Cognizant Technology Solutions Corp ($CTSH) Q1 2026 Earnings Call

Greetings and welcome to the Cognizant Q1 2026 earnings conference call. At this time, all participants are in listen-only mode. A question and answer session will follow the formal presentation. You may be placed in the question queue at any time by pressing star one on your telephone keypad, and we ask you please ask one question, one follow-up, then return to the queue. As a reminder, this conference is being recorded. If anyone requires operator assistance, please press star zero. It's now my pleasure to turn the call over to Tyler Scott, senior vice president, investor relations. Tyler, please go ahead.

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 risk 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 preeminent 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 seven large deals with TCV of $100 million or greater, including one 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 Astria, a global IT managed services provider and a specialist in AI infrastructure buildout, with deep expertise in managing data center infrastructure, enterprise networks, and digital workplace technology. Upon closing, we believe Astria 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 reforging 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 this problem at scale, and over time helped create many of the greatest business architectures of 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 they must be reforged 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 system integrator to an AI builder. Second, we are reimagining our talent, moving away from the traditional pyramid toward 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 non-linear revenue opportunities. And finally, we're 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 AI velocity gap, the gap between massive AI infrastructure spend and the business value realization, and how Cognizant's mission is to be the AI builder who bridges this gap. Our AI builder stack is the connectivity 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 a 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 strategy is our award-winning AI labs, which was awarded three new patents, bringing its total number of patents to 65 in the US 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, our new corporate investment arm that will back early-stage AI startups. 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 industry expertise and its enterprise client base, creating a powerful ecosystem for mutual growth. We are progressing toward the AI builder vision through our three-vector strategy: AI-led productivity, industrializing AI, and agentifying the enterprise. To date, we have well over 5,000 AI engagements across the three vectors, up from approximately 4,000 exiting December. Beginning with vector one, we are addressing a multi-trillion-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 GitHub, and Copilot, Devin, 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 one 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 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 multi-year 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 influence costs. Vector one 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 one, we're starting to see increased velocity in vector two and three opportunities. Let me share some examples. In vector two, 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 US healthcare 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 its operations. One of the value pools we see in vector two, 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 advisors, handling routine interactions and back office tasks so that financial advisors can focus on client-facing activities. Finally, in vector three, 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 three are significantly expansive opportunities across business operations of enterprises to embed agentic capital for productivity, experiences, and new services. In healthcare, for example, we're developing agentic solutions that accelerate and improve the accuracy of prior authorizations to support better patient outcomes. Additionally, we're 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 healthcare operations. We're also sensing a broad structural shift as AI moves beyond digital workflows to governing physical systems, environments, and infrastructure. This is accelerating the convergence of physical AI, agentic 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 healthcare, 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 agentify healthcare operations. Across all three sectors, 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 this shift, we delivered 2.5% and 5% increases in trailing 12-month revenue and adjusted operating margin per employee, respectively. We're 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're exploring 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 true partnership that aligns value creation with shared results. Execution across the sectors requires the right organizational structure and a powerful engine of 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 work is evolving. This is powered by Cognizant 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. And 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, trainings and certifications, AI tools and token usage, innovation, and project experience. To enable us to execute on these principles with the speed and 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're 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's 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're 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's circle performance, including top-tier growth, consistent margin expansion, and EPS growth out-pacing revenue growth. Before I turn the call over to Jatin, I want to thank our associates for their dedication, our clients for their continued trust, and our shareholders for your confidence as we strengthen our foundation to create durable long-term value.

Thank you. We'll now begin the question and answer session. If you'd like to be placed in the question queue, please press star one on your telephone keypad. A confirmation tone will indicate your line is in the question queue. You may press star two to remove yourself from the queue. As a reminder, we ask you please ask one question and one follow-up then return to the queue. Our first question today is coming from Jason Kupferberg from Wells Fargo. Your line is now live.

Good morning, guys. Thank you. So, bookings clear highlight this quarter. Want to see if you have 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. Thanks.

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 seven deals which are more than 100 million dollars, one mega deal more than 500 million dollars, 70% increase in TCV on the large deals. I think it's been a good, good quarter of bookings, two quarters in a row. This is probably the highest bookings growth we have seen since I've been on board 3 years ago, since 3 years.

Okay. Okay, thank you. And you know, 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?

Yeah. Yeah. Jatin, you know, the way I see it is unlike in the past where pricing was determined by the unit price, which is billing rate equivalent, the race now is about the number of units and how well we could deliver with lower number of units for the same output, for the same outcome. And 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 now. 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 it for ourselves. In fact, our bid to date is actually very healthy over the last 3 years, the deals we have been working on. 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, I wouldn't, I mean, there is productivity sharing with clients, but you have to see that as an opportunity to win more and you have to see that as an opportunity to create more momentum for ourselves. So, that's how we are seeing it. Now, that's on the old stuff. On the new stuff, there is, in vector two and vector three as I call it, it is new work. We are also seeing unlock 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, we see, we know while there is price pressure on it, I would say it's an opportunity not to look at labor cost. It's an opportunity to look at how much of the number of units you could optimize using AI.

Yeah. And Jatin, to your earlier question on the visibility of second half and how do we see our guidance range, let me break it down. So, definitely the environment around us, the macro, is significantly more uncertain than what it was in the beginning of February. And therefore I mentioned in my opening remarks that there are a range of outcomes which are possible but across the 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 quarter four and in quarter one, which continue to ramp up and will reach their full potential starting June, July, and therefore that's one lever. The second is acquisition like Astrea will come full on steam from quarter three standpoint. It would be a partial revenue in quarter two. So, these are two additional sort of drivers for a stronger second half than assumption than what it is. As I mentioned, the midpoint does assume a little better discretionary environment than what we have assumed for quarter two, which is sort of impacted by the current environment, but we remain confident as we walk through the rest of the year. And finally, you know, we have had very strong bookings for quarter one, which means we are winning in the marketplace even as in the uncertain environment, customers are choosing Cognizant as a partner of first preference and that is what helping us continue to lead in this environment with a sense of velocity and confidence. Also, you know, a lot of large deal transitions which are happening now between quarter four and quarter one will start to unlock in quarter two and quarter three. So, this is, you know, literally production capacity already in there. We are not making the money, we are incurring the cost. Now, as the transitions get over, we start to accrue the dollars. So, that's actually another tailwind to our journey in the second half.

Thank you. Our next question today is coming from Jim Schneider from Goldman Sachs. Your line is now live.

Good morning. Thanks for taking my question. I just wanted to see if you could maybe kind of unpack the comments you made earlier, Ravi, around, you know, 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 are you seeing, you know, with the increased sort of productivity on units delivered to your customers, I would have thought that you would be seeing, you know, if you're keeping some of that benefit for yourself, a little bit better margin leverage as a result of that as you're getting some revenue growth or is that being masked by the startup cost on longer-dated outsourcing deals you just kind of talked about in response to your last question. And then, you know, I just wonder if you could maybe address, you know, how you expect sort of the token usage to sort of play out in terms of how you bill customers. You talked about AI type rate cards, but are token costs being directly billed through to clients today in terms of time and materials contracts? Thank you.

Great, great question. Both of them. Now, let me first get to the second one. 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 material. For fixed price programs, we have the opportunity to reduce the cost and keep the margin with us. For new deals we do, if this kind of links back to the first question, we actually have the opportunity to outpace the productivity we give to our clients and therefore keep it with us. Our bid to date over the last 3 years is very healthy. So, I'm very excited about the fact that that has leverage for margin accrual in the future. Of course, it has startup, you know, setup costs which we have to establish at the start. So, there is an upfront cost attached to it, but there is downstream savings. On time and material tokenized rate cards, we are starting to see a pattern. I'll give you one example. One of the rate cards I am establishing, which is a template we're taking it to the street, is A0 is completely human effort, A1 is effort which is done by humans, verified by AI, A2 is effort delivered by AI, verified by humans. A3 is autonomous digital labor. Now, when clients do this, you could meter the capacity they've bought from a frontier model company like Anthropic or OpenAI directly, in which 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. So, some clients are coming back and saying, 'You know what? Why don't you take care of the human and the digital effort? You open the tap on computer, you open the tap on LLMs, and you deliver the service, and we don't want to manage the economics.' You know, already we're talking about AI ops, AI finops. You manage the economics, and if digital labor or human labor, it doesn't matter. In fact, one of our research papers talks about a Cognizant unit of measure, which we call it as, it's equivalent to the function point measure, which is equivalent to what we do in digital labor. So, effectively, this is evolving. We are ahead on the curve both to take the accountability of digital and human labor for ourselves, or if clients want to take the accountability for themselves. So, time and material comes in two forms. I could take care of digital labor and human labor, and I could take the sizing and the economics of digital labor, and create throughput for our clients. This is something evolving, and some clients are already proposing this. And on fixed price deals, of course, we're going to share that productivity with our clients. So, that's how we are seeing this, and it's not far off when we're going to see a rate card for this, a rate card which is digital and human labor put together, more mainstream as we go forward. And that gives us an opportunity to actually deliver both human and digital labor through the books of Cognizant. We already have arrangements with the frontier model companies to do that. One is to take care of our developer community which uses it, but also for client work which we can deliver.

That's very helpful. Thank you.

Thank you. The last question today is going to be from James Faucette from Morgan Stanley, who is now live.

Thank you very much. Appreciate all the color and detail today on current conditions, etc. 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 tech 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 mean, you know, I'm going to ask Jatin to add. This is a phenomenal time to create value from, you know, M&A. In line with our reforged first principles, which is about having a platform play, managing business on outcomes versus effort, and AI enabling our offerings. So, if you put all of that together, we have some exceptional opportunities in the market. We also have the ability to anchor this on new pillars in the mix, which will give us expansive opportunities. So, we are not doing this in a tactical way. We are doing this in a very strategic way of filling the boxes for being an AI builder. That's what our case is. Just to give you a sense, today the one we announced does data builder, data center build out services, workplace services, AI infrastructure build out services, and network services. So, Astrea has a phenomenal opportunity to anchor a complimentary piece of work which is attached to the infrastructure services where Cognizant is delivering very well. So, where will we anchor this? We would anchor this on platforms, on outcome-based models. In fact, Astrea delivers work on per user basis, not on effort. I mean, they do workplace services. They also do 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 it. Because the platform play will allow us to go to the outcome model, transaction-based pricing, and outcome-based pricing. In and around TriZetto, we see a ton of opportunity. I mean, our TriZetto business now is growing much faster than what I saw in 2023 when I came on board. And it is highly profitable, and healthcare has a strong moat, a defensible moat. So, we are actually looking for layering it around. In fact, one of the reasons why we partnered with Palantir is to create the opportunity to drive, you know, the healthcare fair control points for medical loss ratio performance and payment integrity and real-time cost intelligence and network performance and all of that. So, we have specific areas where we think we want to do an M&A which will substantiate our endeavor to be a platforms company and an outcomes-based company in the AI era. And we also believe it will uniquely give us an opportunity to create durability of our earnings. So, that's how we are seeing it and this is a good time for a value play. So, we are continuing to, we have a very healthy pipeline. We'll continue to evaluate value assets which are available in each of these pillars I just spoke about.

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

Yeah, I would say, you know, I just highlight quick themes. Financial services is a double-digit growth. Very, very excited about it. Not only are they doing Vector One, they're innovating new products, new services. Vector One is more productivity led and they're willing to experiment with us. In fact, one of the things I mentioned in my earnings script is about opportunity with a management company to apply Agentic on their advisors, wealth advisors so that they could deliver more innovative products. So, financial services is right up there. The second I would say is consolidation opportunities. Consolidation opportunities, I mean, every customer, every Fortune 500 Global 2000 company has a huge set of providers. This is, I mean, they've accumulated, you know, they've created a big network of providers over the last 25-30 years. This is their opportunity to consolidate and get some productivity benefits. We are on the front of it and we are winning a lot on it. So, that is the second. The third I would say is unlock of the third value pool, I would say is unlock of technology debt. You know, I have great momentum on mainstream modernization. Just to give you a sense, one line of mainframe code used to cost $10 to refactor to new age software. It now costs $1.50. So, we have a unique opportunity to unlock and this opportunity didn't exist before because tribal knowledge was missing, there was financial cost to modernize and legacy skills were missing. Now, all of that is out of the window. So, if you unlock that, that is trillions of dollars. So, we are seeing that as a good theme. Then there is operations-led AI. I mean, that's why my DPO business is close to double-digit growth because operations of enterprises are going to be embedded with this new software which, you know, operations didn't have a chance. And if I have to pick specific areas, customer service is the top area where we are seeing this. Employee services is the second area we are seeing. And then traditional areas like financial systems and legal systems. These are places where we historically didn't see a lot of classical software embedded. So, we started to see that. One of the things I highlighted in my earnings script is physical AI. I mean, it's a leapfrog for traditional industries with physical manifestation to actually invest into digital enhancement of physical objects. And we're seeing quite a bit of that. So, I think we are at that inflection point now to take productivity and create elasticity of consumption of software, classical software, and use new software which is, you know, written around the neural networks to an expansive opportunity in enterprises and integrate the two and reinvent and reimagine businesses. I mean, this is a fabulous opportunity for system integrators to be those builders and I'm actually more optimistic than ever before on the opportunity in front of us.

Thank you. The next question is coming from Hian Jin Huang from JP Morgan. You have the last one.

Hey, thanks. Hope you can hear me. Just wanted to ask on Project Leap, but that's okay. Just the offensive or defensive nature of it, what prompted it, the scope of it, and what outcomes we can expect in the short and mid-term from Project Leap.

I'll kick off and I'll get Jatin to add. I mean, we have a mental frame of what our future operating model looks like and I'm pretty confident that that operating model is, we are on the journey to get to that operating model. Leap is to make sure that we get there fast. It's our opportunity to resize our pyramid with a broader pyramid. That's why we are hiring more school graduates, more early careers, and shorten the height of the pyramid so that you get to expertise much faster. That's our model. It is margin accretive because the more you broaden the pyramid, the more you could deliver the services in a more AI-native way, if I may. The second important thing is it allows us to invest into the platforms, AI enabling the enterprise and tokenizing the enterprise as I call it. It allows us to do that. So, we have measured the savings. It is in the range of 200 to 300 million dollars this year and this is partial because we are already in the middle of the year and we have a couple of months to complete this process and probably, you know, three to four months of impact. So, it has a much higher impact next year in 2027. So, not only are we right-sizing the pyramid and remember we are also saying our future offerings are not effort-based, they're outcome-based. More and more. I mean, we'll see a mix of it in the transition. So, when we get to that new operating model quicker, we are going to seize these opportunities faster and we'll be having a more optimized operating model and we will have a kitty for investing into our future so that we can seize the opportunities ahead of others. We also said in our investor day that we will have an expansive margin trajectory which is what we intend to. I mean, last year 2025, we did 50 basis points in spite of the M&A and the investments. This year, we have upped our margin guidance to 20 to 40 basis points increase from 10 to 30. So, we are constantly on that trajectory to keep increasing our margins, keep delivering productivity to our clients, and be in the winner's circle of growth. So, this allows us to do all of this in a quicker, faster way. We get to that future operating model which we have envisaged.

Thank you. Our final question today is coming from Surinder Thind from Jefferies. Your line is now live.

Thank you. Ravi, can you expand upon the last point of 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 what I would call more of a VC type strategy where you take more bets because the pace of change is accelerating. And so as you try to build and adjust the model like...

I think you're spot on. If you look at it, we're going to save 200 to 300 million dollars this year, which is just a few months, and you know, 2027 we have a much bigger opportunity. But we're investing back the rest of the money to generate growth opportunities and be agile enough in the market to generate more growth opportunities. So, you're exactly right. So we're investing more into growth and we're contributing some into our expansive margin. So the idea of doing this is growth and be in the winner's circle.

Thank you. We have reached the end of our question and answer session. I'd like to turn the floor back over to management for any further closing comments.

Thank you so much for listening to us. I mean, we're very excited about our quarter one performance, very excited about the bookings momentum we've had, and the tailwind we have for the rest of the year, and of course our anchor to the AI opportunity, and getting there fast with the LEAP program, and keeping our thesis of being in the winner's circle of growth, expansive margins, and EPS growth being higher than revenue growth. That's our endeavor, and this will allow us to create sustainable durable earnings for the future.

Thank you. Well, that does conclude today's teleconference. We disconnect all lines at this time, and have a wonderful day. We thank you for your participation today.