Cognizant Technology Solutions Corp (CTSH) — Q1 2026 Transcript

Thank you, operator, and good morning, everyone. Welcome to Cognizant's First Quarter 2026 Earnings Call. I'm joined today by Ravi Kumar, Chief Executive Officer; and Jatin Dalal, Chief Financial Officer. By now, you should have received a copy of the earnings release and investor supplement. If you have not, copies are available on our website, cognizant.com. Before I begin, I would like to remind you that some of the comments made on today's call and some of the responses to your questions may contain forward-looking statements. These statements are subject to the risks and uncertainties as described in the company's earnings release and other filings with the SEC. Additionally, during our call today, we will reference certain non-GAAP financial measures that we believe provide useful information for our investors. Reconciliations of non-GAAP financial measures where appropriate to the corresponding GAAP measures can be found in the company's earnings release and other filings with the SEC. With that, over to you, Ravi.

Thank you, Tyler. Good morning, everyone. Thank you for joining us. We delivered a solid first quarter with revenue growth in the upper half of our guidance range, expanded adjusted operating margin and strong bookings growth. I believe our work to become the world's permanent AI builder is resonating, demonstrated by our first quarter performance. Looking at the quarter's highlights. Revenue grew 3.9% year-over-year in constant currency, led by strong performance in North America and driven in part by the ramp of recently won large deals. From a segment standpoint, Financial Services grew more than 10% year-over-year in constant currency, driven by strong demand across banking and insurance clients. Q1 bookings grew 21% year-over-year. We signed 7 large deals with TCV of $100 million or greater, including 1 mega deal valued at more than $500 million. Importantly, we continue to drive profitable growth as adjusted operating margin expanded year-over-year for the fifth straight quarter. Adjusted EPS of about 14% year-over-year was ahead of revenue growth. And we just announced a definitive agreement to acquire Atria, a global IT managed services provider and a specialist in AI infrastructure build-out with deep expertise in managing data center infrastructure, enterprise networks and digital workplace technology. Upon closing, we believe Atria will add a critical layer to our AI Builder technology stack. We achieved these results against a softening demand environment. Market conditions have become more complex since the start of the year, and we expect the impact from heightened macroeconomic uncertainty to persist in the near term. However, while clients are appropriately cautious about making large investments in this environment, they recognize AI's transformative potential and the value of strategic partners. This transformative potential is reforcing our industry's first principles, which underpin our evolving posture as an AI builder. The industry's first principles were born out of an enterprise reality. Technology was so transformational and complex that companies needed help with optimizing the use of technology to meet their business objectives. IT services companies emerged to solve these problems at scale and over time, helped create many of the greatest business architectures over the last 50 years. With AI, the fundamentals are shifting. Software is penetrating deeper into enterprises and our clients now expect more value and measurable outcomes. The old fundamentals are still relevant, but there must be a reforge for a new reality. Cognizant has already embarked on this transition, which demands four significant shifts that redefine the role of IT services firms. First, we are evolving towards owning the full stack of capabilities required to design holistic bespoke AI systems from a systems integrator to an AI builder. Second, we are reimagining our talent, moving away from the traditional pyramid towards interdisciplinary teams that operate at the intersection of domain operations and technology. Third, we are shifting our economics from labor-based to outcome-based models that align our success directly with our clients. Our combined fixed-price and transaction-based portfolio has continued to grow in proportion over the past 3 years, reflecting our ongoing focus on driving nonlinear revenue opportunities. And finally, we are evolving away from simply delivering projects to underwriting operational results for our clients at scale, taking full accountability for the business impact we create. Last quarter, I talked about the velocity gap — the gap between massive AI infrastructure spend and business value realization. Our mission is to be the AI builder who bridges this gap. Our AI builder stack is the connective tissue that translates our strategy into measurable client outcomes. It combines our proprietary methodologies and the science of context engineering with a curated ecosystem of strategic partners and our own differentiated platforms and IP. Our vision is to reimagine enterprise operations, rebuild workflows and break functional silos to unlock AI-native ways of working. We aim to do this by bringing human effort and agentic capital together in a managed, governed and client-contextual delivery model. Some of our pioneering clients have started to progress from AI productivity to unlocking new experiences, products and services. Platforms are key to our AI builder stack. Fueling our platform strategies, our award-winning AI Labs was awarded 3 new patents, bringing its total number of patents to 65 in the U.S. and 88 globally. Our AI Lab continues to sense the future and partner closely with our clients, platforms and products group, and solutions teams to translate frontier research into industry-relevant use cases. To complement our internal investments, we launched the Cognizant Innovation Network, a new corporate investment arm that will back early-stage AI start-ups. We plan to initially focus on investments in AI, data, cybersecurity and cloud technologies and portfolio companies will gain direct access to Cognizant's deep industrial expertise and its enterprise client base, creating a powerful ecosystem for mutual growth. We are progressing towards the AI builder vision through our 3-vector strategy: AI-led productivity, industrializing AI and identifying the enterprise. To date, we have well over 5,000 AI engagements across the 3 vectors, up from approximately 4,000 exiting December. Beginning with Vector 1, we are addressing a multitrillion-dollar opportunity of AI-led productivity across several value pools by helping clients build classical software in new ways, accelerate software development, eliminate technical debt and modernize legacy systems. Our differentiated approach to autonomous software is rooted in engineering-led productivity powered by leading strategic partnerships like Anthropic Claude, Google Gemini, Microsoft Copilot, OpenAI Davinci and OpenAI Codex. This approach has enabled nearly 40% of our code to be AI assisted. Cognizant platforms play a critical role in scaling these productivity gains by accelerating software development with FlowSource, reverse engineering legacy code using agent-based capabilities through SkyGrade and automating incident management with neuro IT operations. A great example of our platform strategy at work is with one of the nation's largest health companies where we now underwrite the integrity of their claims process. Our AI solution automates the validation of over 54 million provider contract updates annually, directly reducing revenue leakage and solving a problem that was previously intractable at scale. Some of the early value pools in Vector 1 where we are seeing client momentum are related to legacy debt takeout, like mainframe modernization, SAP S/4HANA migrations, autonomous software engineering, digital workplaces and autonomous infrastructure services. For example, we are working on a highly complex greenfield SAP S/4HANA transformation at a global scale, focused on modernizing the enterprise core for a North American global pharma leader. What really sets this project apart is our use of a customized AI accelerator that automates both business and IT data validation, replacing a fragmented manual process with a scalable, audit-ready and robust solution significantly cutting validation time and effort. For a leading European telecom operator, Cognizant delivered an AI-powered Oracle Cloud ERP transformation, unifying finance, procurement and supply chain on a single cloud-native platform, achieving 25% faster time-to-market and 40% faster deployment through agentic AI and automation. And with Daimler Truck, we will use Cognizant WorkNEXT to transform and modernize its global workplace services. Our multiyear partnership aims to leverage artificial intelligence and automation to enhance workplace operations across their global factories and offices. As our AI productivity capabilities mature, we are increasingly applying token metering at a project or an individual level to provide early insights into usage patterns, model management and optimization of infill costs. Vector 1 continues to be a primary driver of our large deal momentum. And as a result of the cost savings and shared productivity generated in Vector 1, we're starting to see increased velocity in Vector 2 and Vector 3 opportunities. Let me share some examples. In Vector 2, as we integrate enterprise AI into enterprise landscapes, platforms provide the foundation to move AI from proof-of-concept into production at enterprise scale, managing the full agent life cycle with neuro AI engineering and context engineering. This spans several areas, including data engineering, AI foundry, cybersecurity and integrating AI into the infrastructure and cloud stacks. As an example, with data engineering for a leading U.S. health care client, we deployed an AI-based data validation system to optimize the distribution of pharmaceutical shipments. The solution uses predictive models to validate data before dispatch, reducing downstream errors in the logistics chain and improving reliability across operations. One of the value pools we see in Vector 2 and a key element of our AI builder stack is context engineering. Cognizant's approach to context engineering is to build native work graphs by going deeper into how humans work, make decisions and navigate exceptions in their daily business processes. We're also applying context engineering at a top wealth management firm with an advanced proof of concept where AI agents are being designed to work alongside financial advisers handling routine interactions and back-office tasks so that financial advisers can focus on client-facing activities. Finally, in Vector 3, we are accelerating development of our AI-native products to unlock new agentic labor pools across vertical and functional domains and into core operations. The value pools in Vector 3 are significantly expansive opportunities across business operations of enterprises to embed agentic capital for productivity, experiences and new services. In health care, for example, we are developing agentic solutions that accelerate and improve the accuracy of prior authorizations to support better patient outcomes. Additionally, we are building on our TriZetto product portfolio in a strategic partnership with Palantir to advance an outcomes-based intelligence platform that embeds AI-driven decisioning directly into health care operations. We're also sensing a broad structural shift as AI moves beyond digital workflows to governing physical systems and environments and infrastructure. This is accelerating the convergence of physical AI, agent AI and governed enterprise intelligence, enabling autonomous operations across sectors. Cognizant is investing in the architecture, platforms, partner ecosystem and industrial domain expertise for physical AI. Business operations-led offerings are central to this evolution. We're expanding AI-enabled services across sales, finance, marketing, service operations horizontally and health care, financial services and banking operations on the vertical stack. Examples include the recent launch of Autonomous Customer Engagement with Google to support outcome-based human-AI workforce models across industries and the combined value proposition of TriZetto and Palantir to identify healthcare operations improvements. Across all three vectors, as the importance of platforms grows, we are evolving our commercial models towards fixed and outcome-based pricing, enabling Cognizant to recognize the added value of assets, IP and accelerators that we bring. This is an important pillar of our first principles, shifting our economics to managed services and outcome-based models. Consistent with the shift, we delivered 2.5% and 5% increases in trailing 12-month revenue and adjusted operating margin per employee, respectively. We are beginning to see the emergence of AI-infused rate cards where pricing reflects a blended model of human effort and digital effort. With several clients, we are exposing tokenized rate cards that price work along a continuum from fully human-led discovery to hybrid to increasingly autonomous agentic delivery. This model is intended to turn our outcome-based economics into a true partnership that aligns value creation with shared results. Execution across the sector requires the right organizational structure and powerful innovation and talent. This brings me back to another important element of our first principles, reimagining talent away from the traditional pyramid and towards interdisciplinary AI-augmented teams. To fuel the shift, we have launched an integrated AI skilling stack for our entire organization. It begins with our AI Builder career program, which maps every role at Cognizant to a future-ready AI job family with defined pathways and targeted learning plans aligned to how roles are evolving. This is powered by Cognizant and SkillSpring, our new AI-native learning platform designed to redefine learning in the AI era and cultivate AI-ready talent at scale for our associates and our clients. Progress is being tracked for each associate's personal AI fluency dashboard — a real-time context-engineered view of AI readiness across various dimensions, including AI skills and proficiency, training and certification, AI tools and token usage, innovation and project experience. To enable us to execute on these principles with the speed and the agility the market demands, we are initiating a new program called Project LEAP. This program is designed to accelerate our transformation to the operating model of the future by funding investments in our AI capabilities and partnerships, integrated offerings and platforms, reshaping productivity and upskilling our workforce. By fostering a workforce that is AI-enabled and equipped with future-ready skills, we aim to create a more agile, scalable and cost-effective operating model. Even as we make these changes, we are continuing to invest in growth through acquiring new talent. We hired around 20,000 freshers in 2025 and plan to hire a greater number in 2026, providing a strong pipeline of future talent aligned to how work is evolving and shaping a broader pyramid with a shorter path to expertise. The LEAP program reinforces our commitment to be in the winner circle of revenue growth and supports our journey of expanding margins. To conclude, I want to leave you all with this. Our conviction in the long-term opportunity emerging with enterprise AI adoption has never been stronger. In our industry, the real work happens inside complex systems across legacy environments, regulated processes, global teams and mission-critical operations. Large enterprises do not transform overnight. They undeniably need trusted partners who understand their systems, context, risks and people. And that is the role we intend to play as an AI builder, bridging the gap to enterprise value. To win, we must move fast and stay agile, which is exactly why Project LEAP is so critical. We are reforging our first principles, enabling an AI-era future operating model, equipping our go-to-market teams across the three vectors, adopting new engagement models to deliver value to clients and adopting talent through a blend of digital and human effort. We remain confident the portfolio and capabilities we are assembling can drive sustained progress towards Winner Circle performance including top-tier growth, consistent margin expansion and EPS growth outpacing revenue growth. Before I turn the call over to Jatin, I want to thank our associates for their dedication, our clients for the continued trust and our shareholders for your confidence as we strengthen our foundation to create durable long-term value.

Thank you, Ravi, and thank you all for joining us. As Ravi noted, our first quarter results demonstrate that our AI builder strategy is resonating in the market. In Q1, we delivered revenue growth in the upper half of our guidance range, basis points of year-over-year adjusted margin expansion and adjusted diluted EPS growth of 14%. First quarter bookings growth of 21% was one of our strongest in recent history. This performance demonstrates our focus on execution and our ability to deliver value for clients. As Ravi mentioned, the market remains complex but the dynamics are not universal and vary by industry. Financial Services is benefiting from robust investment cycles, while policy changes are creating regulatory uncertainty in key areas of health sciences. In Products and Resources, trade policy uncertainty and supply chain disruptions remain realities. That said, broadly speaking, we believe the shifts we are seeing in client demand play to our strengths. And we remain confident in our position as a strategic partner to our clients as they navigate a complex macro environment and the rapid pace of AI innovation. Now moving on to the details of the quarter. In Q1, revenues of $5.4 billion grew 3.9% year-over-year in constant currency, driven by a ramp of large deals across our North America region and Financial Services segment, along with the strong performance in the U.K. We have seen increasing demand for our AI and analytics services driven by AI readiness and innovation budgets. Growth also benefited from revenue from third-party products associated with our integrated offering strategy, and inorganic contribution from our three cloud acquisitions. By segment, Financial Services led with over 10% year-over-year growth in constant currency balanced across banking, financial services and insurance customers. We saw both healthy discretionary spending and sustained large deal momentum driven by North America. Health Sciences performance remained resilient. Growth was negatively impacted by approximately 300 basis points year-over-year due to lower revenue from third-party products associated with our integrated offering strategy. Excluding this impact, services in health sciences grew at a similar level to the company. Products and Resources was stable despite headwinds from macro, geopolitical and trade policy uncertainty. We continue to see emerging client demand in areas such as predictive supply chains, agent commerce and hyper-personalization — use cases where AI has the opportunity to create real differentiation. Physical is an early-stage but fast-moving category, and we are positioning ourselves to capture this opportunity as client adoption accelerates. Within Communications, Media and Technology, our revenue with technology customers continues to grow. AI adoption is driving demand for engineering, modernization and platform services. In the Comms and Media sector, the environment has been more measured with added pressure from client-specific dynamics tied to strategic shifts at a large customer. In Q1, segment growth was driven by revenue from third-party products associated with our integrated offering strategy, which contributed approximately 10 percentage points of growth. Turning to bookings. We delivered another strong quarter of large-field bookings. We signed 7 large deals, each with TCV of more than $100 million in Q1, including 1 mega deal with TCV in excess of $500 million. On a trailing 12-month basis, bookings grew 11% and represented a book-to-bill of 1.4. Annual contract value was flat as deal duration increased in the quarter, reflecting large deal mix and continued softness in smaller discretionary projects. Our pipeline remains healthy and broad-based. We continue to see strong demand for cost takeout, vendor consolidation and AI-led services. Moving on to margins. Q1 gross margin decreased by 80 basis points year-over-year, reflecting impact of our integrated offering strategy and increased compensation cost. We remain very focused on driving gross margin improvements over time. This is an important objective of the Project LEAP program. First quarter adjusted operating margin of 15.6% increased by 10 basis points year-over-year. Our ongoing focus on operational efficiency and benefits from the Indian rupee depreciation helped to more than offset the impact of our integrated offering strategy, M&A investments and increased compensation costs. Now to additional details on EPS, cash flow and capital allocation. First quarter adjusted EPS was $1.40, up 14% year-over-year. DSO of 84 days increased 3 days sequentially and year-over-year. First quarter free cash flow was approximately $200 million, impacted by a larger bonus payout this year and in line with our expectations and typical Q1 seasonality. During the quarter, we returned about $600 million of capital to shareholders through share repurchases and dividends. We ended the quarter with cash and short-term investments of $1.5 billion or net cash of $949 million. Now turning to guidance. For the second quarter, we expect revenue to grow 3.2% to 4.7% year-over-year in constant currency. This includes approximately 150 basis points from our recently completed acquisitions, including a partial quarter contribution from Atria that we just announced. Our second quarter guidance includes a more cautious near-term view of discretionary spending based on recent global events and trends. Our full year revenue guidance is unchanged at 4% to 6.5% in constant currency. The macroeconomic environment remains dynamic, and our guidance reflects a range of outcomes. We expect large deal ramps and two full quarters of Atria contribution to be meaningful second-half drivers. At the midpoint, we assume some improvement in discretionary spending in the second half of the year compared to our Q2 assumptions. Our strong bookings momentum, along with a 1.4 book-to-bill ratio gives us confidence that we are winning in the market. Our full year guidance assumes recently completed acquisitions will contribute approximately 150 basis points to revenue growth, reflecting contribution from both CreeCloud and Atria. Beyond this, our M&A pipeline remains healthy and active, and we see a number of interesting opportunities that are consistent with our AI builder strategy. As always, we'll be disciplined and deliberate but remain well positioned to act if the right opportunities emerge. Now a few more details on Project LEAP. This is an important initiative to accelerate our path to a more agile and AI-enabled operating model of the future and improve our cost of delivery. The program is expected to deliver savings in 2026 of approximately $200 million to $300 million with a full year benefit in 2027. We anticipate approximately two-thirds of the savings generated by Project LEAP will be directly reinvested to support future growth across integrated offerings, AI capabilities and partnerships and roughly one-third toward upskilling our workforce, all while maintaining an active and strategic M&A posture. The expected savings generated from the program, net of investments, are enabling us to raise our 2026 adjusted operating margin guidance range to 16% to 16.2%, which represents 20 to 40 basis points of year-over-year expansion. This is on top of 50 basis points of margin expansion we delivered in 2025 and in line with our long-term aspiration to expand margins. As part of this program, we expect to record costs of $230 million to $320 million, which will be substantially all incurred in 2026. This consists of $200 million to $270 million of employee severance and other personnel-related costs and $30 million to $50 million of other charges. These costs will be adjusted in our non-GAAP financial measures. As Ravi noted, we will hire more recent college graduates this year than last year. Our free cash flow conversion guidance for the full year remains 90% to 100% of net income. Tax rate guidance is unchanged at 25% to 26%. Our expected weighted average dilutive share count is approximately 473 million, down slightly from our prior estimate due to the pace of repurchases in Q1. This leads to EPS guidance of $5.63 to $5.77, representing 7% to 9% growth. For 2026, we still expect to return approximately $1.6 billion of capital to shareholders, including $1 billion towards share repurchases and the remainder towards our regular dividend. Finally, we continue to make progress and advance on our evaluation of a potential primary offering and secondary listing in India. We remain committed to acting in the best interest of our shareholders and will provide updates as appropriate. To close, we are delivering on our commitment to stay in the winner circle. In Q1, we grew revenue at the top of our large-cap peer set, posted our strongest booking growth in recent history, expanded adjusted operating margins and delivered double-digit earnings per share growth. While the macro environment remains uncertain, our momentum is clear, and we believe we are winning in the marketplace. With that, we'll open the call for your questions.

So bookings, a clear highlight this quarter. Wondered to see if you had any color on how much of the bookings were new versus renewal, anything on ACV growth — how that looked in the quarter? And just given the fact that there has been a little bit of softening on the discretionary side, it sounds like in certain verticals. I wanted to confirm, Jatin, if I heard you correctly, that the midpoint of the '26 guide now assumes a little bit of improvement in discretionary spending in the second half. Maybe you could just elaborate on that a little bit? And then I have a follow-up.

Yes. So Jason, we don't exactly break out new versus renewal. But for the quarter, it's been very healthy. I would say the growth, especially of the large deals, is driven by newer opportunities in either existing customers or new customers.

In fact, just to add to Jatin, this is the second quarter in a row we've had robust bookings. The new proportion is as healthy as it was in the past. In fact, the top 7 deals, which are more than $100 million — one mega deal, more than $500 million — represent a 70% increase in TCV on the large deals. I think it's been a good quarter for bookings, two quarters in a row. This is probably the highest bookings growth we have seen since I've been on board three years ago.

Okay. Okay. And there was some commentary from one of your large competitors last week talking about AI resulting in increased competition, more pass-through of productivity gains to clients. I mean, you guys have been talking about that pass-through and the AI-assisted coding for a long time. But are you seeing competitors broadly engage in any additional level of contract pricing that you might characterize as irrational?

Yes. The way I see it is, unlike in the past, where pricing was determined by the unit price, which is billing equivalent, the race now is about the number of units and how well you can deliver with a lower number of units for the same output and the same outcome. That is based on how much productivity you can derive out of AI usage in your software development cycle. So we feel very confident because 40% of our software development cycle is assisted by AI. We have infused AI into our rate cards. So when we are up for a consolidation opportunity, we seem to be in the winner's spot because we are able to share the productivity and also keep some for ourselves. Momentum to date over the last 3 years has been very healthy. So we seem to have got this work rhythm of autonomous software engineering, as we call it, and we seem to be doing well. So while there is productivity sharing with clients, you're going to see that as an opportunity to win more and create more momentum for ourselves. Now that's on the legacy stuff. On the new stuff in Vector 2 and Vector 3, it is new work. We also see unlocking of legacy modernization, which is not consolidation — it is actually net new business which kind of got locked because customers were not willing to pay that much to modernize the legacy. Now they're actually throwing that in the mix. And that is actually a business case of how much they spend to how much they could potentially spend using AI to modernize it. So while there is price pressure on some work, I would say it's an opportunity not to look at labor costs but to look at how many of the units you could optimize using AI.

Yes. And Jason, to your earlier question on the visibility of second half and how we see our guidance range, let me break it down. Definitely, the environment around us — the macro — has become significantly more uncertain than what it was at the beginning of February. Therefore, I mentioned in my opening remarks that there are a range of outcomes possible across the guidance range for the full year. What gives us confidence for the second half are essentially two things: the large deal wins that we have had in Q4 and Q1, which continue to ramp up and will reach their full potential starting in June and July — that's one lever. The second is acquisitions like Atria will come full on stream starting in Q3; it would be a partial revenue contribution in Q2. So these are two additional drivers for a stronger second half than what we assume for Q2, which is impacted by the current environment. As I mentioned, the midpoint does assume a slightly better discretionary environment than what we assume for Q2, which is impacted by the current environment, but we remain confident as we walk through the rest of the year. Finally, we have had very strong bookings for Q1, which means we are mining in the marketplace even in the uncertain environment; customers are choosing Cognizant as a partner of first preference. That is what is helping us continue to lead in this environment with a sense of velocity and confidence.

Also, a lot of large deal transitions that are happening now between Q4 and Q1 will start to unlock in Q2 and Q3. This is literally production capacity already in place; we are incurring the cost now and not yet recognizing all the revenue. As the transitions get over, we start to accrue the dollars. So that's actually another tailwind to our journey in the second half.

I was wondering if you could maybe kind of unpack the comments you made earlier, Ravi, around the token usage that you're seeing in terms of token metering and also some of the productivity benefits you're starting to deliver. Just wanted to clarify two things. One is, with the increased productivity on units delivered to your customers, I would have thought that you would be seeing better margin leverage as a result if you're keeping some of that benefit for yourself. Or is that being masked by the start-up cost on longer-dated outsourcing deals you just talked about? And then separately, I was wondering if you could address how you expect token usage to play out in terms of how you bill customers. You talked about AI-type rate cards — are token costs being directly billed through to clients today in terms of time-and-materials contracts?

Great question. Let me first address the second point. Token metering is a reality, both at a project level and at an individual level. We have token metering for fixed-price programs as well as for time-and-materials. For fixed-price programs, we have the opportunity to reduce the cost and keep the margin with us. For new deals, we actually have the opportunity to outpace the productivity we give to our clients and therefore keep some of that benefit. Momentum to date over the last three years has been very healthy, so I'm very excited about the leverage for margin accrual in the future. Of course, there are start-up costs which we have to absorb at the start, so there is an upfront cost attached to it, but there are downstream savings. On time-and-materials and tokenized rate cards, we are starting to see a pattern. I'll give you an example of a rate card template we're taking to the market: A0 is completely human effort; A1 is effort done by humans verified by AI; A2 is effort delivered by AI, verified by humans; A3 is autonomous digital labor. When clients adopt this, they could manage capacity by purchasing compute directly from frontier model providers like Anthropic or OpenAI. In that case, we are responsible for the human effort and the clients are responsible for the digital effort. But clients have started to see that they are not able to optimize the digital effort themselves, so some clients are coming back and asking us to take care of both the human and digital effort. They want us to open the tap on compute, manage the model usage, and deliver the service end to end so they don't have to manage the economics. Already, we're talking about AI ops and AI FinOps. You can manage the economics of digital labor and human labor in one go. In fact, one of our research papers talks about a Cognizant unit of measure akin to a function point to quantify digital labor. So effectively, this is evolving. We are ahead on the curve to either take accountability for digital and human labor ourselves, or allow clients to own it. Time-and-materials comes in two forms: I could take care of digital labor and human labor and size and price it, or clients could manage the digital usage directly. This is evolving and some clients are already proposing this. On fixed-price deals, of course, we want to share productivity with our clients. It's not far off that we'll see rate cards that combine digital and human labor become more mainstream as we go forward. That gives us an opportunity to deliver both human and digital labor through Cognizant. We already have arrangements with frontier model companies to do that for our developer community and for client work.

Jim, I'll quickly cover the question on gross margin. Essentially, Q1 was an investment mode across three dimensions. First was investment in the bench — we have grown sequentially and year-over-year in headcount and have been hiring fresh college graduates, which impacts utilization near term. Second is the integrated offering element: whenever the industry sees a new element of service delivery coming to customers, they expect service providers like Cognizant to act as system integrators. That can carry a higher element cost as part of the integrated offering, and that was slightly higher in Q1. But it's an investment because you almost always see significant follow-through revenue coming through services when you anchor yourself through that early offering. Third is the salary increase we implemented on November 1st, so there is a one-month impact sitting there. A combination of these three factors led to a slightly lower gross margin in the quarter. We spoke about the volatility we would probably see as a result of this investment in Q1, but we are confident the number will continue to improve through the course of the rest of the year. The Project LEAP ambition is to drive significant cost savings through our cost-of-delivery model, and that should help gross margin as we execute for the rest of the year.

Appreciate all the color and detail today on current conditions, et cetera. I'm wondering if you can talk a little bit about what you're seeing in terms of valuation and how you're thinking about the price of acquisitions that you're looking at, particularly as you seem to be looking to add incremental capabilities to the Cognizant base? And I'm just thinking about how we should think about your commitment to spend, what portion of free cash flow and the impact on the inorganic contribution on a go-forward basis?

I'm going to ask Jatin to add numbers in a moment, but from a strategy standpoint, this is a phenomenal time to create value from M&A in line with our reforged first principles, which is about having a platform player, managing business on outcomes versus effort and AI-enabling our offerings. If you put all of that together, we have some exceptional opportunities in the market. We're not doing this in a tactical way; we are doing this strategically to fill the boxes for being an AI builder. The acquisition we announced, Atria, does data center build-out services, workplace services, AI infrastructure build-out services and network services. So Atria is a phenomenal opportunity to anchor a complementary piece of work attached to infrastructure services where Cognizant is delivering very well. We will anchor acquisitions on platforms and outcome-based models. In fact, Atria delivers work on a per-user basis, not purely on effort — they do workplace services and data center build-outs in an outcome-based model. So we think that's a unique opportunity. If there are platforms in the market, we're going to evaluate and look for them because the platform play will allow us to move to transaction-based and outcome-based pricing. In and around TriZetto, we see a ton of opportunity. Our TriZetto business is growing much faster than when I joined in 2023 and it is highly profitable with a strong moat in health care. One of the reasons we partnered with Palantir is to create an opportunity to drive payer control points for medical loss ratio performance, payment integrity, real-time cost intelligence and network performance. So we have specific areas where we want to do M&A which substantiate our endeavor to be a platform and outcomes-based company in the AI era. We also believe it will uniquely give us an opportunity to create durability of our earnings. This is a good time for a value player; we have a very healthy pipeline and we'll continue to evaluate value assets which are available in each of these pillars I just spoke about.

And just from a capital allocation standpoint, we generated $2.5 billion of free cash flow last year. We returned close to $2 billion to shareholders and roughly $500 million to $700 million was invested into three-cloud acquisitions, which technically closed at the beginning of this year but were announced in 2025. This year, again, we generated strong free cash flow. We have committed $1.6 billion to be returned to shareholders — $1 billion via share buyback and $600 million in dividends. Of that, we have now used about $600 million for the repurchase so far. We therefore have fuel in the tank and a very healthy balance sheet to leverage for attractive opportunities. We'll remain disciplined, but we have the capacity to act on the right opportunities.

That's great. You guys have been really front-footed in terms of your own development, prioritizations and how you're trying to implement AI. And your commentary now on acquisitions and some of the benefits they provide further bolsters that view. What types of customers are you seeing — generally, or what characteristics do they have — that are willing to engage with you and match your march forward right now? Where are you seeing the best traction? And where should we look for examples of success patterns?

I'll highlight a few themes. Financial Services is at double-digit growth and is very active — they're innovating new products and services and are willing to experiment with us. Vector 1 productivity plays are resonating there. Second, consolidation opportunities: every Fortune 500 and Global 2000 company has accumulated many providers over the last 25 to 30 years. This is an opportunity for consolidation to get productivity benefits. We are on the front of that and winning a lot of that work. Third, unlocking technical debt: we have great momentum on mainframe modernization. To give you a sense, one line of mainframe code used to cost $10 to refactor to new-age software; now the economics have shifted dramatically, and there's a unique opportunity to unlock that work at scale. This opportunity didn't exist before because legacy skills and economics were barriers; now those barriers are reducing. Fourth, operations-led AI: that's why our DPO business is close to double-digit growth because operations of enterprises are going to be embedded with new software capabilities. If I pick specific areas, customer service is a top area where we're seeing progress, followed by employee services, then traditional areas like financial systems and legal systems. These are places where we historically didn't see classical software deeply embedded, and now we do. Finally, physical AI is a leapfrog for traditional industries with physical assets — we're seeing interest there too. We're at an inflection point to take productivity and create elasticity of consumption of classical software and new neural-network-based software, integrate both and reimagine businesses. This is a fabulous opportunity for system integrators to be builders, and I'm more optimistic now than before about the opportunity in front of us.

Great. Just want to ask on Project LEAP, if that's okay: the offensive or defensive nature of it? What prompted it, the scope of it and what outcomes can we expect in the short and midterm from Project LEAP?

I'll kick off and ask Jatin to add detail. We have a clear frame of what our future operating model looks like, and Project LEAP is designed to get us there faster. It's our opportunity to resize our pyramid with a broader base — that's why we're hiring more early-career talent and shortening the path to expertise. This model is margin-accretive because the more we broaden the pyramid with AI-native skills, the more services we can deliver efficiently. Second, it allows us to invest in platforms, AI enablement, tokenization and automation. We have measured the savings: in 2026, we expect $200 million to $300 million in savings, recognizing that this year is partial since we're already mid-year; the full impact is larger in 2027. So not only are we right-sizing the pyramid, but we are also accelerating our move to outcome-based models. When we get to the new operating model quicker, we can seize opportunities faster and have a reservoir to invest in growth. The program funds investments in capabilities, platforms and upskilling while delivering cost savings that will be reinvested into growth. That's the essence of Project LEAP.

Ravi, can you expand upon the last point — what is the benefit of showing margin improvement in the current environment relative to your ability to invest? Why not just maximize every dollar of spend, maybe broaden the spend across more of a venture-capital-type strategy where you take more bets because the pace of change is accelerating as you try to build and adjust the model?

I think you're spot on. We'll save $200 million to $300 million this year, which is a partial-year effect, and that will be larger in 2027. The idea is to reinvest most of the savings back into growth while also capturing some margin expansion. We're investing more into growth and remaining disciplined on the margin side to be in the winner circle. So the program enables both growth investments and contribution to margin improvement. It gives us flexibility to invest in future capabilities and go after the opportunities aggressively while still being mindful of margin durability.

Thank you so much for listening to us. We're very excited about our Q1 performance, the bookings momentum we've had and the tailwind for the rest of the year. We remain anchored to the AI opportunity, moving quickly with Project LEAP, and pursuing our thesis of being in the winner circle with growth, margin expansion and EPS growth outpacing revenue growth. That's our endeavor, and this will allow us to create sustainable, durable earnings for the future.