elevating our market sensing capabilities and helping our partners do the same through very much tailored dedicated and often IP-based campaigns that we're bringing to market as we speak.

We're also, in some cases, working with our partners to help them build their own platforms and in doing so, driving delivery efficiency and effectiveness for their own build-out operations. These are some of the partners we work with today. As we mentioned, Cursor, there's many more, obviously, and there's a number of very interesting ones that are coming up, particularly around the area of security. Over the last months, we've announced these are just really a subset of the things that we've announced. And so the point here is our relationships with our partners go way beyond credentials. We are pushing the edge of AI innovation, and we're doing that with our partners and with our clients. And so you're seeing a show up in market with AI wins with being named the AI innovation partner for some of the largest CSPs, with announcing agents into multiple marketplaces. And this work continues and will be built on as part of our evolving go-to-market strategy.

And so I want to leave you with 3 ideas. One, we are very serious about transforming our go-to-market approach. We understand that the environment has shifted into an AI-centric environment, and we are there for it. Number two, we believe domain and vertical expertise is a critical success factor, and it is creating not only an engineering mode for us but also a consulting mode and positioning EPAM to win in an incredibly complex market. And finally, we are innovating and amplifying our partnership motions together with over 160 of the world's leading companies. And we're using that to adapt our models, everything that we do from how we deliver, to how we engage with our clients. And of course, we're EPAM. So we're starting with the software development life cycle and the product development cycle. And so it gives me great pleasure to welcome my colleagues, [indiscernible], who is our VP of AI Engineering; and [indiscernible], who's our VP and Head of AI enablement to the stage to tell you more. Thank you.

Good morning, everyone. My name is [indiscernible]. I lead the engineering.

And my name is [indiscernible]. I'm Head of AI enablement.

Adam and I are going to walk you through what is changing in how software gets built and why does it matter for Ripon business? [indiscernible], the creator of Quidco, what is the most advanced IT in the market. In the recent interview, famously said that coding is largely solved with the. If this is true, why do clients still need EPAM. We believe there are 4 reasons for that. First, in the right complexity is growing and the demand for complex engineering is in fed. Second, AI demands and new type of engineering discipline that is difficult to master and the engineering depth is our moat. Third, we are agentipatrum builders, not just users or adopters. We are carifying delivery, and we are scaling a new type of engineering profile to run it. And fourth, what you view for clients today becomes the foundation for autonomous enterprise AI that they will require tomorrow. And every engagement brings its closer.

So now let's talk about the first point, the first dimension, which is enterprise complexity. Our clients operate across 8 simultaneous complexity dimensions, and each one of them getting new requirements with AI. Strategy and economics, all of the client businesses are disrupted. they are discussing what they should be doing and how they should be transforming their primary core products in addition to technology and product transformation they need to run internally, data foundation, your regions are as good as your data. and and the right data is not ready for real. Vendor strategy is a good one. Everybody is talking about we still to select but conversations also shifted to existing SaaS applications that are currently part of everybody's portfolio and now clients are discussing whether they should retain them or they should reveal these capabilities. with AI. And that creates a new set of questions and a new stream of engineering work. Every single dimension is getting new requirements. It is getting more and more complicated, and clients need a lot of help here. And this is even before we talk about the changes that happens inside of software delivery and software engineering itself. Let's talk about it.

When AI generate the code, the hard part becomes how do you create a system that generates it right. So it all starts from design. Somebody needs to encode their specifications or should go inside of them. all them in knowledge, all the business workflows, all of these proprietary knowledge in uncommitted systems that is sitting inside of people's heads, all of that need to go there, then somebody needs to architect the system. It is never a single agent that can do the work. This is always a complex Agentica system that is every woven and ever getting more and more complicated. Then somebody needs to validate their output, somebody need to judge. We see that the same tools produce very different results depending on engineers who are dealing with these tools. And the gap is getting wider. And finally, you need to connect the Agentic systems to ureteric environments. With all of these established legacy ways of working, delivery pipelines, ecosystems, tools, integrations, all of that, and none of that was designed for AI and now we need to deal with that. And that creates a huge complexity inside of software engineering which now is getting an AI engineering discipline that didn't exist 12 months ago to create AI engineering layer that can run the agents that are doing the work. This is exactly what we have done at EPAM.

We qualified the agenetic system, the entire delivery pipeline with agents. I'm not talking about agent augmentation. That was easy part. So this is growing. So what we are doing, they are creating a brand new from the ground up, AI native ways of working that we could fly it in a repeatable pipeline. And that's the blueprint. Now the blueprint is an easy part. The hard part is how you can actually scale it. And the -- in order to run it, you need a new type of engineer to deal with that. Traditional narrow specialized software engineers are actually not good in benefiting from these kind of blueprints. They can get maybe 10%, maybe 15%. But all of these stories about 2x, 3x, they require a very different profile. Somebody who can own engineering tasks end-to-end across all stages of a DLC across multiple technology stacks. And this is where it is becoming very complicated. They need to be fluent in new EI children. They should be using them in very different ways. And then they should be able to judge whether the outputs at every step in the way are what they should be. And this is what we call full stack Agentic engineering profile and scaling this profile is the hard part. Alexa and Sandra later today going to talk in more details about it. So the question is, can anyone do this.

We believe there are 2 things that are required to operate at scale. And most companies cannot assemble both. First, you're going to have strong engineering culture and depth. This is not an upskilling program. This is not a scaled certification exercise for particular skill set. You have to start from the very high point from the very beginning. You have to have that as a part of your DNA already in order to be able to run in this race. And we set these high standards many years ago and now 30 more years later, we are starting from a much higher point than many. And second, you've got to have delivery volume. You have to be able to run this pipeline against real enterprises over and over again, and this is where blueprints are getting battle tested. This is where they are becoming real. This is where you are facing real legacy problems. And this is where they are becoming scalable, and they can bring value to our clients.

So why we think most firms cannot assemble both? Of course, arbitrage firms, their model was optimized for a narrow specialized engineer. low rates, low complexes to work, and there is a required a particular profile to make it a profitable business. and we believe that these firms are exposed. EPAM hasn't been ever really playing a role there. We approach it differently. Strategy firms. They have intellectual depth but they do not have muscle on the ground to make it real to actually deliver on these promises. And product companies, they have engineering culture, they have great products but they're only integrating with the enterprises. They're not working from within inside of this complexity. And EPAM has both. We have the engineering culture and we have the volume and that's the moat. And we believe that AI gets it wider. And this only comes from doing the work. You are as good as your delivery. In AI, the right way to build reveals itself only through doing. No one figured it out from a wide board. All the great founders right now, fits, they are all hands on, they all have a ton of experience. And this is what we have built. And this is why we believe it is hard to replicate. And now Adam is going to walk you through how we are scaling this across our clients.

Thank you, Dima. So what Dima is describing to you is what we call Level 3 maturity. What we have found is that there are multiple levels to this journey. And most people start at level 1. Level 1 is they have access to copilot, cursor, codasist tool. But no one really uses that tool. So if you buy a tool, it doesn't mean that people are going to use it. People need coaching, they need training, they need support. And what they ultimately will find out is that, that tool optimizes one aspect of development, coding. So yes, does it create efficiencies for developers? Sure. But as Dima just said, there is much more to the software development life cycle than just writing code. And that's why you also need agents. And that's what Level 2 is. Level 2 is this combination of codeassit tool with agents to help accelerate your current ways of working. But that's the next challenge. So yes, Level 2 will create the efficiencies that people are expecting with AI, faster cycle time, higher quality, better productivity. But when Dima talks about delivery as code, he's really talking about a whole new way of working, where we get to what's called spec-driven development. But that means that your process has to change. And I have been in IT for 25 years. I know I don't look that old. But when I first started out, it was around moving from waterfall to agile. Companies are still struggling with that today.

So now we're saying, hey, we're going to introduce this new way of working. We have to get over the fear and resistance from people and then once you get to some level of accomplishment, there's yet further improvement. So this is a long journey that people are on to get all the way there. And we do luckily have some really great case studies like PostNL where we are delivering agents. We are getting them to this new world, this new reality. And that is, as Dima said, that moat is the fact that we have so many of these projects right now, and we're learning from ourselves in getting this experience that we can then bring to our clients, and that really sets us apart. As FB mentioned, we've created something called AI Run, and that's our suite of consulting services and education and tools around how to drive this transformation for our clients. We're focused here on engineering [indiscernible], who are going to speak next, they're going to talk about how we're doing this for the business because there's a lot of similarities here.

I'm going to double-click into each one of these for a second. So the first one is Blueprint. So Dima, you talked to a lot of CIOs, how many IT leaders can really articulate the current levels of productivity for the organization?

Well, not very many, definitely not on the second meeting.

So if the Board is saying, "Hey, I want to see 20% productivity boost from AI. That's a problem because they don't know what their productivity is today. So for the last many years, I've been at EPAM for 8 years now, we have something called engineering excellence. It's what makes EPAM so special, our engineering talent, how we really raised the bar in our delivery centers and our projects. And we have a consulting offering that we've been running with our clients where we help them baseline, their teams, their performance, we establish those KPIs and then build improvement plans so that they can be more agile and leverage DevOps and get to continuous delivery. So we're able to take that same methodology, go to an organization, understand how are they working? And then from that figure out, okay, where is the place that AI is going to have the best value for you. instead of just saying, "Hey, let me be haphazard. We can be really targeted in which agents we build, the education and then we can track the progress. And we win projects because we can really articulate, this is how fast you're moving today. This is your current levels of quality. And then here's the benefit of AI.

We have a really great case study with Edward Jones. We're working with them right now. It started a year ago. with a pilot we're able to show with our products and copilot, the efficiency gains we could deliver in a short amount of time. And now we're in the process of scaling it out to the rest of the organization. And we have many of these projects happening right now. Dima showed you this picture, delivery as code. And so I just wanted to go back to it for a little bit, just to articulate a couple of things. In the blue boxes, which maybe are a little tough to see, these represent different agents or maybe it's agents calling agents, there's maybe 10 or so, maybe a little bit more in this picture. If you're an organization, you can't just apply agents blindly to all of your teams. Every team supports a different application. A large enterprise could have thousands of applications that make up their platforms. So what that means is that every team is going to need a different set of agents tuned for them. They have different tools, different technology stacks, different ways of working. And so the scale of this gets pretty big pretty quickly.

And so what we have done is we have built a set of tools for ourselves under the AI Run platform umbrella. We have things like Dial, Code Me, Alita, AgentiQA. which we can bring to a client to accelerate their adoption as well as we can handle how you can take an agent and basically copy and paste it and tune it quickly for the next set of teams and manage that at scale with the observability and governance that's required for a large enterprise. [indiscernible] plug. We have a booth. So later on, if you want to see a demo of the tools, we can definitely show you. The tools are real and they're spectacular.

We built these tools a couple of years ago. It was really important for us to be able to use them to learn. And now we definitely have projects where we don't use our tools, but what it allows us also to do is quickly understand what are those -- the people and process limitations that are preventing wide-scale adoption at a client quickly. but also we can bake this into our own projects. So if the clients going through the transformation that takes many months, maybe years, we can come in with our tools quickly deployed with our full staagentic engineers. and really be able to deliver the value of AI quickly.

And then lastly, before I hand it back over to Dima. When you talk about Level 1 Level 1 and Agile team, people are working in silos. And so when they start to use AI, they can create some efficiencies for their tasks. In the industry, we've had this term called a T-shaped engineer. And a T-shaped engineer means that I have this one skill, maybe I'm a mobile developer, but then I can also maybe do some API development, it may be some back-end work, right? So that's T-shaped. With AI and agents, I can really deliver on this promise because that T-shaped person can be sometimes a unicorn. But with AI, I can give people agents to really help expand what they're able to do. So I could have a front-end developer who now is able to do, like Dima said, full stack engineering. They can work across all levels of the application of the platform and do many different things. And now with AI, they really can run the entire software factory that delivery as a code. And so now what we see in our new teams is this combination of this full agentic engineer with a combination of product and design, and this is how we deliver products in this AI native world. Dima, I think you're going to talk to us about why the -- while this might shrink some of our teams, the demand is actually far bigger.

Thanks, Adam. There now -- I'm also eager to look at the tools again. So Adam just took you under the hood. So now let's talk about the implications to the market. The common assumption is the faster we can go, the few engineers you need and for a lot of work this is true. We definitely see this on the ground. But at the same time, this is actually not the case in many places where we operated our clients. There is a fixed pile of work at the top, maintenance, application support, second-tier applications development, there is only so much work that you can do and this pile of work is due to be shrinking over and over. And all the firms that operate in there, they're all exposed. As I said previously, this has not been the place where EPAM was generally operating.

Where we operate largely is below the waterline. And this is where we see infinite backlog space. Our clients have been sitting on years of worth of [indiscernible] work that previously they were not able to attempt. Products mineralization, technical debt, elimination, new products development, just higher velocity and product to deliver more and more features for their own clients. A lot of this work was put on hold [indiscernible] for the reason it was too complex, too expensive to look at a lot of time to deliver or simply was not possible because of technology limitations. Now AI makes it possible.

[indiscernible] Jones. They had a dormant mainframe modernization program that was in a slow-motion mode. And now with our around platform and the plans, we overcompeted incumbents, and now we are helping them to deliver and now it is active. Baker Hughes, we are a strategic engineering partner for them and helping them to work on a variety of different strategic programs in the range from data products to field level assistance across all the operations. [indiscernible] we came in and we helped them with to accelerate their velocity. We will help them to define the new ways of working. And as we increase our velocity, they wanted to do more of that. They increased their expectations, how many new features they wanted to deliver, and we scaled there our footprint, more speed, more demand.

Firms built on fixed demandware are competing to deliver the same shrinking amount of work for cheaper. Efficiency without growth is raised at the bottom, and EPAM has not been operating there. We live below the waterline. Every time we get faster, clients are attempting to do more. And that's today's picture demand. Now let's talk about what's coming next. Everything that we are building today, the agenticacar systems, the edges orchestration, the enterprise hardening, that's the infrastructure that autonomous agents will require in the future. clients are paying for agenetic delivery today and tomorrow, it becomes the autonomous wear. Moreover, these autonomous agents in the first place, we will be attacking this top of the iceberg that I showed on the previous slide. lower complexity, lower stakes work, where we have not been operating, and this is where we can actually enter there as agents and Agentic platform builders exactly the type of complex engineering work that we've been famous for, and we can enter there as builders, not as incumbents that are protecting the margins.

So let me repeat the 4 key takeaways and the 4 points that we started from. Enterprise complexity is growing. Everywhere adds another, and demand for complex engineering is infinite. Second, AI creates the new engineering discipline that is difficult to master, and engineering depth is our moat. Third, we are agents builders. We are Agentic platforms builders. We are clarifying delivery in new ways to accommodate agents first mentality. And we are scaling a new type of engineering profile to run it. And fourth, the investment that we are making and the work that they actually deliver into day for our clients, for agents. That's the foundation for autonomous enterprise that is coming tomorrow. And with every engagement we are getting closer to it.

So I started with the question. If coding is largely solved, why do clients need EPAM. Coding was never a hard part. Software engineering was. The better I get it right in code, the more what we do matters. Now I want to show you the video, the client testimonial from [indiscernible] Patrick from OneMain Financial. Thank you.

[Presentation]

Good morning, everyone, and thank you once again for joining our Investor Day. My name is Neil Caldero. I'm EPAM Chief DNII Strategies, and I'm on stage with great friend of mine [indiscernible] And together, we lead our enterprise AI transformation agenda on the business side. Today, we want to show you how we help our clients accelerate their journey towards an AI-native enterprise through robust offering portfolio, differentiated delivery playbook and end-to-end capabilities. Our goal is simple. We want to demonstrate not just what AI can really do, but why EPAM is uniquely positioned to win in this era of AI native business transformation. We will walk you through 4 core areas around AI business transformation. The first one, how AI Native transformation is reshaping business innovation and operations and how EPAM accelerate the journey with meaningful impact and growing book of business.

Second, how our unique AI Run transform playbook turn strategy into measurable business outcome. Third, how strategically we expand our service mix to support and lead the next wave of AI adoption to successfully support our clients. And lastly, our clients' biggest AI challenges driving long-term structural growth tailwind for EPAM for both business and engineering altogether. So let's dive in.

Thank you, Neil. We see this space transforming approximately along the same ways that Demand Adam just described. There is maturity levels, there are stages which organizations go through. The most foundational stage is start optimizing current operations, easy place to start, but that requires a very meaningful foundation. Adam and Dima were talking about the foundation and engineering. That is a critical ingredient, must be there. This is not your grandfather's business intelligence capabilities. These are foundational platforms and capabilities that need to be put in place all the way from engineering to data platforms to business capabilities to enable that. Once we solve that aspect of the challenge with our clients, then we can actually start transitioning to building business functions.

Now to make it very clear, this is not about just bottom up. the bottom up is sort of the foundational technology enablement. It is critically important, but that's not the only pathway. The other one is the top down, understanding the business case, understanding what we're actually optimizing in the business will go through some of the examples. Then once we figure out that initial optimization space, well, we can now focus on growing the capabilities, running maybe even semi-autonomously, the capabilities that these organizations have end to end. And then once we capture all of this intelligence from the business process and the capabilities and the data assets and governance that is put in place to run that capability, then we can start identifying this new business opportunities for our clients, working with them together to bring that to the market.

I'll give you 2 examples of work that we have done with our partners, with our clients. Critically important, each one of those started pretty much in the same place, the foundation. cannot skip that. have to enable foundation, have to have the right engineering in place, have to have the right data platforms in place, the governance, the observability, all of these capabilities just to start even within a simple business process optimization. Once you have all of that data, well, all of a sudden, you can actually see how you can start optimizing, how can you build a Agentics around the business process and start optimizing.

In the first case, with the global cosmetic manufacturer, that first business case was demand prediction. We wanted to predict what actually sells in stores. We did that. The only challenge is simple. If you know the demand, but you don't have the supply, you didn't really solve the problem. The business is not really benefiting. So -- well, the obvious projection from there was, let's like figure the supply. The compounding problem because you need to figure out the supply from the manufacturing process or maybe even before that, all the way to when the product hits the store is actually a compound data problem that is much more significant than any one of the individual elements. Just to give you a sense, from a supply chain, economic impact perspective within this organization. A weekly risk reduction, 1% risk reduction in this company from an economic impact perspective or sales versus costs. is about $16 million a week.

In the past, before any of this was implemented humans looking to dashboards, again, that old fathers, grandfathers certain BI system, dashboards and reports and stuff like that, could solve 30%. It's meaningful. $5 million in economic impact, they could have sold it. but there's the long tail. So when we started introducing the capability and sort of integrating all of the data together and working with the supply chain organization to figure out their value stream business process and all of that, we realized that about 50% of what AI actually recommends within the 30% slice still is very much consistent with what the organization actually was doing so far. Excellent result. But it actually recommended the rest and almost closed the entire lease gap of the $16 million a year -- a week, sorry.

This opened another interesting conversation. As Dima and Adam were saying -- Dima was saying about certain SaaS platforms and package capabilities and stuff like that. You see vast majority of organizations out there, manufacturing organization, supply chain organizations, CPG and all of that, they have to rely on packaged supply chain tools because building a custom supply chain implementation across the board is extremely expensive. There is no in the past. There was no ROI for that whatsoever. The largest supply chain organizations may be, but most organizations could not. Now the moment we solve the supply chain from manufacturing to store, all of a sudden, they say, well, we have another tail of that problem. How about from the manufacturing and from the warehouse through the ingredients. They had another package that was solving that, but the 2 were not really connected. So they would manufacture one thing. Demand is something completely different. They optimize for that risk sort of there is a massive problem in between. Come AI.

Now the implementation of that end-to-end supply chain custom built for that organization, all of a sudden is a viable alternative to several complex integrations off-the-shelf tool SaaS platforms, et cetera. So all of a sudden, we're actually capable of solving a significantly more meaningful business problem for the organization while leveraging everything that we have been talking about so far in terms of technology enablement and data enablement and governance et cetera. Another observation that you sort of see on the slide, this field is continuously expanded. You prove one case, not prototype, prove one case in production, organization actually seeing economic impact. All of a sudden, well, we have this other business case, another business case. And then it's expanding pretty much exponential in that case, even within an individual organization. And AI enables that because all of a sudden implementation is cheaper, so you can actually leverage the same budget to do significantly more work.

I would like to speak about another client. You would think that CPG, well, not regulated space, pretty easy. But the reality is risk/reward -- in regulated organizations, the next case is a major Global Pharma. In Global Pharma and the foundation was exactly the same as before, build the foundation, build the data capabilities, build the engineering capabilities, solve a business use case. Once we have done that, this client actually designated as a strategic partner for the entire state of work around AI, they said, okay, we have another major business problem, clinical trials. Clinical trials, 1% of defects in clinical trials, just 1% of defects in that process. caused the organization to $28 million in economic impact because it delays drugs to market, like all of that stuff, most of it is a top line impact. It's not even optimization. It's not really even cost optimization. So now if you are able to solve even into the low double digits in that case, you actually have a very meaningful top line impact on that organization.

Once this organization learn what actually existing setup means, then they are capable of understanding their assets. Now we know what our clients need. We can actually convert that into something that is significantly more meaningful. So you have 2 examples here. One is a multinational for consumer loan and garden products. they're actually leveraging all of the foundation and all of the capabilities that we have built in business optimization said, well, we can go TGC, direct-to-consumer, like we couldn't do that before. We were selling to resellers like all of our life, now we can go direct to consumer. A clear business value that was enabled by AI as well as all of the other work that was done. [indiscernible], which you will actually hear much more details in the panel later on. But they realize -- being a reinsurer they realize that they actually sell data. Again, all that foundation actually paid off and enabled a new line of business for them.

So the reality is that EPAM wins at the first stage. We help optimize because we deeply understand the technology that sort of bottom-up enablement capabilities, the technology, the engineering and the foundation that we can build to our clients with AI native enablement, of course. We win in growing and running the business for our clients because we can layer the rest of the pie from a business transformation perspective. We understand the people transformation, we understand the business. We understand the value streams to understand the flows, now we can actually layer the together and significantly enable these organizations as well. And then we can leverage all of the deep Agentic capabilities. All of our experience over the past 30 years building go-to-market capabilities for our clients and actually enable them to create new set of businesses that they have that are AI native. [indiscernible] please give us the details on [indiscernible].

One more slide, sorry. All of that is actually quite systemic Adam showed this slide before, and we work very closely with the technology organization, obviously, to enable these capabilities. where we have the blueprint for the technology enablement, the prompts, the sequences, the workflows from an engineering perspective, we actually develop the same from a domain and industry expertise, so we come to the customer with like deep understanding of the value stream of what they actually need to solve from a business perspective, enabled by technology out of the box and we are capable to solving that. We understand that none of this is possible with individual contributors. We must build networks of experts to be able to solve these complex problems. And these are networks of experts that include, again, engineering is critically important. But people that understand people change management, transformation, domain, industry, governance and all of the other stuff that needs to be in place to make it work. And then the tools and the platforms that need to be in place to enable that, it's just -- the time to market needs to be accelerated. So we have to come with some accelerators, some harnesses, some productized offerings to be able to make it faster and more effective for our clients.

So now [indiscernible], please take us through some of the details.

Thank you. All right. So now let's talk how we are expanding our strategic capabilities to lead the next wave of air adoption. Successful adoption comes down to 3 kind of like main pillar. Think about it as a 3-legged stool. The first one is the data, which is the fuel and really the foundation for AI. The second one is technology, which is the environment and the infrastructure to really deploy and use it at scale. And the third one is people, culture and process, which is probably the most important pillar here, where you really want to make sure that what you built is adopted and then delivering the business value following the investment.

Across these 3, we are expanding our AI strategic service capabilities to help our clients transform at scale to ensure we stay ahead of the market and help them. Let me walk you through these kind of like 4 areas of expansion. The first one, we are reshaping our consulting model into something entirely new. AI-native verticalized consulting built with and for AI. This isn't just traditional advisory. We use the AI to conduct consulting itself. Instead of slide decks, we deliver prompts, instead of static artifacts, we enable small language models across evolving processes. Instead of isolated recommendations, we codesign simulations with agentic tools, and we really aspire to help business leader run scenario planning with AI agents in days and not weeks or months even.

We deliver consulting also for AI. The practical building blocks that make AI successful in production all the way from operating models, governance, responsible AI, cybersecurity, adoption programs and value trucking. Our consulting proposition is built for one purpose, moving AI from experimentation to production at scale.

The second one is we are building the future of business operations, as FB mentioned. We are experimenting with and plan to disrupt the market through an Agentic-led business operations offering, where we design, build and run high-end processes powered by Agentic AI. This led us expand our share of wallet, evolve our service mix and grow our total addressable market to next-gen managed services. The third one is where technology and domain expertise truly converge. We are building deep industry knowledge with strong AI capabilities and acumen altogether. Through our proximity to clients, we are developing industry-specific data models, co-creating vertical ontologies with strategic partners and assembling prebuilt agentic workflows tailored to how industry run. The payer for our client is simple. Faster AI deployment in their specific context with less risk and greater precision towards the [indiscernible].

The fourth one, we are evolving our accelerators. We have been already expanding Migviser into an Agentic-led migration platform. We're also extending for quite a long time, Dial-AI as an Agentic orchestration platform. Think about it building agents with prompts. You have the ability to deploy a mix from tier models and ensure that AI is really deployed at scale, all the way with governance, security and FinOps from the get-go and from the start. Together, these kind of like 4 capabilities position us to be ready and ahead of the market to deliver real measurable value for our clients.

Let me close with why we believe AI is a long-term structural tailwind for EPAM. Real AI business transformation isn't really just about deploying models or tools. It demands business model reinvention. Think about it as the culture and the mindset shift that enables completely new ways of working, process reimagination, targeting the right workflows and designing AI enhanced experience. Data monetization and modernization, really breaking the silos, capturing new data and building the architecture and the Symantec layer for usable real-time intelligence across the enterprise. And obviously, other critical services and elements across the end-to-end AI innovation life cycle, all the way from AI strategy to MLOps and AIOps.

But think about it. This complex business transformation work stream, also generating significant downstream investment in core technology and engineering demand to enable the foundation to run, deploy and use AI at scale, which altogether, if you think, creating a significant opportunity for EPAM to lead in the market. The business transformation work and the technology work also deeply interconnected. And we see both of them are growing. We are uniquely positioned to deliver strategy and implementation simultaneously to enable the full deployment and full-scale reinforced by our AI native talent and unique playbook. And our end-to-end capabilities is really and truly our competitive advantage. And this is why we believe EPAM will continue to capture market share as AI accelerate globally.

With that, let me conclude and have some kind of like key takeaway to leave you with. The first one is we are driving our clients' native business transformation at scale, a few great examples that Eli show on stage. We are leveraging our unique and proven AI Run transform playbook on the business side to turn AI strategy into measurable business outcome.

We're expanding our service mix to unlock new opportunities while staying ahead of the market to support our clients AI adoption journeys. And our clients' biggest AI challenges create long-term structural growth tailwind and for EPAM within both engineering and consulting strategy simultaneously.

With that, I would like -- my pleasure -- it is my pleasure to introduce our next client testimonial from [indiscernible], Chief Information Officer of [indiscernible].

[Presentation]

That was clearly not [indiscernible]. But there couldn't be an EPAM presentation, you would have some mistakes. the clicker works. So we -- that's typically our typical problem, but now we switched up a bit. But you're going to see [indiscernible] a later stage, probably instead of LivaNova, we're going to play that video.

So we're now going to turn to our question-and-answer session. I'm joined by FB and Elaina here for about the next 20 minutes, call it. Just a quick couple of points. For those in the room, just please raise your hand, wait for the mic to come to you, state your name and firm, and we will get to as many questions as we can. We also, of course, covered the overall strategic overview, our transformation and then our AI native pieces of the business. So we kindly ask to keep you your question is tailored to those sections as we have much more coming up later in the afternoon, including our financial imperatives and multiyear outlook. So with that, we'll go ahead and open it up. We'll take one here in the front, Mr. [indiscernible].

Brian Bergin from TD Cowen. So I appreciate all the color you've given so far. I wanted to ask on the go-to-market transformation. So trying to understand really how material this changes for you. You talked about like a consulting-led approach in the past. So what are you going to be doing differently now? And I think you also mentioned maybe potentially some client-facing personnel changing. Just talk about how you're going to manage execution risk around that.

Let me go back a little bit Brian, good to see you, and thank you for the question. But let me go back a little bit about EPAM. EPAM was historically was very much operating in a seller's market, right? If we created the capabilities because of the resource shortages, people were coming to us and and it was very much us showcasing our capabilities. I think in the last years, we learned that it's much more of a buyer's market, which means that we need to be more proactively marketing our services to them and actually start creating a more targeted go-to-market motion backed by marketing. At the same time, the way how we're managing our client relationships are also changing. And we started to make those changes probably in the last 1 or 2 years. very much focusing and becoming more client-centric and very much highlighting the way how it's solutioning with our clients. also clients right now increasingly more transforming how they're delivering their businesses as Eli and Nir was talking about, and we need to provide help there. Elaina, could you add something to this?

Yes. So thanks, Bryan. Good to see you. For sure, there's a couple of things going on. So as FB said, we have to go get more of the business than we've ever had to before. And we're actually changing that go get motion, not just to sell AI, but changing it with AI. So there's a fair amount of training that's already happened. There's more in terms of sales enablement and sales training to come. And yes, I think that there will be some rotations in the field. I think that's natural and expected and, in fact, welcomed. But one of the biggest changes that we've made this past year is really integrating the industry consulting groups, which were historically for us more of a stand-alone service line into our IBUs into our industry business units. And what that's creating is sort of these high-velocity teams that I spoke about and that you heard about now. Is it a risk? Probably. Is it absolutely critical? Definitely.

Jason Kupferberg from Wells Fargo. I really appreciate all the detail. I wanted to ask about these full stack Agentic engineers interesting new role sounds like. Tell us a little bit about the profile of these individuals? How many of them do you have today, how many of them you think you'll have in 2 or 3 years?

Justin, good to say I think it's a really good question. Clearly, this is something which we are growing rapidly right now. We are very much focused on this space. You will hear probably in one hour or so from now. from Sandra and Alexa, how we're actually creating, how we're finding them in the organization and what training program we are putting through that. Actually, this capability is growing really, really fast because that's the real focus area. What we're trying -- what we're doing is we're identifying them. We are actually putting through them with a rapid pace of understanding it. And we probably, in the last just 3 months, we just doubled the capacity of that capability or that headcount. This is something which is going to be our standard motion going forward. .

And in every discipline, every line of business, we are basically pushing our engineering teams, not just on engineering teams, but even account managers and delivery managers or the sales team at how to adopt and how to use AI. And just 2 weeks ago, we launched a quite aggressive and push programs to making sure that our sales people, account managers are actually using agentic tools to not just deliver their account plans and solutions, but actually understand fully how to deliver these applications. So this is ongoing effort. That's where our investments are going, and we believe this is what's going to differentiate us and going to allow us to really scale in the years to come.

We have one here in the front.

James Faucette from Morgan Stanley. I wanted to ask a little bit, as you change the engagement approach and it sounds like some of the development approach. Is that going to necessitate also a change in the way that things are architected from the beginning? And how does that impact things like sales cycles and project scaling and that kind of thing?

Good to see you, absolutely is changing. And actually, if you will, just a shameless plug, as you are in the audience, go after the session, we have a whole video actually explaining to you how we are using what we call AI factories to in the sales process, how it's actually integrated in our RFP creation, RFP responses, which is really going to change the way we are going to market and actually sells our efforts. But it is changing, not just how we're selling. It's not just the way we are contracting. It is changing how we are architecting the solution, how we're putting together the solution itself. We will be talking about how we call it quality assure or all the proposals and all the estimates and using AI. So this is very much ingrained into our go-to-market motion, the way we're delivering, the way we go to market and actually how we build a solution. and how we're using AI in every possible step where it's possible. It's not just possible where we were able to figure out how to plug it in today. And we're finding new and new ways every day.

Two over here.

It's Bryan Keane at Citi. Can you talk a little bit about going after that fixed demand, some of that work that you guys didn't do traditionally that was more labor arbitrage, how you guys can get into that market through AI and how fast can you disrupt that market coming in at different prices?

I think it's a good question. I think we had early indications that we had success in this space. in the last months and weeks. We met many, many proposals in this area. It's probably early -- too early to call a full success, but we see real promises in this area. You go into again shameless plug. You're going to see some amazing videos and demonstrations behind you around how we -- how we're going after the manual testing space. and how we're going after the intelligent operations space with AI. I was going to be helping that in this area. Also we're going to start seeing capabilities, how we're actually doing BPO automations for some of our clients. And actually, we have public case studies around that where our clients are starting to see real ROI us replacing more traditional call center agents with AI-based solutions. So how fast is going to scale? It's probably early to tell, but we are seeing demand interest from our clients. And because we're coming in with a very fresh point of view, we're coming in with new ways how we're approaching it with a new price point, a new way of delivering it, new way of taking advantage of AI to do knowledge transfer. This creates quite a buzz in our community.

So just to maybe put a fine point on it. For us, it's a transformation pitch. It is not a labor arbitrage optimization pitch. And all of the attenuating things that go with it, including organizational design, platform architecture, et cetera. So it's much more than just a labor arbitrage market capture opportunity.

This is Puneet from JPMorgan. So as you pursue AI native TLC bring AI into SDLC, which changes the way you engage with your customers. Talk to us about change management aspects like from clients' perspective? Like are they ready -- or more importantly, are there employees ready for these changes? And will like all the recent news flow around Entropic and development there in Claude and everything. Has that changed their behavior in any way?

I think, Puneet, great question. I think -- if I want to summarize it, it is a change management process. We're going engage by engagement, project by projects, and we're talking about thousands of engagements, which we are migrating, which we are elevating in terms of maturity. Is our clients, employees ready? No. But it's an opportunity for us. We are giving them education. We are giving them advice how to change the organization, how to introduce new tools, how to actually go through this whole education coaching process. Most organizations just went out as Dima and Adam talked about, went out and bought the tools. And they said here ago, now we expect you to be 15%, 20% more efficient. And then a couple of months later, they found out that it's actually a J curve and their productivity kind of dropped. So they said, okay, why don't we use some online resources. This is where you can read about it, and there are some forums nothing happened. This is the point where we are entering to the picture where we really start advising them and coaching them how to actually mature the engagement model, but they are not ready.

I think all the changes you are referencing, which is Anthropic or open launch of cloud code or codex, this is only for the really mature clients and mature engineering teams. If you just launched in a legacy codes and the brownfield, any of these tools, these tools go go wild and they're actually not going to create any productivity because you need the specs because you need to describe the brownfield itself, the expectations and you need to have the right tooling in place. So it takes a while to adopt. It's a change process, and we see a multiyear adoption for the enterprises.

This is Nate Svensson from Deutsche Bank. I'm going to kind of build on Puneet's question here. I really like the slide with the 3 levels of AI adoption. I thought that was a useful heuristic -- it sounds like most companies are on that first and consist in ad hoc usage stage of adoption. Your differentiation in moat is going from the second to third stage. I guess the question is, if most companies are in Stage 1 today, how do you help them get to Stage 2 to ultimately get to where you have the most competitive differentiation? Why are they going to choose EPAM to go from Stage 1 to Stage 2 versus a different system integrator other sort of competitor? And how do you maintain that client relationship as we continue to progress.

Very good question. I think why are they going to choose PAM because we will go in and show you not just slide decks. So this is the case where we're showing slide decks to you. But in most cases, we are coming with real examples, real blueprints, real proof points, how you're going to get there very practical. How can we actually go in that. It's very hands on experience. our clients are seeing that the leadership team who we have the people in the field are really understand how to make this happen. This is the experience. When they talk to me, they actually kind of see on my my computer, I'm learning a cloud code. And it's a very different discussion when the CEO really starts talking to them about the best way how to use in the enterprise for all the different purposes, a agentic tooling itself. So it brings a level of credibility.

Most organizations actually not even at level most organizations are still level 0. They haven't purchased the tools yet because they have never done the investments. It's just in the last 6 months when people really started to understand that this was really happening. Previously, based on all the different data points. People were kind of skeptical. Now skeptic business is gone, they start investing. But the only thing that they are able to do is go out and make those purchases. That's why probably the revenues of these companies are skyrocketing right now. But the adoption is very, very difficult. So we are going out with the blueprints, with the run books of how to make the transformation with the educational materials, understanding how to actually go through step by step, the change process, understanding how to mature engage by engagement. Because it's not a top-down I would say, big bank. It is happening. You have to do it project by project, going step by step. And as you are maturing these engagements, you can go to the next level. We have examples and we can actually show how you're able to execute that in an organization such as EPAM at 60,000 people scale, and that's very unique.

And that's why they're called foundational services for us.

It's Jamie Friedman from Susquehanna. I was revisiting my notes from Dimitri's talk about the 4 reasons to need enterprise complexity, engineering mode, agent building, autonomous enterprise. If I missed those, I apologize. My question is, if those are the reasons to need EPAM currently. I'm wondering, does it change the relevance of the global delivery footprint? And does it potentially argue for a bigger on-site onshore presence?

That's a great question. I think what we are seeing right now is our clients and enterprises at the same time, they're trying to mature AI mature the engagement model that the maturity of what they're doing. Same time, they are executing in parallel other strategies, such as moving to GCCs in India or other locations. And they're coming to us, how can they upscale their existing so-called legacy GCC with new skills? How can we help them to increase their internal efficiency? Just the other week, I was talking to our clients when making this pitch, they are actually expressing their need that can you engage with EPAM with the EPAM scale globally to tackle their own internal legacy and their own legacy is not on site. Their own legacy is it's a global footprint with different GCCs in different countries, starting from India to Spain to -- in this case, it was Portugal and Slovakia.

That's where engineering is happening today, and you need to meet your clients where their engineers are. So for us, we don't foresee that. And actually, later on, you're going to hear on the panel, how we're seeing all these things play out in each and every different geographies where we are.

Surinder Thind with Jefferies. Following up on earlier question about the client journey and going from Level 1 to 2 to 3. And I think FB, you mentioned that maybe a lot of them are even at Level 0. Can you maybe talk about the propensity of clients to move away from Level 1 in the sense that if the models continue to get better, right? We look at the journey over the last couple of years, would a client not want to continue to try and do more themselves, especially if the models continue to scale at the current pace. And are we in a situation where we have to wait until maybe there's a more maturing of the technology before clients move to Level 2 and 3? Or what gets them across that line? Because it just seems like industry demand remains relatively tepid.

It's a good question. I don't -- okay. So I think the -- and models are maturing very, very rapidly. We all know that the capabilities. Also the price point of the certain level of capability maturity is drop -- continuously dropping. For different business scenarios, business cases, you need different level of maturity. Depending on your price point of engineering, depending on the business case, you would like to use AI for, right? There is different entry points. It might be possible that due to [indiscernible], today for 1 company, this is affordable and/or actually economical to deploy AI today or some decides to wait a little bit later why the, let's say, the models mature or the cost drops because 2 things happening at the same time. Newer models going to come enter at the same level of price points where they are today, old models continue to become cheaper of the token price execution price in finance costs for all those models are dropping.

So some people are start deploying and actually actioning on that as they reach a certain entry point. And some people are waiting for newer models, as you're saying. But maturing, going through in a maturity model it's not really, I would say, optional. In order to get access to the capabilities of the model, you have to go to this maturity. So one way or the other, if you want to tap into the power of the models, you will have to go from 1 to 3. You're not going to get the benefits at Level 1. Actually, probably you're going to as the models continue to evolve, you will be -- continues to be even more disadvantaged by staying on Level 1. I don't know if it makes sense, but that's probably the right answer to this.

Jonathan Lee from [indiscernible]. FB, you mentioned different price points as it relates to the models. But can you expand on EPAM's pricing strategy overall as it relates to how your new go-to-market and your anti approach impacts your pricing strategy going forward, especially as you balance agents versus perhaps higher cost team structures given told scarcity?

Jonathan, thank you. So it's a great question. I think as you saw from our results, we continue to be predominantly in a time and material model. And we actually also communicated to you that we were in Q4, we saw very successful we're successful getting rate increases from our clients, which actually indicates to us that the clients are receiving benefits of the more volume which we deliver to them in the T&M model. But also I have to tell you that most of the times, the tokens are paid by our clients because we are operating in the clients' infrastructure due to security reason you took data confidentiality. And in that infrastructure, the clients are the ones who are deploying the models and they're paying for the tokens. Going forward basis as we are migrating away or transitioning away from timing materials to more advanced capabilities or more advanced contracting models, we will be seeing that it's going to be part of our commercial model. We're going to factor in the price of the tokens into our model itself on top of it or on or maybe on a transparent way. It's a work in progress, how we're going to charge our clients to model the tokens because all the tokens are the price is very volatile.

So it's very difficult to figure out how to price it in at this point of time. But we expect that once we are more in the fixed price or more advanced models, the cost of compute will be included in our price. Last but not least, I think 1 takeaway that or AI native projects and revenues are operating and higher profit levels compared to EPAM average. They're more profitable.

And that wraps the first Q&A session of the day. We're going to take a break and reconvene here at the bottom of the hour, so 10:30 for those that are attended in virtually. For those in the room, please enjoy some refreshments and drinks, and then we'll get back to our seats here. When we come up next Arkadiy Dobkin, our Executive Chairman will kick us off getting into our engineering DNA. Thank you very much.

[Break]

Hello, everybody. Good to see many familiar faces here. So I'm Arkadiy Dobkin, Executive Chairman and Founder of the company. So I've been here for a long time and past COO position to be in September of last year, as you know. So I think being here for a very long time and hearing the previous conversations and Q&A sessions, where we actually try to answer very, very difficult questions and present the picture which complex, not in very simple terms. We kind of engineered our presentation as well. And I probably best in the years have a little bit more holistic and casual conversation today. But there are 3 key messages, which I think, important, and I would like to concentrate on this, that engineering excellence is still very -- sorry engineering excellence is a critical differentiator and in the each, it's even more important to cover through entire implementation cycle. I think history matters. And similarly like in previous ways. I don't think it's going to be a revolution. It's going to be evolution for multiple reasons.

And I think history is important to remember. And I think similarly like in the past, the human talent will be the critical differentiator. Everything else will become eventually equalized and become more commodity, but there actually the people who deliver in the last mile will be critical. So -- with this, I would like to, for a couple of minutes back to the history and explain at least for some new people in the audience that from the very beginning EPAM slightly different than other major players on IT services market. Our first clients were software companies. And for the first 10 years, 100% of our services were focusing on building products for software companies, very, very different business. The second 10 years, we started to work with digital natives, Google's Xpedia's EPIX games of the world and actually helping them to scale. At the same time, you understand that this 20 years of our first years of existence, actually establish very different DNA, very different processes, very different talent selection than majority of the industry.

It's important and it's become important after our IPO when we grew very, very fast when we were able to address the demand of completely different skills. So I'm using the same slide, which you saw already in FB's presentation because the equation, which you're asking and we're asking ourselves, is it still important? Is this engineering still going to be differentiator with all this noise and rumors and credible people taking around us, how code is over and maybe code what about engineering, but maybe engineering [indiscernible] and what the next model will bring and all of this. With this, I would like to add opinion one more expert. And I'm not going to read the slide, but please read it.

Even insured, the author said this program is about to share the fate of the [indiscernible] by the end of this decade for [indiscernible] among the rental program system in a listing software engineers. And it was published in this book. in 1992. It wasn't published by somebody. It was published by Ed Yourdon who was a father of structuring program and critical person in creating object-oriented programming. And he was a visionary and one of the top 10 computer scientists of his generation. Why I'm saying visionary because this book was published in 1992. He stasis was that assuring and new program in methodologies will kill American programs. Think about 1992, the whole offshore in Indian market was $100 million. from about $200 billion global IT. He was brilliant.

But 3 years later, 4 years years later, he published another book called [indiscernible] reduction of the American program because he admitted that he's hugely underestimated and prevarive. Silicon Valley innovation, growth of economy, thanks to Internet and one more point complexity of the enterprise. He hugely underestimated that, and he was wrong in his first book. So this bring us to actually to the EPAM life cycle, the history, the way from foundation to going through the crisis. And we started in 1993, actually, at some level inspiring by his book about offshore. And we run to Internet era. And you know what that is this point, the skills which have to deliver this new type of applications didn't exist. You cannot go to the market and buy each of these Internet including actually created the hype, the program as C++, C like real people don't need any more, [indiscernible] will do it. And then it was disappearing because each time complexity was underestimated.

Then we came to the area of cloud, mobile and data and same stuff. And we, as an engineering firm, we're starting to build our own platforms. It's been mentioned to scope, we will talk a little bit more about it. But we also engineer not only digital platform, we engineer our educational learning platform as well because we cannot find those people we have to find the right candidates and develop them. And that's what we did during this second era better than anybody else. That's why we were growing. This is where was impossible to predict what type of new applications going to happen. Think about it, we're talking about the AI impact on existing type of applications. And that's what underestimating coming from.

Because the main change is going to be in the future, we don't know yet what it is. And now the AI era, and that's what we were covering before me. And the pattern again across all of this was that every productivity were from 4G to [indiscernible] to open source local promised to reduce builders. Demand and in practice, each time the lower cost went, the more market expanded, more opportunities, more cheaper way than new, and this new were growing like a snowball. So that's why if you think about in addition to everything else, what's happening with regular productivity, which we kind of focus in the first part, entrepreneurial drive of people innovation levels of something, which we have no idea about it today, potential economy growth with AI and making everything cheaper in intelligence, and enterprise complexity, which I don't think I need to explain even with the comment before that some companies even didn't buy the tools. the silos of knowledge, so huge incorporations, you're working there

AI not going to bring any benefit and less, it's all uncovered together. So with this in the AI era, it's going to be actually growing demand. I'm pretty sure about it. not theoretically for [indiscernible], we entered the market when traditional software could never afford to serve before. The last mile become very critical build differentiation. Everything else will be equalized. And we're going to address level of complexity. We have no idea about it today. Similar like think each time 10 years back, Sintrom AWS to Amazon bookstore. Can we imagine all of this happening?

So I think the shift of the bottleneck going to be up and up and the last 80 -- 20%, which usually taken 80% of the big engagement because of complexity. They will move even to higher, and the 80% was relatively easy. Yes, it would be much more easier to do. So I think at this situation, the people who deliver in this last mile -- leading this last mile, which would be very, very scalable. It's a key differentiation. And these people who have to work in ubiquity and unknown sink very quickly because AI making everything all very, very fast.

And I think bringing other current authority Boris [indiscernible] with he's like probably you saw his podcast. He was talking about exactly importance of engineers. And this is what Jim was talking about it, this full stack Agentic engineer who can cardinate, people who can orchestrate. And if you think that it's very new thing that it's a mistake. I think that's exactly EPAM was benefiting from this type of people in complexity during the previous decade. This is how we differentiate ourselves in the past.

The point was that the talent we build, sometimes these type of people were not even in enough demand. We were putting them on some coding positions. But we understand with our insight to the systems and to our educational learning process, which we're going to talk in a minute how to identify them, how to develop them and how to scale them historically, for the last decades.

So key takeaways, we're probably really underestimating the scale of a driven market expansion and the complexity of enterprise. The second engineering matters and Anthropic people saying this as well. coding simple engineering becoming much more sophisticated. Think about it like new terms, which come in like almost each couple of months. Prompt prong engineering, okay, this is legacy. Context engineering, intense engineering. I don't know what it will be tomorrow. And right talent. And this was 30 years of our focus. By the way, Dima who presented here. He was graduating from computer science, but he went through our educational 6 months boot camp before he started to work at EPAM. That was happening 20 years ago, and this is what's happening today. Thank you, and I would like to invite Sandra, our [indiscernible] the Head of Engineering Exane actually to bring much more details on what I was sharing with you.

All right. Good morning. My name is [indiscernible]. I'm Head of Engineering Excellence AI.

And I'm Sandra Lachlan, I am EPAM's Chief Learning scientist.

Arkadiy just showed us that we need the right talent. [indiscernible] Adam gave us a glance of a full-stack agenetic engineer, and it was even a question from the audience who are those people. So let's take a look. Full stack agenetic engineer is not just a new role which built from scratch for AI era. It's an evolution. It's built on a foundation of narrow specialist available in the industry. And EPAM narrow specialist, it was already better because of our engineering DNA, culture and excellence. Now we need to expand this foundation with a full-stack development ownership of application layers across all technologies. We need to deepen it with understanding of AI tooling, and also understanding of AI native workflows, capability to orchestrate adjuant fleets across all stages of development.

But how we can even approach this new talent profile, how we can build it -- and we are doing it by breaking it in skillskills, which are becoming less prominent and important skills, which I still need to stay because they still might have. and the skills which are emerging and rising because they're becoming a new must have. How we build those talents. To build those talents, we have our educational program with universal coverage -- and we built this program using our own proprietary recourses. We do not want just to use materials from the market. because we believe that external knowledge needs to be processed and pass through the lenses of EPAM experience, our experience to deliver AI native work. We combine it with a formal education and informal education running global AI conference last year, thousands of people, 45 countries because it's important to build horizontal connection with people between people. So they can exchange knowledge, learn from someone next door. We run master classes together with our partners from Amazon and Microsoft. So it's a very good program, but is it enough?

If that seems common to you, it is. Percent of employees who've gone through courses, who's clicked through what, how many classes do you have? Those metrics are table stakes, worse, there illusions of competence. Training people is not a strategy, and it's certainly not a differentiation. Leading in the AI services market requires going far beyond those basics. Building the AI native talent that you've been hearing about today is actually a 3-pronged challenge. It starts with identifying the skills that are in demand today and critically the ones that will be needed tomorrow, exactly the kind of skills that you heard about this morning from Dima and Adam an Ark.

But development really isn't about training. People can train and learn nothing. And most people learn from informal things like reflection in practice and getting feedback. For development, there are 2 key things to learn about. One is motivation. Can organizations drive their people to learn even when it's hard or not fun. And the second is validating the skills. If you can't use those skills in production, it doesn't matter. But the most critical metric for professional services organization is actually deployments. Can you put the right skills and the right combinations on the right client projects to create value?

This 3-pronged challenge fundamentally shifts the metrics that matter for talent development. Instead of focusing on number of people trained, the companies that grow people and those that invest in them should be thinking about different metrics altogether. How quickly can you sense the right skills? How fast and how thoroughly are people upskilling and demonstrating that they're using those skills in practice. And critically, how quickly are you staffing the right people to the right client projects. In this era, the future will be met had by those people who focus on those metrics. You're not going to be surprised to hear that is who we are.

For years, you have heard about telescope AI. EPAM's proprietary 30-year homegrown in the making system that is focused on people and the backbone of our business. Today, you're learning why we keep talking about it. And that's because telescope was purpose-built to do exactly these 3 things. In a world where organizations know more about the chairs in their buildings than the skills of the people who sit in them, EPAM has built our business to know exactly what we need, who we have and where best to put them. And for a company whose business is people, that knowledge is competitive advantage. Before Alexi shows you the metrics that we track, please know that some of these numbers are operational and proprietary. It's why you're not going to see hard numbers for everything. But most importantly, you can't interpret these numbers without a context, and the industry is just not there yet. They're not tracking the same numbers that we are. We believe that they will get there. We think it is inevitable, and we are welcome to -- we're excited about that the day when they do. But until then, we're going to offer you a glimpse into how we treat talent as a business asset.

So we have 3 functions: sense, develop and deploy. Sensing starts from market and industry. Industry first. Our practice leads carefully process all information coming from the industry on what is going to happen in the next months and years. But we do not just listen. We process a converges information than the skills. Skills, which are retiring, retaining or rising because it drives the development of our learning programs. And the same skills are used to understand demand on the market and predict demand in the market because we know how much new positions our clients need with AI-ready skills. And I should say that this demand is quickly accelerating. But it's not enough just to sense industry in the market. We need to sense our people to understand why -- how we can provide them to our clients.

And this sensing is definitely not only about how many training modules they have completed. This sensing is about the way how they converted this knowledge and the real work experience and build real skill. So we combine evidence from different sources from the complexity of delivery of real work they've done from reviews and assessments, how quickly they learn, endorsements from [indiscernible] peers, and it's all together creates a universal standard applicable or across all our global workforce across all our countries. And I should say that we are sensing that we have enough AI-ready engineers to cover all our client needs.

And now we need to deploy but we don't want to deploy people just based on availability. We want to deploy people based on the verified mastery based on our ability to provide deeper purpose engineers to our client. That's why our telescope AI and proprietary AI-driven matching model uses 25 different attributes to find the right people with the right skill for the right project of our clients. And results are evident. Roughly 80% of positions with AI skills at this moment are staffed within 7 days. And the rest doesn't take much longer. But it's about speed. You can start quickly, but this is the quality and quality is here. Our NPS in comparison from 2024 to 2025, grew on plus 4% and taking into account that our NPS is already above industry average.

The fact that we have hundreds of the university partners is good, but the way that we use them is actually what matters. Instead of relying on faculty to keep pace with AI or hope that they listen to us and change their courses. We learned long ago to engage directly with students like Alexi, like Dema using our own instructors and our own proprietary coursework, the same coursework that we use with our people inside. This means that students in our pipeline are trained on our evolving definition of AI talent, and they're tuned for the local client demand. And because we've invested in them and because we have built relationships, EPAM gets to snap up the best talent before anyone else. This model is not new for AI. It's how we've operated forever and it's not something special that happens in one geography.

We built this model in Eastern Europe and then scaled it to all of our major delivery centers around the world. And that's why, as you will hear from Larry and Vic, we can have a standard, very high for engineering talent anywhere we go in the world. 4 years ago, I stood here and said, young EPAMers can't be hired. They can only be built. That has not changed. but the value to our business has. In a world where AI native juniors aren't available anywhere on the market, EPAM has a global pipeline prepared for local client demand on day 1.

So results are evident. So we have engine and it's running. We are sensing market in an industry, which allows us to predict what's going to happen next and how much people we need. It helps us to build the supply gaps through our learning programs, combining formal and informal education and then verifier skills, be sure through the real deliveries through the production. We are able to deploy our people for purpose, right skills, right people for the right project. We can do it quickly and keeping quality and deploy function goes back to the sense, and that's the way how the feedback loop completes. That's why how the whole engine is working, and we cannot only today create several full-stack agentic engineers, so many of them, we can do it tomorrow and day after tomorrow just because this engine is what drives this success.

The market commonly completes EPAM's success with our historic footprint in Eastern Europe. That has never been correct. Our roots in Eastern Europe set the highest expectations but this talent engine that we've been telling you about all morning is what has scaled those expectations to EPAMers worldwide. In other words, our ability to provide clients with the best engineering talent is and has always been due to what we're showing you today. A platform and business model specifically designed to sense develop and deploy cutting-edge talent. As you have heard through the years, what defines cutting-edge has changed, but the success of our model has not. We have maintained world-class talent in every era and in every area of the world. From this perspective, full stack agentic engineers are not a new challenge for us. They're just the next frontier. Competitors are scrambling right now to recreate telescope AI and our skills-based organization as they should. Meanwhile, we will continue to refine our engine and use it to help our clients get ahead.

As you've heard all morning, AI is changing and expanding, not diminishing the need for expert engineering talent. In fact, AI has only made the need for that foundation stronger. Value follows constraints. And in a world of AI, one of the biggest constraints is human skills. To meet the moment, IT professional services organizations must sense what those skills are, motivate employees to develop them and deploy the right combination of skills to the market. That's it. That's what it takes to lead in the IT services market. And in this, EPAM has a 30-year structural built-in advantage. Thank you.

All right. And I want to welcome to the stage Chief People Officer, Larry Solomon. Thank you.

Hello, everyone. It's great to be here. I'm Larry Solomon, as you just heard, EPAM's Chief People Officer, and I've been in that role for coming up on 10 years now. Now earlier in the session, you heard Adam [indiscernible] comment that he's been in and around the IT industry for 25 years. I've been in and around the IT industry for 40 years approximately. Now I know what you're all thinking, I know what you're all thinking, especially those in the front row. There's no way that, that guy up there has 40 years of work experience under his belt, right? I see a few -- okay. All right. Thank you for that.

But to get more serious, I first want to thank you for coming today. It's much appreciated. I'm going to quickly take you through our global talent and delivery model that has evolved over the past few years. And why that evolution has made us stronger, more resilient and better positioned than we've ever been in the history of the company to support our clients all over the world.

Our delivery model today is not only stable, it's optimized. We've built a model that's more balanced, global and flexible than ever before. And that foundation has been what's led us scale rapidly, move talent where we need it, move talent when we need it and deliver for our clients, no matter what the heck is going on in the world around us. And we've had a lot going on in the world around us, as you all know.

Now I like 3s. So there are three key takeaways that I'd like you all to take away today. First, we've successfully rebalanced our delivery base. The 2022 invasion of Ukraine was a catalyst in unbelievable almost unreal, incredible catalyst that accelerated our move into nearshore and offshore hubs without sacrificing client continuity and the quality of our delivery to our clients. And let me assure you, you can't learn that from the fine educational institutions that we have within a few miles from where we are today. You can only learn that by experiencing it, by living it. And that's what we did.

Second, it wasn't just about moving people. It was about derisking our entire delivery execution model. And we've built a rock-solid culture of resiliency, resiliency first.

Finally, we're now truly distributed around the world, harnessing the lessons that we've learned from crisis. And fortunately or unfortunately, crises have become a core competency of ours. But it's helped us create a global engine that provides better access to top talent. And you've heard about the importance of top talent, and you'll hear about it today afternoon. And this is now a durable competitive advantage for our enterprise.

Now to understand where we are today, you need to look at where we came from, where we started. So back a few years ago, in late 2021, we were already in the process of diversifying. But as many of you that have followed us know, our footprint was still quite heavily concentrated. And at that time, 59% of our delivery professionals, 52,000 strong at that time were based in three countries, and you probably know them: Belarus, Ukraine and Russia. And while this served us well for many, many years, it represents a geographic concentration risk that we knew we absolutely had to address and deal with.

So let's fast forward now. A few months ago, the end of 2025, look at the shift in the circles on the map here, our delivery force has grown to almost 57,000 production professionals. But the distribution of where they are around the world is like night and day. We've reduced our concentration in Ukraine and Belarus by 38%. And at the same time, we aggressively ramped up other parts of the world like India, Latin America, and Western and Central Asia. This is what optimized and balanced looks like. We're no longer dependent on any single geography, on any single region. We're much more regionally balanced and diversified today.

Now I'm extremely proud of how fast our teams pivoted. We have a saying that we use quite often around the place, "Speed kills when you don't have it." And we had it, and we still do today more than ever. We relocated people. We opened up brand-new locations. We expanded our mobility programs, and we built talent pipelines in new markets all at a pace that no other company could match. This speed and agility is absolutely part of the core of what and who EPAM is today.

So today, the model is a real strategic advantage for us. It helps us deploy the right skills to the right clients in the right places at the right times, it improves our cost positioning. It expands our access to top talent and gives us the geographic flexibility that is extremely, extremely difficult to replace. We're poised to capitalize on this more balanced footprint. We've derisked our execution with stronger business continuity. We have better and faster talent access from a much wider pool of specialized and unique skills that our clients are demanding from us every day. And as you'll hear from others, we're integrating AI-enabled optimizations across our company to improve our cost profile and utilization across the regions. So ultimately, the model that we're talking about here supports an important 24/7 or follow the sun delivery cycle, and that creates faster iterations and turns for our clients. So today, we find ourselves even faster, safer and more globally diversified than at any point in the company's history.

Now some of you may recall the concluding comment that I made at these events in prior years, and I'm going to say it again today, so it's okay if you don't recall. I'm going to say it again today because I believe it's more true now than it ever has been. We hold the cards that we've been dealt, and I wouldn't trade in our hand for anything. I wouldn't trade in our hand for anything.

With that, I am excited and delighted to hand over to my good friend, my colleague, and frankly, one of the most talented and smartest leaders that I've had the privilege of working with in my 10 years at EPAM, Victor Dvorkin. Thank you very much.

Thank you, Larry. It will be hard for me to prove it. Good morning, everyone. I am [ at the ] company for 28 years, in the role for 10. And I will try to prove as a scientist that what we've built is actually one of the best delivery engines in the industry and that it will be actually rewarded by [indiscernible]. Let's start.

So first, clearly, enterprises got access to really powerful model right now. There is no doubt. And what it means that the demand for work will increase because they will understand better, they will want better, and they will ask us to do more. We spent the whole morning talking about enterprise complexity, legacy systems, complex platforms, integrations, hallucinations we didn't talk about that and real operating pressure which [ they ] have. This has been our environment for 30 years, large transformations, regulated industries, complex platform engineering and also Google scale, product engineering at speed. This is actually how we want the digital wave in the past. Great models for us, in our opinion, is an opportunity because this is what makes our delivery engine actually unique and that's what will make AI run the enterprise.

I will show you probably one of the most complex slides so bear with me. Larry spoke about our allocation strategy. Our allocation strategy is a serious advantage. I'm showing you an example of a large client. They have a headquarters in U.S., a headquarters in Europe, a local GCC and Latin American subsidiary. Think about the complexity. We have nearly unlimited flexibility how to configure this type of engagements meeting the most strategic, regulatory and pricing needs of our clients. And we -- as Sandra and Alexi said, we sense, develop and deploy our talent. But I will add. We also continuously assess our talent globally and unify our skills globally through globally unified assessments. Every engineer in order to get promoted need to be assessed from an engineer actually to [indiscernible]. We just finished the cycle right now. And this consistency is a key.

I will complicate the slide more. Data practice. As you see, it's global, it's in every location. And this is our major strength as well as cloud, digital and product engineering, SAP, Salesforce and other practices. This horizontal capability is massive with thousands of professionals, leadership, competency centers, partnerships with cloud and platform providers, methods, tooling, training, certifications and operations.

I will complicate the picture more. I will add verticals. By the way, talking about hallucinations. In health care, they produce unsafe output, in financial services, noncompliant responses. In supply chain, the output looks great, but think about the world, it will not work today. And that's why vertical is super important. That's why [ to shape talent ] matters the most for AI adoption. And that's why organically, with all clients together and through acquisitions, we are continuing to develop vertical capability. [indiscernible] spoke about consultants, I will talk about engineers. Think about health care, life science, financial services, media, gaming, more, [indiscernible] talent make system work with AI.

Think about now 3D pictures we just covered, right? It is absolutely unrealistic to run [indiscernible] So many years we developed our digital ecosystem covering talent, skills, knowledge, technology and I will show you [ delivery ]. This is a delivery view of a delivery engine. See, it looks fine. Green. But I actually would say it's a bit too much Green. And that's why we will drill down on a specific account.

What we can see. Through AI power systems, we can now instantly understand what the risk we are doing, what type of analysis we should have and how to remediate the problem. And this also accumulates our reusable delivery knowledge which helps us with estimates and with many other.

The same view through the agent. You can see that agents and teams can [indiscernible] or from other environment or actually through the agentic factory, and this is coming -- [indiscernible] Yes, I got the glasses. So what -- how to explain [ with bot ] that's very easy. If you have a project with [ bot ] will come to you. That's how I would explain it somewhere in the [indiscernible] Yes. But most interesting, [ the bot ] also work on our newly-baked AI factory, which we can demonstrate today. It helps to validate our proposals, it helps to check the estimates and the value if we bring it to our clients.

With that, I will leave you a few things as everybody. We have really advanced capabilities, global scale, consistent standards to shape expertise and [indiscernible] platform, which runs our delivery engine, which runs [indiscernible]. And with that, actually, I have one more thing. To fuel the organization [indiscernible], we prepare a panel with [indiscernible] teams around EPAM. And I would like to welcome Amit Singhal, Head of European Delivery to introduce the panel. Thank you.

Thank you, Vic. By the way, that Vic bot is real, it's calling me every day. It's much nicer him calling than Vic calling me. My name is Amit Singhal, SVP and Head of Delivery for EPAM in Europe. I joined EPAM roughly 10 years back, but who's counting.

So as Vic said, I'm going to host a panel for you, so you can hear from some of our regional leaders. So please join me in welcoming them. How are you all doing?

Great. Very well.

Okay. So sitting at the far end is Enver, my partner in crime in Europe. Maybe we should have set together, but it's okay. Enver heads our business in Europe. By the way, congratulations on getting to the top place in [ white lane survey ] in Europe. You and I both seeing an interesting trend in Europe where business is growing much rapidly than we hope we like it than we had hoped. We are across sectors and industries. I hope that's not an accident and there is a strategy behind it. So keen to hear from you what's going on there.

Next to Enver is Srinivas, Srini as we formally call him. You and I joined roughly at the same time [indiscernible]. Your mission was to build a different kind of India for EPAM in the region and scale it. And it's one of the largest location now. So he must have done something right, Srini. So congratulations, and welcome.

Thank you.

You took a long flight to get to Boston through a narrow air corridor?

I did. That's right.

Martin, new kid on the block. Very new to EPAM leadership team. Martin, you were born in Argentina, you lived in Brazil and Mexico. So you know the region a little bit. And you're enjoying your journey so far with EPAM?

Very much.

Okay. So just much like Srini, Martin joined us to consolidate our investment in the region and create one team, which can be plugged into a global delivery model that Vic talked about. So welcome.

Thank you.

And last but not the least, Stepan. Stepan leads our team in Ukraine and all of us know the war is still ongoing and everything that [ throws ] Stefan and his team and continue to do good work. So on behalf of entire EPAM family and [indiscernible]. Stepan, can I say thank you.

Thank you. Thanks for having me.

Thank you. That's amazing. So thank you all. Let's get into it. There's a lot to talk about, but let's try and focus on a few things. I'm very keen to talk about resilience of EPAM delivery, how Gen AI adoption is going across complex enterprises. How do we balance our global mindset, but equally, Srini, for example, in your case, working locally with GCC.

So Enver, if I could start with you. So you and I know Europe is a melting pot of cultures and languages and it's fragmented. There are complexities. How do you lean on [ big ] EPAM to deliver best-in-class services for them?

Indeed, Europe is a great mix of cultures and languages. The place where global companies, a number of global companies are rooted from. It's also a significant market for a number of localized businesses. So as Vic and Larry said, we as a company, invested heavily into reinforcing our global delivery engine, so we can serve clients from everywhere in the world. At the same time, working for a number of years without [ lines ], shoulder to shoulder we cumulate a significant amount of industry knowledge. So today, I believe our winning combination is in the market, Western European talent for client proximity, senior leadership and regulatory alignment. Eastern European teams or near shore teams for -- in that engineering talent and for business knowledge and offshore teams for technical talent for scale and cost efficient execution. So if you add on top of this mature governance and now AI-powered productivity gains, then you get the [ engine ], which is both resilient and highly efficient.

So the right team supplied in the right proportions at the right time, to the right situation is the winning combination. Martin, if I could come to you next. So it similar to what Enver said, but we know Latin America is not Europe, right? So you know it better than the rest of us. What's your sort of winning combination in the region? Both for your local customers, which you brought with you from [indiscernible] and plus EPAM global customers?

Thank you, Amit. A pleasure to be here. It's been almost a year and a half since [indiscernible] became part of EPAM and I think that due to that, we have a much stronger EPAM in [ either ] America, and I'm glad to see that. And the reason is that because we now have great engineers plus all the AI platforms that EPAM built. Plus now we have a strong leadership team based in the region that knows the regions for one, and we also have a strong installed base of customers that were born in Latin America, they are playing in Latin America.

So as Larry, I like the threes, but I need to tell you four things, four avenues that we are pursuing in Latin America. The first one is the one that EPAM was pursuing since the beginning is how to supplying or how to do nearshore from Latin America to the U.S. and that's something that we continue growing and developing more capabilities. And those employees of those consultants are working with us are also going to be able to serve our local customers in Latin America.

The second avenue is how to bring those new technologies that we are building on a global basis for our installed base in Latin America. And we are very proud now to have, I say, the Navy Seals that will help us to expand our presence in the region. We have the platform.

We surely need more of them.

Yes. But this is something that we -- in the past story of [indiscernible] so I'm very proud now we are -- I think that we're going to be very successful on bringing those things to [ either ] America.

The third avenue is that we also have global customers that we are having operations in Latin America, but we were not able to serve in the past. Now we are working with them. We are helping them to deploy those technologies in Latin America. You know that Brazil, for example, is a very complex country. And we do have an operation there, and we are getting to know them and expand that relation.

And for that -- and last is we also have -- or EPAM has a very installed -- a mature relationship with a lot of the large technological partners. And they were demanding a kind of -- how EPAM was able to go with them to the region. And now we are partnering with all of them. And I think that that's going to be another four avenue that we will explore in order to grow in the region. And I'm very happy to see this combination as a winning one.

Yes. You said something very interesting that if you want to be resilient in the global world, one of the critical item is to have a strong leadership based locally. Great, Stepan. I've got so many things I want to ask you, but time is limited, I can see it there. First of all, like there is hardly a week goes by where I don't come across a customer who's been working with your teams in Ukraine. And all I hear is great words. And I know it's not just sympathy. On the other hand, when I talk to your people, I see motivation. I see a high degree of engagement. What the secret sauce? What's going on in the middle?

Thank you, Amit. I think that's the most common question I get asked. And first of all, all the credits should go to the Ukrainian team. They are awesome, brave, resilient and I'm really proud to be part of it. Now answering your question, I think there are several components that help us to be successful.

First and foremost, I believe that we secured the foundation. So basically, companies [indiscernible] in the day one. They created [ 100 million ] dedicated funds to help our people, their family. And there is an expression you want your employees to take care about your clients, take care after their employees. So that's exactly what we did.

Second, I think we focused on the [indiscernible] and that might be not obvious for people outside Ukraine, but for Ukrainians, the biggest motivation is [ feeling ] yourself useful. So you can put that country in trenches so you can protect country on economical front. And I remember a conversation with the client, like who was kind of reluctant to open work for Ukrainian teams just out of sympathy and well, kind of -- he told me "Stepan, I cannot push your people to work during wartime." and I told him "Well, I appreciate you [indiscernible] but the truth is, is that our people has a tremendous motivation to work because it brings revenue, it increases taxes. It helps to protect like work in place at the industry, et cetera." that purpose gives our people control while kind of everything else is volatile. And he was like, "Well, I didn't think about that from that angle." and that was eye-opening for him to open like work for our teams, and they've been delivering for him ever since.

And last but not least, I believe it's our results [indiscernible] attitude. So you know London Stock Exchange, our huge clients. So they have a massive program of migrating hundreds of applications from on prem to Azure. And by the way, like several previous attempts failed with other vendors. So just recently, we completed the first migration of the application that was done by a small Ukrainian team with a little bit of a sleepless nights, of course, with the usage of AI and it was done on budget on time and [ clients came back was that ] it was the most seamless migration ever in his career.

So at the end of the day, while the environment may be volatile, we prove that our delivery is a constant thing. So we just -- we don't just meet the standard. I hope that we set the new one that could be called resilient partnership.

No, it's absolutely [indiscernible] I mean I see this every time we are having client conversation about Ukraine. And as you said, if you want to help Ukraine, work with us. So great. Thank you, Stepan.

Quick follow-up. One other interesting thing we saw in Ukraine was very early adoption of Gen AI. And in fact, some of the EPAM IP like [indiscernible] was born in Ukraine, which became part of EPAM [indiscernible] platform. Again, what was sort of the driving force behind it?

Well, great question, Amit. So in order to understand like how it happens. You have to understand Ukrainian engineering DNA. And to be honest, we've always been very fast adopters of everything new. So look at our Ministry of Digital Transformation, our mobile app with the government in the mobile, with all the document services, defense tech, nearly cashless society. So for us, like AI is not [indiscernible]. It's a kind of skin in the game. If you don't disrupt ourselves, you're not going to win. We're not going to be successful in front of the clients. And yes, indeed, both tools [indiscernible] which are part of AI [indiscernible] platforms that [indiscernible] was talking about was worked in Ukraine and by Ukrainians, which basically proves that we not just deliver despite all the adversities but we also innovate. And yes, we see a shift in the engineering role from kind of how -- this is core generation to a certain extent, to what and why, which is focusing on complex clients' challenges.

And here is an example from real life. [indiscernible] who is a product manager of the [indiscernible] it's an AI-native agentic platform. She was doing a demo. And during the demo, the app crashed. And instead of just panicking, she just like when to [indiscernible] agent and described the bug and asked agent to fix it, run the test and deploy to production. We went for [indiscernible] coffee break, returned back and boom, it's already fixed and in production.

So like Boris from Anthropic that Claude is coding Claude.

Exactly. That is exactly the level of maturity we bring to our clients. So it's not just about what [indiscernible] generation. It's about automation, the full cycle of [indiscernible] development. So at the end of the day, we believe that AI is a multiplier for human brilliance. And given all the companies we have, and our strong engineering DNA, we believe that we're going to remain steady innovative partner that our clients trust and will continue solving the company's challenges.

It sounds amazing, Stepan. And as you said, if you want to win, you have to disrupt yourself first.

Exactly.

Srini. We should talk about India. Not about the pollution and traffic and the population, but EPAM India. So it became the largest location in EPAM and in a span of what, 10 years or so, roughly?

That's right.

And clients tell us, and we see it ourselves, but client tell us, which is probably a bigger proof point that it's very different when they work with EPAM India versus the competition. What's behind the [indiscernible] story? How did you go about doing it? What's really different?

Yes. Thank you, Amit. So I think the differentiated ourselves in the India market by building a modern engineering company. And it was built on our EPAM global engineering culture and hiring quality talent. We did this over 10 years, and we did this very differently. Today, I have very senior leadership teams in India that manage mature practices in cloud, in data, in data science, and now in AI and Gen AI.

So again, locally strong leadership. [indiscernible].

Yes. And I remember the first global AI workshop was conducted in Hyderabad. This is for a week more than 2.5 years ago. And we have all our senior AI leaders in Hyderabad, and most of them are actually in this room today. And then we were done, one of the [ OKRs ] that we came out was to make EPAM India the first AI native location in EPAM. And that, for us, really started with training our engineers. Today, our AI literacy in EPAM India is 90% plus. More than 70% of our projects leverage AI tooling, either our [ AI run ] or some agentic ID that is provided by our client. In addition to that, the teams in India have also contributed to our AI initiatives. We built the AI ops platform that we leverage on all our managed services engagement.

Which is now part of EPAM, AI run [indiscernible] umbrella.

That's right. We also built an AI reverse engineering tool and agentic [indiscernible] for use on our modernization projects, right? And if you think about it, some of EPAM's largest implementation on [indiscernible] Claude code are being run out of programs in India today.

Yes. Now we see that, we see AI adoption at scale with large enterprise in India. So well done. Thank you, Srini.

Quick follow-up. Again, being the largest location, you play a very big role in [ EPAM diversification ] for U.S. customer, European customers all over the world. But then you have other side of the coin as well, which is GCCs, which are rapidly coming up and building in India. So could you talk a little bit about it? And do you think GCC is a big opportunity for EPAM?

Yes. Good question, Amit. So as you're aware, we today work with 150-plus clients in India, and we work with them in various different delivery models. The traditional outsourcing where the teams are exclusively based in India and [ hybrid ], and we do quite a bit of work today in the hybrid model, where we have teams in India, but we also have teams in one or multiple of the other locations. And like you said, in the local market, we work with those global capability centers or GCCs. Today, we work with somewhere between 50 and 60 GCCs in India. And we've been working with them for more than 10 years. And over those 10 years, we've built strong local relationships and today, I think in most of them, we are their trusted partner. And I think that's happened mostly because of our advanced engineering skills, our AI capabilities, which really complements what the GCCs themselves are looking to build in India.

So the answer to your question is, yes, Amit, I think their rapid growth over the last few years in India is actually an opportunity for us.

So [ premium skills ] in proximity to GCC is what they're looking for and it sounds like we're winning there. No pressure. Okay. So before we wrap up, there is one big question we have to sort of talk about, which is we see an industry is talking a lot about it. There are a lot of large complex enterprise clients that are stuck in this R&D and POC phase and not really able to scale Gen AI into their environment. We have seen some early success with these organizations. So can I ask both you and [indiscernible] Martin to share some examples where you believe that we managed to unlock?

With pleasure. Would you like me to start? Okay. Yes, indeed, clients are quite excited and to a certain extent, under pressure as you rightly said in the multiple POCs in the last couple of years. And now they're really eager to see real implementations with real returns of the investments. So I believe opportunities is big and [indiscernible] very well positioned to capture it.

The key arguments for this are, as you all heard our top-notch technology, excellence, second is industry. which accumulated over the years. And third is our early and very practical investments into AI. All of this helped us perform very concrete industrial end points of view on how AI and modern platforms can transform our client's businesses. And importantly, we did not stay on PowerPoint levels. So we went all the way and implemented industry-specific accelerators and our clients use it nowadays.

Just to give you a couple of examples. First one was [indiscernible] they used produce [ sigma ] report, very well known in the industry. And we helped the industry to ID, validate and deliver sigma [ report ] something that connects all resources, all publications, all data sets and helps end users to talk to the data, to the data [indiscernible] in the national language. So we developed the system using two [indiscernible] and it went live in a very short period of time.

And another important example is going to be [ 1 and 1 ] or how we call it in Germany, [indiscernible], a major German telco. And they wanted to reimagine the way how they interact with the users. So we developed for them, an agentic AI platform that today handles hundreds of thousands of end user calls not only helped to cut operational costs, but it improved the client's [indiscernible]. And again, we used our AI transform platform to develop it. And the first agents went live just within several months.

Sounds like I need to say good luck to our friends who are running traditional BPO industry. Okay. Martin?

I have three examples of Latin America, and this is Latin America. One is there's a large utility company in Brazil that is doing a big migration from a legacy system into SAP on the cloud, and there is a big need to migrate tons of data but at the same time, they are going through an M&A strategy towards acquiring companies in the region. So they were thinking about how to do it. We were competing with some of the local competitors, and they were going from all the traditional approach of migrating data. So we came with [indiscernible] one of the platforms that we have. We've been able to prove them that by using this platform, we're going to be not just able to do it faster in the first time, but also have a repeatable agent that will help later in the future acquisitions. So that's one of the first cases and it's very interesting.

The second one is like we have a large manufacturing company in Latin America, where it's having like -- cameras [indiscernible] the plans.

Not for spying?

Not for spying, but at the end, we transformed those cameras into a living agent that is serving what's going on. So now we are able to track all the [indiscernible] into the [ plant ] and foresee what they are doing and optimize their roads, but also monitoring inventories, and we are helping them with health and safety in terms of seeing if the people are in the right places that are using their helmets and the like. And that was a physical platform that was there without taking the value and [indiscernible] that.

And last but not least, in terms of agentic we also implemented an agentic platform in one of our customers that is in the bakery industry to help them to better serve their suppliers and give them information of where their payments were, if there was something that it was blocking, [indiscernible] expect those payments to happen. And that allows them to reduce like 30% of their physical agents and [indiscernible] the BPO that you were mentioning.

So I think it sounds like based on examples, both of you said, it's a combination of industry depth, good old [indiscernible] engineering but applied in a forward deployed capacity to work with clients closely. That's great. Thank you Martin and [indiscernible] for sharing cool examples. And thank you, Srini and Stepan, for what you do, how you do. [indiscernible] two of you, we have a good part of EPAM, so no pressure again. It sounds like resilience by design. We need more of it. So thank you all, and that's a wrap.

Next, you're going to hear from our CFO, Jason Peterson.

But before Jason comes on the stage, again, let's hear from one of the EPAM clients. They're called LDC, one of the largest global trading commodity -- soft commodity trading company and logistics company. So enjoy the video, and then you'll hear from Jason. Thank you.

[Presentation]

In this final presentation of the day before FD's closing remarks, it's probably going to be no surprise that I'm going to talk about the business from more of a financial perspective. I'm also going to lay out our expectations for the coming 3 years, 2026, 2027 and 2028. I'm going to focus on our accelerating revenue growth. I'm also going to talk about our improving profitability, and then I'm going to talk about our ability to continue to generate strong free cash flows.

First, I want to explain kind of what's in this slide. And so off to the left, clearly, it's 2022 through 2025 are actuals. For 2026, what I'm showing you is just the midpoint of the guided range from our most recent February earnings call.

I think the point that I want to make, and I think Larry did a really good job of kind of reminding us kind of what we've been through over the last 4 to 5 years is that we had to deal with increasing sort of difficulty in our operations in Belarus. We had the invasion of Ukraine. We exited Russia. That was both a delivery location, and it was also a revenue-generating market for the company.

We were able to maintain steady revenues throughout this time period, returning to growth at the end of 2024. further improving our growth rate in 2025, where we recently discussed our organic constant currency growth rate of approximately 5% and more recently discussed our expectations for 2026 with a 3% to 6% organic constant currency growth rate.

If I look over to the profitability side, from a non-GAAP operating income standpoint, we're nothing if not adaptable. Again, what we've been through with having to move our populations, support our employees, make certain that we've maintained our customer commitments, continue to invest significantly in capabilities, particularly all the AI capabilities we've been talking about.

We're able to maintain sort of steady non-GAAP operating income throughout the time period, again, returning to growth in 2024, further accelerating that growth in 2025. And we're talking about solid growth as we move from 2025 to 2026. Up to the far right with the non-GAAP diluted EPS, again, you've had growth throughout the last 3 years.

For 2026, including the share repurchases, we actually returned to double-digit growth in non-GAAP EPS between 2025 and 2026. So I think this is really interesting, and you've seen this kind of throughout the day. And why it's interesting to me is that not only is our expanded geographic footprint, a source of revenue growth for the company, but it's also an opportunity for us to continue to expand profitability.

I think we've talked about the fact that we really have delivery excellence regardless of geography. So we've got AI capabilities globally in all of the regions in which we operate. And so what we'd understand then is that, of course, now instead of just delivering from Belarus, Ukraine and Russia, we now have the opportunity to deliver around the globe. We can meet client expectations for different time zones, different price points and when clients have specific sort of preferences in terms of geography.

Okay. Now on top of that, let's talk about profitability. And so I think what everyone would understand is when the invasion of Ukraine happened, the exit from Russia, we had to move quickly. We had to move into new countries. We had to grow rapidly, okay? The net result was that we were taking care of our employees. We're meeting our client expectations for delivery. At the same time, we were growing and then obviously focused on cost efficiency, but it was a lower priority.

Today, we've been much more focused on cost efficiency in some of the newer geographies and the geographies that scaled quickly. I think I've been saying for the last couple of years that even if you're worried about bill rates in India, we can still maintain high levels of profitability there and that India actually generates higher profitability than the company average.

If you add to that, the fact that we've been focused on the cost efficiency, India continues to improve profitability and the gap between India profitability and EPAM average profitability continues to grow. We've done similar things in Western Central Asia, where we've continued to grow our profitability. LatAm has been interesting because one of the advantages of the NEORIS acquisition is we've learned a lot more about how to operate efficiently in Colombia and more recently in Argentina.

So in all these cases, this gives us a further opportunity to sort of improve our profitability. It's one of the reasons why we're guiding towards profitable revenue growth in 2026 with an expansion in gross margin. So this is effectively just a reiteration of guidance, right? So it's $1.385 billion to $1.4 billion for Q1. For the full year, 4.5% to 7.5%, which digests down the 3% to 6% organic constant currency growth. What you'll note for the non-GAAP income from operations measured as a percent of revenue is that the 13.5% to 14.5% for Q1, okay, at the midpoint is higher than what we generated in Q1 of 2025.

The same thing is true for the full year 2026. The midpoint of the 15% to 16% range, again, higher than what we actually produced in 2025. So we're seeing not only revenue growth but improving profitability. Again, you go to the bottom portion of this page here and you add the addition of the share repurchases, and you've got double-digit growth in non-GAAP diluted EPS, approximately 14% in Q1 and at the midpoint of the range of approximately 11% for the full year.

From a long-term financial algorithm, what you're really looking at is a focus on continuing to grow and to accelerate that growth through success in the market for AI native and AI foundational services. We're looking to continue to expand profitability. Again, that will be with a focus on sort of cost efficiency. And then we've all talked about AI productivity and the opportunity to share in those benefits with clients, give them some cost efficiency, retain some for ourselves, which improves gross margin. We've always had strong operating cash flows, modest capital expenditures, so that produces strong free cash flow.

And then from a capital allocation standpoint, we continue to invest in our business. We've done strategic M&A. And more recently, we've introduced share repurchases, including the $300 million ASR that was announced in March of this year. So from a growth standpoint, I think what I'd first do is take you off to the right side of the page. So we are participating in an immense $1.8 trillion IT services market. Again, we're quoting the Gartner statistics. That market is growing. Underneath or within that market, there's a much higher growth opportunities associated with AI native, AI foundational.

And then we've talked off and on throughout the day about kind of the more greenfield opportunities for EPAM, Agentic BPO, AI-enabled managed services. There'll probably be some contribution from M&A over time. So what we are looking to do is continue to accelerate our revenue growth by participating and more importantly, succeeding in the high-growth markets with the goal of eventually returning to 10% or double-digit organic constant currency revenue growth. From a profitability standpoint, I talked about the fact that we were from an actual standpoint in 2025, 15.2% adjusted IFO.

As you move to 2026, you've got the guided range of 15% to 16%. And then what we're looking to do is continue to improve profitability over the next couple of years, returning to a 16% plus in 2028. And again, what we'd be focused on is both improving gross margins and then in 2027 and 2028, also gaining some additional benefit from SG&A. I think I've talked over the last couple of quarters about our focus right now is to continue to invest in business development and sort of sales-focused marketing. I don't expect us to see a lot of leverage in SG&A in 2026 instead what you'll see gross margin expansion.

Then over time, you'll see a little bit more efficiency benefit from SG&A. At the same time, we're focused on generating between 50 and 70 basis points gross margin improvement after 2026, that would come from the cost efficiencies, that would come from the pyramid or seniority index we've talked about, nothing heroic, just kind of returning back in the direction of what we might have generated historically, utilization improvement and then the AI associated benefits, again, sharing those with our clients. From a free cash flow generation standpoint, we've always had strong free cash flows or generated strong free cash flows over $500 million in 2023, over $500 million in 2024. More recently, we actually generated over $600 million in 2026.

As I look forward, we'd be committed to continue to maintain the 80% to 90% conversion rate that we have historically targeted. As I look at our financials over time, that means we would generate over $1.8 billion plus in free cash flows over the time period 2026 through 2028. So I think most of us are aware of the fact that [ EPAM ] has got a very strong balance sheet.

At the end of 2025, we had $1.3 billion in cash. We have modest debt. We have an untapped credit facility. On top of that, we've got the ability to generate the $1.8 billion in free cash flows that I talked about. As we look over the last couple of years, our historic use of cash, clearly, we invest in our business. I think we've talked about this throughout today, right, in terms of the skill development, the education, the platform technologies, the AI capabilities, the IP and the assets.

And so we're spending hundreds of millions of dollars on that. That keeps us at the cutting edge and gives us the opportunity to continue to grow faster than the rest of the market. So we'll continue to make those investments. We'll continue to do strategic acquisitions. And then over the last couple of years, we also introduced share repurchases. We would continue to do those. So off to the right here, so we'll continue to reinvest in the business. You'll have capital returns in the form of share repurchases and of the $1 billion that was authorized.

Most recently, we still have $450 million left in that. Finally, you'd continue to see some level of M&A, probably more in the tuck-in category in 2026. So if I then just sort of close here on the M&A objectives, we clearly would look to sort of expand our end market capabilities, particularly industry vertical capabilities. And clearly, that augments our AI capabilities. We also might use M&A to help us effectively be an entry point for select geographies. This is the type of idea where you sort of create a beachhead, which then you can grow behind. Then finally, we would use M&A to sort of deepen the scale of certain high-growth capabilities.

I've always thought of our M&A strategy is one that is not necessarily designed to buy revenue, but it's really designed to sort of help shift the company to create an opportunity for the company to address different opportunities and then further our organic constant currency growth rate. Most of the companies we acquired do have our services businesses, so there's strong free cash flows. And then finally, our historic focus has been to make certain that we're able to sort of maintain the 16% plus profitability. Over the last couple of years, we got away from that. In the future, what you'd see is we make certain that we did acquisitions that allowed us to either achieve the 16% or actually sort of facilitated the achievement of the 16% profitability range. So in conclusion, we're focused on ongoing acceleration in revenue growth. We intend to continue to improve profitability, returning to the 16% plus adjusted IFO level by 2028. We're going to continue to generate strong free cash flows, the $1.8 billion plus that I've been talking about.

We'll continue to make disciplined capital allocations, including share repurchases. Again, with that, that's the end of my presentation. We are going to have Q&A after this. But right now, we've got one more customer video. I think it's Bank of Ireland, and thank you very much.

[Presentation]

Okay. A lot of content today. We've got our final Q&A session with several of our leaders. Same rules go as the first session. [Operator Instructions] And then for those online, if you submit a question, we are looking -- we'll field those as well. Let's go with the first question right here, the glasses.

It's David Grossman from Stifel. You did a great job of laying out the structural tailwinds from AI and why EPAM is well positioned. to benefit from those tailwinds. And I think what's notable is historically, at least these massive changes in technology have been accompanied by accelerating growth for the industry. On the other hand, industry growth has been relatively low, call it, the last 18 to 24 months. So in your opinion, what is so different structurally about this cycle? And what needs to happen for growth to not only reaccelerate for the industry, but obviously for EPAM as well?

David, good to see you, and let me try to address that. I think what's really different at this time is the rate of change of these fundamental technologies are so much faster. our clients, ourselves and everybody who is participating in this is just watching the race what we are seeing. And it's somebody in the audience, we discussed it already this morning that some people are just waiting to things get cheaper, right?

They are waiting for -- if you wait 1 more month, maybe the model will get better. Maybe if you wait 1 more month, the model not just gets better, it gets cheaper. And just probably 6 months ago, when we reached the point where the model's results are good enough and they're cheap enough that you actually can launch these transformational programs.

So I think we got so accustomed to that people rush ahead and allocate capital and start making these investments that we underestimate the resistance and the time and the cautiousness people are having with these new AI models because it's no longer just an IT change. Cloud was the internal affairs of the IT department.

This is a business change. This requires business leader committing into a massive change program, how to change the whole business processes and also addressing the technical debt, which they're carrying today because without addressing the foundational element of AI, which we keep talking about it, the cloud migration, the data and data product creation, the legacy modernization, you're not going to get the benefits.

And also, you need to upskill your teams. Everybody is reluctant to get locked into a vendor, locked into an engagement model. And everybody is hoping that they can do this without massive changes to their organization. So this has created kind of, I would say, wait-and-see period. But now what we are feeling that organizations are no longer able to wait longer.

They are just ready to launch into it. And we have these active discussions, which makes us very optimistic that going forward, we're going to see the demand bouncing back. Now when do we see for the whole industry to start doing that? When one player, one client of ours or maybe a client of our competitors, actually, succeed with the transformation. Maybe they don't even do the full-blown transformation of the whole company.

But if you transport just one line of the business and achieve some level of efficiency gains or speed to the market, which we've never seen before, that will force everybody else in that vertical, in that geography to do the same and do transformation in [indiscernible]. So I think this is where we are, and we are in the tipping point.

This is the first time when you start hearing from the frontier players, the Anthropics, the OpenAI is that they actually done the engineering and they're actually now seeing that Version is actually seeing that the first time we really saw real efficiency gains from software engineering using AI, something which really surprising, the first time we actually trusted the AI to do the coding was late last year. I think we just underestimated how much time it will take to get to this stage, and we are there. Now it's going to start happening.

Maybe in the back...

Maggie Nolan with William Blair. Why is vertical expertise more important now? And EPAM has a broad set of verticals that they address. So do you need to narrow that focus? Or are there ones that you're going to start with first to maximize success?

Megan, good to see you. And I think it's a good question. Why now? In the digital transformation space, horizontal skill sets were much more important. People were actually applying horizontal capabilities into a wide variety of industry industries. During the AI transformation, on the other hand, they are -- they have to solve business problems.

They have to now tackle the business challenges. That requires real industrial knowledge. That requires you to discover how to automate that piece of functionality. That requires you to really understand deeply what to do. You can walk around and you will see how we are tackling it in energy, how we're doing it in health care and life science. But in order to do that, you really need to understand what you're doing because as Rick mentioned that the models will hallucinate. If you're not grounding it into vertical expertise, what you're going to produce is not going to be safe.

If you look at LivaNova case study, which is an AI engineering case study, the fact that they have got their software FDA approved -- and by the way, we use a ton of agentic solutions. It underlines what you need to bring to the table in order to make it safe order to make it really productive in this environment. Vick, Elena, do you want to add something to it?

Just I think the cycle change that we see is broadly a move from digitizing businesses, which is what we've been doing for the past 10 years with cloud and modernization to transforming them. And I know we've been using digital transformation kind of as an industry term. I think we're really on the forefront of actual business transformation. So it's not just digitizing or creating data platforms.

It's actually reimagining new business models with an AI-centric point of view. A, that's hard, technically hard, but it's even more difficult from an industry point of view because particularly in regulated industries, you don't just get to try it and see if it sticks.

Maybe one more thing. We have -- I -- we have actually -- we are not starting from scratch. Like from 2014 or 2015, we are building health care and life science at scale of the whole organization end to end. And you will see Greg today, she will see it and show it. And it's engineering, it's consulting, it's advisory strategy and all the levels. So it's a good question about focusing, but we are doing it, and so it's improvement.

It's not necessarily we need to be locked in somewhere. The same happening with energy [indiscernible] from large workloads there. And so time after time, gaming, so you see it with us actually over [indiscernible]

Surinder Finn with Jefferies.

As you think about the build part of the equation and you start to build bigger, more complex platforms and all the orchestration that's going to be on top of that in terms of the agents, who at the end of the day, owns the IP? And do you have the ability to maybe manage or run those platforms and monetize the agents or the capabilities? Or does EPAM still remain within the build parts and then you just kind of let your clients run the platforms at that point. And then you -- I don't want to say you walk away, but then you work on the next project.

Thank you much. I think it's hard to see where this leads. I think we're already in the position that the build versus buy equation is flipping. We are starting to build more and the clients are choosing to build more instead of buying off-the-shelf packages or SaaS solutions or we are actually rebuilding some of these SaaS solutions for the clients to take it in-house. In the current wave, what we're seeing is that people want to own their own IP, especially when you are talking about agents.

Remember, this is a workforce transformation. You want to own your own workforce. And even if your workforce is no longer humans, they could be agents. But you, as an organization, you have to risk mitigate. You are dependent on your workforce. So we are seeing clients really want to own the agents themselves. They want to have flexibility. This is the next level of risk management. You cannot be locked into a vendor like EPA or even to a model or even to hyperscalers because now your whole business starts dependent on that workforce. I think we have to start seeing this transformation itself in a very different eye.

We have to see it as a workforce or actually whole business transformation and less on IT transformation. And once you start seeing it from that angle, and I had these discussions just the other week with an insurer, they are seeing this from a risk management point of view, who owns the agent itself because they are going to be so much because in the end in the end of the transformation, they're letting go their original workforce. And now they are relying on that new agent workforce. -- in that equation, your business dependency is switching, and they want to own that dependency.

So there's not just the IP over the build versus buy, the critical sort of rights issue is to the data. And it actually is probably one of the reasons why the frontier companies will likely not end up owning the full end-to-end because there is a critical mission type of not just rules and logic, but actually the ownership over their own data. And yes, we can maybe operate some of the platforms that we design and build, but it would be a rare thing where we would be the owners and controllers of the underlying enterprise data set.

Fani Kanamori from HSBC. As you said, the technology is evolving very rapidly. So how do you ensure that your employees are upskilled in such a fast-changing technology? And how do you price in this technology as AI native services likely requires a long contract period? So how do you price in these kind of changes?

That's a very interesting question. I think we already saw in this AI transformation space, probably 2 or 3 technology shifts by this point, right? I do remember when Andrea Horowitz very proudly launched the next-generation AI architecture, which is probably 6 or 8 months later was out of date. I don't know if you remember the REG architectures and all the different vector databases, which everybody was crazy about probably 18 months ago, 12 months ago.

And today, nobody talks about it anymore because the context window grows so much. I think staying on the frontier is requires you to continuously do R&D, continuously have people who are on the frontier and actually on the edge of the model. So we have team members and evaluating, building new types of capabilities in-house. And from that, designing new types of educational programs, educational programs, which Sandra and Alex was talking about, how we're pushing it out. And I think Vik was also indicating that we codified the environment which we are operating. So in reality, we are running the internal systems with agents, with MCP connections to the internal applications. So you can actually run operations as a code in the organization. So this is a very different shift. But how are you educating them continuously, how you are actually making them work continuously we running program. Maybe, Larry or Vic, you want to talk about this?

Yes. Just the one thing I was going to add is, to some degree, a lot of this starts from the beginning, from the selection, and we have very, very rigorous technical requirements and expertise that comes from EPAM that starts even before the individual joins the company. So we try to only include in that pipeline of candidates that we select those that we believe have the strongest technical jobs.

And just to continue on this, this is a very important comment because one of the key differentiators of the AI engineers is judgment. So we actually continuous, and this is what A started to say. We were selecting people with judgment all the time, maybe subconsciously, maybe consciously, but now we understand exactly how to select them, how to separate those who have it, those who do not have it. [indiscernible] had a great message on talent density. Those are important building blocks. Now about the speed and desire and everything. It's all about also top down by example. If B is coding, I'm coding, we can demonstrate it, we can show it.

And the next managers will be coding with code, with something else, and this will stimulate newer technologies. They also have mandatory requirements for education. So if you are not educating, it's a bit of a problem.

Now going back to the pricing, which is I think was your underlining question, thing where you're sitting and what your role is. I think we are clearly for this type of skills, we are able to charge higher rates, which actually we talked about it before that our AI native portfolio is -- drives higher margin. And -- but I think it's a continuous moving target because some of these skill sets becoming commodity and as technology rapidly changes.

Let's go here and we'll go there.

It's Bryan Keane at Citi. Maybe for Larry and Victor. How do you imagine the delivery model in terms of people? Do you need more or less as this evolves over the next 3 years? And then just one for Jason. accelerating revenue growth, given the industry dynamics right now, the question obviously is on visibility.

What kind of comfort can you give us in visibility, either contract bookings or when you look out 2 years, what percentage do you see? And how do you get to that number of accelerating revenue growth?

Yes, I can start by saying on the more or less, I think the answer is yes. It's both. I think in -- not only from a geographic perspective, but from a skill set perspective, more of some of these, less of some of those. And if you go back to recalling some of the things that Sandra was talking about, the level of data and the signals and the metrics that we track in order to figure out as best we can where we need those people, what skills helps us get a little bit ahead of that curve.

I think the other thing that I would say is we work really hard to put a plan in place every year. And my view is it's only valid for 1 day, January 1, because on January 2, something has already changed, especially in the market that we're in today. And the companies that are going to win are the ones that can figure that out and pivot the fastest.

Yes. And so for the accelerating revenue, so first, I'd just start with this year 2026. So with the guide of 3% to 6% organic constant currency, our focus is on making certain we can at least hit the midpoint of the range. And clearly, we're all driving to achieve something to the higher end of that range. There's already kind of line of sight to larger opportunities that if we can close and we're trying to close, I think sort of drives us above that midpoint of the range. As I look further ahead, it's the ongoing success with clients. It's all the things we've talked about that clients can't do this themselves.

They're increasing dependency on partners like EPAM. But hopefully, what we've convinced you of today that this isn't easy and EPAM is extremely well positioned to participate in these high-growth market opportunities. And if you can be successful in a market that's growing rapidly, that drives higher revenue growth. And that's kind of how I would think about it over the next couple of years.

We have time for one more question.

Puneet from JPMorgan. It was interesting to see like all those like the regional heads coming here like on the same table in the panel. So talk to us like how does EPAM operate across different regions? Is it like -- because like the individual regions might have different cultures like the policy. So like is it the same culture, same EPAM across everywhere, same type of people like in terms of profile, type of people you hire across all regions? Or are there differences based on that region's policies or culture?

So let me try to start with it. V is running a global delivery platform. basically, he runs the factory itself, right? It's an engine. In this engine, we are enforcing certain level of uniformity, right? What Vik highlighted is the assessment. And basically, that's our requirements, what -- how you're going to get promoted. That's the way you are actually being assessed -- that's the way you are actually reaching the next level.

Is it the same culture? No, because we are coming from different parts of the world. But there are unifying elements. There are volumes which we are sharing. There are ways how we're communicating. And we have to collaborate. We have to work together. We are working together to deliver to one client. And throughout this delivery, we're actually kind of syncing up -- we have the same volumes, what we're pushing out. We are being assessing people in the same way. We're hiring for the same goals and for same profiles with the same criteria.

We're running the same process globally, how we run compensation, how we run assessments, how we're going to provide feedbacks and performance management. It creates one level of sync. And overall, we're hiring engineers. And engineers kind of understand each other and kind of synch it in a weird way, right, in a geeky way. But I think that's who we are.

If I could just add...

Absolutely.

Sorry, go ahead. I Think a short way to look at it is globally consistent, locally relevant. And at the end of the day, it's what's best for the client, Client-centric decisions that are locally relevant with the global consistency in processes, culture, core values, but locally relevant is extremely important.

Excellent. Thank you. That wraps our Q&A session. I'm going to hand it back over to Abi for closing.

If you figure out where the clicker left the building, who has the clicker? All right. I hope by this point, with the team, we made clear our positioning and why we have the right to win in the AI native era. And I really would like to thank the team itself to make it such a great presentation and actually present this message. Our people have navigated technology, social and geopolitical challenges and changes. We have emerged stronger out of it. We learned a lot. And I think we are the most resilient organization out there, not just in terms of -- against geopolitics, but any type of technology and social change. Why invest in EPAM?

We will be the winners in AI era. We are best positioned to be a leader for enterprise AI transformation. We have the strongest engineering talent or engineering DNA in the industry with a track record of. Okay, with a track record of solving our clients' most complex [indiscernible] problems. We are delivering already AI foundational and AI native work, and it's expanding and it's growing significantly. We have a clear strategy focused on accelerating and driving profitable growth with margin expansion.

Our 2028 goals are accelerated revenue growth, 16% plus non-GAAP operating income margin and delivering $1.8 billion cumulative free cash flow throughout 2028. Thank you very much. Okay, it doesn't work. As I said to you, something has to break. Thank you very much for coming. And for the audience online, we would like to thank you for attending and see you next time. Thank you.

Good day, everyone. My name is Kahelani, and I will be your conference operator today. At this time, I would like to welcome you to the EPAMs Fourth Quarter and Full Year 2025 Earnings Release Conference Call. [Operator Instructions]. At this time, I would like to turn the call over to Mike Rowshandel, Head of Investor Relations.

Good morning, everyone and thank you for joining us today on our fourth quarter and full year 2025 earnings call. As the operator just mentioned, I'm Mike Rowshandel, Head of Investor Relations. We hope you've had an opportunity to review our earnings release we issued earlier today. If you have not, copies are available on epam.com in the Investors section.

With me on today's call are Balazs Fejes, CEO and President; and Jason Peterson, Chief Financial Officer. I would like to remind those listening that some of the comments made on today's call may contain forward-looking statements. These statements are subject to risks and uncertainties as described in the company's earnings release and SEC filings. Additionally, all references to reported results that are non-GAAP measures have been reconciled to the comparable GAAP measures and are available in our quarterly earnings materials located in the Investors section of our website. With that said, I will now turn the call over to FB.

Thank you, Mike, and good morning, everyone. It's a pleasure to be here with you all, and I look forward to seeing many of you again in just a few weeks at our Investor Day in Boston. Today, we are pleased to share another quarter of strong results as we close out a very successful 2025 and continue to execute our long-term growth strategy, further positioning ourselves to win in the AI native area. We are confident of our unique differentiation and look forward to building on the momentum we created throughout 2025.

At the start of last year, we noted that for us it was going to be a year of transition. In fact, today marks my second earnings call and my very first year-end report, underscoring the fast pace at which we continue to operate and adapt to conditions both extraordinary and operational here at EPAM. As we look ahead to 2026, we see a year of AI momentum marked by our clients' ongoing shift in spending towards AI investments and strategic deployments.

Importantly, we expect to build on our growing momentum in AI native services, supported by our AI foundational services that enable clients to scale AI across their enterprises. These offerings are becoming a more substantial piece of our total services mix, illustrating our ability to capture higher volume and more strategic opportunities as AI investments accelerate across the market.

Let me share why we believe EPAM is positioned to win this new AI native services category. While we are seeing measurable productivity gains at scale, we are also seeing complexity dramatically increase at faster pace than we have seen in prior cycles. Clients are facing growing pressure to continue to invest in AI, and that means platform modernization, data and cloud foundations, security and critical AI-native upskilling.

As a result, AI presents a favorable opportunity for EPAM within the build versus buy value proposition. EPAM continues to be positioned in this sweet spot as we believe we are entering an age of building. With our internal AI-native engineering transformation nearly complete, we are now shifting to develop more verticalized AI-native business offerings and consultancies. This positions us to deliver a strategy and execution to clients simultaneously, helping them build their own AI native businesses and platforms.

Before getting into details, I would like to quickly reflect on a few things from the past year, which highlight our differentiated position and underpin our confidence as we continue to grow our revenue and improve our bottom line trajectory over the long term. First, we believe we have clearly demonstrated and we'll continue to demonstrate that we're positioned to win in the AI native engineering category or advantage comes from our highly differentiated engineering and AI-native talent, along with the tooling and workflows that enable us to deliver production grade at scale.

Notably, in Q4, we generated more than $105 million in pure AI native revenues, where we continue to see solid momentum and strong sequential growth. As a reminder, our AI native revenues are defined across 2 groupings, number one. AI native IP products, platforms and solutions where AI was the core of the solution versus simple work accelerated by the use of AI tools. And number two, AI-led transformation initiative across the entire enterprise.

Importantly, our definition excludes all the [ IF ] foundational services along with any AI assisted work performed by EPAM employees within the software delivery life cycle. Looking ahead, we continue to see robust demand for our AI native services and expect to scale these revenues in excess of $600 million in 2026.

Second, our developers and builders DNA forged by over 30 years of experience in custom software product and platform engineering, prepare us incredibly well for this new super cycle to stay ahead of the curve. We expanded our 3-year AI readiness mandate to keep pace with advancing technology new agentic delivery and new commercial models that help us meet our clients where they are to enable their unique AI journeys, even under extreme geopolitical and macro adversary or business model and brand of very high quality and execution have persisted and today give us a leading edge on AI strategy and delivery at scale.

Third, we are supercharging our client 0 mentality by extending AI capabilities across our entire business. We have been pioneers builders and change agents in transforming the software delivery life cycle and advancing the [ AI ] maturity model with talent IP and the ways of working. Now we are adapting our go-to-market approach for a more AI-centric environment, focusing on industry and verticalized expertise and innovating engagement and commercial models to adopt new and emerging trends.

We are transforming the way we engage with existing and new buyers, expanding our market growth opportunities across all regions and buyers personas. Our most recent announcement of empty lab expansions demonstrates this AI-native momentum with our proven AI native agency now expanding to help CMOs across North America become the growth [indiscernible] tax for their businesses. We are bringing AI-powered creative talent, accelerators and innovation frameworks to the business of marketing. We will be sharing much more on this at our upcoming Investor Day in March.

Finally, our strategy is being validated by the market and our partners in a significant way that underscores our unique AI native capabilities. With Microsoft, we were thrilled to be named the 2025 Microsoft Innovate with Azure AI Platform Partner of the Year. With AWS, we are recognized as 2025 AWS Global Innovation Partner of the Year. With Google Cloud, we launched several advanced AI agents on Google Cloud Marketplace. Most recently, we announced a strategic partnership with [ Cursor ] to build and scale AI native teams for global enterprises.

Beyond partnerships or technical [ acumen ] is recognized by independent benchmarks. EPAM's [ AIron ] developer agent was recently ranked in the top 5 on SWE bench verified leaderboard an industry-leading benchmark designed to evaluate large language models and AI agents on real world software engineering tasks. Furthermore, Gartner has positioned us as a leader in the emerging market quadrant for generative AI consulting and implementation services, further solidifying our standing as a trusted guide in this complex landscape.

Now let's turn to some Q4 highlights. Our fourth quarter results came in better than expected, marking another quarter of outperformance. In Q4, we delivered double-digit revenue growth, including solid year-over-year organic revenue growth of 5.6%. Our underlying growth momentum remains broadly intact, with 5 of the 6 verticals growing year-over-year and 4 out of the 6 verticals growing organically. Notable standouts included financial services, emerging verticals and software and [ high tech ]. Across geographies, [ EMR ] delivered strong year-over-year growth, followed then by the Americas and APAC. We continue to add talent across all key geographies.

Now turning to the demand environment. Overall, the client sentiment remains intact with no material change over the past 90 days. AI continues to trigger both incremental and sustained demand and is driving positives in our pipeline. Based on our current visibility, we expect client budgets to remain relatively intact in 2026 compared to 2025 with the continued shift in spending towards scaled AI deployment. Even with the progression of AI towards larger programs, there is a growing emphasis on ROI and the need for scalable enterprise-grade solutions.

While these are larger programs naturally introduce a more mature procurement process, including RFPs and a modest extension of sales cycle, it also represents a larger opportunity for EPAM to deliver even greater volume through bigger and more strategic, higher impact initiatives, something we are observing in our sales pipeline today.

Now turning to our AI progress. EPAM is uniquely positioned to guide clients through the market towards AI-native transformation. We continue to invest in people, accelerators and advanced tooling to capitalize on our expanding growth opportunities. As a part of evolution to a pure-play AI native company, last quarter, we launched our [ AI on Transform ] playbook and frameworks, along with our AI native business transformation offering. Together, [ AIron ] for SDLs and [ AIron transform ] are the building blocks for our IP-enabled go-to-market strategy and I'm pleased to say both are picking up early adoption in 2026.

These frameworks and tools support the hundreds of AI native projects we had active in Q4. In line with last quarter, between 60% to 70% have expanded from initial proof of concept into larger programs, a clear indicator of our ability to scale AI native solution into production and convert early wins into more meaningful revenue.

Incremental and highly connected to our AI native services is our AI foundational services, which encompasses the critical AI readiness and preparation work for our clients are undertaking. Demand for these services remain quite strong, and the size of this portfolio is already significantly larger than our pure AI native revenue base. Once again, in Q4, we saw outsized growth in both our data and cloud practices compared to the rest of the business.

Now turning to some client examples to illustrate the impact we are making. EPAM partnered with [ ASCO information services ] to enhance software development processes using the [ AI run ] transfer framework. EPAM played a critical role by providing AI guidance, helping to establish governance framework and building an adoption dashboard to measure real-time performance metrics.

Through each phase of the rollout, EPAM and ASCO maintained a strong emphasis on measurable outcomes using the dashboard to track metrics such as [ Velocity Cycle ] could review lead time, AI impact and productivity gains. In addition to measurable productivity gains, [ Asco ] also established a robust foundation for future continuous improvement in the use of AI development tooling.

[ Bayer ] partnered with EPAM to develop an AI-powered pricing tool that optimize pricing strategies across 35 countries. Leveraging machine learning, the tools delivered EUR 20 million to EUR 30 million in incremental yearly profit, reduced analytics time by [ Tenex ] and provided advanced scenario planning capabilities. This collaboration transferred [ Bayer's ] pricing processes, enabling smarter data-driven decisions.

We've also seen compounding value of our long-term trusted partnerships with our clients like [ Zalando ], where driving impact across data, analytics, AI and cloud transformation. Our collaboration has yielded 3 significant outcomes. First, we have developed a pilot for a Gen AI-powered styled solution, giving mobile users an interactive, highly personalized shopping experience. Second, leveraging our proprietary [ Mikwiser2 ], we rapidly migrated their massive data warehouse platform, which fuels the business intelligence to Amazon Bedsheet.

Finally, we built a sophisticated machine learning solution that combines automated tagging with intelligent oversight to solve the complex challenge of managing extended producer responsibility compliance. Lastly, we are also incredibly proud to announce a new multiyear partnership with National Geographic Society, where EPAM has been designated as Nat Geo's preferred digital transformation partner. This collaboration is about far more than modernization. It's about utilizing innovative technologies to inspire the next generation of explorers and solution seekers.

By leveraging our engineering DNA to modernize their nonprofit infrastructure, we are also helping Nat Geo to engage global audiences through distinctive experiences that bridge the physical and digital worlds. Our efforts to lead in the age of AI and digital transformation also being consistently recognized by the industry top analyst firms, validating our strategy and quality of our execution. Throughout 2025, we have been honored to receive several key leadership distinctions.

For example, EPAM has been named the top IT vendor in Europe for application services and general satisfaction by [ vital research ] for the third consecutive year, which included expanded coverage across categories, ranking first across multiple categories, including application services, general satisfaction, innovation and service delivery quality. The report highlights EPAM's commitment to delivering high-quality services and innovative solutions. This milestone reflects the trust and partnership of our clients and the dedication of our teams.

Gartner recognized EPAM as a leader in the major quadrant for custom software engineering, a testament to our deep rooted engineering DNA. Furthermore, Gartner also named us as a leader in the emerging market quadrant for generative AI consulting and implementation services, highlighting our early and impactful entry into this transformative space.

Forrester positioned EPAM as a leader in the Forrester [indiscernible] for modern application development services, reinforcing our strength in helping clients to modernize and innovate across their technology stacks. IDC market acknowledged our end-to-end capabilities by naming us a leader into 2 critical areas or third year in the row of recognition. CX Design Services and CX build services. This underscores our unique ability to not only envision, but also deliver world-class customer experiences.

These recognitions spanning engineering, generative AI, customer experience and application development, affirm our position as a trusted partner for enterprises navigating complex transformations. They reflect the hard work and dedication of our global teams and [ unwavering ] commitment to deliver intangible high-volume outcomes for our clients. We see this as a strong validation that our integrated approach from strategy and design to engineering and AI native delivery, it's what the market needs today.

To close, our operating momentum exiting 2025 is strong as AI continues to be the net growth driver for our business. We are encouraged by our progress, transforming our company or go-to-market capabilities and our offerings. The EPAM foundation we have built over the past several years, diversifying our global delivery model, enabling our entire organization with AI and bringing meaningful solutions to market with our [ AI ROM ] playbooks and underlining IP position us to continue delivering sustainable revenue growth while also expanding profitability. Jason, over to you.

Thank you, FB, and good morning, everyone. In the fourth quarter, EPAM generated over $1.4 billion in revenues, a year-over-year increase of 12.8% on a reported basis, exceeding the high end of our Q4 revenue outlook. On an organic constant currency basis, revenues grew 5.6% compared to the fourth quarter of 2024. We delivered another quarter of very solid year-over-year organic constant currency growth. reflecting our steady and focused execution throughout 2025.

As FB mentioned, we continue to benefit from the momentum we've created across our AI native and AI foundational services. One thing is clear. Clients need help in their AI transformation journeys and our advanced engineering capabilities, AI assets and strong delivery execution are helping clients address their most complex business challenges. Our growth this quarter was well balanced, reflecting our relevance and agility across our major geographic regions.

Moving to our Q4 vertical performance. Five of our 6 industry verticals posted year-over-year growth. As highlighted last quarter, NEORIS and First Derivative revenues moved from inorganic to organic in November and December 2025, respectively. Financial services once again delivered very strong growth, up 19.8% year-over-year on a reported basis with 5% organic growth in constant currency. Growth was mostly driven by ongoing strength in insurance, banking and asset management.

Software and hi-tech grew 18.1% year-over-year, driven by strong execution and broad improvement across large clients. Consumer goods, retail and travel delivered 10.9% year-over-year growth, notably driven by retail and consumer goods. Life sciences & health care increased 2% on a year-over-year basis. Revenue growth in vertical continues to be driven primarily by clients in life sciences and med tech. Business information and media delivered flat year-over-year revenue performance. Our emerging verticals delivered another quarter of strong year-over-year growth of 19.1%. On an organic constant currency basis, growth was 9.7%, primarily driven by ongoing strength in energy and telecommunications.

From a geographic perspective, the Americas, our largest region, representing 58% of our Q4 revenues, grew 7.6% year-over-year on a reported basis and 2.2% in organic constant currency. EMEA comprising 40% of our Q4 revenues, grew 21.8% year-over-year and 11.7% in organic constant currency. And finally, APAC, making up 2% of our revenues grew 0.6% year-over-year and declined 4.3% in organic constant currency. Lastly, in Q4 revenues from our top 20 clients grew 7.3% year-over-year, while revenues from clients outside our top 20 increased 15.5%.

Moving down the income statement. Our GAAP gross margin for the quarter was 30.1% compared to 30.4% in Q4 of last year. Non-GAAP gross margin for the quarter was 31.7%, compared to 32.2% for the same quarter last year. Relative to Q4 2024, gross margin in Q4 2025 was negatively impacted by higher variable compensation expense, driven by our stronger second half performance.

GAAP SG&A was 17.3% of revenue compared to 17.4% in Q4 of last year. Non-GAAP SG&A came in at 14.5% of revenue compared to 14.4% in the same period last year. GAAP income from operations was $149 million or 10.6% of revenue in the quarter compared to $137 million or 10.9% of revenues in Q4 of last year. Non-GAAP income from operations was $230 million or 16.3% of revenue in the quarter compared to $208 million or 16.7% of revenue in Q4 of last year.

Our GAAP effective tax rate for the quarter came in at 24% and our non-GAAP effective tax rate was 22.9%. Diluted earnings per share on a GAAP basis was $1.98. Our non-GAAP diluted EPS was $3.26, reflecting an increase of $0.42 or 14.8% compared to the same quarter in 2024. In Q4, there were approximately 55.3 million diluted shares outstanding.

Turning to our cash flow and balance sheet. Cash flow from operations for Q4 was $283 million, compared to $130 million in the same quarter of 2024. Free cash flow was $268 million compared to free cash flow of $115 million in the same quarter last year. We ended the quarter with approximately $1.3 billion in cash and cash equivalents. At the end of Q4, DSO was 72 days compared to 75 days in Q3 2025 and 70 days in the same quarter last year. Share repurchases in the fourth quarter were approximately 1.2 million shares for $224 million at an average price of $192.33 per share.

Moving on to a few operational metrics from the quarter. We ended Q4 with more than 56,600 consultants, designers, engineers, trainers and architects, reflecting total growth of 2.7% and organic growth of 2.2% compared to Q4 2024. In the quarter, we added approximately 500 delivery professionals. Our total head count at quarter end was more than 62,850 employees. Utilization was 75.4% compared to 76.2% in Q4 of last year and 76.5% in Q3 2025. Q4 2025 utilization was impacted by higher levels of vacation, driven by the shift in delivery locations as well as the introduction of juniors, who initially operate at lower levels of utilization. The addition of juniors is intended to improve our seniority index in 2026.

Turning to our 2025 full year results. Revenues for the year were $5.46 billion, up 15.4% on a reported basis year-over-year. On an organic constant currency basis, revenues were up 4.9% year-over-year. Income from operations was $520 million, a decrease of 4.5% year-over-year and represented 9.5% of revenue. Our non-GAAP income from operations was $831 million, a growth of 6.7% compared to the prior year and represented 15.2% of revenue.

Our GAAP effective tax rate for the year was 25.3%. Our non-GAAP effective tax rate was 23.5%. Diluted earnings per share on a GAAP basis was $6.72. Non-GAAP EPS was $11.50, reflecting a 5.9% increase over 2024. In 2025, there were approximately 56 million weighted average diluted shares outstanding. Cash flow from operations was $655 million compared to $559 million for 2024 and free cash flow was $613 million, reflecting a 94.7% adjusted net income conversion. And finally, share repurchases in 2025 were approximately 3.5 million shares were $661 million at an average price of $186.67 per share.

Now let's turn to guidance. Before moving to the specifics of our 2026 and Q1 outlook. I would like to provide some thoughts to help frame our guidance. We are encouraged by the underlying momentum of our business and the steady outperformance delivered throughout 2025. We step into 2026 with higher confidence in our long-term strategy and growth trajectory, supported by healthy client sentiment, a solid pipeline and strong momentum in AI native and AI foundational services. We see relative stability in overall client budgets with a continued shift in spending towards build and strategic AI programs.

Similar to last year, we are seeing some slowness in decision making at the start of 2026 as clients finalize budgets and established priorities for the year. Our organic constant currency revenues now include NEORIS and first derivative. As we noted throughout 2025, NEORIS' largest client headquartered in Mexico has been significantly impacted by a challenging economic environment, including the impact of U.S. tariffs.

Revenues from this client will decline sequentially from Q4 2025 to Q1 2026 and then are expected to stabilize throughout the remainder of the year. The full year 2026 revenues from this client will decrease relative to 2025. And this decrease is expected to have a negative 1% impact on EPAM's 2026 organic constant currency growth rate.

In 2026, we remain committed to improving overall profitability and specifically gross margin. Our guidance assumes that we will be able to continue to deliver from our Ukraine delivery centers at productivity levels similar to those achieved in 2025.

Now starting with our full year outlook. Revenue growth will be in the range of 4.5% to 7.5%. Foreign exchange is expected to have a positive impact of 1.5%. Therefore, the organic constant currency growth rate is expected to be in the range of 3% to 6%. We expect GAAP income from operations to be in the range of 10% to 11% and non-GAAP income from operations to be in the range of 15% to 16%. We expect our GAAP effective tax rate to be approximately 26%. Our non-GAAP effective tax rate will be approximately 24%.

For earnings per share, we expect the GAAP diluted EPS will be in the range of $7.95 to $8.25 for the full year. And non-GAAP diluted EPS will be in the range of $12.60 to $12.90 for the full year. We expect weighted average share count of 54.4 million diluted shares outstanding. For Q1 of 2026, we expect revenue to be in the range of $1.35 billion to $1.4 billion, reducing year-over-year growth of 7% at the midpoint of the range.

Our guidance reflects a negligible inorganic contribution and estimated 4% positive FX impact during the quarter, producing an approximately 3% organic constant currency growth rate at the midpoint of the range. For the first quarter, we expect GAAP income from operations to be in the range of 7% to 8% and non-GAAP income from operations to be in the range of 13.5% to 14.5%.

Our Q1 income from operations guide reflects the impact of resetting social security caps and slightly softer revenues in the month of January as clients in certain verticals finalized budgets as well as the negative foreign exchange impact. We expect our GAAP effective tax rate to be approximately 30% and our non-GAAP effective tax rate, which excludes tax shortfall related to the stock-based compensation to be approximately 24%.

For earnings per share, we expect GAAP diluted EPS to be in the range of $1.32 to $1.40 for the quarter and non-GAAP diluted EPS to be in the range of $2.70 to $2.78 for the quarter. We expect a weighted average share count of 54.7 million diluted shares outstanding.

Finally, a few key assumptions that support our GAAP to non-GAAP measurements for 2026. Stock-based compensation expense is expected to be approximately $202 million with $53 million in Q1, $53 million in Q2, $48 million in Q3 and $47 million in Q4. Amortization of intangibles is expected to be approximately $69 million for the year. with approximately $18 million in Q1 and $17 million in each remaining quarter.

The impact of foreign exchange is expected to be an approximate $3 million loss each quarter. Tax effective non-GAAP adjustments is expected to be approximately $70 million for the year, with $90 million in Q1, $19 million in Q2, $16 million in Q3 and $15 million in Q4. We expect tax shortfall upon vesting or exercise of stock awards to be around $4 million for the full year, with an approximate $4 million shortfall in Q1 and minimal excess tax benefits or shortfalls in the remaining quarters.

Expenses associated with the 2025 cost optimization program are expected to be $14 million in Q1 and $11 million in Q2. And one more assumption outside of our GAAP to non-GAAP items. We expect interest and other income to be $12 million for the 2026 full year with $3 million in Q1, $2 million in Q2, $3 million in Q3 and $4 million in Q4.

My thanks to all the EPAMers who made 2025 a successful year and will help us drive growth throughout 2026. Operator, let's open the call up for questions.

[Operator Instructions]. Your first question comes from the line of Maggie Nolan with William Blair.

Great. I wanted to ask about the first quarter guidance. At the midpoint, it's a little bit lower than the full year organic revenue and margin guidance. So how do you expect the year to build? And how is the visibility when we think about the larger deals ramping bookings pipeline, those types of factors?

Okay. Let me talk a little bit about Q1, and then I'll hand it over to FB to talk about the remainder of the year. So I think probably the incremental piece of information that we received between our last earnings call and the one obviously we're doing today, is the NEORIS' largest customer was going to ramp down business between Q4 and Q1.

Now we have met with them in their headquarters in Mexico, and we do think it stabilizes from this point forward. But we have kind of a mid-single-digit decline in their business between Q4 and Q1. And that probably is the biggest kind of incremental factor. Even with that, if we can run closer to the high end of the range, we're talking about at 3% or maybe somewhat better organic constant currency growth rate in the quarter.

Maggie, this is FB. For the remaining quarters, I mean, I think we already have a very nicely built pipeline and as we are seeing the opportunities arriving, we are actually seeing how that would be converting from it. We see very good traction in the European and the Middle East markets which we feel that's going to be -- allow us to deliver on the year.

Okay. Great. And then, FB, you had made a comment on wanting to bolster the vertical industry expertise. Are there investments that you need to make in sales or delivery in order to achieve this? And are those going to be material to the P&L? Maybe a few comments on how that will impact your competitive positioning as well.

So I think our current P&L reflects already the guidance reflects the investments, which we're planning to make in 2026. Yes, we are prioritizing investment into business development and prioritizing, developing besides just the AI, which is our biggest investment area, building out our industry capabilities and vertical accelerators and expertise themselves.

Your next question comes from Jonathan Lee with Guggenheim Partners.

Last quarter, you called out an expectation of 2026 organic growth being faster than that of 2025. With that in mind, can you help us reconcile that commentary to the 2026 outlook that at the midpoint on an organic constant currency basis is slower than what you delivered in '25? Is that due to NEORIS' largest client? Are there any other factors there?

Yes. Jonathan, thanks for the question, and it's certainly a good one. And so you're right. I think we had 4.9% organic constant currency growth in 2025. The midpoint of the range would produce 4.5%. Since the last time we talked, as I told Maggie, we did get incremental information on the NEORIS largest client.

As I called out in my fixed remarks, we expect it will have -- the decline on a year-over-year basis will have a negative 100 basis point impact on growth. So you've got the 4.5% of the midpoint of our range obviously, would be 100 basis points higher on the rest of the business. I think the other thing that we're trying to do from a guidance standpoint is to make certain that we guide to kind of what we can see today. We're not assuming improvement in environment. Clearly, we've got some opportunities that we talked about throughout the remainder of the year. And so we're clearly going to work to drive towards better, and we'll update you on our progress throughout the year.

Understood. With that in mind, can you help us -- can you help us walk through what's contemplated across the low end and the high end? How much [ Go get ] is still needed? And are there any verticals that you would expect to accelerate versus decelerate in the near to medium term?

So let me start with the verticals. We continue seeing very strong demand in financial services and energy. We also kind of forecast or expect our life science and health care to gain momentum later part of the year, which is typically very much calendar dependent. So that's -- and clearly, high tech and software and hi-tech continues to be a growth area for us.

In terms of between the low end and the high end, I think we're not contemplating anything like changing macro environment in order to achieve the high end of the range. Just like this year, we are expecting that we are going to winning the deals and some of the clients start accelerating expenditure in later quarters.

Your next question comes from James Kupferberg with Wells Fargo.

So I wanted to come back to some of the commentary around the elongated sales cycles. And then I think, Jason, you mentioned some client in decision at the outset of the year. So are those dynamics impacting the full year guide or just the shape of the year, i.e., the Q1 outlook. So putting NEORIS largest client on the side, I just wanted to understand those broader dynamics that you both alluded to in prepared remarks.

So I think as the year started, it's starting similar to last year, right? We actually do have better visibility in 2026, what we had in 2025. but it's kind of starting in the same way in terms of shape of the revenue decision-making process. At the same time, as clients are now really decided to actually embark on large AI transformation programs. That's naturally drives them towards a more stringent, let's call it, slower process, which is involved procurement which is naturally going to slow down the decision-making process itself.

But I think this is just make things bigger, right? And it's actually as the programs are bigger now and more substantial, this is actually just makes a little bit of a delay, and that's going to be realized on those project starts will be come in the later part of the year. but I think it's more natural to the shift what we are experiencing.

Okay. Okay. So it sounds like those dynamics didn't really impact how you guided the full year. It's just more about the shape of the year. Is that right?

That's correct.

Okay. Okay. And then, Jason, just real quick. Anything you can give us on gross margin and free cash flow expectations for this year?

Yes. So that's great. So we had, obviously, really strong free cash flow in 2025. The only thing I would say is as we look ahead towards 2026, we did come out in 2025, but above our traditional 80% to 90% conversion guide and think -- do not think that we'll continue to do that. I think that we should operate within the 80% to 90% range.

And then from a gross margin standpoint, and this also would kind of answer one of Maggie's questions is we do intend to continue to make investments in business development and partnership programs to drive top line revenue growth. With that said, I don't expect as much benefit from productivity and efficiency and SG&A again, because we're going to recycle some of those benefits into investments in business development.

So most of the improvement will come from gross margin. What we are seeing is better execution in some of our expanding geographies like Western and Central Europe. In India, as we've talked about and the profitability in each of those or continues to improve on a year-over-year basis. Plus we're getting a little bit of price as we enter the year. And so all those things give us confidence that we can improve our gross margin between 2025 and 2026.

Next question comes from the line of Bryan Bergin with TD Cowen.

First on the growth guidance, Jason, on the large client, I think I heard you said you expect that to be down, I think, sequentially mid-single digits. What does that translate to as a headwind to year-over-year growth for the first quarter? And also for the first quarter growth guide, are there any build date dynamics to consider?

Yes. So it's 100 basis points approximately for the full year, and it's also about 100 basis points impact on the Q1 number. And so again, you could do the same thing. You could add 10% to our guide for organic constant currency, and that would be the -- our book of business, excluding that one large customer. The build [ day ] impact, you have fewer builders as you go from Q4 to Q1. So that clearly has some impact on both profitability and on revenues you probably will have lower vacation, though. So maybe there's kind of a net-net on that when I think about the revenue going from Q4 to Q1.

Okay. And then as it relates to the workforce, can you give us an update on permitting and global delivery optimization, kind of the effort and the progress there and your expectations around billable engineering resource additions for '26?

Yes. The interesting thing is, in Q4, we actually did see better utilization in Q3 to Q4 if you adjust for vacation. As I kind of hinted in my prepared remarks is we finally have gotten to that shift where we do have more people taking their year-end holiday around December 25 rather than January 7.

And so what we are -- so what we did see is lower bench. We continue to focus on that. through our cost optimization program. We are getting, I would say, better cost outcomes, I would say, great execution in Western and Central Asia, Eastern Europe and India. And at the same time, we're moving to make certain that we're cost efficient in those geographies. So we are seeing improving profitability in each of those more rapidly growing geographies. And we continue to work on utilization improvements throughout the year.

Addition to that, throughout 2026, we'll continue working on optimizing our pyramid, and that's why we started to onboard the juniors already in Q4 in 2025. So that's very much -- it's going to play out throughout the year. And we will continue working on it as we talked about it in previous quarters on optimizing or delivering organization or [ delivery pyramid itself ] to actually go back to shape, which is more healthy and more sustainable on a going forward basis.

Your next question comes from David Grossman with Stifel.

So Jason, you did the job of kind of explaining the impact of the acquisitions on growth in '26. I'm just curious, maybe you could do the same and help characterize what impact pricing is having either positive or negative year-over-year in '26. And also whether there's any kind of mix shift dynamics that may still be impacting revenue growth. And I'm speaking specifically of mix shift to India?

Yes, that's fair. So we did get a little bit of price improvement in the second half of 2025 and what we are seeing as we enter 2026 is at a quite significant number of clients in both Europe and North America are giving us at least low single-digit rate increases. And so is not the way it would have been, let's say, 4 or 5 years ago, but it's definitely a somewhat improving pricing environment relative to the last couple of years.

I think to your point, with India, we continue to execute successfully across the broad range of geographies. India is growing faster than the other geographies. We are still priced at a premium there and the profitability in India continues to sort of expand beyond our average. So last year, I said, hey, India is operating at profitability higher than EPAM average. This year, we expect it will operate at an even higher level of profitability, getting closer to our most mature geographies.

But India still obviously prices at a somewhat lower rate on a dollars per hour basis. So there's probably some impact there. But again, we continue to feel that it's actually -- it's probably positive or margin accretive, any expansion that we see in that geography.

Great. And then I think there were some commentary in the prepared remarks about -- and I think, FB, you said this again in the Q&A about decision-making slowing. However, the deals are getting larger. I think the industry has been talking about this for the past 12 to 18 months. When does that [ dam ] have to break at some point, when does the spending have to accelerate despite uncertainty?

I wish I would have a crystal ball for that. But I think we are seeing more and more larger programs, which makes me optimistic that we are getting close to that point. So I think right now, there are clearly in certain industries, financial services, for example, in Europe, people are no longer able to hold back their transformation and nondiscretionary CapEx expenditure.

Plus in certain other industries, we're already seeing people are no longer able to delay their decision making around AI investments, and that's triggering larger programs. But as larger programs are being requested or being executed, clearly, the governance around the selection process. The procurement is actually becomes a little bit more bureaucratic and when all the enterprises are making larger decisions, they are -- the selection process naturally slows down.

Yes. Are there any data points you can share that would kind of help us understand the momentum that may be building or accelerating in terms of conversion?

I think in AI, we're definitely going to start sharing one. But I think what -- the data point which also was part of my opening remarks is that the scale of the AI native revenues, we expect to reach $600 million in 2026 for EPAM. So it's actually scaling up, growing very rapidly, but it's still a smaller part of our business.

Your next question comes from Jamie Friedman with Susquehanna.

I had a couple of more quantitative questions. By my math, the revenue per utilized head year-over-year grew about 10% -- almost 11%. And because pricing conversations can be quite subjective that we think of as price. So I'm just wondering if you would react to that, is that revenue per utilized had reflecting a better pricing environment? And then I have one quick follow-up.

Yes. I think as we've talked about over the years, the revenue per head calculation is not one that we usually do internally because there's just an awful lot of noise. But I know it is something that people do externally.

Just to remind people of the noise, foreign exchange can have an impact. Obviously, price can have an impact. utilization can have an impact. And then there's different kind of revenue recognition elements that can also have an impact where you might have done work earlier in the year and then recognize revenue later in the year. So all those things can kind of impact that number.

The other thing that I do want to remind people of is that we are reporting numbers that are employees only. We do have some contractors. If the contractors grow, they might -- they obviously would generate revenue, but it wouldn't necessarily be in the denominator in that head count figure. So with all those things said, Jamie, I would do the same math that you would do, and I would see that revenue has improved.

I would say some of that is foreign exchange base. Some of that is price. And then we did have a specific 1 or 2 revenue recognition, recognize revenue where the work was done earlier and that was recognized in Q4. So all those things contributed somewhat to that beat. And at the same time, even if I adjusted out any of those benefits, we still had a beat relative to our original guidance for Q4.

Okay. And then just to follow up with that, Jason. The other thing that makes the math -- that limits the math is the shift to fixed price. And you had a 150 basis point increase in fixed price as a percentage of total revenue to 20.2%. And I would imagine that, that's -- since it's not [ time materials ], it's not gated by head count. So could you -- but at the same time, your free cash flow was really good and your [ DSO ] was good.

So anyway, in terms of the journey to fixed price, which you've been talking about for a while, and it clearly evolved last year quite a bit. How should we be thinking about that as the impact on, say, free cash flow? Because we don't see like unbilled revenue, and it's hard for us to get other details. So any comment about how the fixed-price transition impacts free cash flow.

And I'm sorry, someone asked me to ask you about the implications of that for repurchase would be helpful, free cash flow repurchase.

Excellent. Excellent. There are a lot of questions in that.

Sorry about that.

Yes. No, that's fine. Okay. So you're correct that we are seeing an evolution towards more fixed fee. Yes, I think I have said in my prepared remarks that I do think that at least in the past, it does give us an opportunity to improve pricing as we introduce, let's say, somewhat different commercial models in response to the changing mix of AI native and AI foundational revenues. And so I think you will continue to see an increasing mix of fixed fee.

Again, we don't think it goes from 20% to 50%, but in 2026. But it is -- I would suspect it will continue to increase throughout the year. From a cash flow standpoint, I think it's hard for me to say exactly how the fixed fee impacts that because there are different types of fixed fee. So some do have a monthly fixed kind of development associated with them, and that would have a very similar feel to [ T&M ] in terms of how we get paid.

There might be some opportunities to have milestone payments that maybe occur before revenue recognition which we give you an increase in deferred revenue and at the same time, allow you to sort of drive -- potentially collect cash in advance of revenue recognition. But I think I'd take us back to what I said earlier, which is I'd really think as we look ahead that we'll operate in the [ 80s ], not in the [ 90s ], the way we did in 2025 from a free cash flow conversion. And then just quickly to fork in that share repurchase clearly with the share price where it is today, you'll continue to see us reasonably active in terms of share repurchases, particularly in the first half of 2026.

Your next question comes from the line of Bryan Keane with Citi.

I wanted to ask just on the big debate going on with AI eating software and potential implications for the IT services market. Obviously, software stocks have sold off. And as a result, we've seen the IT services stocks also under pressure. So how do you think about FB especially the AI pressure potentially from [ anthropic ] and Open AI as some of their modules get pushed out?

So Bryan, thank you very much for the question. I think we're actually very, very bullish and optimistic. This is going to open up a tremendous opportunity for EPAM. It's going to turn [indiscernible] the buy versus build question, right? And EPAM is a builder. We're going to build much, much more software, right? There is no limit how much software people would like to build.

Yes, the coding part of the activity will be automated. But this opens up the potential for all the high-end work what EPAM is famous and known for, right? It is going to make us stand out because we can use these tools. We can bring our engineering capabilities to it, and we can deliver the solutions our clients [indiscernible].

So actually, I'm much more on the side of AI will enable building more software, more capability. We are a builder. We are not maintaining software. We are not running business processes. We are not in, what people call it, we are not input limited. We are what we want to build, there is a tremendous appetite out there. And if you listen carefully for the comments from [indiscernible], comments from Open AI and a couple of podcasters. They all talk about how much more software people want to build.

And right now, because building software becomes easier per unit, people are going to build more. That's what I think about and that's how I see the situation. I think the market a little bit confused. It's very hard to decipher all the signals, but on the long run, we are optimistic and actually very, very bullish what this is going to mean for us.

Got it. Got it. And we see the pure AI revenues growing significantly for you guys now. I guess the flip side of that, is there any AI pressure as a result of some of the productivity and pricing that gets passed on to the consumer? Do you see some pressure also in addition to the pure actual revenue growth that you see from the AI revenue?

Yes. I think the one thing I'd say is just into to echo FB is we don't have BPO, we don't have application maintenance that probably is more likely or really large testing practices that might be more impacted.

The other thing I just need to make certain that it's communicated is we are not seeing a pressure on our pricing due to AI. Again, most of the pricing that we have is time and materials. As I talked about earlier in our -- earlier with some of the earlier questions is that we did see rate improvement in the second half of 2025 and are seeing rate improvement again here in 2026.

So I certainly understand that if you've got a large book of multiyear fixed fee business, that, that might be subject to sort of pressure in certain types of revenue streams. But with the build work that we've historically done and this more advanced AI work, we aren't seeing bill rate compression associated with that.

Your last question comes from Jim Schneider with Goldman Sachs.

Relative to what was just referenced in terms of the pressure on the software stocks and the services stocks. Maybe share with us your thoughts on capital allocation, what are you thinking, what is the board thinking in terms of the desire to potentially do more inorganic actions versus potentially be significantly more aggressive with buyback.

Jim, thanks for the question. I think -- we continue to -- on the share buybacks, which as Jason also already communicated, we announced the share buyback talent earlier the previous quarter. And in the next couple of quarters, at least definitely in the first half year, we were going to come to make acquisition as appropriate and repurchase shares and especially what we are -- want to execute is small tuck-ins. But that's our plans at this point of time. And once we stabilized our previous acquisition, that's when we look for other opportunities.

So Jim, in the near term, you probably still have a focus on share repurchases. And then over time, I think we'd be more open to kind of scaled M&A activity.

Fair enough. And then just one question on the AI native revenue that you called out in the quarter. By my math, it kind of gets you to, for the full year, sort of an 80% increase in the run rate of AI native revenues as we exit Q4. Can you maybe comment on whether that's directionally correct? And then more importantly, can you talk about how you believe that maybe your AI native revenue is different from some of the AI revenue or bookings numbers being reported by your peers?

Yes. So I would say kind of directionally correct. So very high rates of growth on a year-over-year basis. And we talked about the fact that we were seeing strong sequential growth throughout the year and expect to continue to see solid sequential growth in the quarters going forward.

I think our definition is very tight and I think FB did pick that up during his prepared remarks, but if you want to provide some more color, FB.

So I think it's very important that our definition of AI native revenue is super tight which means that we're not including a lot of things, which probably some of our competitors do include. So just a reminder, we basically include type 1, which is new types of solution where the center of it is AI itself and the AI model is making it possible. We're not including anything in this, which is [ AIS state ], i.e., you're delivering with the solutions which you need to be -- which we are delivering has to be built on top of.

Number 2 is when somebody embark on an end-to-end enterprise transformation, which we call [ AI 360 ] that's what we include in the second time. We're not including in the second number, any kind of work, which is what we call data or AI foundational events. Actually, those revenues are much, much larger for us than our AI native revenues.

This concludes the time allotted for Q&A. I'd now like to turn the call over to Balazs Fejes for closing remarks.

Thank you very much. I would like to thank all EPAMers, who made 2025 a successful year and who will make us deliver throughout 2026. And thank you all for attending the call. And I'm looking forward to seeing many of you on our March Investor Analyst Day in Boston. Thank you very much.

Thank you for standing by. My name is Rebecca, and I will be your conference operator today. At this time, I would like to welcome everyone to the EPAM Reports Results for Third Quarter 2025 Conference Call. [Operator Instructions].

I would now like to turn the call over to Mike Rowshandel, Head of Investor Relations. Please go ahead.

Good morning, everyone, and thank you for joining us today on our third quarter 2025 earnings announcement. As the operator just mentioned, I'm Mike Rowshandel, Head of Investor Relations. We hope you've had an opportunity to review our earnings release we issued earlier today. If you have not, copies are available on epam.com in the Investors section.

With me on today's call are Balazs Fejes, CEO and President; and Jason Peterson, Chief Financial Officer. I would like to remind those listening that some of the comments made on today's call may contain forward-looking statements. These statements are subject to risks and uncertainties as described in the company's earnings release and SEC filings.

Additionally, all references to reported results that are non-GAAP measures have been reconciled to the comparable GAAP measures and are available in our quarterly earnings materials located in the Investors section of our website.

With that said, I will now turn the call over to FB.

Thank you, Mike, and good morning, everyone. It's a pleasure to be here with you on my very first earnings call as a CEO. And please just call me FB, be as Hungarian names are notoriously difficult to pronounce and why FB because in my native language feminine comes first. This quarterly call arrived faster than even my standard double espresso shot in the morning, and that's really the theme for the day. Things have been moving quickly since we spoke last, and today, we have positive news to share.

Our third quarter results came in better than expected, marking other quarter a broad outperformance and strong delivery execution. We continue to benefit from AI and AI native led demand or thesis that data and modern cloud architecture are critical for adoption and oralization is broadly being confirmed by what we are seeing. Our clients are prioritizing their AI build-outs, turning to EPAM to help them accelerate their investments and innovation in AI. The unique combination of our deeply rooted engineering DNA and our globally recognized best-in-class AI-native expertise continues to differentiate our offerings and help us further expand wallet share within our existing client portfolio and targeted new logo segments.

At the same time, we are more focused than ever on upgrading our engineering skills advantage and investing for the future with new advanced AI playbooks and accelerators. Serving a client 0 for adoption, we believe innovation starts from inside, which is why in parallel, we continue to restlessly push our AI literacy and AI adoption rates.

Looking at our progress year-to-date, more than 90% of EPAMers have completed their mandatory AI literacy education and approximately 95% of our engineers have completed foundational AI education. Additionally, our internal business processes are increasingly benefiting from AI-driven efficiencies. As you can see with the recent launch of EPAM AI Transform, which includes next-generation AI managed services, and EPAM agent in QA, we are programmatically expanding new offerings and highly specialized capabilities, often in conjunction with our clients and strategic partners, to help clients transform themselves into AI native organizations.

Our efforts are being recognized by our partners as well as industry analysts such as IDC Marketscape who have positioned EPAM as a leader across experienced engineering, custom build and AI consultancy capabilities. Further, [ Glader ] ranked EPAM #7 on their 2025 best led companies list along Grid Forbes, who recognized EPAM as one of the world's best employers or first time being recognized across both. We will dive into the details a bit later in the call, but first, I would like to provide a quick update from my early days of CEO and my recently completed [ Vertu. ]

Over the past quarter, I met in person with many senior client executives, ecosystem partners, and of course, many, many EPAMers from all around the world. I experienced firsthand the high level of optimism appetite for EPAM proven quality of execution across our global deeply specialized talent base. I am pleased with our continued and growing ability to ensure higher levels of performance across a much more globally diversified footprint than ever before. But our work is not done.

AI presents a permanent fleet change in our industry and across our clients' businesses, driving the need for investment in modernization, data and cloud foundations and critical AI native skills. EPAM is positioned to lead both the foundational and the transformational programs demanded by AI as clients need support from trusted partners who can reliably deliver through the need to [indiscernible] balance costs and productivity with an increasing need to reinvest, innovate and keep pace with change.

In line with [ Amara's ] law, we believe that as the productivity growth and our cost to develop software declines, complexity will significantly accelerate pushing the bleeding edge and resulting the boundaries of what is possible. And triggering a flywheel effect of demand for EPAM's unique breed of capabilities and global scale. We believe that as complexity rises, so does enterprise risk, raising the importance of highly advanced engineering with proven enterprise-grade quality execution.

While we have seen the flashy white coding video shorts and headlines in our view, the absolute need for true engineering expertise, risk management, full terrace and reliability are overlooked and underestimated.

Now let's turn to some Q3 highlights. In Q3, we delivered another quarter of double-digit revenue growth, including very strong year-over-year organic constant currency revenue growth of 7.1%, which exceeded our expectations set a quarter ago. This marks our fourth consecutive quarter of positive year-over-year organic constant currency growth, reflecting a steady build of improvement and strong execution in our core business as we continue to ramp our AI native services. Our broad-based growth momentum carried forward in Q3 with 5 out of 6 verticals growing year-over-year. Notable standouts included emerging verticals, financial services and software and high tech.

We also saw solid improvement in life sciences and health care, along with consumer goods, retail and travel while business information and media remains steady. Geographically, all 3 regions delivered strong year-over-year growth. We continue to add net organic headcount across key locations, such as India, Central Eastern Europe and South America. With increases partially offset by ongoing optimization in select pockets that we have discussed previously.

Now turning to demand environment. AI continues to trigger incremental demand and is driving positives in our pipeline globally. The majority of our top 100 clients remains highly engaged in AI-native initiatives. Clients engage EPAM to build out their data platforms and modernize their cloud, often redirecting work from other partners who successfully sold advanced capability, but failed to deliver it.

Overall, we continue to see improvement in the demand environment as we're seeing a continued upshift in investment towards everything that supports adoption and its deployment to production. This is where reputation for trusted quality and execution remains a significant competitive advantage and a key enabler for us to continue to maintain our pricing integrity.

We gained traction with our ongoing client-centric initiatives while at the same time, continuously strengthening and optimizing our global delivery footprint, which is enabling us to better meet market demand. When you look across the AI project life cycle from proof of concepts to medium-sized use cases and the large-scale project in production, we're seeing a continued shift in the volume of project towards medium- and large-sized projects. Many making use of our own IP, such as diode, AI run and other components, both open source and proprietary.

Of the hundreds of individual AI-native projects, we had active in Q3 between 60% to 70% have expanded into larger programs from the origination of proof of concepts, illustrating our ability to scale and deliver AI native solutions in production. We are also seeing positive signs at the top of the funnel, enabling us to replenish our pipeline or some projects come to a natural clause.

Our hard work and continuous effort to further position EPAM as a leader in AI native services is serving us well as our pure AI-native revenues continues to grow nicely with a third consecutive quarter of double-digit sequential growth. And of course, as we have discussed before, the foundational services necessary to meet AI work are a core fundamental to our business. In both our data and cloud practices, we saw outsized growth in Q3 compared to the rest of the business, which is incremental and highly connected to the momentum we are seeing with our pure AI native revenues.

Now turning to our AI around transform and agentic QA announcements. First, a couple of core beliefs to frame our evolving AI approach. Number one, AI is not just a technology. It's a transformative force that is already redefining how enterprises innovate, operate and create value in the future. And in this context, advanced engineering, bleeding edge, AI technology and tool sets on with deep knowledge across the software development industry, a new product life cycle are the core competencies that will drive the most tangible AI outcomes. This will become even more evident as we see further rise of AI in the global and regional lineups of players in both Western market and Broadcast APAC, LatAm and Middle East.

Number two, we believe in the building AI responsibly, with trust, transparency, governance and measurement outcomes at the core. AI must deliver real outcomes with proper traceability and risk management.

Number three, we believe we are creating a new AI native engineering profile or North Star when it comes to talent development strategy, embedding AI intelligence and orchestration of agents directly into the development process. Over time, this role becomes the architect of AI native products and experiences augmented by agents to expand the scope of what teams can achieve in the future.

And finally, AI investments are in interest rates. Our approach is to invest in accelerators, tooling and people who help us deliver reliable outcomes on the promise of -- we do not sell foundation AI in a silo. Instead, we use our expertise and advanced IP to sell and deliver with AI, a with proven quality and execution that guarantees outcome and volume realization. This is true across our entire IP portfolio and is shaping into a structural blueprint we are calling AI Run.

AI Run transform represent our unified AI strategy that harmonizes our go-to-market motions with better activation across strategy and consulting, frameworks, and methodologies, talent and advanced tool sets. We have 2 key offerings: AI innovation business transformation and AI native engineering transformation.

The first offering is focused on optimized expand runs across AI Industry Solutions, AI horizontal solutions and AI product design and experience. The second offering is focused on mostering the DLC advancing the Agentic delivery life cycle known as ADLC and preparing for product development life cycle known as PDLC. This is nooses AI-native delivery, AI-driven modernization and PDLC agenetic solutions. We will be talking more about these offerings in the quarters to come.

Our AI Run blueprints, encompasses or AI frameworks and include our AI 360 AI factory Iron SDLC and AI adoption and education frameworks, which are agnostic and provide critical flexibility, which help EPAM deliver more enterprise-grade AI solutions at scale for our clients. Our AI/Run talent, houses or verticalized industry teams, ontologies and accelerators, which includes strategic advisory, data models, process modeling and solution built with partners. Most importantly, this is the scaffolding we are using to define the forward skills of the future and the parts for upscaling people and organizations.

And finally, our AI Run tools combines our best-in-breed IP assets, such as [indiscernible] and Iron platform with our strong AI, data and cloud ecosystem partner solutions and many available today on our partner marketplaces. You may have seen we also recently announced one of these tools, Agentic QA, which reset the gap between automated and manual testing, enabling clients to move faster by reducing lead times and costs.

What's impressive is that our agentic QA is shown to be 10x more efficient than manual testing, driving a 50% reduction in manual efforts and a 30% reduction in testing costs covering 90% of the manual checks performed on standard releases while ensuring a high degree of quality and precision.

Now turning to some client examples to illustrate some of our progress. This past quarter, we announced several collaborations with both new and existing clients which illustrate not only evolution of our client proposition, but also how EPAM is able to systematically address innovative needs while offering real volume. A few notable examples. Agentic customer service breakthroughs are real with [indiscernible], a major provider for telecommunications, cloud and Internet services in Germany.

By deploying EPAM's AI/Run transform Blueprint and leveraging Microsoft Azure, this client launched AI voice agents that handle over 100,000 calls weekly with the first agents going live under 3 months into production; two, our collaboration with Hugo Boss and our empathy lab studio is reimagining what means to be a sports fan in the age of spatial computing. This innovation is shaping the next generation of motorsport tendon lifting the bar how luxury fashion, sports and technology intersects.

We are blending our deep expertise in groundbreaking user experiences with gaming, funnel engagement, advanced data and analytics and working with our clients to help package the 2025 TV award-winning solution for the AI native age.

Three, finally, we are putting EPAM and NEORIS together in a way that goes beyond simple synergies. For a U.K.-headquartered global biopharmaceutical company, EPAM, with the addition of NEORIS recently became a global strategic supplier across a broad range of transformation pillars. A key joint win for us is in helping the client to build out a modern data and a center of excellence, which spans across multiple programs and new locations, including Ibero-America.

To close our operating momentum is strong. We are pleased with our performance throughout the year and continue to work on improving profitability. We are confident in the upward trajectory we have been working hard to build and sustain over the past several quarters and feel good about our Q4 positioning, which has improved over the past 90 days.

We are focused on what's right in front of us and finishing 2025 strong, which we believe should set up a solid foundation to build upon in 2026 and as we continue to work on expanding our organic constant currency growth rate. we are prioritizing client-centric, disciplined execution while bringing a new level intentionality on building verticalized and differentiated horizontal go-to-market offerings.

Looking ahead, we see our investments in upskilling differentiated AI playbooks, IP partnerships and new lines of services such as Agentic business process outsourcing, helping us to further capture new demand.

Jason, over to you.

Thank you, FB, and good morning, everyone. In the third quarter, EPAM generated revenue of $1.394 billion a year-over-year increase of 19.4% on a reported basis, exceeding the high end of our Q3 revenue guidance. On an organic constant currency basis, revenues grew 7.1% compared to the third quarter of 2024. We delivered another consecutive quarter of very solid year-over-year organic constant currency growth, reflecting ongoing steady execution.

Our growth in the quarter was driven by a continued shift to quality and accelerating momentum across our AI native, data, cloud and AI foundational initiatives. We're making early headway with the launch of our AI run transform strategy, which complements our underlying growth momentum, positioning us well to continue to capture demand.

Our outperformance in the quarter was broad-based. We also recently announced a new $1 billion share repurchase program. The underlying strength of our business and continued momentum coupled with our efficient free cash flow generation and a strong balance sheet enable us to take advantage of the current market dynamic while returning cash to shareholders.

Moving to our Q3 vertical performance. Five of our 6 industry verticals posted year-over-year growth, with 4 of the 6 growing double digits. NEORIS and first derivatives continue to contribute substantially to our financial services and emerging verticals.

Financial Services once again delivered very strong growth, up 32.7% year-over-year on a reported basis, with 6% organic growth in constant currency. Growth came from banking, asset management, and insurance clients. Software and [ Hi-Tech ] grew 19.1% year-over-year, driven by strong execution and broad improvement across large clients. Life Sciences and Health care increased 11.8% on a year-over-year basis. Revenue growth in the vertical continues to be driven primarily by clients in life sciences and med tech.

Consumer goods, retail and travel delivered 9.9% year-over-year growth, marking a notable rebound relative to prior quarters. The vertical also delivered solid sequential growth, which was driven by growth in consumer products and retail.

Business Information & Media was steady and delivered flat year-over-year revenue performance. Our emerging verticals delivered another quarter of very strong year-over-year growth of 38.9% with New York continuing to contribute to the verticals performance. On an organic constant currency basis, growth was 15.1%, primarily driven by ongoing strength in energy and materials.

From a geographic perspective, Americas, our largest region, representing 58% of our Q3 revenues, grew 16% year-over-year on a reported basis and 3.9% in organic constant currency. EMEA comprising 40% of our Q3 revenues increased 24.9% year-over-year and 11.8% in organic constant currency.

And finally, APAC making up 2% of our revenues increased 17.7% year-over-year and 14.2% in organic constant currency.

Lastly, in Q3, revenues from our top 20 clients grew 10.2% year-over-year while revenues from clients outside our top 20 increased 24.4%.

Moving down the income statement. Our GAAP gross margin for the quarter was 29.5% compared to 34.6% in Q3 of last year. Non-GAAP gross margin for the quarter was 31% compared to 34.3% for the same period a year ago. As a reminder, the prior year period benefited from a cumulative catch-up related to the Poland R&D credit. The third quarter of 2025 includes a single quarter's benefit of $13.2 million.

Additionally, for Q3 2025, we recognized higher variable compensation driven by expected stronger second half performance. combined with ongoing lower profitability associated with recent acquisitions, both contributed to the lower gross margin level. GAAP SG&A was 16.8% of revenue compared to 17.7% in Q3 of last year. Non-GAAP SG&A in Q3 2025 came in at 14.1% of revenue compared to 14% in the same period last year.

GAAP income from operations was $145 million or 10.4% of revenue in the quarter compared to $177 million or 15.2% of revenue in Q3 of last year. Non-GAAP income from operations was $222.8 million or 16% of revenue in the quarter compared to $222.9 million or 19.1% of revenue in Q3 of the previous year. Non-GAAP income from operations in Q3 2024 was similarly impacted by the Polish R&D credit.

Our GAAP effective tax rate for the quarter came in at 25.6%, and our non-GAAP effective tax rate was 24.1%. The Diluted earnings per share on a GAAP basis was $1.91. Our non-GAAP diluted EPS was $3.08 compared to $3.12 from Q3 of last year, reflecting a $0.04 decrease year-over-year. In Q3, there were approximately 55.8 million diluted weighted average shares outstanding.

Turning to our cash flow and balance sheet. Cash flow from operations for Q3 was $295 million. compared to $242 million in the same quarter of 2024. Although seasonality always has a positive impact from Q3 cash flow, cash flow from operations in the quarter exceeded the impact of typical seasonality and resulting in the highest level of quarterly cash flow from operations in EPM's history.

Free cash flow was $286 million compared to free cash flow of $237 million in the same quarter last year and also represented an all-time high. Cash and cash equivalents were just over $1.2 billion as of the end of the quarter. At the end of Q3, DSO was 75 days compared to 78 days for Q2 2025 and 74 days for the same quarter last year. Share repurchases in the third quarter were approximately 493,000 shares for $82 million at an average price of $167 per share.

Moving on to operational metrics. We ended Q3 with more than 6,100 consultants, designers, engineers and architects, reflecting total growth of 17.5% and organic growth of 6.4% compared to Q3 2024. In the quarter, we added approximately 300 net delivery professionals. Our total headcount at quarter end was 62,350 employees. Utilization was 76.5% compared to 76.4% in Q3 of last year and 78.1% in Q2 2025.

Now let's turn to guidance. Before moving to the specifics of our 2025 and Q4 outlook, I would like to provide some thoughts to help frame our guidance. Based on the strength of our Q3 and solid Q4 visibility, we are expecting a strong Q4 exit ending the year with higher organic constant currency growth rates than we forecasted just 90 days ago. At the same time, we are not expecting to see a significant release of excess client budgets and typical seasonality will also have an impact.

Compared to Q3, Q4 is negatively impacted by a higher number of holidays, vacations and potential furloughs. As a reminder, we acquired NEORIS first derivative in Q4 2024 in November and December, respectively. As per our usual reporting practice, revenues from these acquisitions were moved from inorganic to organic in Q4 2025 as contemplated in our previous guidance.

Facing a better-than-expected performance in the second half, coupled with improving visibility into Q4, we are raising the bottom end of the range for 2025 full year organic constant currency revenue growth and now expect the midpoint of the range to be 4.6%, an increase from the guidance we gave 90 days ago, which was 4% at the midpoint of the range. While driving top line revenue growth, we also remain focused on improving profitability. While there is more work to be done, we've been pleased with the results of our ongoing focus on improving account profitability, which is evident in our improved profitability outlook for Q4 and full year 2025.

Lastly, we continue to work on improving utilization and we continue to reduce isolated pockets of bench while adding that headcount to support growth. Our guidance continues to assume that we will be able to deliver out of our Ukraine delivery centers at productivity levels similar to those achieved in 2024.

Moving to our full year outlook. We now expect revenue to be in the range of $5.0 million to $5.45 billion, reflecting a year-over-year growth of 15% at the midpoint, with inorganic continuing to contribute approximately 9.1% for 2025. Based on current spot rates, foreign exchange is now expected to have a positive impact on revenue growth of 1.3% and we expect year-over-year revenue growth on an organic constant currency basis to now be 4.6% at the midpoint.

We expect GAAP income from operations to now be in the range of 9.4% to 9.7%, and non-GAAP income from operations to now be in the range of 15% to 15.3%. And we expect our GAAP effective tax rate to now be 25%. Our non-GAAP effective tax rate, which excludes the impact of benefits and shortfalls related to stock-based compensation will continue to be 24%.

And Earnings per share, we expect the GAAP diluted EPS will now be in the range of $6.75 to $6.83 for the full year, and non-GAAP diluted EPS will now be in the range of $11.36 to $1.44 for the full year. We now expect weighted average share count of 56.2 million fully diluted shares outstanding.

Moving to our Q4 2025 outlook. We expect revenue to be in the range of $1.38 to $1.395 billion, producing a year-over-year growth of 11.1% at the midpoint of the range. Our guidance reflects an inorganic contribution of 4.3% with a 2.4% positive FX impact during the quarter, producing a 4.4% organic constant currency growth rate at the midpoint of the range.

For the fourth quarter, we expect GAAP income from operations to be in the range of 10% to 11% and non-GAAP income from operations to be in the range of 15.5% to 16.5%. We expect our GAAP effective tax rate to be approximately 24% and our non-GAAP effective tax rate to be approximately 23%. Earnings per share, we expect GAAP diluted EPS to be in the range of $2 to $2.08 for the quarter and non-GAAP diluted EPS to be in the range of $3.10 to $3.18 for the quarter. We expect a weighted average share count of 55.1 million diluted shares outstanding.

Finally, a few key assumptions that support our GAAP to non-GAAP measurements for Q4. Stock-based compensation expense is expected to be $44 million. Amortization of intangibles is expected to be approximately $18 million. The impact of foreign exchange is expected to be $1 million. Tax effective non-GAAP adjustments is expected to be around $16 million. We expect a tax shortfall related to stock-based compensation of around $1 million. Severance driven by our cost optimization program is expected to be around $10 million. And one more assumption outside of our GAAP to non-GAAP items, we now expect interest and other income to be $3 million for the remaining quarter.

We remain focused on driving revenue growth and enhancing profitability. -- we are confident in our strong positioning as we enter Q4. We will continue to run EPAM efficiently, maintaining our focus on both growth and profitability throughout the remainder of the year. Thanks again to all our employees for their dedication and focus, on serving our clients and driving results for EPAM.

Operator, let's open the call for questions.

[Operator Instructions]. And your first question comes from the line of Maggie Nolan with William Blair.

So I wanted to start with the push that you mentioned into AgenticBPO. Do you intend to enter that space with proprietary products? Or can you talk about maybe build versus buy decisions from clients for processes?

And then just like the ability to automate this, how that may be or may not be any different from the robotic process automation wave that we saw several years ago that ended up being sort of difficult to accomplish given the variability of processes.

Good morning, Maggie. Thank you for the question. Actually, it's a really interesting subject. It's early days for us. As you know, we made 2 acquisitions in this space. First was first date where the line of business better in business services, that's where we really went after that acquisition with the pieces that we could automate with Agentic AI, the KYC and fincrime elements of their business.

The second acquisition was [ Lynxus, ] which was this year, and it was a small BPO to really understand the space itself. So going back to what we are seeing. We are seeing our clients are keen to try out, but it's early days. We are using EPAM build platform itself, in order to really deliver the automation, but it's a very different than RPO in the past. What we try to do is we're trying to experiment on simple and more complex agentic flows, which requires high level of degree of engineering going beyond simple RPO or BO or simple [indiscernible] capabilities.

We don't know yet where the market will go. We don't know the very best when it's leading. Right now, we are seeing a big momentum from the clients, which we are -- but it's a very small sample that you've been talking about in its early days for us.

Your next question comes from the line of Bryan Bergin with TD Cal

I wanted to ask about is we think on your 4Q exit rate considerations. And I think beyond that, as we move forward to 26, I should be thinking about growth potential? And specifically, if you can kind of comment on the impact of bill bays and furloughs and things like that as you go through 3Q and 4Q and then into 1Q as well as just any other important factors such as how growth in NEORIS and [ FP ] may affect your organic growth rate as you fold those in going forward?

Yes. Brian, this is Jason. So as I think most people know, there's a negative impact from a seasonality standpoint, if you look at sequential Q3 to Q4 -- and so that impact is kind of 3 things, which is 1 is fewer build as, you've got more vacation. And then you also have a higher degree of orals. So all of those things produced some tens of millions of kind of headwind on sequential growth Q3 to Q4.

When I look at the performance of our business throughout 2025, Q1 to Q2, Q2 to Q3 and Q3 to Q4, if you adjust for foreign exchange and you adjust for sequential factors, our sequential growth rate has actually been surprisingly consistent, the other thing I would add is you've got probably a little bit of headwind on foreign exchange sequentially Q3 to Q4. Just to sort of maybe answer a question that you hadn't asked, is that our guide at the midpoint of the range contemplates, I think I said 4.4% organic constant currency growth. If we operate at the high end of the range in Q4, we'd be at about 5% organic constant currency growth.

Your next question comes from the line of Jason Kupferberg with Wells Fargo.

So the organic constant currency in the quarter, obviously, the 7%, I think, kind of best-in-class now among the peer group. But just to kind of build on the last question, I guess, can you kind of break down the sources of what looks to be some deceleration in the Q4 on a year-over-year basis, you just walked us through the sequential Jason, I just want to make sure you kind of -- we have the puts and takes right there and then how we should just at least directionally be thinking about where the organic growth can go in '26 versus, call it, a 4.5% exit rate for this year.

Okay. Still -- yes, so from a year-over-year standpoint, I think maybe the biggest difference is we see clients continue to make investments and move forward on programs. What we're not seeing is the release of excess budget at the end of the year, the way we saw in Q4 of last year. And so I think that is probably the biggest difference. Clients continue to invest, but there isn't a big kind of opening up the wallet at the end of the year.

From a demand standpoint, it still feels broad-based and it still feels, again, like we're continuing to see growth in financial services, high tech and also kind of the emerging energy portion of the portfolio [indiscernible] thoughts on 2026? Or -- at our content, we believe that organic country will be higher than this year. we see the moment is driven by very much, as we mentioned, some of the E and the F fundamental up until build out the foundational build-outs. And we see the pipeline for 2026 plating vetiver nicely at this point of time. It's early days, but we see positive signals.

Your next question comes from the line of Jonathan Lee with Guggenheim Partners.

Welcome to the first, hopefully, many earnings calls as CEO it's interesting to hear that clients are redirecting work from partners who failed to deliver effectively highlighting that you're winning share from peers. Can you help size that contribution and unpack your competitive advantage here versus your peers? And how do you expect to maintain that gap going forward?

Jonathan, thank you very much for the kind words.

I don't think we can size it yet, right? I don't think we can size it how much work is actually redirecting to us. We are seeing that major programs, competitors who failed to deliver. Now clients are interacting the work to us -- and the reason why because it's actually delivering these solutions in enterprises, much more difficult than what it seems on a YouTube short retic dokie. -- unitary deep engineering skill set capabilities across the foundation elements on data, on data platforms on cloud or enterprise platform themselves or actually modernization in order to deliver on that as we to consider the cost you need to end cost engineers, but stopes are quite expensive.

You need to consider risk aetnactual reliability and performance. All of these requires deep engineering skills. So how are we going to keep our advantage because we are investing in our people is investing in our in our engineering talent, investing into tooling methodologies and investing into the playbooks, and we actually try and get out and experimenting on ourselves. That's why we believe being that the customer is being the client sale is so important for our future.

[Operator Instructions] And your next question comes from the line of Jim Schneider with Goldman Sachs.

In some of your public commentary and interviews recently, I think you've kind of struck a cord about focus on costs for the company. Can you maybe give us a sense about how that focus on cost is being manifest across the company and how that might materialize in terms of SG&A or other kind of cost savings or margins over time?

Thank you very much. So I think in the last 3 of months, I was talking about the focus on pyramids. We focus on actually balancing the pyramid. -- when we diversified our delivery. We actually went into certain geographies due to certain locations, we were not able to really create the ideal pyramid structure. Now we're working on that and we're trying to balance the rebalancing the com is actually allowing us to really focus on and bring down some of the costs.

Second is also the CEO and putting more emphasis on profitability on the deals emphasis on the capabilities to actually deliver profitable projects profitable growth, which is really manifesting for us selecting the right clients being more picky and more selective on the field, what we take, which we can only do because our demand is changing and the demand is up for us and that's what you are seeing the effect of that.

Yes. I think I'll add a piece on this as well. So as FB indicated, with that focus, we are seeing an improvement in account margin in the second half of the fiscal year. And I think probably what is most notable is throughout the year, we've been talking about a 15% midpoint of our profitability range. And at this time, we feel pretty strongly that we'll operate in the upper half of the 14.5% to 15.5% range. And as we talked about in my prepared remarks, is we expect to operate in the 15% to 15.3%. And that is a result of a number of things, including a better account margin as we work through the fiscal year.

That's helpful. And then maybe as a follow-up, you gave many data points relative to your AI project traction and increasing size of deals in AI. Can you maybe give us or level set any kind of quantification in terms of the size of your average AI project today? And then where you hope it may go in, say, 2 years?

I think in our prepared remarks, we had kind of explain how the projects are evolving, moving from protofconcepts to medium- to large-scale engagements. So it's an evolving set. We have hundreds of engagements right now. And most engagements typically start on a solid the proof of concept and also they're scaling up some of them get into the tens of millions of dollars range as we go forward. We do see most of our top 100 clients are actually engaging with with large AI initiatives, which looks like. So it won't mean that right now, we are executing large projects, but they have large initiatives.

We are hoping to -- most of our revenue will be coming in the coming years from these initiatives, either because of transformation, either because introducing or creating the foundational event for the AI deployment, which is right now 1 of the main driver for our business.

Your next question comes from the line of Jamie Friedman with Susquehanna.

Some of your comments were considerably more technical than what some of us sort of accustomed to, and we appreciate that because that's where the industry is going. So we'll adjust. I wanted to ask specifically about a genetic delivery, life cycle management. Yes, that one. So what -- in terms of like the vectors or phases that the customers need in order to proceed with the genetic delivery, how would you describe the chronology of that aspect and the relative size of that 1 in delivery life cycle relative to some of the others that you mentioned.

Thank you for the question. So we need to start considering is when clients were just delivering software products, they still have to master SBLC cycles cost clients. Most of our clients and most of the industry haven't really fully mustered the SBIC. When you start deploying agenting capabilities and trying to automate large scale of processes and works using agenting AI capabilities. You need to really following an agent development process, agent life cycle. And it is also conflicts even more complex than compared to SDLC. So it's not a simple of impost looks in order to make it really work in the enterprise, right?

So I know that everybody believing that this is a simple step and adjusting development life cycle. It is a complex of any SDLC lifestyle, and you need to really oster it. And this is going to -- we think it's going to be a bigger problem because you were going forward than fostering PLC. The reason being is now no longer just touching on certain elements of your software spec, but now you really need to consider how you automate processes, which you never automated before.

You are going to step into automating previously very manually intensive components and automating those are very, very complicated and difficult and ever prudent process itself, migrating and it's not just you need to upskill your teams who are doing it. And it's no longer just engineers who we're talking about. You need to also introduce the right tooling, the right processes across the enterprise. And if you want to really take -- get the benefit and it also started considering not just the element of can I actually automate this during automation, I really also want to achieve a certain line because if the automation results into a higher cost, then you kind of deliver on your product.

So we think this is a large shift. It is not going to be a very quarter requires tremendous amount of work to make apron. And companies will have to partner with organizations such as income to actively do that in what we call an ER factory model where you are introduce the foundation, build a foundational component build the right process in place, the right governance itself and then you go process by process and building the agented operations.

Your next question comes from the line of David Grossman with Stifel.

Just kind of looking at a high level of the business and how it's been performing. It looks like the revenue per head is up for the first time in 3 quarters despite flat utilization. So -- maybe you could just talk a few minutes about what's going on under the covers here? Is it geographic mix, where you're delivering from? Is it perhaps growth outside the top 20, which has been very strong and historically a pretty good leading indicator of kind of new business activity and funnel. So maybe you could just illuminate what's happening there.

David, good question. And one of the things about the revenue per head count number is that there is a lot of, I guess, what I'd have to call noise. And so utilization, as you pointed out, is 1 of the factors on exchange actually impacts as well. And so it is a number that I think most people will look at and try to sort of draw a conclusion from how much price uplift is the company getting as the increased revenue per head count. But I think there's more noise in it that I think people realize, okay, -- but as we look at our number and I subtract out some of these factors that I just referred to.

What we're really seeing is we are getting somewhat better price than we've gotten in the past. Some of that is probably mix related Again, I'd say more kind of customer mix. And as we talked about, it's consistent with the account margin improvement that I referred to earlier in the call. And so again, some of it is foreign exchange but some of the really is actual price.

And when did the contract profitability, when -- is this the first quarter that it really inflected -- or has it been inflecting and just not visible.

Yes. I think we've been working on it throughout the year. I think we've talked about it a fair bit last quarter. And so it's all the things that drive that, including pyramid -- and again, the pyramid that they will probably have more of an impact on 2026. And I think it's just really beginning to probably show up in this discussion as we see both solid profitability in Q3. And what we're now expecting is much better for offerability in Q4 than we originally anticipated 90 days ago.

And so again, some of that is account profitability improvement. And I think, as I said earlier, I was very convinced that we were going to operate at about 15% this year. And now, as you heard me, we're talking about operating in the 15% to 15.3% range.

Next question comes from the line of Bryan Keane with Citi.

Congrats on the solid results. Jason, let me just follow up on that discussion. What does that mean for headcount growth going forward in this model and maybe even revenue per head going forward? How should we think about that as we get into the fourth quarter and into next year? And then my second question is just the organic growth of FD and NEORIS, maybe you can help us with that.

Yes. So you would -- you'd expect us to see us add headcount in Q4. It will be similar to what we've been doing throughout the year, where we do have some pockets of ex expense that we continue to kind of reduce and we'll be making net additions globally. And so you'll see an increase in head count in Q4.

From an FD and our standpoint, be talking about very early in the year, the lead customer at ERS was impacted early by U.S. tariffs and kind of generally kind of political and economic instability in Mexico. And so we definitely see a decline in that customer on a year-over-year basis. And so it probably has a modestly negative impact on organic constant currency growth. But both of those businesses have kind of stabilized at this point, and we think there's a lot of strategic benefits. But again, particularly with that big customer from NEORIS has a modestly negative impact on organic constant currency growth for.

Okay. That's helpful. And then any comments on revenue per head on what that might look like going forward?

So it's always -- utilization and foreign exchange really moves the needle on this one. So it's difficult for me to tell. What I will just do is comment on pricing. What we do think is that pricing is better at this time than it was last year at the same time. maybe it hasn't improved a lot over the last 90 days, but it is a somewhat better pricing environment. And we are expecting modest price increases as we enter 2026. Again, maybe not at the level that we would have gotten 4 or 5 years ago, but in kind of the low single-digit kind of range, which is [indiscernible] environment then certainly, 2023 was, so...

Next comes from the line of Sean Kennedy with Mizuho.

Very nice results. Great to see the growth momentum in the business. So I have a follow-up on the AI projects. I appreciate it's still early, but how does the AI work differ from EPAM's non-AI projects? in terms of duration and profitability now? And how do you think that could evolve in the future? Also, are you seeing certain clients in terms of size and industry engage in AI projects more than others? mine.

So I think -- the project, I don't think it's fundamentally different in required to see engineering discipline, engineering capability. It might have more skew towards data or so towards data platform or the capability around AI. So it requires a little bit different engineering as different understanding.

On the other hand, it also requires a combination of the business domain understanding. And really you need to combine it because now you are start automating processes which were not automated before. So building the platform is probably very similar to what we've done in the past. -- preparing the foundation, cloud migration, data platform build-out, data engineering or building -- modernizing the back end. This is very, very typical for EPAM. But when you are really start automating new processes, that's where the main capabilities. select people is an understanding of how to automate that process and understand the specific industry is where needed.

Profitability wise, at this point, probably similar than others. But I think there is a clear potential for later for better profitability also you are potentially not just delivering the projects maybe on a material basis, what we can export alternative business models, too.

And I'm hoping, of course, that with these kind of projects, we are able to charge probably higher rates to begin with.

Your next question comes from the line of Darrin Peller with Wolfe Research.

This is [ Paul Bragg ] on for Darrin. Jason, I appreciate all the color on headcount. Just curious, longer term, if you think the greater usage of AI will perhaps impact the need to hire in any way? And just to what degree as you increasingly embed AI internally? Is that perhaps allowing for lower delivery requirements?

I'm going to turn that one over to FB.

So we continue to be that the to AI does create efficiency against your -- the demand increase or outstream any kind of efficiency gains that we are seeing. So we believe that going forward basis, we continue to hire continue to grow. -- or organization will grow, we need to bring in maybe differently trained teams.

And we also bring them on is anticipating that your next question, we're going to continue ranking in junior engineers because with the right training, with the right background with the right education, we do believe that the balance pyramid is the best serving not just our clients, but also intact.

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

It's Antonio on for James Faucet. I wanted to ask more on -- back to the like AI part of the equation. Just on on your build versus buy strategy? I know that you had touched on that earlier, but I'm just trying to get a sense of like what is the growth like of your like Gen AI like revenue?

Yes, a little bit hard for me to tell exactly what you're looking for there, but -- what we continue to see is this strong sequential improvement in revenues for what we call the G&A native. And so that continues to be kind of double digits sequentially. We saw again during this quarter. And then as that has been talking about and maybe you want to add some color is that we continue to see strong growth in the, what we call the foundational side, which is the cloud modernization and data and that piece of the business.

So we continue to see lots of demand coming in. As Jason mentioned, the AI native revenue is growing sequentially very strongly, up double digits. -- we are seeing our clients building more solutions and actually the taking advantage of AI software engineering feature or capability functionality because of functionality close to it decreases, they're actually building more. So we believe that before going forward basis, they will build more than buys actually. -- the equation or the percentages will start skewing towards pillars the buy side. So that's -- that's our thesis, and we are seeing evidence around that.

Got it. Got it. That's helpful. And then as a follow-up, I wanted to ask on the software and high-tech vertical. What are some of the key drivers for that growth? I know it's grown pretty nicely sequentially. Any like onetime factors there? Or is this just a broadening out of demand there?

Yes. I mean we've had a few large customers that are growing nicely. We've got 1 client that particularly has a large kind of platform program that they've been investing in -- you won't see the growth rates stay like that forever in that space, but we've been pleased with the ongoing revenue generation from the Hi-Tech portion across.

At this time, there are no further questions. I will now turn the call back over to FB for closing remarks.

Thank you very much for attending my first earnings call. Really, I would like to thank all the EPAM employees for delivering a successful quarter, and we talk next time in 90 days approximately. Thank you.

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