Cognizant Technology Solutions Corporation (CTSH) Earnings Call Transcript & Summary

All right. Hello, everyone. Good afternoon, and thank you for being here. My name is Tyler Scott. I lead the Investor Relations team here at Cognizant. It is great to see so many people in person. It has been a while since our last Investor Day. And for those of you tuning in on the webcast, thank you for joining. So today, we're really excited to talk about the long-term opportunity that we see ahead and our strategy to get after it. But before we get started, I have the privilege of providing the best update of the day, which is the legal disclaimer behind me. So as a reminder, today, we are going to be making forward-looking statements. We will be referencing non-GAAP financial metrics. And the disclaimer on the screen behind me is available on our Investor Relations website. And non-GAAP reconciliations to the numbers that we're referencing today will also be available and are also available in the 8-K that we filed this morning. All right. So we have a very, very exciting day today. It is jam packed. To start our CEO, Ravi Kumar is going to talk about our strategy to leverage our differentiated capabilities and our strategic investments in AI and embedded engineering to lead the next wave of enterprise transformation. Then you're going to hear from leaders from our unique platforms and engineering services as well as some of our cloud and data practices. I think it scrolled down a little bit. After that, we're going to have some more partnership -- we're going to talk about our partnerships, investments in technology, domain expertise, our talent, our operational modernization to position us over the longer term. After that, you're going to get to hear directly from some of our clients and some of our partners who are going to talk about how we are driving the AI transition. And finally, Jatin Dalal, our CFO, is going to bring it all together to talk about our financial results and how our financial road map is expected to drive long-term shareholder value. And then finally, Ravi will join Jatin back up on stage, and we'll take Q&A. We hope that today you come away sharing the excitement that we have about the long-term opportunity and how our strategy is going to capture it. And so we have a lot to cover. And now I'd like to turn it over to our CEO, Mr. Ravi Kumar.

Thank you. Thank you, Tyler. Good afternoon, and thank you all for joining us today. I'm so grateful that you chose to come here. Every time you come for a Cognizant event, I'm very grateful. I chose this point of time in my journey with Cognizant. I spent 2 years in Cognizant, I joined in 2023 January. To tell you the story, our journey. After we have rebuilt our mojo on the flywheel of clients and employees. We reinvigorated the company, built resilience and durability, and put some points on the board. We are on that inflection point of a new growth trajectory. We are super excited to you -- to talk to you about our aspirational goal to be in the Winner's Circle, and I'm going to define the Winner's Circle as we go forward. And establish Cognizant as one of the world's top tier IT service providers. We made great progress so far in this journey to be on the Winner's Circle. And this is a great time for us to reflect and also tell you the story ahead. I want to take this opportunity to also introduce my leadership team. Some of you, you're going to see them as speakers, some of them in the audience. And I'm so grateful to my Board who has been kind enough -- 5 of my Board members have also been -- are a part of the audience. So you should be able to interact with all of them during the day. We have some showcases there. It's a tiny space, if you want to see more of it, please write to us, we want to send you more information and hopefully engage. So that's broadly what I had to start with, 30 years of heritage, engineering modern businesses. In these 30 years, we've had an era of globalization. Enterprises across the world used technology to scale. It was a peaceful era of globalization. And as this scaled, they used technology and they used providers like us. So in some ways, in this 30 years, there were cost budgets allocated for tech transformation. The last 10 years, there was a different -- a new swim lane of tech disruption happening through digital transformation, and we had access to the revenue budgets, the growth budgets of our customers. But over these tech disruptions, over these 30 years, we built a heritage of sensing, incubating and scaling new technologies which are relevant to our clients. And we did this so well that we made the next wave bigger than the current wave. And that was the strength of Cognizant. We built this unique franchise value, as I call it, of client intimacy, strong client relationships, expertise at the intersection of design, domain, technology, and we had a flexible co-creation culture. That remained consistent across every wave we went through. In the process, we drove the application development wave. We defined the SMAC wave. We were the ones who defined the SMAC wave. We led the initial wave of digital transformation. We kind of slowed down a little bit on the extended digital transformation wave between COVID and after COVID. And since 2023 to now, we course-corrected, bridged the gaps, reinvigorated the company, built resilience and durability and invested in the next wave way ahead of anybody else. Invested in the next wave, way ahead of our peers. And we think we are so uniquely poised. You're going to hear from some of my colleagues on the AI disruption around us. There's a lot on this slide, so I'm going to touch a few points. We have a stable leadership team. Significantly reduced attrition. We revived this grassroots innovation movement in the company. One of the heritage of Cognizant, which I feel so excited about is every time there was a tech disruption, we actually built human capital from inside. We had this unique heritage of hiring from schools, keeping people for 10-plus years. I have 70,000 people in the company who have more than 10-plus years. And they know their craft well, and they traversed the rescaling infrastructure of the company, and moved to the next disruption in an economically viable way. So we had such amazing economics, which we have restored now. That is going to make Cognizant what it is for the future. That is what is going to make us a leader to get to the Winner's Circle. The expansive margins. We've built a trajectory. At the start of my period in 2023, I actually spoke about a next-gen program. We created this flywheel where you take out cost, run a tight ship, and push the money into -- push the savings into expansive margins. I've actually spoken about expansive margins for the future. And invest into the future so that we stay resilient but we also capture the opportunity ahead of others. We went from 14.6% in quarter 1 of 2023, to 15.7% in quarter 4 of 2024, including the 30 basis points impact we had because of an acquisition we did, which was very strategic for us, Belcan. That flywheel is going to continue. And we are going to keep the expansive margin trajectory for the future years. A large deal momentum. We have created a muscle of large deal momentum through AI productivity, very unique sole-sourced muscle with AI productivity. We did 29 large deals last year. In fact, one of the things I'm excited about is we built resilience and durability. I spoke about it a number of times. And I did so because we are no longer just a health care -- we're very strong in health care by the way. We did 10% growth Y-on-Y or health care. Financial services, but we actually expanded ourselves to all the other industries. Now we have industrial, comps, retail and CPG. We expanded our large deal engine to -- from U.S. to Europe. And we now operate on 4 pillars of tech services all the way from tech services, to BPO, to infra led transformation to engineering-led transformation. So we do believe that irrespective of the times around us, we are more resilient and more durable because of the spread of services on the spread of verticals. Look at the preliminary results, 10 percentage points down on attrition that gives me the leverage for lower cost of human capital and higher fulfillment rates for our clients. Every time I go and see a client, I ask them what is so special about Cognizant associates? They tell me every time I meet an associate, they not just do what we tell them to do. They look for incremental innovation. They look for adjacencies and they create a sense of value add beyond what is the spec of the job. We now have a grassroots movement in the company, 250,000 ideas. 47,000 already delivered to clients and they've probably created incremental value and incremental projects. 14,000 people have returned. My Head of HR who's going to talk to you later. Kathy, she's going to talk about 20,000 more people are waiting on the wings and 5% to 7% of what we hire today is actually returners who are coming back to Cognizant. We spoke about AI productivity, and I'm going to touch upon it in the subsequent slides. We use AI productivity to sole source and create large deals, and we share those benefits with our clients. In addition to what we've shared with our clients, we have 12,000 more releases where we have created incremental productivity. In Q4 of this year -- of last year, we did 2% organic growth with more than 15,000 people -- less -- less than 15,000 people from the previous year. So that's the power of AI productivity, which is like kind of going like it has a great curve now as we go forward in 2025. 900 basis points, we bridge the gap all the way from Q4 of 2023 to now, organic 600 basis points of growth, 300 basis points of growth in organic. So we kind of have taken the trajectory all the way from minus 2.4%, to 6.7% Y-on-Y in quarter 4. The highest NPS score and the highest employee satisfaction, 2 years in a row. So we are back to the winning heritage. We've built resilience and durability and we are prepared to lead the next wave. And I actually think we are very, very well positioned for the next big opportunity in front of us. So what is the future of IT services? How do we see it? And there are a number of things, but I want to highlight two important things we invested on. And we do believe this is going to change the way you're going to see tech services in the future. First, artificial intelligence. Double-engine transformation. One related to hyper-productivity, which is today and it is already happening since 2024. And the second is AI-led innovation, AI-led new revenue models, AI-led growth models, where the foundation is being built today. Both are actually unique big opportunities for us. The second, I'm very conscious about saying this is embedded engineering and not ER&D because we caught this wave later, and we caught this wave after the legacy ER&D spend was a big opportunity for tech services companies. So what are we talking about as embedded engineering? The last 10 years of digitization was to tech services in some ways, happened in services industries. The next 10 years of digitization is going to happen in and around physical. We invested even before I came on board, since 2020, we have been investing on embedded engineering, to make the physical, intelligent, connected and in some ways autonomous. And we're going to see a ton of opportunity there. So we're excited about the future of ER&D, as you call it, which we see it as embedded engineering. We are so lucky that we have massively invested into both these areas. On the AI labs, you're going to hear from my colleague, Babak, way back in 2023, we invested. The Neuro platform suite, you're going to hear from my colleague Prasad. Cognizant's heritage was to catch these waves very early. So we have a heritage of building platforms. What I mean by platforms is whenever you're catching these waves early, technology is evolving. There are always going to be gaps. Gaps to make it enterprise grade. And as they get productized, you're going to see those gaps. So we build intellectual property on the edge, I call it fast software. So we are one of those companies who have always been interested in building -- fixing those gaps, productizing it, and running along with the services, bundling it with the services. We have now done that for AI, which is evolving at a rapid pace. And I call it last mile infrastructure as well. You're going to hear about multi-agent orchestration from Babak. It's very interesting. Every software ecosystem is building agents. We build an orchestration layer which we believe is a gap today, which can actually get agents from different ecosystems to talk to each other and generate the kind of productivity clients are looking for. We have called out $1 billion of investments in 2023 for AI, and that was way before this was taking off. Let's look at the embedded engineering opportunity. In fact, we did similar investments in embedded engineering as well. We've built labs. We built investments in IoT, IT and OT. We built investments on investments on intelligence on the edge, smart manufacturing. So the spend we are going to see now is multi-trillion-dollar. Embedded engineering is going to go from in-sourced to outsourced. Cloud and data, which was happening in the last 10 years, will get catalyzed. There is $2 trillion of tech debt sitting on balance sheets, which will get unleased. In fact, I was talking to a bank last week. They have a lot of legacy infrastructure. They don't have the tribal knowledge, they don't have financial capital to pull it out and they don't have legacy skills. It's a unique, unique opportunity with the power of AI. And operations are going to be digitized. You're going to see some of the things we are working on. We're going to see a new wave of digital operations opportunities. The embedded engineering opportunity is fascinating. It cuts across all verticals, and that's the strength of what we have done since 2020. We have invested in boutique companies, which are in specific industries. In Health Sciences, we have two companies which actually we bought way back in 2020, on life sciences manufacturing based in Ireland. We are building connected pharmaceuticals and connected health care using them. Financial services, deep fintech is still a huge opportunity. Network engineering. In fact, I was talking to an automotive client a month ago, they work with us on all the IT systems and they also work on writing software for autonomous driverless cars. They have budget constraints on the IT work they do with us. They have unlimited budgets for writing software for driverless cars. So that's the power of what embedded engineering capabilities can do. Of course, with Belcan, our CEO of Belcan is here today. We have the same opportunity on aircraft. Embedding software into the aircraft ecosystem. This is the 3 vector opportunity of AI, and this is how I see it, and this is how Cognizant sees it. It's a massive opportunity to disrupt work, workplaces and workforce. There is a platform shift, and that's why this opportunity is so uniquely big. There is transformer technology on the algorithms. Massive compute, and Internet scale data, all coming together. And when they come together, the scaling laws are very different. Till now, technology disruptions were always seen with the Moore's Law which kind of moved every 18 months. The AI disruption is through AI scaling laws which are actually moving every 6 months. They're doubling in every 6 months. So cost reductions, compute efficiency, increased accessibility. We are unlocking thousands of use cases at a rapid pace, and the models are getting cheaper and cheaper, which means the value will move from the infrastructure to the front. And enabling that hyper productivity for our clients, industrializing AI and agentifying the enterprise, which is, I think, a mind-boggling opportunity I want to talk about, it just changes the TAM on what we can address. Let's see the first vector. It is today and all the ways in 2024, all our large deals, large -- a good number of them we sole sourced based on AI productivity. I and Surya, my Head of Americas, we went and spoke to one of our clients who is up for renewal a year from now. We went and consolidated. We gave them productivity. We shared the benefit. We consolidated and got their top line bumped up. When you share productivity, your top line goes down. It's managed -- it's called managed rebaselining. And when you do managed rebaselining, you have to consolidate. And in the process, we constructed a big deal where we sustained our margins and we created an incremental value on the top line. We have a platform called Flowsource, which unifies human effort and machine effort. 20% of the code written by us is written by machines. In fact, we are the only system integrator, which has quantified code written by machines. We are the only system integrator which has quantified it. I did that in my last earnings. In my earnings before, I actually spoke about a number of lines of code written by machines. And we think that will change the way we are seeing this. We want to repurpose the savings for innovation. We want to create a bigger opportunity for ourselves. So this gives us the opportunity to work in times of uncertainty where savings, productivity and efficiency can also lead to opportunities. Look at the impact. I spoke about the 12,000 FTE, 70 implementations we have on Flowsource, 20% of the code is written. We actually pick all programs where we have managed services. Jatin is going to talk about how our fixed price programs has gone up by a number of percentage points since 2023. Look at how we are adopting it. There are 360-odd accounts where we do a lot of managed services work. 83% adoption, 37% are scaling, 56% are having an impact today. This is something we're doing grounds up. We want to change that universe. We want the 2,000-plus clients of Cognizant who have managed services work with us so that we can share those benefits. Vector 2. I call this industrializing AI. And I call this industrializing AI because it is a unique heavy lift you need to replumb the existing stack. You have to replumb the existing stack, all the way from the data, the cloud foundation. Naveen, our -- one of my colleagues is going to talk to you about the unique opportunity there. How the SaaS layer is going to take a part of the logic and you're going to move the logic to the dynamic AI stack. And we want to rewire the experience layer. My colleague, Ben is in the audience. He's actually running a unit called Cognizant Moment, which is about making UI generative. We believe just-in-time design, design the customizers to what you're doing, to when and where you're doing it, and it will keep adopting with you. That's the UI we are going to build. I mean that's the user interface. The existing user interface is out of the window. So the ability to reorganize all of this is a uniquely big opportunity. In fact, if AI is also going to take a part of the human labor, the software to labor equation is going to change, which means you need to know the work graphs behind. I was at a customer service function for a health care client recently. And I was looking at what our customer services agent does. And if you want to replace that with an AI agent, you need to know the work dynamic behind it. They picked data from different places, they consolidate it and push it to client -- push it to solve queries. So you need to know what's happening behind it. We -- I and my financial services head met one of our clients, and we wanted to agentify a teller. You need to know what a teller does. So the work graphs are equally important. So we did productivity studies. In fact, we partnered with Oxford Economics to do productivity studies. We have 1,200 projects running on Vector 2 adoption. A lot of heavy and lift. These will translate to Vector 3 at some point of time, and we have 100-plus platform implementations. As I spoke about the platform story. My colleague, Prasad, is going to double click on this. We have created the last-mile infrastructure to catalyze the embrace of AI. And that's why our clients are loving us. It's a unique differentiator of building last mile infrastructure, which will help us accelerate and take -- and change the pace at which this embraces. Reduce the cost, reduce the risk in doing AI embrace in enterprise landscape. Remember, enterprise landscapes are so heterogeneous. I mean technology of the past, you first had governments, than big enterprises, then small enterprises, then consumers absorb it. In the last 10 years, consumers get it first and then enterprises get it at the end of that cycle because it is heterogeneous and complex. So these platforms, our last-mile infrastructure intellectual property, which we own, and we bundle into the services and a lot of it is now AI led. In fact, we have business platforms, which Surya is going to talk about and our TriZetto platform is completely AI-enabled. And you're going to hear from one of our clients talk about it as well. The third vector, which is agentifying AI. Software's newfound ability is to go after labor spend, instead of just serving as an enabler. In fact, this has radical implications. For the first time, technology is not just offering tools for humans to work. It's providing intelligent, scalable digital labor that performs tasks autonomously, makes decisions and learns through the process. Now what does this mean? We can actually tap into labor pools around software, agentify it. The question is, will that be up for identification? The question is, will that be up for outsourcing? So we are building a capability set, which compels customers to view it in a very different way than how they see today. We're also connecting with the AI native start-up ecosystem. One of my colleagues, Sandra is going to talk about our partnerships with startup ecosystems. Startups in the past, were up to disrupt big businesses. The AI native startups today want to help transform big businesses, because their algorithms are meaningless without the access to their state. So we want to be that bridge, that value-added bridge, between startups and large enterprises. This is an unlimited TAM and unlimited totally addressable spend. You can tap to untapped human services. We call this Service-as-a-Software. And I'm going to talk about 2 real examples as we go forward. Let me talk about the first one. There is a showcase out here about a client who is actually agentifying the sales function. So if you look at a traditional SI, for $1 of software, there was probably $2 of services, if I'm implementing CRM, the sales function. That is probably a $100 billion market. Now if I look at the labor pool around it, the opportunities people are punching in, the forecast people are punching in, the sales incentive comp, which is happening. If I put all of that together, it's a $1 trillion. And here is an example of a client you can see it in our showcases, who's actually doing an RFP by agentifying and Cognizant is actually helping them do so. So what is the TAM now? It's not $100 billion of software services. It is all the labor attached to it. Let me give you one other example. It's about labor, which doesn't exist today. There's a medical devices company, which is a client of ours. I went to see them 2 weeks ago. And they were -- they do all systems work with us. They build compact medical devices, which sits at people's homes. And people 50% to 70% of the time, take it to a clinic because they're not able to use it. And they use a nurse to get it done. Right now, I'm working on a digital nurse, for X dollars an hour, to self-serve at your home. That's untapped services. Now look at what we could do with agentification. It's the art of the possibilities. All the way from horizontals to verticals. Surya will talk about an underwriting example. He has 100-odd identification projects running in various verticals. Fascinating opportunities. The question is where can you build the capability? What will get agentified? What will get outsourced? Will they just give you the identification work or will they give you the combination of the 2? I think that is what we have to look at. I mean we have to make the choices of what we will do and what we will not do. I see this as trillions and trillions of dollars of opportunity. But we have to pick and choose what we think we will uniquely win in the market. So this is not just IT spend. This is labor's pool spend. This is about labor pools which don't exist today. And look at the preliminary results. In fact, the one in the middle, 25% health care claims is TriZetto. We can auto adjudicate and reduce the effort significantly with the power of TriZetto, which has $0.5 trillion of claims going through our books. So what's our right to win? We sensed this early. We invested early. We have a platform approach to take common problems clients have, translate that to intellectual property, which we can bundle with our services. Those are the platforms Cognizant owns. And we have the capability at the intersection of technology, industry and operations, which has been a heritage, a 30-year heritage for the company. Our strategy is to drive long-term shareholder value. We are confident in our strategy and its ability to drive long-term shareholder value creation. As you saw this morning, our Board approved an increase in share repurchase authorization. And we're committed to add $500 million more to share repurchases this year in addition to the $600 million we were planning to do, underscoring a conviction in the strategy and the opportunity we have ahead. And you're going to hear from Jatin. In fact, his presentation is the last so that you can see all the numbers and you don't go away. So a new set of strategic imperatives are evolving from the past, amplifying more on talent. The lowering infrastructure. Scaling innovation, more platforms, more of grassroots innovation, accelerating growth using AI, both on productivity and on the new opportunities on agentification. We want to be in the Winner's Circle by 2027. And our definition of the Winner's Circle, our definition of the Winner's Circle is to be a top-tier player. You can see the 10 players at the bottom. So among the 11 players we want to be in the top tier, which is top 3 or 4 players by 2027. We were 10th in 2022. We were 8th in 2023, we were 6th in 2024, and that's why I chose to come here when we put some runs on the board, as I call it, or points on the board. And we were above peer. I mean if you look at the averages, we were 8 percentage points below the peer average, 3 percentage points below the peer average. 50 basis points above the peer average, and we want to be in the Winner's Circle. And the Winner's Circle is not about top-tier revenue growth. We want to gain market share. We want to keep our large deal momentum. We want to skill for the future. We want to do gradual margin expansion. We've created that flywheel of gross margin and operating margin leverage. And which means our EPS growth is going to be higher than our revenue growth. So 10 to 30 basis points in our outer years. Remember, in 2025, we've already said we'll do 20 to 40 basis points, in 2025. In 2026 and onwards, at a minimum, we want to do 10 to 30 basis points, invest back the balance into growth, depending on -- I mean we want to have the flexibility to invest back into growth, but we want to keep an expansive margin profile and 90% to 100% free cash. This massive opportunity ahead of us, our differentiation, our current momentum, our early investments into the next wave, our early wins gives us the confidence for this compelling path to be on the Winner's Circle and for shareholder value creation. We have a great agenda today, ahead of us, some showcases. I will now hand over the -- hand over to my colleague, Prasad, who's going to talk about unique IP-led differentiation using platforms and digital engineering. And then you're going to hear from Vibha about the embedded engineering story for us. Thank you for listening to me today.

Thank you. Thank you, Ravi, and a very good afternoon to everyone. I want to start by introducing myself. My name is Prasad Sankaran. I've been here for 2 years at Cognizant. Prior to Cognizant, I spent 25-plus years in the industry at the intersection of technology and industry largely at Accenture, where I was the Senior Managing Director, did a lot of global leadership roles. And after that, I was a senior partner at Bain & Company, I was a leader in their enterprise technology practice and also part of their private equity groups. I'm going to be joined today by my colleague, Vibha, and she and I are going to talk about two topics. Platforms and engineering, and Ravi touched upon both. But what we want to be able to do after -- at the end of the session is really leave you with a good view of what we're talking about. So before I jump into the first part, which is platforms, I want to talk about how I'm going to take you through it. First of all, I want to talk to you about what do we mean by a platform when we talk about that in the Cognizant -- when we talk about it from a Cognizant perspective. There are multiple types of platforms. Second, I want to talk to you about how a platform fits within our clients' ecosystem. Then we'll deep dive into a specific platform, and I'll use one of my own, which is Flowsource. Ravi touched upon it. It's something that we use in software engineering to drive a huge amount of hyper productivity. And we use that through a lot of the new AI that's available. Copilots, LLMs and so on. And then we'll get into the last slide, which is going to really be about the kind of results that we see. So let me talk about how -- when we talk about platforms, what do we really mean by platforms at Cognizant. So over the last several years, our clients have been on a journey to get on the cloud and to become digital. However, they have a lot of legacy that they haven't been able to decommission. So it's been a combination of legacy as well as cloud, as well as digital technology. This requires a lot of talent and budgets that they are short off. And as Ravi pointed out, over the last couple of years, you've seen the significant pace in AI development. Lots of new things coming out, lots of diversity in the ecosystem, whether it's in cloud or in AI. And clients are really struggling with that want to pick up and the time to implement is significant. So what we are doing is two things. We're offering what we call repeatable software solutions, but at an enterprise scale. And that's what a platform essentially is. But what it also does is it satisfies that last mile challenge for our clients. So they're able to take that, drop it into their ecosystem, and it directly connects to provide the last mile connectivity. What are some of the benefits? First of all, it's inexpensive to do that rather than them trying to do it themselves. The second is it can be done very quickly, speed is of essence. High quality and most importantly, it's going to drive hyper productivity for us. So what I'm going to talk about a lot of these things around platforms really drive Vector 1 that Ravi spoke about. Now let's look at how they fit into our clients' ecosystem. So this is a pretty -- it's a simple picture, but it's characteristic of any sort of client that you look at, right? So the left-hand side is all the legacy technology that's there. Lots of mainframes, mid-range servers, lots of COBOL, even SAP, all of that. On the right-hand side, is what they've been doing over the last decade with hyperscalers moving to the cloud. They have started building new systems in the cloud. They've done some amount of lift and shift. So they've got this thing going on. And the middle part denotes the data silos that exist. So there's lots of fragmentation. And my colleague, Naveen is going to talk about the data challenge, because there is no AI without data. So we have to be able to solve for that as well. Therefore, we came up with a platform approach that really solves three things for our clients. The first thing it helps them with innovation. So how can you quickly drive innovation. So I'll talk about that a little bit with Flowsource. Babak will touch upon that when he talks about other aspects of our Neuro IT suite. How can we get there quickly? How can we give you our clients a sustainable competitive advantage to drive this through? The second thing that we do is how do we address the legacy? How can we move the legacy, hollow it out, move as much of it to the cloud and decommission as much of it. That's what our modernization platform, Skygrade, and I'll talk about it a little bit and Ignition, which Naveen will talk about, help us do. So they do two things. One is they haul out your legacy. And the second thing is they move a substantial amount of it to the modern technology, and therefore, you're able to make that work with -- it's interoperable with the new, so to speak. The last thing is you talk to any CIO, and they'll tell you that a substantial part of their spend is still running their estate, running the old, running the new. So one of the things that we've done with our platforms here, Neuro IT operations, WorkNEXT, et cetera, is how can we take out that manual effort? How can we autonomously manage that estate? And again, it does a couple of things. One is it takes your cost out and drives budgets that you can use for innovation. The second thing is it frees up your own people. That is our clients' people, and they've been doing more manual tasks, eyes on glass, managing the estate. We can take them out and drive them more towards doing innovation, which is much richer for them, and it is also great for our clients because it helps kind of shift where the people are. So I'm now going to talk about Flowsource. Ravi touched upon it. It's a full stack platform for software engineering. So when you go back a couple of years, before the advent of AI tools, you had designers, you had developers and you had testers working together. What we're doing now through Flowsource is bringing this cross-functional team together, and they're able to now have a similar unified experience. And all of the tools that we're talking about are subsumed under this Flowsource platform. And by the way, if you get a chance, I can show you a Flowsource demo during the break. It's very impressive. It uses LLMs, it uses whichever core companion you want to use. You want to use, GitHub Copilot, that's fine. You want to use Gemini. It doesn't matter. What it does is it generates 20% to 50% productivity. And already, we are seeing that 20% of the code, where it's applicable is now being written by machines. And that number is only going to go up. What does it do for us? In the 1 year that we've had Flowsource out, we've had over 70 client implementations. And right now, we have 120 in the pipeline that we are driving towards completion. So this has been a huge area for us. We've got great feedback from analysts and advisers that this is indeed a differentiating area for us, and it's going to drive Vector 1 in a huge way. Just to summarize some of the results in looking at what we've done here. At a media client, they were spending a lot of money just running their platform, running their infrastructure, running their applications. By using Neuro IT operations, we've taken out 40% of the cost. But more importantly, 92% faster triage and issue resolution, direct impact to their customers. So that makes a direct difference immediately, and we can drive that very, very quickly. The second is a health care payer client where we use Skygrade. We move them from the mainframe to a cloud. We did a 30% lower cost as well as migrating 2 billion claims that we're sitting on a mainframe database to a database on the cloud. I won't go much into Flowsource, but it really reduces the time to market because of how we're able to bring things together. What has this done for us? It's obviously reduced cost for our clients. It increases speed to market. It helps us rotate IT staff for our clients from just doing the mundane to doing the really nice stuff, really cool stuff that helps them in their careers as well. But more than anything else, and Surya will talk about this, and Ravi touched upon it already, it's a key for us to win large deals. And all of the large deal momentum that we've driven last year or the year before, and we continue to drive today, this is a significant part of it because this is real. What we are driving is real. We are showing real results, and Surya will touch upon it. Like I said, we have over 400-plus examples of where platforms have been used at our clients. Now I'm going to switch to the second topic, which is the engineering opportunity. Like I said, I'm going to talk about one part of engineering, and then Vibha is going to come in and talk about the second part. So as I set up the engineering opportunity. This is how we'll go through it. First, we'll talk about the two parts. One is software engineering and the other part is advanced engineering and IoT. I want to talk to you about the differentiation because we have one of the largest engineering footprints in the world. Then I'll deep dive into digital engineering, which is my space in software engineering, and I'll show it to you with an example. So if you look at our engineering services, it's all about making our clients' ability to innovate, making them have sustainable competitive advantages over their competition. And there's two aspects to it. Software engineering, which is building custom software for enterprises. So writing a wealth management application or a retail banking mobile app. So it's for our health clients and our banking clients. It's a core of what we do and have been doing. And then we're going to talk about engineering and IoT, which is all about building software for physical devices, which Vibha will cover in detail. So when I switch over to this part, I have 3 parts of my software engineering business, which is about 100,000 people and drives about over $6 billion of Cognizant's revenue on an annual basis. The first is design and build, which we call digital engineering, which is actually building those new products. The second is quality, engineering and assurance, which is testing it and making sure it works. And some of this we do independently. So a client will call us and say, I'm using these other two companies, but can you come in and assure everything that they are doing? And we are one of the best practices in the world. And then running mission-critical applications across the board. What's differentiated about us? Like I said, we have one of the biggest footprints in the world. And I think these are the factors that bring it together. The first is clearly a global footprint. And truly global, it's not just offshore and onshore, but it is near shore as well. So it's a 3-shore delivery model, and we look at every client and see what is their culture, what is the best way to address it. In some cases, we just do 2-shore. In lots of cases, we do 3-shore. We're able to have deep skills in Central and Eastern Europe and Latin America, and that's actually driven through a series of specialized acquisitions that we've done over the years. And we brought all of that together, and we have a unified model. So it's not that you deal with just one acquisition and those people there, but really bringing that holding together. The other thing that we're able to do is really look at proximity of our clients from a Central and Eastern Europe standpoint, and Manoj will talk about some of the benefits, but there's a language benefit. There's a time zone benefit for LatAm to the U.S., for Central and Eastern Europe to Western European clients and so on. So really, it's a question of bringing this together in that global footprint. Platforms I won't go into, but it drives nonlinear productivity. And then there's the modern talent approach that Kathy will touch upon, but this is huge for us. Modern ways of working or modern methods. We want to be agile. We want to be product centric in how we do things. Second is new talent archetypes. We used to talk about developers and testers. But now we are focused on full stack engineers and SDETs. So we're trying to completely shift to the new archetypes because that is what is going to drive growth and drive our leadership in this space. And finally, being AI proficient. We want to be AI proficient across the board. We have trained all of our people. We are training people who are coming in, and I won't go into it in detail, Kathy, will cover that. And then partner ecosystem, which Sandra will cover, but it's very, very important to what I do because participate with partners, to understand their road map, to get our people certified to good market jointly, and to be able to just give them feedback on what our clients are looking for. So very important part of what we do. And lastly, I'm going to cover a couple of slides on digital engineering, which is the first part that you saw. This is all about building new products. So there are two motions to it. Clients are looking for new digital applications that we want to build, which is all about building the latest mobile app or building the latest platform app. We built that in an agile manner. We make sure that it's AI-infused we build it with the business first in mind. So it's all about building new stuff. The other thing is the $2 trillion point that Ravi spoke about. So there's a ton of legacy out there. And even as we get more productive, there's going to be all of this work still to be done, because we have to take this backlog out. You have to take this to the cloud, we have to make this modern. So this is a huge part of what we do. It's technology and business led. We're taking that -- the tribal understanding, as Ravi said, that we have and then being able to convert all of this to the new. So let me bring it alive with an example. So we've been working with a leading bank in the U.S. It's been a few year journey. The bank actually asked us to come initially and said, we want you to look at the user experience and kind of redefine it for us. So we said we're going to get engaged on digital transformation, on product strategy and then bring a unified experience. The results are that they have the #1 consumer mobile application in banking today. It's easily the best in the U.S. and well recognized. The other thing is 77% of all consumer interactions in banking now are digital, and we continue to increase that. So that's what we came to do. But -- and that's the left-hand side of what you saw before, that is building the new product. But we've enhanced our relationship to where we've been able to tell them, look, you've got mainframe that you need to move to the cloud. You've got to reimagine your banking software. So that's all motion 2, which is all about the legacy to cloud to modern, and we've been able to do that. And what does that do for us? Results for us? We've had a 22% 3-year CAGR in just the software engineering space, and it's driving $88 million of revenue increase for Cognizant. Clearly, digital engineering is a space for us that we are starting to see huge interaction, huge uptake and so on. And it's all driven by our platforms as well as our engineering ability. So at this point, I'm going to pause and invite Vibha to talk about advanced engineering and IoT.

Good afternoon, everyone, and good to talk to many of you before. I am Vibha Rustagi, and I'm heading the Global Engineering and IoT practice for Cognizant. I've been at Cognizant for 10 years. And in fact, prior to that, Ravi also mentioned how M&A is really an important tool for us. I came through an acquisition of itaas which was -- as a CEO, which was doing engineering services in the communications, media and tech space. But today, I'm really excited to talk to you about two things. One is the huge opportunity of digitizing the physical world. And second is how we are enabling the differentiation of becoming the next-generation contemporary player in this industry. And we are -- look, we are at the core of our customers' business. We are building, we're designing, we're making, servicing, scaling solutions that are intelligent, that are connected, that are autonomous, and that are driving efficiency and that are driving innovation and growth for our customers. Now these end-to-end capabilities across the ecosystem is helping our customers bridge the physical and the digital worlds. And I'll draw your attention to the bottom of the screen. The digital things can be anything from sensors, embedded systems, cars, factories, buildings, anything that's physical. What we are doing is we are embedding the engineering from the chip. We are going to embedding the software in the products and the factories, allowing autonomous technologies to mobilize static products and static factories. And with this, I'll tell you that this kind of engineering and R&D spend is representing a very large and growth market. You'll see here that in this market, with a 10% CAGR, by 2027, the expected services spend in this market is $280 billion. And if you look at the horizontal spend across the domains, we are 100% aligned in this area. And in the spend by the industries, over 80% of this mirrors where we are focused in our industries. So we are aligned with the market mix. We're aligned with the industry spend. And what we're doing here is we're covering this market with 4 distinct and differentiated offerings across the very high growth industries that are listed at the bottom. One of them that's highlighted is the A&D industry, which we have done with Belcan's acquisition. In fact, Lance, the CEO of Belcan, is here somewhere. Where you Lance? You can talk to him afterwards in the back. So this modern and futuristic engineering requires deep domain expertise, which is what we're providing through these offerings. I'll take you through these real quickly. The smart products, what we're doing for our customers here is we are going across the entire life cycle, the entire product life cycle. This means going from inside the product with embedded systems to outside the product across the networks to beyond the product. For example, product as a service. In this space, we're going from chip to cloud, and we've also done an acquisition of Mobica, which further solidifies our embedded capabilities. In intelligent mobility. Again, we are engineering inside the car, working on ECUs, which are electrical control units and embedded systems, to outside the car for connected platforms, autonomous platforms and from -- to beyond the car. So for example, the car to the grid, again, going from chip to cloud and beyond. In this space, we have done an acquisition of ESG Mobility that is further solidifying our automotive stack. Similarly, under intelligent operations, which is the third one, we are modernizing the plants for smart manufacturing and autonomous factories. Again, from inside the factory with shop floor modernization, Industry 4.0 to outside the factory with smart logistics, to beyond the factory with autonomous manufacturing and operations. In this space, we are accelerating the innovation with acquisitions that we've done in the past of TQS and Zenith, and also with our strategic partners that Sandra will talk about, AWS and NVIDIA. And this is really some really core work that we're doing here. Now this, in the fourth offering, spaces and sustainability, we are creating solutions to -- we make the spaces highly efficient. Whether these are buildings or factories or warehouses, and in each of these industries, we are providing sustainable solutions for better outcomes. Now this is the kind of transformation we are driving with these capabilities across all our clients. I have several examples of this, but I'll give you a few today in each of these categories -- in some of these categories. In smart products, for example, one of our clients who is a global tech leader in electrification and automation, is creating a suite of chargers that's intelligent and that's future ready, and that's communicating with the new age EVs. Now this charging EV is a really complex mechanism. It happens in real time and the chargers and the EVs need to communicate and decide on the charging profile that's acceptable to the EV and to the charger. What are we doing here? Our team of engineers is working across embedded systems, they're working across chargers, across hardware, across charging platforms. And we are executing a very highly technical and complex work, which is driving the future of EVs, IV chargers. And in this space, we are implementing this solution across 35,000 units. Now in the automotive space, did you know that 30 million to 100 million lines of code goes inside a car today? Now the value of the car is embedded in more of the electrical ECUs and the embedded software than it is in the mechanical components. And cars are now connected to the cloud to keep them current, to keep them updated, to add features, which is commonly known as a process called FOTA or SOTA. It's firmware on the air and software on the air. So we are providing deep engineering expertise across every aspect of this product life cycle in the car. At this time, I'd like to address your attention to the first example where we're working with our European auto OEM in autonomous and electric movers. What we're doing here is we're playing a really pivotal role in their autonomous journey. We're doing the electrical and electronic design. We're integrating various ECUs in the electric vehicle. And we're doing verification and validation, commissioning and deployment of this prototype. In the smart manufacturing space, we are working with one of the global paper and packaging majors, or companies, that is integrating real IoT data across 20 of their plants. And this is integrated -- all of this is integrated with the AWS cloud. Now this solution is using some of the newest technologies in GenAI. It's using some of the newest technology in digital twin and also in data collection. Now as I transition to the next slide, I'll talk about some of our solutions, our platforms, our GenAI solutions. We have many of these. You see 5 of these running here, but I'm only going to talk about two. The first one is our Neuro Edge platform, and Prasad referred to it in one of his AI portfolios. This is -- this platform is delivering compute power by bringing intelligence to the edge. Now there are many benefits of this, but I'd like you to remember just three of them. One of them is around the automation and the latency reduction, and that gives you real-time data processing. The second one is reducing the time that goes to the cloud. So now you're efficient and you're doing all the processing at the edge. And the third one is enhancing privacy and data security. And this immediacy of real-time edge processing is very critical in some industries like automotive, in industries like A&D, in industries like med tech or manufacturing or retail. And this is where we are implementing this solution across our customer base. Our digital twin solution. This is one we've developed in partnership with AWS and with NVIDIA's Omniverse platform. And this is for manufacturing plants and factories that are connected, that are intelligent, and it's done through simulations and modeling. This enables us to drive optimization in the -- AI optimization in the factories and make it more autonomous. Now with many of these innovative solutions, cutting-edge capabilities, centers of excellence, state-of-the-art labs, we are going to market with a highly differentiated portfolio as the contemporary next-generation player in this industry. And this is what gives us the right to win. I want you to remember 5 key takeaways from this. Number one is that our offerings are aligned to the spend in the domain and the industries. The shift from physical to digital, we talked about how the ER&D or the engineering work is being outsourced. You heard the numbers, $280 billion of spend. But what's important here is it's also being spent in the regional markets. So our -- we are leveraging our global talent pool across all the regions across EMEA, across APAC, across the Americas for providing these capabilities across all of our clients. And then the second -- the third one is our global network of labs. You see the phygital infrastructure. This is much more than IT infrastructure. This is labs that have products, manufacturing labs, automotive labs, garages, studios. So there's a lot of infrastructure that's going in from a physical standpoint. And the fourth one, of course, is our strategic M&A. I spoke about a few. But here may -- we're making the investments across key domain areas in our M&A. And combined with our strategic partnerships like NVIDIA, like Qualcomm, like AWS, Siemens, just to name a few. This is what is giving us the access to the markets. And finally, I spoke about the cutting end solutions. Assets and process frameworks, we are accelerating the time to market, speed, speed, speed, I know you heard that. But as we do that, what's important is that we deliver a robust quality deliverable. Now these especially in mission-critical domains like aerospace, like nuclear like automotive. This is how we're going to market with a highly differentiated portfolio. And combined with what Prasad talked about on the engineering platforms, Cognizant's engineering and R&D portfolio of over 100,000 engineers worldwide, is uniquely positioned today to drive the next wave of transformation. Thank you very much. And I would like to invite Naveen Sharma to the stage next.

That was good. Thank you, Prasad. Thank you Vibha for setting that up. So you heard a lot about how we're going to market with engineering, both embedded and for clients. I'm going to talk about something that makes it real. The foundations of all engineering programs end up sitting on data and cloud. So those are the areas I'm going to talk about. My name is Naveen Sharma. I run our data analytics and AI business at Cognizant. I've been here 16 years, and I'm going to walk you through the journey of where we stand with data and the cloud. So let's first look at the market. To the left, you see the numbers, right? $840 billion TAM that we estimate exists today. Look at the CAGR of that. Such a large market with such growth potential. You can do the math. It's expanding $64 billion every year. Where we stand today is the bottom left. You can see we're very well qualified. Nearly 40% of our revenue comes from doing work in the data and cloud space for our clients. Now how did we get there? How do we realize this value? Go to the top right of the slide, and let's talk a little bit about our differentiation. Vibha touched on this theme already. Our go-to-market is very strongly indexed on industry focus and alignment. I'll show you -- I'll talk a little bit about some of the solutions that we've built. So 120-plus solutions that are purpose-built for the industry. In addition to these purpose-built solutions over the last few years, we started to build purpose-built AI and machine learning models. So if you're a bank, you're looking to reduce the amount of credit card fraud that happens. You're looking to flag it quickly. You're looking to make sure that the fraudsters don't get away with too much. We built a model that helps you flag it, help you detect it, help you stop the transaction in near real time. Similarly, we've built models in health care. I'll talk about one of those in subsequent slides. The thought here being health care is a complex business. To review claims in health care, you need folks that have had a certain amount of medical education. How do we take those folks, those highly expensive folks, specialized in their area, and how do we take their effort away from doing paperwork review to something that is higher value? So we'll show you that in a few moments. This has been built by a large set of platforms that are more horizontal. I spoke about industry use cases. Data and cloud is also platform specific, that is horizontal. I'll talk about a specific platform, Ignition. Prasad touched on a few of these platforms already. Vibha touched on 1 or 2 of those. I'll show you what these platforms can do to speed up the journey for our clients. This is what we're doing in inside. At the bottom right of the slide, you can see some of the recognition that we've received from analysts -- industry analysts, that reviewed the space for a living. In each of these analyst content collateral that is published, we end up in the top right. On the top right is, I think, you can look at these names. You can see where the competition is, and you can see where we are, and we feel very proud about our position in here. Bringing it back to what Ravi touched on, the 3-vector strategy, right? So this is -- every client that we work with is executing on all 3 vectors. Some are further along on Vector 1, some are starting Vector 2. Some have already made the leap into Vector 3. Doesn't really matter. Every client is on this journey somewhere. To realize these three vectors, we think they have to start looking at a new technology stack, and that's what we call out on the right. I'm going to walk you through this. I'm going to start at the bottom and work my way up. And once I do 1 or 2 of those, you'll see where I'm headed with this. The bottom of this is a scalable foundation. For the next 10 to 15 minutes, I may call this cloud, but I want you to think of this as the true basic foundation. It's the cloud infrastructure, it's SaaS capabilities. It's the digital engineering work that Prasad touched on. It's the work that happens within APIs. It's a work that happens within BPO. It's a work that happens within cybersecurity. Unless you have a secure and scalable digital foundation, you're not really going to build up anything over it. The layer above that is the enterprise data layer. Now this used to be fairly simple. Plug in and connect my enterprise systems, and I'm good to go. That's no longer the case. The data that our clients work with today is not just structured. Every single client that we work with now has video data, has image data, has audio data, sometimes has clicked stream that comes in from their website from their mobile apps. So how do you bring all of these different data sets together and be able to actually derive meaning out of them? That analytics and insight from the data is the key part. So those are the two layers that I'm going to talk about. But to realize value, you do need to look at the other 3 layers as well. So going back up, the decisioning, trust and model management layer. Be it a simple analytics model, be it a simple machine learning model that you've built over the years or be it an AI model. These models are not going to govern themselves. These models are not going to configure themselves for your enterprise. That configuration, that governance, that adapting the model to fit into your workflow is the third part of this stack. That's obviously something that takes effort. We've been doing a fair bit of work in this space, very proud about this. The layer at the top is closer to vector #3, agentifying the enterprise. That's the multi-agent orchestration. So within your enterprise, you've now got multiple agents. Each purpose built, each speaking to your enterprise systems, each serving different client needs. How do you bring them all together to make sure they behave responsibly? The right work is being done by the right agent, the right outputs are being passed to the next agent, and all of this is acting in cohesion. That's the work that Babak is going to show you in the multi-agent orchestration space. If you haven't seen that demo, I highly encourage you to stop by. George somewhere in the back of the is going to walk you through that demo. And I think that's going to be fascinating. The layer at the top is the experience layer. We already spoke about this. Ben has been working on this with this team on rewiring that whole experience layer. It is no longer just boxes on the screen. It's going to be a mix of every single modal communication that you have, bringing all of these together. So those are the 5 layers of the new technology stack that we think you need to realize. I'm going to focus on these bottom 2. So let's start very quickly with those 2 layers. On the left of the slide, you'll see the work that we do within this space of enterprise data. It doesn't matter where you are in your data journey. We have clients that are in what we would consider the foundation layer, right? The data foundation that they built is traditional. The data assets that they have are traditional. For some reason, they haven't moved away from the traditional ecosystem. That's okay. We play in that space. We help them maintain that space. We help them optimize that space. And sometimes we help them unlock value that leads into the next layers. The next layer is your data and AI management. This is where you start to make sense of data. So you've got data. Is it good? Is it reliable? Is it trustable? Do I really know who my clients are? Who my suppliers are? Who my stakeholders are? Where is my data quality. All of those things come together, not just in data but also in AI assets. Third part, data modernization. This is our biggest piece of work in this space. This is where we help clients move into the new. The new is defined as anything that was -- we define it as anything that was built in the last 10 years. And we think this is something that's important. It's our largest book of work in this space. It's also a book that keeps evolving. So what was 10 years ago, Hadoop was modern. Today, we do a significant amount of work modernizing clients away from Hadoop. So this creates its own refresh cycle. The BI and visualization layer is being redone. Very, very few clients want to go down the path of traditional dashboards. This is all turning into conversation AI. Ask a question, get an answer, do it quickly without making me click through 10 steps. And the last piece is analytics and AI. The most exciting piece of work that we do. This is where we build new models that help clients be predictive and also build prescriptive models that tell them what to do next. So that's the stack on the data side. Let's shift to the cloud. And remember, this is my expanded definition of the cloud. So it's cloud and SaaS and cyber and all of those things that go together in that foundation. Every client is in a different place in their journey. There are some that are still making the move to the cloud. For those clients, we come in and we help them build the capability from upfront. So we help them advise on what to do. Is it a singular cloud? Is it a multi-cloud? Is it a mix of cloud and on-prem? We help them design and migrate to the cloud. Once the client is on the cloud, the next piece is the enablement for the cloud. So now you've got an asset that is scalable and does new things. How do you take advantage of that? How do you make sure you do it in a secure manner? How do you make sure that the 10 things you were doing on-premise are not the same 10 things you're doing today? So that optimization that's securing is what happens in this second offering for the cloud. And the last piece is the most interesting one. This is new capabilities that we unlock. So enablement by the cloud. Now you're on a modern stack. Now you've got the latest and greatest capabilities. How do you unlock new business capabilities that you may not have had that drive top line, help you manage your bottom line. So bringing all of those things together is what we do in the cloud space. This is a data and technology view, Here's an industry-specific view. So I touched on this. I'm going to do a very quick drive. So I've got examples of 5 different solutions, right? Over 120 exist, but we've called out 5. Look at the first one in here. For our life sciences clients, life science companies go through a large multiyear journey in trying to identify and trying to speed up the R&D process. A big component of that is identifying sites where trials can be conducted. This asset that we've been working on for years actually helped them improve site activation by over 57%. If you're a quick service restaurant, that's where OrderServ comes in. Every quick service restaurant struggles with how do you build that digital infrastructure to quickly bring in orders, to deliver orders fast and to do it with a certain amount of cost predictability. OrderServ helps our clients reduce the cost for building up that scalable architecture by 30%. It's something that a QSR can deploy quickly and manage costs. This next one is something that I touched on already. If you're a health care payer you get thousands of claims that come in where people are saying, I should have been given this treatment, why was I decline this treatment? The traditional manner has been, you have to pay someone that either has a nursing background or a medicine background to review those claims. They have to review those claims, go back and forth and they still use fax machines for some of this. Go back and forth over the fax machines and then turn around an answer. We've short-circuited that whole process. Built a solution that uses generative AI. To look at the inbound claim, review it, turn around with the decision very quickly. Currently running at 86% accuracy. And this improves every single implementation that we do. So this is something that I want to call out. Let's talk a little bit about a broader story that I'm going to go deeper into Cognizant Ignition. We spoke about how data is prevalent, how data really drives what an enterprise does. What does that really mean for each of the clients? So let me just walk you through Ignition in a little bit of detail. The way to look at Ignition is it's a set of tools that help you manage your data journey, where you are. So on the left side, you'll see -- we've got an asset that helps you discover where you are. What does my data estate look like? What do I have and where does it sit? And how do I manage it? Once I know what I have, how do I migrate it on to wherever I want to go? So X to Y sort of migration, sitting on Teradata today, I want to go to a Databricks or Snowflake or something else in the future. Once I'm doing that, how do I integrate with my existing assets? How do I make sure that integration is done with quality and predictability? And then how do I start to drive meaning out of it. So those are the 5 modules in this asset. The guiding principles for doing this are in the middle. We're not going to go to a client to tell them to use AI without using it ourselves. So we use a fair bit of AI to look at data quality to manage the migration, to do metadata discovery when we go from Platform 1 to platform 2. Use a fair bit of no-code and low-code capabilities within this platform. So the implementation is faster, the build time is faster. We've been able to do this with about 140 folks, patents that are protected here, and look at the outcomes. Over 12 petabytes of data that have been moved using this platform. Over 1 million hours, person hours of savings realized from this platform. To give you a sense of the size and scale of where we deploy this, one of the largest banks in the country headquartered right here in New York City, use this asset to speed up their data modernization journey. One of the largest telecom providers in the country used this asset to speed up their data migration and modernization journey. So that's an example of the kind of work that we do with these platforms. How do we build these platforms? Well, one, not in isolation. We've got a large number of net partners that we work with. The ones that you see on here are some of our long-standing relationships. The good news here is that we're in podium position with each of these. Sometimes it's size of revenue, sometimes the number of trained resources, sometimes in our joint go-to-market. Sometimes just having the data and analytics practice of the year consistently. So these are all companies that we work with over the years. There is one at the bottom is interesting. If any of you were at GTC, you would have caught Jensen at the Cognizant booth telling everyone that if you want to modernize your business, go work with Cognizant. That's a hilarious video, I'd love to show it to you if you're interested in seeing that. Stop by in the break and I'll show you what that is. So take this energy from all partners and the capability that they have. Bring in the work that our people do. We've got a large pool of very talented resources, people, that work on these platforms. When you combine the 34,000 data and AI associates, and 19,000 cloud engineers, the 38,000 cloud architects -- when you combine all of them together, that's when we start to get the grassroots innovation really firing. So all of these platforms that you see on the right came about as a result of that grassroots innovation. The investments that we made obviously help it, but this is how we keep that engine running. So we never actually fall behind the curve. So that's how we build this stuff. I shared all of this. So what does that mean for a client? What does a client do with any of this? So let's talk a little bit about that. Let's talk about this client, which is a very large biopharma company. They focus on antiviral drugs. They focus on HIV, AIDS, cancer, all sorts of serious health conditions that need a fair bit of science. For this client, we started off in the first tower around cloud modernization. So they were on the cloud. How do you modernize the cloud and optimize it for them? Be it something as simple as going in and saying, how do I take your IT operations and bring it into this century? How do I make sure that your applications are safe, secure and risk-free? Doing that sort of basic work allowed us to unlock the next phase, which is the data modernization journey. So as they moved into their road map of cloud-first data management, how do we make sure the data is secure and available to all the applications. Look at some of the savings we've realized for them, right? 70% automation of data and schema migration conversion. The next one in here is on master data harmonization. They did an acquisition. They were able to bring in data from this acquired company in a matter of 3 months, harmonize all of the records, have the sales force pointing at the same set of prescribers, same set of employees, just consistency between two companies. Leading to the third tower, which is enterprise and Agentic AI. This is where we use machine learning to build out the set of multi-agent capabilities. These agents go across customer service, employee experience and then we use our orchestration layer to bring them together. So that by itself is an example of what we've done, a journey that we've executed for a client. The thing that you don't see on the slide that I want to draw attention to, this is not a left-to-right arrow. Every time we did something in the first tower, it unlocked something in the second tower, which unlocked something in the third tower. And when we unlocked something in the third tower, that actually created this flywheel of, now I need new capabilities in my first tower. So in some ways, this flywheel is powering itself in terms of innovation for our clients. And obviously, that allows us to go deeper and build more meaningful relationships. So to summarize our right to win. We go to market by domain. We build domain-specific solutions that obviously leads to these things, right? So you get a faster deal cycle. You get higher client retention. We are able to deliver fast. We spoke about our suite of platforms, unlocks net new revenue streams for us, allows us to push new capabilities into our client ecosystem. We do AI-powered data modernization that leads to larger contract sizes, leads to higher margin consulting work and creates long-term stickiness. Number four. The space of data ops and cloud cost optimization is big for us. Every single CIO that we work with feels that they're spending more on this than they plan to. We've got the ability to go in and help them unlock that value. We'll commit to commercial models where we realize a certain percentage of savings that we would save generate for the client. If we don't save them anything, we don't walk away with anything. But if we do, we get a certain percentage, which leads to long-term stickiness for us. And the last piece is AI driven compliance. This is going to become bigger and bigger for us. We feel very strongly about this. We're the first SI to actually have ISO-42001 accreditation in this. We feel proud about that. We're going to keep investing in building in this space. So really to summarize, the market is large, the space is growing. We feel that we have a very good position in this space, given the work that we've done, the capabilities we've developed and the value we deliver for our clients, continue to invest in building these capabilities and where we stand today. We think we have the largest data analytics and cloud capability across our peer group. So given that advantage, we feel very strongly about our position in this space. With that, I'm going to hand it over to Surya, who is going to talk about the work we've done with one of our clients.

Thank you, Naveen. Good afternoon, everyone, and thank you all for taking time to be with us today. I am Surya Gummadi. I'm with Cognizant for more than 25 years. So I joined the firm 25 years ago from college. And over the years, I have moved around the firm. We have been in business development, sales, presales, a bit in the program management. I also worked in Mergers and Acquisition and Integration. I was the one who worked on the acquisition of TriZetto and integrating it into Cognizant. And I managed a couple of business units including health care, which is our largest business unit before taking on as President of Americas a couple of years ago. I proudly say that I have spent more than half my life here at Cognizant. And since this afternoon, we have heard strategy from our CEO Ravi, and we have heard about our investments in AI from Prasad, Vibha. And we have just heard about our data and cloud strategy. So now I would like to take this opportunity to bring this to the forefront and show an example of how we bring this to our clients. It's my pleasure to invite CIO of KeyBank, Amy Brady, to have a conversation on these lines. Amy? Thank you, Amy.

Great to be here. I think I stuck out like you tell the client in the room.

It was not by design by the way. So Amy, you have been the CIO for KeyBank for almost a decade. More actually. A little bit more. A quick intro of yourself, please?

Yes. So great to be here. So I'm Amy Brady. And yes, I joined KeyBank about 13 years ago. And prior to that, I was with Bank of America for a mere 25 years. So I have a little bit of experienced financial services. At KeyBank, I'm responsible for all of our technology organization. So from front to back. I also have the privilege of running all of our shared service back-office operations. So think loan servicing, deposit processing, collections. I also run our Intelligent Automation Center and our contact center. So every voice contact that our clients have with the enterprise. I have our Chief Data and Analytics Officer, who reports to me for the enterprise. Enterprise security services, which is in a bank fraud, AML, physical security, cybersecurity, all the things that keep you up at night. And on top of that, I have the joy of running all of our real estate portfolio just to add a little bit to it. But keeps me busy and I love it.

That's a very short intro, I guess. Now, anyway. So actually, Amy, let's start our conversation with the same question that Ravi got this morning in CNBC from Sara Eisen. So on one side, we are navigating the biggest tech transformation of our lifetimes. On the other side, we have this global economic uncertainty and geopolitical tensions. So how are you -- or how is KeyBank navigating this volatile environment. And what does it mean to your priorities and spending patterns and things like that?

Yes, I wish I like Ravi had a crystal ball and how this is going to end up. But look, I think We, in general, and financial services are optimistic, cautiously optimistic about this year. On one hand, we do believe the administration will be lessening regulatory burden across multiple industries, including financial services, which is a good thing. Because a disproportionate amount of our spend has had to go towards regulatory requirements over the past several years. For those of you who don't know, KeyBank, obviously, we are one of the largest top 20 banks in the United States. But if you are not in one of our geographies, you may not have heard of us. And so we are one of the largest regional banks in the United States. And so regional banking has been a little difficult over the past couple of years. So we're excited about that part. For our clients right now, much like for Cognizant, there's a little bit of uncertainty based on what's going on in Washington. And so we are seeing clients came into the year with optimism, a little bit of caution right now and executing transactions, but they believe that there is kind of a light at the end of the tunnel. And if we could settle on things like tariffs and things like that. It might make some of our clients decide to enter into the waters a little bit faster. So we remain optimistic for the year ahead. But it is going to be a year unlike -- I mean, well, not unlike, just like the last 5 years with a lot of uncertainty. So I think most of us have become very good at being agile and adaptive and changing in the marketplace. So we're all having to do that.

So AI continues to be your #1 priority?

I wouldn't say it's a number one, but it's up there. It's up there.

And how are you industrializing AI into the enterprise? How are you redoing your plumb lines across your tech stack leveraging AI, GenAI, Agentic AI?

Look, I think everything you've just talked about for the last hour or so, I'm kind of smiling going, well, we do that with Cognizant. We do that with Cognizant. We do a little of that with Cognizant. So we've got the whole spectrum over the course of our 19-year relationship which has evolved and grown and absolutely changed over the years, right, on the types of services we buy. But when I think about the priorities, first, you have to modernize -- constantly have to modernize your system. So there's always a portion of our investment that's going towards that. And you're helping us that with that. We don't get off of all of our legacy systems probably in my lifetime, but there's a goal to get there, right? So you're constantly having to do that. Second, you're constantly digitizing. And so when I think about that, it is front to back. How are you constantly making the experience for our clients, whether they be a consumer, or an institutional investor, they want a digital experience, and they want it to be as easy as their favorite app that they have on their mobile phone. And so we have to continue to work on that, making self-service really simple for all of our clients in the various segments. Payments is a huge part of our business. So constantly investing, trying to figure out how do we make those investment products stickier. And that's all done through technology, making it easier for our clients. And then when you talk about data. Cognizant, I'm really proud of this. Cognizant has been on our data journey with us for the 13 years I've been at Key. And actually, when I visit India, we still have people on our data effort, our data supply chain, we call it, who have been with us since the beginning of our journey. Who are still on our journey there and run -- and help us run our data foundation. As you just heard, Naveen talked about. But that data is now so much more valuable to us. And it is the fuel for the AI. It is the fuel for generative AI. It is a fuel for taking the robotics work that we started together 8 years ago and now thinking about how do we agentify that work. And so I think there's so much more ahead of us to do. I will also say, we have to work together to figure out what's the business value. It's not tech for tech's sake. It's how do I create value for the enterprise using these technologies?

And first of all, thank you for long-standing strategic partnership, 19 years. And talking about that business value, how are you tracking that? Or how are you measuring that value?

We're in the infant stages, as you know. So we have about 20 proof of concepts going on right now with generative AI. Now in financial services, we've used AI for decades. We've used advanced analytics. We've used artificial intelligence. We've used some machine learning for decades. We're good at it in certain areas, right? We're good at it in credit and financials. But when you think about taking it to replace some of your workloads to your operations or really making -- enabling decisions to be made faster, that gets a little harder and say, how are you going to prove the value? Where is the business value? But there's got to be that discipline. Because if not, you're going to see that one chart, I think someone talked about where CIOs get concerned about cost. So as your tech costs go up, you better be producing value because the CEO is then going to come around and say, hey, your tech costs are going up and my revenues haven't kept pace with that. So constantly having to evaluate that, and we're being very disciplined to make sure that, that happens.

Yes. So it's interesting you say that. I've been talking to some of our clients. They view this in two dimensions, inside out and outside in. The investments that are -- they are making in AI. One dimension is the benefits that it serves them, or it serves a client like you, it serves KeyBank in terms of unlocking the productivity or driving the revenue growth or improving the balance sheet and things like that. The other dimension is, what does it mean to your end clients? What does it mean to your consumer who walks into your banking center at the teller? So how do you...

Yes. So I would say -- now this is Key's position. And I would say, in a regulated industry, we're not -- we don't want to go really fast with putting some kind of agent out there that will make a decision for the client and offer that up without any human in the loop. I think we've got a lot of proving to do and there's lots of opportunities to deploy this technology for value without having to go there first. I think we'll get there over time, but I don't think we need to go there first. Plenty of opportunities where we've got manual processes, whether they be in my tech shop or our operations shop. And all of that, ultimately, if you can automate that and make it smarter and better, make it easier for our clients to do their work. We also, I think, can use these technologies to make our relationship managers smarter. Really arm them. Again, going back to -- we've been on the data journey. We moved our data to the cloud in 2019. We moved off Hadoop in 2022 with your help and moved to Google Cloud. So our data is there. We have the speed. But are we using it to really present it to our clients at the time that they need it the most? That's where I think that opportunity is there.

And while you do that, how are you managing change? Or how are you doing the change management with your workforce?

Yes. I mean that's a huge investment. We've started something many years ago called Future Ready, in my organization, where we take time to train our people and retrain and are constantly investing in the training and we use partners like you to do that with us, which is extremely helpful. Because as a financial institution, I can't have the best in every one of these disciplines that we need, but we have to have a few of them. And so we absolutely have to invest in reskilling our people, whether that be technologist or we're going to need less lockbox agents, or less contact center agents, but we want those people who know our processes and our clients to have opportunities in other parts of the institution.

And Amy, you have heard this afternoon. And in fact, you are very aware that Cognizant has spent -- pledged about $1 billion of investment into AI over the last couple of years, and we are continuing to invest...

We plan on taking advantage of that.

And we have built the infrastructure, as you have seen in the AI labs and know Babak very well. So we have more than 25 PhDs doing constant research. We have 54 patents. And we have built these platforms. And we are building these industry-specific solutions. As a client, how would you see this? What's your reflection on the partnership?

I think one of the when I first saw Babak, you all get to meet him in a moment. But when I first saw him, and he talked about agentifying your enterprise. He did it, one, you can tell he knows what the heck is talking about, he is brilliant. But two, he did it in a way that the average enterprise user could consume the information. And what really sparked my interest was we have about 400 bots running today who have IDs as employees in our system, right? So they are doing tasks every day somewhere in my enterprise. Large amount of them are in our operations team. But they are task-based bots. They're not smart. They're not decisioning. What I saw was the ability to take those bots and really take it to the next level. Now to do that, we need the data. We need intelligent people like Babak and others to help us build from where we are to that next level. How do we make ourselves smarter. And so I think there's a great opportunity there.

I mean thinking -- talking about agents, in bots. Last week, Jensen at NVIDIA tech conference, he was referring to the IT organizations of the enterprises, potentially morphing into semi HR roles. And he was -- it's interesting. He said that he said that these IT leaders will have to select agents, train agents, manage agents and patents like any HR organization would do. So how are you envisioning this agent-centric enterprise?

And I don't think we should underestimate. There's also another level of you need to monitor the agent's performance, and you need to understand when something in that value stream changes, are you retraining your agents? And that is not insignificant as you deploy all of this. Remember, so honestly, as a CIO, I remember when I first started, it was like simplify your system, simplify your ecosystem. Our ecosystems have gotten more and more complex. And quite frankly, I think they will continue to do so. And so it's how do you build the intelligence around your -- even your IT ecosystem. You're not just with one cloud provider, you're with multiple SaaS providers. You're on-prem. You've got all of these things interacting all the time. And by the way, you have to have 99.99% availability 24 hours a day, 7 days a week. So that has to get smart too.

Right. And any AI conversation is not complete without talking about the risk and the guardrails that one needs to -- so what's -- how is KeyBank managing that? What's your perspective on that?

I would say we're learning. Again, I'll go back to, I think, certain industries maybe have an advantage where they're not highly -- as highly regulated as financial services. Our legal and compliance are really struggling with some of this autonomy of some of these tools. And what does that mean? And so I think we're trying to walk our way into it without sprinting and getting ahead of those groups as well. So we've all got to learn together.

Thank you, Amy. And you know what, since you mentioned about Babak and he knows what he does, so here is a deal for you. So he's going to create agents on the fly for the KeyBank for a business problem that you're going to give to him.

And I'm getting this for free?

Yes, you are getting it for free. Amy, it's always a pleasure talking to you. And thank you for the long-standing partnership.

Hello, everyone. My name is Babak. I am the CTO AI for Cognizant. My background is in AI. I got into AI in the late '80s. It's all I've done. All I know, it's all my career. It wasn't as cool as it is today for a while. And it's a burning spotlight right now. I want to talk about AI and agentification. I also want you to see why I think Cognizant is the place to be right now for someone who's been in AI. I have a PhD in AI. I was the main inventor of the natural language behind Siri, which is now years ago and not as good as it used to be. I started the world's first AI-based hedge fund. And -- but I'm here. I'm at Cognizant because I think the opportunity is here. The opportunity to identify the enterprise is right here and right now. So let's dive right into it. Let me first talk about the investment that we're making into innovation. And so there is a process, there's a pipeline of our AI PhDs coming up with, and pushing the envelope, on the latest and greatest in AI. And that making it into our various different platforms. And there is a method to this madness. I'm sure you've seen this through my colleagues' presentations up until now. There's an ecosystem to be built, and it's wide and it's deep, and our platforms are hitting every aspect of that. And the platforms, the innovations are manifesting themselves through these platforms. And I'll talk and I'll demo some of those in a moment. And of course, we have a number of AI studios around the world where we showcase these -- sorry, I have to unlock my laptop here. And it's asking for a password, sorry. And we work with institutions and academia. We have a number of patents. Again, these are 57 patents right now, peer-reviewed papers. Just speak to the fact that a company like Cognizant is valuing innovation very, very deeply, and it's helping us. But before I show you some live demos here and Surya put me up to actually building an agent for Amy. I'm going to do that. Let me level set on what we're talking about here is what is an agent after all? Is it just the latest like reincarnation of AI? Or LLMs or GenAI? Or is it -- what's real about it? So going from left to right, this is a GenAI model. It's a model. What that means is it takes some inputs and through some process of predicting what we might want to see, it produces some outputs. So that's a model. It doesn't do things. It just produces things. It generates things. That's why it's GenAI. If we go ahead and enable this model with some tools, then it becomes an agent. That moment of switching from a model to an agent means we're imbuing this process with engineering. We've moved to an engineering discipline. We have to decide what is the responsibilities of this agent? What are the tools that we're going to give it? Where is it sitting? What kind of micro services is it representing? What kind of data is it representing? It's engineering. It's customization. And then, of course, if you have one agent responsible for a portion of what you're doing in your enterprise, you will have other agents as well responsible for other portions of what is happening, and you want these agents to work together, and that's a multi-agentic system. And what I want to show you is the fact that we are moving towards a multi-agentic enterprise. We are going to be building these agent systems as networks with clients building some of those agents. We'll help them build some of these agents, custom for their specific use cases. They will be provisioning some of these agents and customizing them from third parties, say, Agentforce, or Agentspace, or everybody's got their agents now. And plugging them interoperably into this multi-agentic system. Let me just give you one quick example of why this system is progressively more powerful. You can ask a GenAI model to write you some code, and it will do it. And you will get a relatively impressive percentage of a coding benchmark solved just right off the bat. Just take the code that it produces and run it, and it solves that problem. That's what a model does. If you actually give an agent the proper tools, for example, to run that code in a container and allow the large language model behind the agent to view the result of running that code, it can iterate on the code and improve it. And without fail, our coding benchmark is improved just by simply doing that, just allowing the LLM to run the code in a safe container, viewing the results and improving it. We get better results more of that benchmark solved. Here, we're moving from writing code to building software. It's a team that's coming together. I actually have that example here. It's a project manager, working with a QA specialist. Some agent that assesses unit code -- unit test coverage and adds unit tests. It's a team that's building a software. That's what we're looking at. And of course, that third multi-agent system, if set up properly, is beating all of our coding benchmarks. Okay. So Gartner believes the future is in multiagency. Not only do we believe that we've seen it. And not only have we seen it with our clients, we've seen it with ourselves. We're a very large company. Our HR department has its own IT. Every unit within our company being an innovation-driven AI-driven company. AI first company, is building these agents. And these agents are begging to be connected to one another. It just doesn't make sense for you to go to one agent and ask it a query and for it to say, well, out of scope for me. Go see another agent that can do it for. You want these agents to be talking to each other. And when you do that, you're breaking the silos. And when you break the silos, you're reducing cost, you're improving efficiencies. Okay. So let's -- enough slides and let's actually build the system here. If we could go to my laptop. There we go. Okay. So as I mentioned, we're doing this internally. This is our Intranet and it's a collection of various different very useful apps that come together. And we've incrementally started agentifying this. And we can actually use various different entry points to talk to this system. And by virtue of talking to it, the agents representing the various different apps that are useful to an employee will be talking to each other. I encourage you to come over and actually see this, and we will give you a full demo of this and how it works. But what I want to do is show you the behind the scenes of this and the actual agents. Let's go to our Neuro AI platform. This is the platform that we use to build individual agents, actually identify and scope them, and I'll do that right now and then put them together into a multi-agent system. But before I actually build an agent, let me show you the intranet agent, the one Cognizant Intranet and it's asking me to log in. Okay. We didn't practice this part. Sorry about that. As you can see, security is very important to us here at Cognizant. And once this loads, I will be able to show you -- there we go. So here is one of our multi-agentic systems. It's rather small, so I'm going to just slow it up just a little bit. And I mentioned our Intranet. So you can see here these agents representing the very certain functions within our Intranet. It starts to look like our org chart. It starts to look like functions that as employees within Cognizant, we are taking. And of course, it's human in the loop. Of course, it's augmented. But it's growing incrementally and organically, and that's how we set it up for our clients. We allow our clients to -- various different divisions with our clients to build their agentic subnetworks and have a manner to test them and plug them into the larger agent network. So if I ask it a query such as a life change event. I just had a baby, what do I need to do? So I used this on purpose, I showed this to an analyst and they're like, wow, life change events, you type that in, and the agents identify which down-chain agents are responsible for dealing with this, and you get one consolidated response. There's some benefit changes. And by the way, you can take some time off. Now that you have this baby, you might want to take some time off. And I can follow up with that and actually take some time off. And hopefully, this gives you an indication of how the system is breaking the silos and I'll show you some more of that, but let's just build one of these agents. These agents have to be grounded. And in order to build a grounded agent, we're going to go into a multi-agentic system. So what I'm going to do is I'm going to use agents to help me build an agent. So it's a bit meta. We're using agents to build agents. So I have a number of agents that are human in the loop agents that we're going to interact with. And Amy is standing there. So we're going to start off by just typing in KeyBank. Any particular division within KeyBank? Or should I just keep it with KeyBank, Amy?

Why don't we do commercial lending?

Commercial lending. Okay. So what the system is going to do is it's going to -- so this is obviously not implemented at KeyBank. So I don't have the data of KeyBank. It's going to do with search online for publicly available information on KeyBank, and it's coming up with a number of ideas as to what kind of agent we can use. So this is a collaborative process of identifying the use case. And it's picked one of them, and it's actually doing an ROI analysis on that using some guesswork and some public information. It's picked commercial market finance decision-making. But we could do any one of these. So Amy, are any one of these interesting for me to build for you or should I do a different one, up to you?

You choose. You are the banker today.

I choose. Okay. Okay. How about we do SBA loan eligibility and with that, yes?

Yes, good luck with that.

All right. So now I'm moving to the scoping agent. What the scoping agent is going to do is it's going to think about what is the data that's going to be necessary. Remember, we're building an agent that's grounded into KeyBank information and data or third-party data that we might have to bring in. For example, we might have to use Cognizant Ignition to provision that. And it's come up with a rather detailed sort of scoping of that. It's saying I'm going to help with these types of decisions, Amy is nodding her head, so I think I'm on the right track here. And it's giving us these outcome objectives. You can think of them as KPI. So are these in line with what you would expect in this? Okay, great. Wonderful. We typically do -- when I was out there at KeyBank and working with Amy and her team, we spend a lot of time here going back and forth as they threw like, oh, but this is different here, that. It's perfectly fine to talk to any of these agents in any order as you're actually building the system. Okay, now that we have this, we're going to move to generating some data. Let's just generate 1,000 rows of data. Why am I doing this? Because I don't have access to Amy's data right now, but I want to get her the POC running on synthetic data. So I can show her and she can play around with it right now, and we can modify the scoping and the design if we need to. So we're having this agent actually write some code that would generate some data, synthetically, that would resemble the data that we need. And we can use it as a template as we go in as Cognizant and actually provision the real data and bring it in for use here. And finally, when it's done writing the code, we're going to have some agents build it. And that's the last step I'm going to go through here. I will very much encourage you to come over behind -- these walls are going to go away, and there will be some demo pods over there, and we're going to build these types of agents for you guys. Just walk up and we'll build one for you on the fly spontaneously right there. Just to complete this, I'm going to have it create the use case and make it explainable, and I'm going to ask the orchestrator to do that. And we'll let that go on. I can show you this fully developed in a moment. But before I do that, let's just take you here and show you what is actually running, which is this opportunity finder set of agents. So we're at a step where a number of agents, this is my team, are coming together and designing that agent for Amy autonomously. Because we gave it all the information, all the data that it needed, including running that code in a container, moving the data, the synthetic data on to the cloud and running against that. But we have a number of other agent networks here, the agent that we're going to end up building for Amy is going to plug into a multi-agentic system similar to the one that you're seeing here. And we're going to be able to -- and this is a rather large one that we're going to use. And it's, again, breaking all the silos. So the consumer banking side as well as the commercial banking, the wealth management, whatever that one is, they will all come together and help especially if there's a complex command that's coming in. Okay, I think I'm running out of time. Let's go quickly back to the slides so that I can just wrap up. And that's not my slide. So yes, I hope by what you saw, you noticed and with the speakers that went before me that this agentification is something that is happening, it's inevitable, it's organic. It has requirements that need to be fulfilled. It's an ongoing process. It's incremental unlike past moves, for example, to the cloud, that was a big lift and shift. You can do this incrementally and plug in new agents as you go. It requires interoperability. And these are -- there's a lot of engineering and custom making. And because as Cognizant, we own that last mile, we have the IP. We've recognized early on that multi-agency is the future of the enterprise. We are very, very well positioned to build this future for all of our clients and ourselves. So with that, I'm going to invite you to a short little break as well as hopefully some demos that we can give of our various different platforms. Thank you. [Break]

Client panel. So Ravi, do you want to come up and introduce?

Thank you so much. We're going to have a quick panel with Paul Markovich, the President and CEO of Ascendiun, which is the parent company of Blue Shield of California. Paul has been in the health care space for many, many years, dedicated his career to transforming health care, built statewide health information network for seamless patient care, launched innovative care delivery partnerships with California Medical Association. We have an 18-year partnership with Blue Shield of California. Very excited about the work we do. We started with -- way back in 2007 with development and support custom work. Then since 2015, we have been working with Paul and his team on the expansive opportunity we had with TriZetto facets. And now we are involved in the transformation on the cloud data. And very grateful to you for coming over for the Investor Day, all the way from the West Coast. So thank you so much.

It's a pleasure to be here.

So Paul, very quickly, we've been through this partnership journey over the last 18 years. Tell us how you see Cognizant, if you see Cognizant differently and how the partnership has evolved? I've always asked clients tell me that one differentiator you believe we bring to the table, which none of our peers, I'm going to put you on a spot. If you can -- if you feel there was something you believe has evolved a partnership for such a long period?

Well, maybe what I'll do is start with the context of where we're trying to go. And then I think it will be clearer how the partnership helps us get there and why it's valuable to us. So everything for us starts with our nonprofit mission to create a health care system that's worthy of our family and friends, and sustainably affordable for everyone. So God forbid, one of your loved ones needs to access the health care system, A, they can afford it. And B, when they access it, they get treated the way you'd want your loved ones to be treated at their time of greatest need. When we've looked at that, we realized you can't possibly, incrementally improve an irretrievably flawed system and make that happen. I mean there's just so much structural inflation in the health care system. The incentives aren't aligned. There's a lot of manual process when it could be automated. I mean I don't need to tell you this, you live it every day, right? And so what we realized is, well, we have to reinvent the system. Many of you may have seen our announcement back in August of 2023. We went live January 2025 with a completely different pharmacy distribution option and actually ended up making pretty big industry news at the time. And that was an example of saying, wait, this system isn't working. We've got to start from scratch, think about how it should work and then make that happen. So we've created a series of things we need to do to -- we need to digitize, simplify and automate everything we possibly can, get a lot more productivity into the system. We need to align incentives. We need to truly deliver on this notion of personalized care. And we've developed the approach that we want to take to get there, but there's a whole series of capabilities required to make that happen. Including you can't get to being integrated with providers the way you need to and truly turn it into a real-time system, unless you're fully in the cloud, right? And unless you're truly taking advantage of the latest and what technology makes available. And there are certain core things you need to do every day. You need to do this also while you're -- the proverbial you got to be able to change the tires where you're driving kind of notion, because we're still processing a lot of claims every day. We're still answering the phone. So how do you move from this legacy world to this future world? And to me, this is where it's just incredibly valuable, like 15 years ago, it was around -- we started the journey to migrate to facets probably closer to 20 years ago, but over 15 years ago, I think we finished the migration in 2014, but we did a lot of customizations. And of course, we were doing this with on-premises data centers. So what we've structured now is this movement to the cloud.

This is a new version of TriZetto.

Right. And then the -- taking the customization out of the system, which allows it to not only perform better for Blue Shield of California, but creates the platform by which we can then sell and share it with other Blue plans as well, which is a part of our strategy. So like we simply can't get to doing something like resolving all claims in real time, which we absolutely need to do and will do unless we can complete this work together. And so it's really fundamental to us getting to the vision that we have in mind, really achieving the mission that I described at the beginning.

And one of the things you're really -- what fascinated me is not only are you building the future of health care for yourself, you're flipping it around and you want to take it as a utility to other health payers and health plan providers. That's fascinating. I mean it is going to be a game changer for the ones who don't have the CapEx and the ones who don't have the infrastructure to do that.

Right. Well, I mean, we figured out a while ago that it wasn't an existential threat to us, but we're probably investing around $150 million, maybe a little more than that in capital expenditures. I think you guys call it CapEx each year. We probably need to be 2 to 3x that to really drive the agenda at the level that we want to. But to avoid having that put undue short-term pressure on our rates, we just need more scale to do that. And I went out and basically tried to negotiate nonprofit mergers for about 5 years and with other Blue plans. And it's not easy to get that done. And what I realize is that all the Blue plans loved the business case, but always balked at the potential changes in control, right? And this is a common phenomenon in nonprofit conversations. So the idea was, well, why don't we create this new entity called Stellarus. It's one of the sister companies to Blue Shield and Ascendiun is the parent of Blue Shield and Stellarus. And we'll figure out like how do you get the value of a merger and scale without merging? So how can I go to the other nonprofit Blues and say, you can keep your board, you can keep your CEO. You don't have to go through a regulatory takeover. But we can share a technology platform. We can share capabilities like this pharmacy capability. We can collectively invest at a more rapid scale and accelerate this whole transformation by doing it across, and we can do it a lot faster than we otherwise would. So a part of what we were doing, and again, a part of the reason why this partnership is valuable is that we're not just trying to get it to perform for Blue Shield. We're creating that platform in that vehicle that allows -- that can be multi-tenant and multiplan. And so yes, it's pretty exciting.

And we are excited also because this is one of those unique opportunities to create a distribution network for our health care assets using tier 1 strategic partnership with a client. And as much as we do it directly, we now find a client to actually take it to other clients, which is as fascinating. So Paul, one of the other questions which is around in the U.S. for the last couple of years is the health care cost in the last 20 years have gone up by 200%. There are only two sectors which have significantly gone up on cost over inflation for the last 20 years is education and health care. We've used a lot of technology, but it hasn't actually manifested into productivity gains for the sector. So tell us how does this change with AI? I mean there's a lot of talk on how AI can be that real inflection point for health care?

It can be, and it needs to be. I mean, health care is too damn expensive. It's the biggest strategic threat that we face as an industry, is that at some point, there's an economist, I don't remember his name, who was quoted as saying, if something is unsustainable, it won't last forever. And that's health care costs. We simply cannot afford to keep paying more in health care costs every year than price and wage inflation. At some point, this is going to get fixed. The question is, is the private sector going to do it? Or are we going to hit some fiscal and political crisis and is the public -- or the politicians going to come and solve this thing for us in terms of affordability? So this is really our obsession. Like the biggest challenge we have with our mission is getting to affordability. And health care has had this perpetual negative productivity problem. I mean, literally, if you just look at the macro numbers, we just keep throwing more and more money into it at a higher rate than rest of inflation, and macro quality scores don't budge. Macro satisfaction scores nationally don't budge. So we just keep throwing more money at it and not getting any better outcomes, or output. That's just absolutely negative productivity. So to me, what it boils down to is you have to -- and you look at it and all these opportunities abound. I mean we still -- 1.5 years ago, I had my own little sports weekend warrior injury. So I went and got an MRI. I went and I saw an orthopedist. I go to the MRI, I get done, they hand me a CD-ROM. I go to my orthopedist and he hands me -- probably hands me the printed fax that he sent to refer me to a physical therapist. And by the way, all these people know who I am, right? So this is the San Francisco Bay Area in 2023 and we're using faxes and CD-ROMs. Like I don't have anything in my home that can read a CD-ROM. I don't know if you do. But -- maybe you guys do because you see this as an investment platform sometimes.

We are a next-generation company. We don't...

Okay. Okay. But so we just have so many opportunities to do it, but we need two things. We need will and we need skill. Will means you've got to get the incentives lined up for everybody, including the physicians, the hospitals, everybody, to be more productive. And people don't understand sometimes they jump into health care and they start applying technology. And they don't understand it's like, wait a second, if I get more productive and I can't charge as much, you're cutting into my revenue. So if there isn't the will, like if I'm doing fee-for-service, and I'm doing less service, that's not necessarily a good thing for my bottom line. So somehow you got to get the incentives aligned where you're motivated. That's what I mean by will. You're motivated to actually do the right thing and be more productive and get administrative costs down and automate. And I think folks tend to overlook that. You've seen a lot of technology get thrown at the health care sector, and they forget the fact that if you're not motivated as an organization to do it, you're not going to do it. The second thing you need is skill. That's where artificial intelligence comes in. And so there's -- and there's just -- I mean there's opportunities, I think, abound, whether it's in Ambient dictation for physicians, which we've been using to -- I mean, we've got physicians that are seeing 2 to 3 more patients a day and going home earlier not spending as many hours because their voice is being captured. It's immediately capturing the electronic medical record in the clinical notes. I mean it can be applied in getting to real-time prior authorizations, real-time claims, real-time quality calculations and scores, real-time value-based payment calculate -- I mean, all of this stuff can do -- that's the vision that we have basically is we're going to -- we're creating -- we already created for our members a comprehensive digital health record that brings together the electronic medical record information from the physicians, the hospitals, labs, pharmacies. And then that's a basis for 8 use cases, which include the things I mentioned. Real-time claims, real-time prior authorization, real-time calculation of quality scores and care gap interventions. And the list goes on, basically. But that drives huge administrative and productivity savings. It enables pay for value in the alignment of incentives with physicians and hospitals, and potentially gets to a much better quality of care as well.

In fact on the TriZetto platform, we now have integrated open AI interfaces. We have AI assistant. We have auto adjudication of claims, which has gone through a significant jump. In fact, I was actually in one of the customer service functions of one of the peers, and the amount of work we think we can reduce using AI and actually transfer that money to value care, as you said. One of the other exciting transformations which is going to happen in health care for sure, I think, is vertical integration. Payer providers -- so that the incentives are aligned. And we think it's a unique big opportunity for transformation for companies like us because you have to integrate the systems with the payers and the providers together to create more straight-through processing. Is that coming on the way you think?

Oh, it has to. There's just no way to get to unlock this value unless that's the case. And it can't possibly come -- like you're not going to have a whole bunch of Kaisers nationally because it just is too expensive and too intense to go out and just buy physician practices. And then I mean these are highly paid professionals. They don't tend to stick around. They'll walk with their feet if they're not -- let their feet do the talking. So I don't see a whole bunch of like big consolidated ownership of physicians...

But you do see payer provider...

That's what I'm saying is you have to integrate. You're going to have to have that ability to say, if I'm a member of Blue Shield of California, I should just be able to go on your app and schedule an appointment with a doctor. That means you should be -- you need to be integrated with the scheduling software, right? I should be able to just -- when I walk out of the physician's office, my claim should be settled, I should just be able to do, touch a button, and pay whatever I own in terms of out-of-pocket. So all these things that you -- I talked about before, quality scores, claims settlement, risk adjustment. All of those things have to require the integration, the technical and workflow and operational integration between the payer and the provider, I don't see how a health plan in the future is going to be able to be effective without doing that well.

Absolutely. And that will also integrate the incentives. I mean one of the biggest challenges for higher cost is there's no incentive for the providers to reduce costs. There's no incentive for the patients to take more proactive care because somebody else is paying for them. So that might actually be a good inflection point to change the way the industry works. I'm going to ask you one other quick question. There's a lot of talk about Medicaid and Medicare going through some change. What would be your view? I mean, the current administration is already talking about it. What's your view on it?

Well, look, I think a great way to be wrong is to make political predictions with this administration. And so I just take this with a massive grain of salt. But what I would say is that it's easy to talk about really big dramatic cuts in things like health care spending. It's a lot harder to actually do it. And I think you're seeing that right now in the sense that...

Will this come back into some other firm Medicare...

Well, here's -- I mean, my understanding of where it is now politically. And just bear in mind like there could be a tweet in 15 minutes and all this could change. So -- but the like the house basically said, we're going to put a placeholder in to say $880 billion in Medicaid expenditures. We're not going to touch Medicare. The Senate, they had to reconcile the bill, Senate did nothing. So the Senate was zero and the house is $880 billion. And what they agreed to do process-wise in this reconciliation is that the Senate is looking at, no, we're not going to just pick a number, we're going to pick policy changes that we want to make. Like maybe we'll do work requirements. Maybe we'll do a reconciliation or remediation of your membership eligibility as frequently as monthly. Things that -- and then we will figure out what that saves after we've done it. So they seem to be, based on that unlikely to touch what people call FMAP, which is the percentage of amount that the federal government pays. And they're far more likely to be in the $100 billion to $200 billion range in terms of savings rather than $880 billion. Now again, going back to my first statement. Making political predictions is just a folly, I think, in this world. I think that's where it stands right now. I think that there's too many Republicans that are in states and districts where there's a large number of negative impacts for really big cuts. And an example, David Valadao from California, lost his house seat in 2018 after he voted for repeal and replace, then won it back a couple of years later. And a guy like that is like, yes, he's seen this movie before, right? I mean his whole district is something like close to 70% Medicaid coverage, right? He's in a Biden plus something in the district. So I look at that and say, I don't see like mass -- there's going to be changes.

It is just good for technology. I mean technology is going to be an enabler for change. So...

But the fact is that, yes, that's why I think that the private sector has to do this. We got to do this. And we've got to use technology as a driver to make it happen to get the costs and trends down. Because I think the private sector needs the government and the government needs the private sector. I don't see the -- I don't see Medicare fee-for-service saving Medicare from a cost standpoint long term. That doesn't mean the Medicare Advantage program doesn't need to be restructured and changed. Or there might even be changes in Medicaid. But the fact is we -- I don't see on the immediate horizon, like these big really large cuts. There will be some probably in Medicaid, but the long-term challenge remains. And that long-term challenge is it's getting shorter term as costs keep going up the way that they are. and they all come back to you, how do you drive improved productivity? You can't drive improved productivity without the application of technology.

In fact, we are very excited. It's our largest industry vertical. We have the -- we are the largest -- we are the largest tech services provider in health care in the United States. $0.5 trillion of claims go through our platforms. 2/3 of the insured population in the United States is on is on our platform. So we're very, very excited about the change, the transformation, the extraordinary relationships we have with clients like you. Any quick question, we can take one. We're running out of time. Any quick questions from any one of you to Paul?

[indiscernible]

Yes, I did hear the question. And it was about whether the transparency is going to jump start some of this change, right? I sure hope so. That said, I've also watched as entities have actively forwarded it. So in the first Trump administration, they issued a requirement to be transparent with all of the -- like the negotiated prices between hospitals and health plans. And then the hospitals went and posted this information, and you need to be a rocket scientist a physicist, an actuary and you still can't piece together how to compare some -- one plans rates versus another. So they sort of intentionally made a complex thing more difficult to track, but extensively abided by the transparency requirement. So I hope so. I would -- I think I would love to see way more transparency that the system is entirely too opaque. I think it has the potential to have that driving force, if you will. But I'm also mindful of how active self-interest can undermine it sometimes.

Yes. But that -- in that example, if we just use the agent that was just shown to us about an hour ago, we could actually parse through that complexity pretty quickly.

It is also bunch of the silos. AI is one of the biggest silo...

Yes, but they sort of also -- yes, I hear you. There's things like they'll selectively withhold a certain piece of information that you need. Like what's the stop-loss threshold on the contract. So I know when I hit that stop-loss Yes. Anyway, I won't get into too much technical detail, but it's amazing the creativity they can go into trying to block transparency. But I agree with you, artificial intelligence and policy can really help.

I mean, even the agentification is going to be a huge productivity. I mean, the number of areas we are thinking we can tap into us by agentifying. I mean there are tens of thousands of people who just process claims in every payer. So Paul thank you so much. Thanks for spending time with us. Thank you for coming here all the way from California, and we're very excited about the strategic partnership and the ability of Blue Shield of California to take the TriZetto platform to other payers and create a network for us. Thank you, guys.

It's my pleasure. Thank you, Ravi.

Hello, again. In this segment, we're going to cover markets and geographies. So we are primarily going to cover three things: an overview of our market, our performance highlights and our go-forward priorities. So I'm going to cover Americas so which is, as you all know, 75% of our book of business today. In Americas, we serve all the four key market segments which includes Health, as you all heard, the client panel. The Financial Services, the Products and Resources, which is relatively broad, which includes Retail, Consumer, Manufacturing, Logistics and CMT, Communications, Media and Tech. Health is our largest business contributes to roughly 35% of our book of business today. And we serve across the continuum in health, payers, providers, biopharma and medical devices. And with market-leading platforms, which is TriZetto which serves 2/3 of U.S. population, we are highly differentiated in the segment, and we are a market leader in health. The next big segment is Financial Services, roughly 28% of our book of business. Even here, we serve the entire continuum banks, capital markets, cards and payments, fintech and insurance. This is a turnaround segment for us. After many years, as you may have noticed in the last few quarters, we have shown performance improvement, both sequential and year-over-year in this segment. Products and Resources. This is a relatively small segment and growing segment for Cognizant, about 22% of our book of business here today across retail, manufacturing, consumer and logistics. And CMT, Communications and Media and Tech, the smallest segment of our business today, but growing at a much faster rate. Historically, as you all probably realized Cognizant has been heavily indexed towards Financial Services and health care. But over the last 2 years, we have invested in Products and Resources and we have accelerated the growth in Products and Resources and CMT, and we have accelerated growth in those segments. And we have built resilience in our portfolio by broadening our breadth. In the last 8 quarters, now I just wanted to double-click on the performance highlights in the last 8 quarters. So we have executed with precision on three things, on three dimensions. First, we focused on winning in the market. Second, we focused on establishing trust with our stakeholders, which includes clients, analysts and advisers and partners. And third, while doing the above two, we also focused on enhancing our delivery muscle. Towards winning in the market, we revamped our go-to-market engine. We overhauled our sales engine and we have tailored our offerings to the markets that we serve. We had precision focus on large deals, winning in large deals. I'm going to double-click on that. And towards building trust, we have established high-touch communication and engagement with our clients, all the way from CEOs like Paul. And Ravi himself, he has done 400 to 500 meetings in the last 7, 8 quarters. And 40% of those meetings are with CEOs. And it's just not at CEO level, so we have established high-touch engagement at various levels on the client side. And with many of you, with partners, with analysts and advisers, we have been constantly engaging with you all. We have been updating on the progress that we are making. We have been previewing the solutions that we are building with all of you and getting your feedback and calibrating those solutions. On the similar lines, we have worked seamlessly with our partner network, and we have launched go-to-market solutions jointly with our partners. And simultaneously, we have enhanced our delivery muscle. We have strengthened our delivery industrialization framework. And we have plugged our capability gaps along the way. A combination of all of these led to the outcomes that you see on the right-hand side of the screen here. The turnaround in Financial Services segment. Acceleration of fastest growth in our Health segment, acceleration of our Products and Resources, Communications, Media and Tech. Highest-ever NPS scores, as Ravi said, 2 years in a row. And we did all this while expanding margins, and contributing to margin expansion for the overall Cognizant. Now quickly zooming forward. Yes, we have executed perfectly on those three dimensions. Now what's ahead. So we're going to focus on 5 priorities for the next 12 to 24 months. First and foremost, you have heard in the last couple of hours, the breadth and depth of capabilities that we have built in AI. So we want to take those to the market. We want to convert that mind share to market share. The next priority. While we serve in those four market segments, there are certain subsegments within those market segments where we are underrepresented. We want to focus on those underrepresented market segments and double down and gain market share in those segments. And third, we just spoke about TriZetto as a platform. So we have platforms in some of our businesses. So we have the world's largest claims administration platform in the TriZetto. Based on our analysis, we also have third largest clearinghouse. And we have shared investigator platform for clinical trials. So we want to lead into market with platform-centric solutions, and we want to expand these platforms into adjacencies and into global markets. And then next large deals. There is an elevated activity on large deals in the market, primarily driven by two things: the vendor consolidation; and cost optimization agenda of our clients. So we have executed that well over the last few quarters. We want to build on that momentum, and we want to accelerate in the large deal segment and now focus on mega deals which is winning billion-dollar-plus deals. And finally, the fifth priority is GCCs. There is a lot of activity in the GCC space. And we want to be on the right side of the equation for the new wave of GCCs that are emerging. So we have a focused strategy to capitalize this GCC opportunity. So I'm quickly going to double-click each of these. On converting AI mind share to market share, we have explicitly quantified the market opportunity in three vectors: Enabling high productivity; industrializing AI; and agentifying the enterprise. We have spoken about that in the last few hours. To capitalize on this opportunity, we have built new AI GTM playbook, go-to-market playbook. And this playbook will have four dimensions or four vectors. First and foremost is new capabilities. We have built new AI capabilities. We have just not built those capabilities. We have customized it for each of the markets that we operate. And the second dimension of that playbook is, new selling skills. So we have infused fresh talent into our sales engine with AI selling skills. Not only that, we have trained 100% of our sales force in AI skills, so that they can take our AI offerings to market. The third vector is the new pricing models. Along with our managed services and fixed bid pricing models, we have extended our pricing models to pricing for agents and pricing for outcomes, leveraging our GenAI platforms. And the fourth dimension of that playbook is new partnerships. So we have extended our traditional partnership ecosystem to AI native. So that we can leverage their expertise and build joint go-to-market solutions. This 4-dimensional AI GTM playbook is already put to use. So we are executing it across all those three vectors of opportunity today. And I'm very glad to let you know that we have conquered the first vector in many ways, enabling hyperproductivity. We are engaged with almost all our clients, almost all our clients across the markets that we serve and help -- and are helping them unlock the trapped productivity in the first vector. And we have 1,200 plus active engagements in the second vector, which is industrializing AI. And we are having more than 100-plus active conversations as we speak, on the third vector, which is identifying the enterprise. And this third vector is going to unlock the value pools that we never had access to before. As an example, let's take underwriting, whether underwriting in a health care context or in an insurance context. It has 5 or 6 steps starting from data gathering, data generate -- data, validation, profiling, applying the networks and all that. So there are 5 or 6 steps in the process. Historically, clients have outsourced only 1 or 2 steps of the underwriting process. They have kept the remaining 4 steps in-house based on the complexity for the regulatory concerns and the other aspects. Now we are having active conversations with clients to package underwriting as a service with agent orchestration, with regulatory compliance. So this is the value pool that we never had access to before. And this is the value pool that clients are willing to engage in conversations right now as an example. So we are having 100-plus such conversations to agentify enterprises across our clients. The next is how we want to differentiate with our platforms. TriZetto as I said, the world's largest claims administration platform. Based on our analysis, we also have the third largest clearinghouse. And our TriZetto platforms serve 2/3 of U.S. insured population today. And we have a clinical trials platform. Over the last 8 quarters or so, so we have invested heavily into these platforms. We have infused AI into these platforms. We have modernized these platforms. We have built agents on these platforms so that these platforms stay relevant into future. Now we want to do two things with these platforms. We want to expand these platforms into adjacencies. For example, our platforms today are -- TriZetto platforms today are heavily payer-centric. We want to expand our TriZetto platforms into provider space for prior authorization that Paul was talking about earlier or RCM, revenue cycle management. We are also looking at opportunities in dental and vision to expand Aristo platforms. And we're also looking at property and casualty insurance space, where if our platforms can be customized into that space, our health insurance platforms can be customized. The second thing that we want to do with our platforms is to take them global. Today, our platform sir, catered to the U.S. market. Now we are beginning to see the demand for our platforms globally. Almost all 7 Emirates of UAE have shown interest in TriZetto platforms. So we are trying to customize our platforms and build an Arabic wrapper to take our platforms globally. So with this strategy, we will continue to invest in our platforms and lead with platform-centric solutions. And you have seen the progress that we are making on the right-hand side. So we will continue to grow. We've been growing this platforms business. The third thing is the large deals and GCCs. Large deals, as I said, there is an elevated level of activity. So we have done really well, and we have done well by doing 3 or 4 things. We were laser-focused on the industry solutions. We were extremely agile. We were extremely agile. And on these large deals, all the way up to CEO were involved. Ravi himself participated in many large deal defenses. And many clients have given us this feedback that this has become a unique differentiator for Cognizant again. The extreme agility. And Prasad spoke about this morning, we have leveraged our AI tool kit that we have built. We have leveraged our AI productivity, our and AI platforms to win bulk of these large deals. As you can see on the right-hand side, our large deal wins have more than doubled in the last couple of years. And we want to continue to focus on these large deals market. We want to build on this segment and then focus on mega deals going forward. And now GCCs as I said, there's a lot of activity in GCC's market. Almost every single client of us either already have a GCC or is contemplating to have one, but at least thinking of having discussions to have one. So we want to address that market. Both the clients who already have GCCs and the clients who plan to have GCC. So for the clients who intend to or who are contemplating to have GCC we have incubated a global capability center service line within Cognizant, and we have launched a catalog of micro services, which is talent as a service, recruitment as a service, training as a service, HR as a service, marketing as a service, to help them accelerate their GCC setup. And for the clients who already have GCCs. We want to extend our go-to-market channel, which is client partners and account manager network to mine those GCCs and be their expansion partner or growth partners. So we started executing on this strategy, and we have seen initial results. We have won 6 deals in the last few quarters, and we have more than 20-plus active conversations with the clients who are planning to set up GCCs. And finally, the fifth priority, focusing on underpenetrated market segments. So we have identified four of those: aerospace and defense; energy and utilities, and oil and gas; communications; and health care provider. Aerospace and defense complete white space for Cognizant, completely underrepresented. We did not focus on this value pool ever. So we have invested heavily, both organically in building the capability, and we have also invested in a strategic acquisition of Belcan. Similarly, energy and utilities, and oil and gas. While we serve in manufacturing and logistics, this segment has been left unattended. So we are now focusing on it. We are building the market blueprint. We are identifying the value pools and market entry points in collaboration with partners. And health care provider and communications, though we serve in these market segments today, we are heavily underrepresented. Most of our health care business today is on the health care payer side and biopharma side, but we are underrepresented in provider. So we are investing to accelerating growth in the provider space by focusing on adjacencies like RCM and other channels. And same thing with communications and media, where we are heavily indexed on tech. Now we are focusing to accelerate in the communications and media. So bringing it all together, over the last 8 quarters, we have successfully executed on winning in the market, building trust with the clients, with all the stakeholders, clients, advisers, analysts, partners, and enhancing our delivery muscle. That becomes the bedrock of our execution engine. On that bedrock, we are going to execute on these 5 priorities that I outlined. And we are confident that unsuccessful execution of this, we can continue to deliver the market-leading growth and help Cognizant pivot to Winner's Circle while expanding the margins, and we are committed to doing that. Thank you. And now I would request my other colleague, Manoj, to cover the geography across the ocean. As you can see he is...

Let me assure you. This business is not limping back to growth. Pardon me while I sit down; I sprained my foot last week. So my name is Manoj Mehta. I live in Amsterdam. I've been with Cognizant for 20 years. And I've seen -- we've witnessed quite a bit of change if I look at Europe. Literally, when I came Europe was full of very small, I wouldn't say, small but very localized organizations in each country. If I see where we are today, I think that's where the market has changed. There is this incumbency of a lot of these European players that is -- they are struggling in that space. Second is when global vendors like us came on the scene. This was around 15, 20 years back, the main reason why vendors like us came in was purely for labor arbitrage, looking at cost skills. I see that market change. So Europe and EMEA typically is a complicated market. We've got over 100 countries. So the most important thing when I took over this role 6 quarters back, was focusing our spend? How do we actually focus our spend? How do we focus our SG&A in certain key markets. And that's what we'll talk about. So I see massive opportunity in Europe as long as we are able to capture the opportunity. The other thing that's very interesting is the macro situation today. So while others see uncertainty in Europe, I actually see a lot of opportunity I actually see a lot of first-time outsourcers coming in. So there are still a lot of vector 1 deals that Ravi spoke about. So we still have clients who are coming to us for the first time saying, how do you outsource? Do you really have a capability? How will you fit into my culture? How will this fit into Europe? And I think that's where a lot of our focus has been. The clicker works, right? So first is what are we focusing on, right? So I think markets, U.K. has traditionally been 40% of our business. But I personally believe there will be massive opportunity in Continental Europe and the other parts of Western Europe. So I think we're focusing very hard in the short to medium term in Nordics, in Germany and certain parts of the Middle East. So also Middle East, we're seeing certain spaces like health care, Surya spoke about because I cannot take TriZetto to Western Europe because of the way European health care systems are set up. But very clearly, in the Middle East, we see a lot of opportunity. Similarly, other verticals, we do a lot of work with biopharmas in North America. That is a business that can easily get translated back to us in Western Europe. A couple of other sectors, which are interesting. One is automotive. Automotive in Europe has very large premium OEMs. And they're honestly getting hit from both sides. One is from tariffs in the U.S. and then China on the other side. European ports are full of Chinese cars standing at the ports, very different price points. The kind of interest that we've seen with a lot of these OEMs over the last quarter has been absolutely tremendous. And I'll speak a little bit around some of the deals that we are winning in this space. The other new sector for us is public sector. Globally, Cognizant hasn't done much in the public sector space. We started in the UKI. And I think it's amazing. In the last few quarters, we've ramped up to over 1,500 associates purely on site. They are helping improve citizen lives in central government, in defense and health care. We are winning large deals in that space. I'll give you a couple of examples. I think we won $200 million deals in the last 2 quarters in the public sector space. Second is, we spoke about platforms. So think a little bit around how we are getting positioned in Europe. So going back, market's changing. Our platforms are coming in very strong. The whole business of labor arbitrage has really translated into what can we do to drive productivity, what can we do to drive AI. Prasad spoke about it, Naveen spoke about it on how do we bring the whole thing to market. The third advantage and this one is really unique for us in EMEA are the acquisitions that we've done over the last 4 or 5 years. Now ESG Mobility, Mobica, Thirdera, I think also acquisitions in the space of experience, acquisitions in the space of digital engineering. We've created 14,000 people in EMEA and this whole ecosystem is working so well and so well integrated with our global delivery model, the client experience into working with Cognizant, our recognition as a brand has changed dramatically. And the last part is, how do I demonstrate how is it working? So if I bring your attention to the right side of the screen, first is renewals. We are seeing almost 90% of our clients renewing back with us. There is a lot of push towards driving automation and productivity. I think a lot of these we've discussed through the whole day. But the second thing that I'm seeing in Europe is a lot of that saving being translated into change projects. Discretionary spend in EMEA is quite high. We've done 35% more compared to last year, and we see that continuing in the medium- to long term. I love the fact that our brand is getting positioned in some of our key countries very well, our ability to drive new logos, create new clients, we've doubled that. New logos is around 8% of our TCV in the last 12 months. So I think we are seeing a massive uptick in the pipeline. A large number of big deals coming in almost half of the business is net new deals coming in. Here are three examples of clients, we wouldn't have one in the recent past. And I'll give you a context around that. First is in the public sector. We spoke about our entry into public sector, HMRC is about child benefits. Imagine taking down claims from 30 days into 3 days. Our Cognizant positioning into creating that business was massive. Second, skip all, I think I live there. I live in Amsterdam. So I think this is home. So I had to bring that as an example. We are seeing the need of operational efficiency at each airport. You saw what happened to Heathrow last week. One day of downtime, these guys haven't still recovered. So the need of operational efficiency is extremely high. Schiphol also has a lot of regulatory and data protection issues. They were looking at a very agile digital engineering company. So I think we brought in a lot of that skills from nearshore, which we wouldn't have been able to deliver otherwise. The last is demonstrating our ER&D skills. Vibha spoke about it a while back. Imagine almost real-time error detection and correction with over-the-air software updates. This is pure German engineering combined with global sourcing. The kind of experiences that we are now being able to bring to clients has changed dramatically. And that brings me to my final slide. So what is our right to win. And that's my question of our focus. As we look at our chosen markets, we obviously have a very strong roster of clients in our chosen markets. I think we've got terrific references. But I think what differentiates us is the overall experience of working with Cognizant. Our ability to bring in the platforms into end, our ability to go deep and establish trust in each of the geographies that we can deliver locally with similar cultures, with data requirement that Europe comes in, along with a global delivery approach. So I'm quite confident about the kind of opportunities we have. And let me end here, and I'm going to invite Sandra up to stage. But before that, I think as she will talk about our partnerships. We have a video with one of our partners coming up. [Presentation]

So it's a pleasure to be here. I'm Sandra Notardonato. I run the Cognizant global partner ecosystem and influencer relations. I joined Cognizant a little less than 2 years ago after 15 years at Gartner as an IT services analyst. And before that, I was a sell-side analyst always covering the IT services industry. So I've been advising investors, enterprise buyers, technology vendors and service providers on the inner workings of the IT services industry and the role that it plays in the technology landscape. So I bring a unique perspective to my remit, which is to jump start and really recreate our partnership and alliance program. Over the last couple of years, we have been completely transforming this effort of our partner ecosystem. But before I get into the specifics of what we've done, I thought it would be a really good idea just to click on a couple of things here that help the audience here level set on what partners bring to the table, what Cognizant brings to the table. And just to be clear, I've been given the charge of catching up on some time. So I'm only going to click on a couple of things here. So first and foremost, market reach and credibility. The importance, I think that Amy shared on how vast the ecosystem that is required in today's market really forces us to think about how we want to partner in the market and how we want to build that credibility with our partners to capitalize on that services attach rate that Bill just mentioned. Our partners are an innovation accelerator. We use them to build our innovation capital, which is a really critical part of our story. They are a critical input as well to our incubate and scale framework that Ravi mentioned. So obviously, a very important way for us to pivot towards where the demand is coming. And as Bill mentioned in his video, trust and advocacy is so incredibly important with our partner universe because it gives us the -- as they advocate for us in the marketplace, it gives us sales momentum as well as the acceleration in terms of our combination and the impact we have in the industry. Cognizant also brings great value to our partner ecosystem. And I'm going to just touch on two things here. As I mentioned to you before, we've completely transformed our partner strategy. And because of that, we are now a much more relevant player in the industry, and that gives us the right to compete in ways that we have not been able to in quite some time. I'd also highlight the fact that we have unique partnering opportunities that we offer to our partners. You've heard a lot about the platforms that Prasad has built and is building an SPE. We have TriZetto. We have other industry-specific platforms. Our partners want to align with us and those platforms to transform what we're seeing in the marketplace. And from a workforce perspective, the expertise that we have industry proprietary domain. All of that makes for much better client experiences and client outcomes. And that's another advantage or value that we bring to our partner organizations. So what have we done over the last 2 years? So first and foremost, I'll talk about how we have completely transformed our go-to-market strategy. Specifically, we have created vertical sales programs across our markets in the United States, our verticals in the United States. In EMEA and APJ, we're picking very focused strategies around specific partners by account, which sounds very much like blocking and tackling. But the great thing about blocking and tackling is that when you do that, it has an immediate impact on the ability that you have to change and drive the incremental growth that we have been trying to drive. Another thing that we're doing, we're putting more sales enablement within our own organization and sales enablement within our partner organization to ensure that we're selling the 120-plus offerings that Naveen talked about in his presentation. And the other hundreds of codeveloped solutions that we have in the marketplace. So that drives more revenue, greater streams of revenue. We're leveraging new commercial constructs. These new commercial constructs are a reflection both of our ability to enter new markets, be more price competitive when we want to work on large deals, particularly those that are asset based. So all of those elements of what we've done from a go-to-market perspective are underpinned by what we're working on, which is also creating greater operational rigor in order to make sure that our program around partners remains very competitive and future-looking. Scaling with our high-value partnerships. So what do I mean by that? I'll give you a couple of examples, Microsoft. Just a couple of years ago, we were #5, #6 global system integrator driving Azure consumption revenue. In 2 years, we've been able to go from that mid-single-digit global system integrator to #2 globally and #1 in the United States. Of course, migration is a very important strategic growth initiative for Microsoft. So the more we can show them our value, the more we get the benefits of that partnership through incentives, et cetera. With AWS we're accessing never-before-received investments in the form of strategic collaboration agreements. We have multiple strategic collaboration agreements with AWS in the areas of smart manufacturing, health care as well as there's some very domain-specific as well. So that's another example of how we're coming to market together with AWS to scale and have greater impact on our revenue. From a foundational perspective, with Salesforce, we are a launch partner for Agentforce. We have -- we are #2 when it comes to certifications in Data Cloud, which is obviously very important to that -- to their story. With Oracle, we're entering the second year of the Oracle Cloud program that's opened many doors for us in terms of new revenue opportunities associated with Oracle Cloud. With SAP, we're a validated RISE partner, a very critical validation in the landscape of SAP currently. So those are just some examples of what we're doing with our high-value partnerships. We're also broadening and diversifying our partner network. You heard Bill McDermott in what he said. We're a global elite partner to ServiceNow. What that means is that there are 6 of us that are in this very top tier in order for us to be elevated into that top tier means that others have had to drop out. So we're gaining share in ServiceNow, and I can tell you that, just a couple of years ago, we were #15 when it came to selling ServiceNow licenses in the marketplace, we're now they're #1 salesperson, or sales company, I should say, on that ServiceNow platform. So we're gaining market share in the ServiceNow ecosystem. With other partners such as Snowflake and Databricks we are building business groups as we put the nomenclature of a business group around a partner that drives a tremendous amount of internal effort, investments all of the energy that goes into creating solutions that then we scale in the marketplace. So really making a bigger impact in data and analytics. Last week at NVIDIA, we have actually taken this partnership essentially from 0 to, let's say, 60 within a 12-month period where we had a very limited partnership with the company 12 months ago to a tremendous showing at GTC last week where we demoed 8 solutions, one of which was around our health care LLM, where we're actually addressing some of the things that Paul mentioned around the excess costs that are associated with health care. This health care LLM is actually focused on extracting more accurate medical coding and taking $60 billion of excess costs out of the system. We also showcased our Omniverse and digital twin technology with Trane that was something that Vibha mentioned earlier this morning, and we are launching our technology start-up ecosystem, working very closely with our strategy organization as well as other parts of the industry to ensure that we're building out a very competitive partner ecosystem. I'll just touch on building a culture of innovation capital. The point I'll make here is very much around our intellectual capital. We work very closely with training and development, learning and development, which is in Kathy's organization. And our service lines to ensure that we are forecasting accurately the number of resources we need associated with any particular partner today and for a specific period of time as well as what we are predicting over the course of the next few years. So very good strong performance over the last couple of years has that translated into impact, business impact. First and foremost, if we just talk about the funnel and lead generation, based on the systems that we are currently using, and I'll make it very clear that we are always looking to improve our operational processes. We have a pipeline as of last week of roughly $11 billion in partner supported TCV. That means that these are examples of engagements that we are working very closely with our partners in the marketplace and driving that engagement. In terms of our bookings, our impact on bookings last year was $6 billion of partner supported TCV, also a number that we see based on the data that we collect, and we'll be updating you on that as we recreate and build stronger systems around that. I'll just touch on a couple of other things here in terms of our win rates. Our win rates are improving. When we go into the market in a prescriptive way with our partner, not only does our win rate improve, our sales cycle is shorter and our deals are larger. Remember that a partner is always going to want to work with a GSI. So now with this transformation that we have made, we are much more active with our partners, and therefore, it's driving not only a bigger denominator, but also the ability to drive a higher win rate. In the world of lighthouse deals next week is Google Next, be on the lookout for some very interesting things that we're working on in the retail industry with Google around call center transformation and new streams of revenue, which I touched on before in terms of selling better our co-developed solutions. I'm just going to say here that our sense incubate and scale is really critical, not only to the partner program in terms of the microcosm that it is of our overall business. But it is a critical program because it helps the company to pivot in the direction that we need to go in order to drive growth and create shareholder value. So what do I want to leave you with today. I want to leave you with the fact that for the most part, the real heavy lifting behind our partner ecosystem transformation is behind us. It's always going to need work. There is no doubt about that, but the big changes, I think, are behind us. We have a framework that drives continuous innovation that is also going to keep us moving in the direction of where demand is coming or going. I would also point out that the foundation that we have created is scalable, which allows for that continuous recreation of what we need in order to be competitive. And if all of these things come together and if we continue to build on the successes of the last couple of years, I feel very confident that we'll be able to take that partners sell with TCV to 2x what it is today as a percentage of total bookings which, in my opinion, not only helps to add to our growth acceleration story, but it also brings incremental opportunities that we feel really good about our position with our partners. So I thank you very much for your time. I went over a little bit. Right now, I'd like to bring Kathy Diaz on to the stage. Kathy is our Chief People Officer. She brings a tremendous amount of expertise leadership in running our 340,000 person organization. So Kathy, I'll transfer it over to you.

So I have been asked to bring us to the Q&A a bit faster. So I'm going to spend a few minutes with you talking about our talent strategy and our people. And then I'll invite my good friend, Jatin up to talk about our financials, and then we'll get to Q&A. And I also wanted to offer up that I will be in the reception. So if anything I touch on, you want to expand on please catch me. So it's great to be here with everybody. I've been here at Cognizant coming up on 5 years, and I've been in the Chief People Officer role for just about 2 years. Prior to Cognizant, I spent time in several different industries, including pharma, retail and education, mostly in HR, but I also spent some time in finance and IT, and that actually serves me pretty well in this job. But I've known Cognizant for over 20 years as a client. And so I got to see firsthand the value and the capability that Cognizant brings to its clients. And it's one of the things that attracted me to the job to begin with to see how I can do that at scale. So in the next few minutes, I'm going to talk a little bit about our people, our talent strategy and our learning and skilling culture and especially why we are confident in our people and our ability to stay ahead in this new wave of opportunity that's upon us. Okay. So as a people company, talent is our strategic asset. And at Cognizant, we've really figured out what I call the secret sauce of making that happen. In the last 2 years, we've made significant progress in our very bold ambition to be an employer of choice. And I'm happy to say, and I'll talk about a little bit more about what we've done to do just that. And it really started with going back and harnessing the deep and very successful heritage of this company and unlocking the entrepreneurial spirit of our people. along with our sensing and our ability to stay ahead of the game, and that's what puts us ahead. During other periods of technical transformation, we've been able to sense ahead and skill ahead, and that's what I'll talk about. And turning all of that into a strong talent strategy that positions us to win. It's a simple but very powerful combination. We have become a magnet for talent now, and we're ready for the future. So you'll hear some of the executive committee talk about the mojo of Cognizant is back, and it's really true. Our talent, learning culture and our brand, quite frankly, are stronger than ever. We have really what I call a big small company. You have the power of a big, large enterprise organization that has amazing scale with the agility of a small start-up together in one company. Cognizant engagement scores are significantly above global and industry benchmarks. And in fact, last year, we gained on our lead ahead of the industry. And there's a couple of things about that engagement score that I want to talk about. In the last 2 years, we've improved in 3 areas, and I think they're very relevant for the times that we're in, psychological safety, customer focus and innovation. Those three things, we heard from our associates that they really appreciate the way that they have freedom to explore innovate in our company. Learning and growing is in the DNA of this company. We've -- in 2024 alone, we skilled 275,000 people. We've also promoted 136,000 people, which is roughly 40% of our organization. Our grassroots innovation is really powerful. And the fact that we actually empower all of our organization at all levels of the company to innovate. And what we're finding is the people that are -- the early career talent and those that are the closest to our clients, those are the ones that are bringing the value. And we celebrate it. Not only do we empower people but we celebrate those successes. And this is probably the thing that I'm the most excited about is that, we have the highest return higher rate in our industry. And what I mean by that, it's people that have chosen for whatever reasons to leave Cognizant and come back. We had 14,000 people return to Cognizant, and we have a pipeline of another 20,000 people that are interested in coming back. And what's fascinating is we interviewed thousands of them to find out why did it choose to come back? And the answers, and we have key themes that have emerged. The first of which is people appreciate the freedom to innovate. We empower people here to do what they think is necessary to serve their clients, and they appreciate it. They also talk about our culture. They do say that we're friendly here. So I hope you're finding that people are friendly. People are approachable. But the biggest thing is if somebody has an idea, people will really listen to them and they're able to be an entrepreneur here. And lastly, the vast amount of opportunity that we offer to people is incredible. And the outside world is noticing. You'll see some of these awards that are noteworthy. And quick spoiler alert to tomorrow, we will be announcing that we're on Fortune's most innovative companies list once again. So I'll talk a little bit about sort of our future and how we're thinking about the future. So you heard all day today or all afternoon, how my colleagues are talking about the next wave of transformation. And Ravi is talking about getting into the Winner's Circle. One of the main things that we need to do is make sure that our learning and skilling keeps pace with the pace of change. And so a couple of examples on the left and that is how we're evolving roles. So if you think about an AI ethics expert didn't even exist a few years ago. So we are sensing ahead all these new roles, and we already have prompt engineers, all these different roles coming into the company. We're also building new career paths. So for example, people in our Cognizant moment who are in design or experienced people, they're going to have a different career path than a traditional engineer, and that's important. We're expanding our talent pools, broader skill sets are needed. For example, take somebody that has a biology major with engineering in the health care setting. Those are the types of things that are emerging. On the right-hand side, you see an illustrative talent model, which brings together all new rules with digital assets. I'd like to call this hybrid intelligence. It's agents amplifying humans. Cognizant's talent is really ready for the future as these opportunities expand across our industries. So I'm just going to touch on a couple of parts of this talent strategy, and I'll just double down on two. One is, we are a learning powerhouse in this company. It's something that's been decades in the making, and we're doubling down on this as a key strength. You've heard that we just opened another immersive -- actually an amazing learning facility in our Chennai campus in India, and we're going to keep investing. We have also a talent intelligence patent-pending solution called MySkills, which I'm happy to talk to anybody that wants to talk more about this. This is on fire in the company. And I'll just say this only in a few months, we had 2.7 million skills added on to this program. And why is that important? We're able to get people onto projects 60% faster. We're able to have much more efficient pricing models. And probably the most important is that it's informing our learning and we're able to use adjacencies to help our learning be very efficient. All this together, our future-ready talent strategy positions us to support our clients in this new growth wave. So I'll just touch on a couple of takeaways. One is technology does not drive change alone, technology and people do. And that's why it's so important to focus on your talent strategy. And for us, it's our entrepreneurial culture with our learning strength which is unparalleled. I talked about psychological safety. When you take that with customer centricity, it's a key ingredient for innovation. When we -- and I'll just say that this is what's enabled Cognizant through multiple waves of transformation in the past and what will also position us in this new wave. And that's the Cognizant difference. So with that, I'm going to say thank you for your time. Please find me in the reception, and I'm going to invite my good friend, Jatin, to talk about our financials. Thank you.

Okay. For our CFO, it's a good trade-off if you are getting to cocktails faster by sacrificing a tea break. So I hope it is [indiscernible]. Okay. So thank you very much for being here. Very good to see some of the familiar faces in this room. So thank you for being here. I'm going to try and bring everything together what we have spoken since this morning. I'll be purposeful about the slides I cover so that we leave enough time for Q&A. This is what we have really invested in, and this is the summary of all that you heard since morning. Let me show you how it has impacted our financials. The first is bookings. If you see across the chart, you will see a clear positive progression. Our bookings growth is significantly ahead of our revenue growth. Our TCV both in number terms and value terms has increased significantly since '22. And we are running this business with significantly higher book-to-bill than we used to do in the past. So strong bookings and excellent customer retention gets you to the next chart. This tells you a story. This tells you a story where we have increased our aggregate revenue growth by 900 basis points across last 4 quarters of which 500 have come organically. And let me remind you, this is not -- this was not the time. All of you know this industry very, very well. This was not a time of plethora of growth. This was the time when the industry was either shrinking or sluggish. And this is what we have been able to push through all the things that we have described since morning. And if you see our Q1 guidance, either side of the range, organically, you will see -- continue to see this progression. So if this slide doesn't tell you about or give you comfort of our progress, probably no other slide word. Even as we have executed on revenue, we are executing on the margins. There are two things that we have done in the last 2 years. The first is the NextGen program. Many of you know about it. You heard about it in every earnings call, excellently run program. With that, we have delivered 140 basis points of additional savings in SG&A. The second one is what I call as operational excellence. Operational excellence is a jargon. But let me tell you very simply what it means. It means that for a given outcome that you want to create you want to shrink the quantity of input resources. It is as simple as that. And if -- I will give you two data points for that. Even as we are accelerating the revenue that you saw in the previous chart, we shrunk our bench cost by 30 percentage points between Q4 of '24 and Q4 of '23. Second, which is even more heartening to me as a CFO. It's almost like eating a desert. That we grew our revenue between these 2 quarters by $100 million organic services revenue. I'll underline organic services revenue even as we shrunk our headcount, aggregate headcount, you can go back and look at our numbers, our total size of our company shrunk by 16,000 employees. And that is operational excellence in my mind, to shrink the input as you continue to push on the outcomes. And as a result, as you can see, we delivered 20 basis points higher operating margin for 2024. After investing 30 basis points of margin dilution in Belcan, which is a great strategic asset for us. And that's not enough. All the work that we did on left side also helped us invest. This is a very nice picture of a balanced portfolio, where we have invested. The first and foremost is AI. The whole sense incubate and scale model in AI has come to life. So it's one big investment we have spoken about. But I'll tell you two more, which are not very visible. The first one is data, cloud and infrastructure. You know, Cognizant has always been a formidable player in applications and BPO business, which is the bottom two. But in last 2 years, we have really invested in data, cloud and infrastructure. And that's the result that you are seeing when you see that our large deal wins have gone from 17 to 29 because you can't win large deals. If you are not a full stack player, across BPO, application and infrastructure, you can't win it. And hence -- and so that's a great data point. I'll give you on the portfolio side. If I wake up any one of you at night and say and ask you a question, what is Cognizant known for. You will tell me, BFSI, health I'll tell you. And I'll give you a reason for you to add one more, which is CMT. CMT, which has been an investment in terms of platforms, people, leadership that we have done over the last few years, is now 17% of revenue, but I'll give another data point, but it's 40% of our top 10 customers' revenue. So if a company which is traditionally known for health and services, has 40% of its revenue coming in top 10 customers from CMT. It tells you the sort of breadth and depth that we have been able to achieve in terms of our portfolio. So far, I have spoken about the progress we have made and the portfolio that we have created. And that takes us to the slide that Ravi spoke about, which is our ambition to get to the Winner's Circle by 2027. I skip the slide in the interest of time on M&A, which has been a critical contributor for our success. In fact, the very fact that two of the leaders who came through acquisitions over a period of time, spoke to you this morning tells you the importance of M&A in our scheme of things. With M&A and the portfolio we have done, we believe we can get to this number. And Ravi spoke about briefly what we will achieve. But I'll also add how we will achieve. I think the most crucial for us would be to achieve the GenAI opportunity, which is in front of us, the IT-OT opportunity, which is in front of us. If we can -- this industry has been for leaders a chair of -- a game of musical chair. If you are able to catch a wave early and invest early, you will have -- you will be the growth winner for the next 5 years. You can go back and check it, let's say, 2009 to 2014, it was infrastructure services, right? It was led by TCS and HCL. If you see between 2014 and 2018, it was digital, which was, by the way, led by Cognizant and Accenture, and the numbers will tell you that story. Next few years belong to gen AI, as all of us know it. And we believe that we have a great story there. And that -- capturing that is essential for us to get there, and I think we are very well convinced to that. Second is continue to win large deals. And third, which is underpinning all of this, is excellent delivery and execution and customer satisfaction. And that, I think we have done a great job about in last 2 years because I can tell you, you can't ramp up large deal wins without executing well on the deals that you already won. There is no customer today who will give you a large deal without speaking to 5 or 6 CIOs with whom we are working today on a large deal. So I think we have done that. Even as we grow our revenue, we want to expand our operating margin. For 2025, we have mentioned 20 to 40 basis point margin expansion. That, I would like to remind you, is after absorbing 8 months of additional dilution coming out of Belcan. So even if you take -- for 4 months, it was 30 basis points, you take 50 basis points, that's a large expansion that we have already committed as part of 2025 guidance range. For outer years, we believe we can deliver another 10 to 30 basis points of margin expansions. There are 4 levers, of which 1 of them is enabled, and I'll come to it in the end. But I think the first is really the vector 1 or hyper-productivity lever that we have heard about -- we heard from Ravi and we heard about it throughout the year -- throughout the day. That is the biggest lever. And let me go back to that same operational excellence point. I spoke about through traditional levers and early onset of hyper-productivity, we have been able to achieve what we achieved on operational excellence. We can go really far. We are saying 20% of our code is written by AI. It can become much more. In that case, you can shrink the quantity required to get to outcome much more. Now, you take this quantity and look at the average cost of this quantity, which is the classic pyramid. And then you go to the first lever. This year, we are hiring 20,000 freshers or fresh graduates, recent college graduates as part of our study, which is more than double of what we did last year. And why it is crucial? It is not crucial just from a cost angle. If you go back and look at your own household, I look at my own, who consumes AI the most? It's not me. It is my children who are between 12 and 22 are the largest consumer of AI. If AI is going to be next win, this is the workforce we need to recruit. And, therefore, that whole pyramid optimization is just not a cost play. It is about being competitive. It is about being smarter than the next guy in the marketplace. The other operating leverage is hyper-productivity applied on ourselves, and therefore, making sure that the SG&A growth is much lower than the revenue growth. And the 1 enabler in the middle, which is quietly sitting there is portfolio evaluation -- evolution, which is to continue to go towards and convincing customers to focus on outcomes and increasing managed services, fixed price business. In last 2 years, we expanded this by 2.5 percentage points. Number look small, but you are talking on a base of $20 billion. It's not easy. But it will improve. And as it improves, our ability to deploy this lever improves. Lastly, let me talk about cash. We have a very healthy business. We can generate 90% to 100% of net income. We can convert into free cash flow. We are committing to deploying all of that into a model of 25, 25, 50. 25% is around a dividend, 25% on share buyback and 50% being earmarked for M&A. And I've spoken about how M&A is crucial for us to find high-growth area, which can help us expand our existing relationship much better than what it would be otherwise. There are 2 more data points, 1 which Ravi referred to and all of you are aware that the Board of Directors this morning has announced that the outstanding authorization for share buyback has increased by $2 billion, which takes us to an outstanding authorization of $3.1 as of this morning. And we will do $500 million more of share buyback in 2025. This is specific to 2025. Otherwise, we'll stick to 25, 25, 50 as a strategy as we go forward. Finally, before I move forward, I want to tell you that we have a very healthy and robust balance sheet. And if there are opportunities, which are on the horizon, which make eminent sense for Cognizant, we can always leverage it to go after it. So our balanced capital allocation is built on a foundation of healthy balance sheet where we can take a calculated bet if we want to if we saw great opportunity in front of us. This is really the summary of our financial roadmap, which we believe will create shareholder value as we move forward. Top-tier revenue growth by 2027, annual adjusted operating margin expansion of 10 to 30 basis points. That supports EPS growth ahead of revenue growth. I want to remind you that for last 2 years, for '23 and '24, our EPS growth indeed has been ahead of our revenue growth. And we are committing to continue that journey. And finally, making sure we convert our cash well and we follow a balanced capital allocation. Before I end, I want to summarize our story, this is my endeavor to put everything that you heard since morning on a single slide. There is a great market opportunity in form of Vector 2 and Vector 3 on AI and whole IT/OT convergence on the other. Cognizant has a clear strategy that you heard since morning, and we have a much more balanced and diversified portfolio of services than we had before as an ammunition to go after this opportunity. That can create financial results. That can lead to a virtuous cycle of reinvestment in high-growth areas and a balanced cash back to all of your shareholders. And that's all I had to say this afternoon. Thank you very much. We'll be very happy to take your questions.

So, Robbie, Rod Bourgeois here with Deep Dive. Very big picture question. You have been executing a transformation and talent and culture, which seems 1 of the drivers of your improved revenue growth and your margins. Can you give us a sense of how far down the transformation of talent path you've already progressed and how much room is left on that? Just very big picture. Is there a lot of room left in order to get to the Winner's Circle? Is talent and culture still a big part of that path?

That's a great question. I mean we are a human capital company. So the first thing I did when I came on board is to have employees on my side. And then I had clients on my side, and now I'm hoping investors are on my side. So the way to do this is Cognizant's culture, I actually spoke about it. The heritage of this company was people who started school and become precedents of the company, like Surya is. We have 70,000 people who have 10-plus years in Cognizant. And that was the essence of who we were. Because every time there was a new wave, everybody went and hired people. We first used our reskilling infrastructure to get ready at scale at economics, which our clients loved it. We've got back to that. So we're hiring 20,000 school graduates. We have hugely invested into learning infrastructure. We think when the next wave comes, we have more people inside even before we can start to hire. And we are a magnet. We are a hiring magnet. Right now, I have the ability to hire 20,000 laterals per quarter. So I'm not only preparing for a slow-velocity market, I'm preparing for a high-velocity market if it happens at any point in time. Now the strength of the company, I mean, I went through this myself. I don't think Cognizant needs anybody else's culture. Cognizant just needs to be Cognizant, and it will be super differentiated. And the strength of that culture, it comes from entrepreneurial spirit, high on innovation. I mean, I test vetted with so many clients. What makes unique this associate from Cognizant in comparison to all the other associates you're working with from other companies, they said, they come with the spark. They show me new innovation ideas and they feel empowered to go back and tell their managers to invest into it. So we want to be that big, small company who we were before. I'm just taking it back to the roots, and that's what culture is all about. Now on the client side, we had the super agility as a company to be a $20 billion firm, but still have the agility of a small company. Every time I go to clients, they will tell me 2 things. Either you have breadth of capability or you have the agility of a small company. So on the client services teams, we actually had both. We had breadth of a big company, and we had agility of a small company. So we were this big/small company, which Kathy was mentioning. So I am actually leading that, leading that from the front. I have -- I'm not exaggerating 500 client CXOs from 500 different companies on the cell phone. And I'm telling them, you don't need to call me, and I hope you don't. But if you have to, you can. That's the power of who we are as a company. So that culture, I think -- I mean it's progressively got to a point where we now have the differentiation. We have the gold standard, but I'm going to keep stepping that up. Our Bluebolt innovation initiative, 250,000 ideas driven by associates inside the company. And 50% of the -- more than 50% of them are AI-led. And these are people who are now thinking, I can throw an idea at my organization. They will bring it to life. And I'll have the opportunity to take it to clients. Our clients are starting to see that. My NPS scores have gone up 2 years in a row. I mean, the first year, there's a little bit of a novelty value for a new CEO. The second day, it actually dips, mined and dipped. It actually went up, both at NPS and on employee satisfaction. So I'm super confident that we are on a great journey on employees and we'll remain a magnet. And when the high velocity comes, we'll not only retain, but we'll actually attract more from the market. So it's a journey. I think I'm pretty close to saying that we've got back to that module. I mean, more to do always.

Thank you. Over here in the corner, Robbie. Ramsey El-Assal from Barclays. And thank you for the Analyst Day. It's been a great day, a lot of good information, good insights. It was impressive to hear Prasad talk about 20% of code being generated by a machine. I was wondering have you seen any changes in how your clients are looking at pricing in the context of these like sort of internal hyper-productivity gains? Are they asking you to pass through any of these benefits you're seeing? Or is the structured pricing remains so much static?

It's a great question. When I first wrote about lines of code written by machines in quarter 3 of last year, many told me that, "Look, you're exposing this to clients." I actually think this is not the time to be defensive. This is the time to be going and telling clients. You know what? We have -- I mean, look at what happened in labor arbitrage. Clients came and changed their operating model because of labor arbitrage. Clients are going to change the model when you get productivity back. So wherever we could, we are managing that rebaselining, wherever we could. I mean, if I don't do it, somebody else will do it. The challenge with managing rebaselining is the ability to consolidate and increase your top line by consolidation even if you give away gains to clients. If you do this proactively, which we did, I mean, last year, a large number of our deals were sole-sourced. In a low-velocity market, we did 29 $100 million deals. And remember, the company was coming back into stabilization. So I had to fight that out to get there. So with that proposition, where you go to a client and say, "Look, you take our portfolio, you take the surround around it, we can consolidate, we can share the gains." I can keep my top line and incrementally do more, and I can actually keep my bottom line. I will secure the client for the next few years. And then subsequently because AI advances are continuing, I can actually get more productivity even after the contract is done. But first, if I'm securing the contract, then I can have more. That's how we got the 12,000 releases in addition to what we gave away to clients. So clients are already rebaselining. And I think we are leading the path and that's why we're winning those deals. I want to -- I want my sales teams to feel that level of confidence that when you do this, you're not going to shrink, you're actually going to grow. And wherever we have been able to, I think we've been able to manage to secure it. And before I do that, I can't be having high attrition, not a stable leadership team to go and tell them, you know what, you're doing this much business with us, give us more. I can only do that when I have a base where the attrition numbers are very low, my employee satisfaction scores are high, my fulfillment rates are high. Then I have the license to do this, which is what happened. I mean in the first year, we got all of that set, then we went and told clients. And we consolidated deals. I have numerous examples between '23 and '24, and we will do the same in '25 as well. I mean we will go and proactively sole source and create deals. And if we don't do that, I mean this is -- your question is absolutely valid. Now it is going to have a bridge between how much shrinks and how much growth. But if you have a compelling proposition, it will grow.

Jason Kupferberg from Bank of America. I really appreciate the day. So I was curious just to ask about the Winner's Circle, right, the aspiration to get there, top 3 or 4 out of the 10. What are maybe the top 1 or 2 drivers of making that happen? Because we heard a lot about Cognizant's differentiation today. But if you were going to kind of narrow it down to the real critical success factors that get you there in a couple of years, what do those look like?

Two. First, I think the compelling hyper-productivity we are powering with our platforms, I don't see any other player who can do that. So I'm pretty confident. Show me the portfolio. I'm going to give you productivity, which is better than what I did before and better than anybody else can do. And I think we want to be in that journey because this is an evolving science. You can never be off the table. You always have to keep investing and investing and investing and be ahead of the curve. So that's one. The second I would say is we are now no longer seeing this as tech spend of enterprises. We are seeing this as an opportunity with a total addressable spend, for lack of the right word, anything below the cost of goods sold. Anything which is operations-led, we can identify, we can digitize and we can drum. And that's why the capability set we have to build for the future, we have to be careful about what we choose and go behind it. So I'm actually super excited about it. The underpinnings of both are the investments we're making on platforms. I mean, those platforms are the last-mile infrastructure. And what Babak showed today, what Prasad showed today, they all needed to heavy lift in AI journey. If I wait for a couple of years, most of the software will have this. What I'm talking about today -- and today, that's the reason why clients are not embracing it, and we are actually solving those problems on the way. I call it fast software. I call it intellectual property on the edge. And these are the 2 reasons, I would say. We have a blockbuster sales team. I mean I'm super excited about the agility of the company, the speed at which we can unify as a firm. I mean for a $20 billion company, everybody seems to know everybody. And very agile. My CFO is on speed dial, I'm on speed dial, everybody is on speed dial for a commonality of purpose, which is about winning at a client. I'm trying to create the same velocity inside. I mean we need to have the same velocity inside. We are executing in the last 2 years, $50 million deals, $100 million deals. We've put them together on a bid versus did program. Jatin reviews it every week, I review it every month. The Board reviews it every quarter. And we are on track. So I'm actually very optimistic. I mean, look, the velocity of the market would be slow. The velocity of the market would be high. As long as on a relative scale, I'm bidding my peers and going up, the growth rates could be different depending on the velocity. And the swim lanes you activate, low velocity, I'll be activating all the productivity deals, which we spoke about. In a high velocity, I will activate the innovation and revenue growth deals, including discretionary spend, which we are by the way doing on financial services now. As discretionary is coming back in financial services, we seem to be capturing the most.

James Faucette, Morgan Stanley, over here. Next to Ramsey in this corner. Thanks a lot for the time and all the effort for the benefit of the investor community here. Just wanted to ask a question. You obviously are making a lot of investment into AI capabilities. I've liked a lot of the commentary around platform and how that can drive efficiency. I'm wondering though, a lot of times we hear or increasingly are hearing from some, even your software partners, how they think that they can take on more of what traditionally has been done by services companies themselves and help improve the time to efficiency for the customers. What's that balancing act? And how do we feel -- how do you think about where you fit in the future versus where the software companies fit, especially as they look to change some of their delivery?

I think that's true. Your observation is right. More and more things services companies do will actually get productized. And as they get productized, we actually look for new frontiers. And that's what I'm doing with Vector 3. I mean, look at it when the cloud happened. When the cloud happened, I was doing Investor Days then as well. And the plumbing to building ratio has changed. Everybody said services companies are going to be killed, everything is going to be productized. It's true, it got productized. The plumbing was 70% of what a developer did then, 30% was building. The cloud flipped that ratio on its head. 70% is building now, 30% is plumbing. You know what, we have more cloud opportunities now than ever before. I think the expansion, the -- I think we underestimate the elasticity of spend on technology. There is so much more technology to be spent, there are only 26 million developers around the world. The world needs more. So I actually believe this is only -- it's a paradox. It is going to actually create more spend. So the more for less formula, I truly believe, will take -- will give us more elasticity. And the spend is now going to be not just in technology, it's actually going to be at the intersection of technology and the apps. I mean, look, if I have to go back to that example of underwriting, I have a very different profile of capability needed. Recently, I heard, one of the banking institutions talk about riding an IPO with agents. It went from 3 -- 4 weeks to 3 days. Now the question is, do you want to be in the agentification business? Or do you want to be in the business of writing S1? And if I want to be in the business of writing an S1, the universe has increased. I don't want to be. I mean, there could be other areas, which are similar. Customer service, a great example. We didn't do a lot of work on customer service. We just did technology work underneath it. Right now, thousands of people in customer service function are my universe now. I mean, every company has 15,000, 20,000, 30,000 customer service agents. So I think we have to start to look for new addressable pools because the services we do today will translate to software. I'm pretty sure about it. We can do that. I mean it doesn't need a software company to do it. We can do it. And even after we do it, I think we have to look for other addressable pools versus just technology spend. Technology spend is not the universe I'm looking at. If technology spend is the universe we're looking at, I mean it is a shrinking market. Today, 20% of the code is written by machines. There will be more and more and more code written by machines. And as that happens, I just think the addressable spend is only going to be increased because technology will be embedded into everything we do. And that's the lens we are taking, and that's the lens, on which we are investing into the future. So we see this TAM as a big -- a much bigger TAM than how we traditionally saw it. Well, do we need deep programmers? We would need deep programmers to write the AI algorithms. But that will be another swim lane, which -- I mean, like writing autonomous software for cars. I'm telling you any car company, you go and tell them, I have autonomous software engineers. There is no budget. It's unlimited budget, but they're not enough available. So it's just the -- I mean, the way you see it.

I just want to add in short term in Vector 2, Ravi covered the Vector 3, but even in Vector 2, we see clear opportunities for agentic -- multi-agentic framework or central coordinator role that a system integrator can play, which is difficult for a software agent force to do. I'll give you an example. As a CFO, I want to know -- I remember this opportunity, what happened if we collect the cash, then we pay the vendor? It's an easy question. But the moment I say opportunity, you go and go to the agent of sales force, but that won't be able to travel to my SAP platform, which has collection data. And it won't be able to go to Ariba platform, which has maybe the payment to the vendor sitting. So you need this multi -- central coordinator in a multi-agentic framework, which can talk to each of this individual ecosystem and give you an answer. So even today, there is a role of a classic system integrator in Vector 2, which Babak was speaking about, which Naveen was speaking about, which we are winning as we go. It is not about day after tomorrow, it is today.

Cloud migration, data migration. In fact, I spoke about how the stack is going to be disrupted. The UI layer, billions of dollars has been spent on the UI layer. It's going to be completely out of the window because you don't need a UI anymore. The experience of talking to an algorithm in conversational style, I mean Ben is actually my colleague working on the -- transforming the experience in the world of AI. That's going to be billions of dollars. So we are really looking at the future stack and then starting to think about what the opportunity is.

Jim Schneider from Goldman Sachs. Thanks for the great presentation, and thanks. Since you've become -- you've been at the helm, Ravi, the turnaround and the financial performance is apparent to most people and then certainly to investors, I think. As you go forward, maybe talk about, you've been very clear about the areas you're focusing on, but sometimes, you continue to execute on a turnaround, what you focus on is just as important as what you don't focus on or what you choose to sort of put to the side. So maybe share with us some of the things you're deciding to put to the side or deemphasize, whether that is certain types of verticals, certain service types or deal size or smaller deals, et cetera?

That's a great question, actually. Traditional BPO services, which are, say, F&A, procure to pay. All of them, I wouldn't take them in the traditional way. I would actually take them in the new way of delivering it. So those -- I mean, call centers, let's say, call centers. Call centers are up for disruption. I'm so glad we are not in that space. But you have to see it with the context that I can go and disrupt it. But if there is traditional call center work comes on my way, I will probably -- just to run it, I will not take it. But if I have to run it and transform it, I will definitely do it. What else, I mean if I look at that chart, there are so many areas, which we should not be involved in. I mean if I presented this Horizon 3 chart, I think identifying what to do on that chart, and identifying what not to do on the chart, I think it's going to be a very important decision point because strategy is all about taking decisions of what not to do as much as what we want to do. Anything else you want to add? Well, it's a good question actually. I have to start to think about -- look, in a low-velocity market, you don't have -- you don't think that way. In a high-velocity market, you start to think what not to do. In a low-velocity market, you're trying to grab things, which come your way.

It's Darrin Peller from Wolfe. When we think about the Winner's Circle growth profile, obviously, it depends on the market's growth rate itself, but when we, first of all, consider organic versus inorganic, I know you kind of moved a little quickly through some of these slides. So maybe just a little more color on what you're anticipating from an inorganic contribution? And then even taking it a step further on headcount, you guys have 330,000 people now and so much, much larger base. So in considering how much you will need to acquire talent inorganically to really allow you to grow the headcount you need, just help us understand that as well, if you can? And then maybe just a little bit more on the intended mix in terms of offshore, on-site, offshore if you looked at a couple of years?

Yes. So our going-in hypothesis is really, the growth is powered by organic growth. So it is not something, which is fully inorganic growth. It is -- like you have seen our performance in the last few quarters that a large part of the growth came from organic. So when we say we want to reach Winner's Circle, that is -- the strength of that reach is coming through organic growth. It will have inorganic because there are clearly areas we can even think now that we need to invest to capture a high-growth area. So that will have an addition of inorganic, but that won't be the primary driver for us to reach Winner's Circle. Your second question around headcount growth. Headcount growth is something that we would probably not hazard a guess today because it's a 3-year journey we are talking about. We are already speaking 20% of the code is coming through something like -- is coming through AI. So this is an evolving world. Difficult to say how much it will come, but I think, one thing is going to be certain that every incremental outcome that you are generating, we are going to generate it with less and less human effort than what we are traditionally used to seeing. So that is a hypothesis. On on-site versus offshore, it is really -- I'm sure you would agree, it is a factor of the demand cycle. So in a high-growth discretionary-led scenario, it is more on-site-centric growth. And in more cost-based growth is essentially through offshore. So it depends how each of the year pans out. So again, that's difficult to call out today.

Bryan Bergin, TD Cowen. Thank you for all the detail today. As you have clients adopting more generative AI solutions and as you yourself are doing so, too, I'm curious how you think about the sources of margin expansion may change? And as you think about as well as the clients adopting solutions, do the contract structures have to change?

Yes. So I think for years, we've been talking about outcome-based pricing. The closest we got to outcome-based pricing is transaction-based pricing or fixed price deals, managed services. But we haven't actually as much gone to outcome-based pricing as an industry. I think we have a unique opportunity now to go to outcome-based pricing because you could really lend technology for a task and hand it back. I mean that's almost a simplified answer. I mean I could lend a bunch of agents to take care of my holiday season as a retailer. Like I am lending human labor, I lend digital labor. So, I mean, I spoke about one example in my -- as I was speaking, and this is a client who is actually asking me to build a digital nurse. And they do not want me to be an engineering partner. They actually want me to be a partner who can share the benefits of digital nurse. So I think we've got close to that point, so there is an opportunity. I believe because of our platform's heritage, we have a mindset for that. I mean I make money on TriZetto by looking at the number of transactions underneath it. And now I'm making now the next model for TriZetto is to look at spend, which is flowing through versus transactions because if you're order adjudicating claims, you have lesser transactions. So we have to start to think about it. It's also going to pose more risk because you have to not just bet on the model, you have to bet on the business of your clients. And in anticipation of returns, you have to put your costs up. So I'm actually thinking we could be ahead of the curve on that, but it is also about how much appetite you have to bet on those kind of models. That's what our platform plays all about. We are actually investing ahead of time on platforms in anticipation that we want to win business in the future. So it takes you a little more on that risk profile as we go forward. I'm going back to the previous question, which was about what we not do. I've always started to think about not to do things, which don't have a context to take you to the future, which is like data centers. If somebody told me to take a data center, I wouldn't do it. But if somebody said take the data center and move it to the cloud, then I would take the data center. Because I'm kind of betting on the end -- on the future, not on the present. So I think pricing -- pricing will become much more exciting. As we go forward, it will be more risk-weighted. Yes. Please go ahead.

First of all, a very well laid out, very briefly packed -- I mean, succinctly packed event. So thank you for that. So the question, and this could be either one of you playing ball. On the sole source, the deal incubation. So clearly, that is evolving, and that's where the TCV is the profitability, but it's a lot of conversational sales, which also means multiple cycles, as opposed to an adviser orchestrated RFP, which has time lines, time bound, et cetera. So the question is, with that context set, how are you navigating the deal shaping universe with many a times, the conversational selling is on the shoulders of account managers? Including things like GCCs, which we spoke about, which is becoming a second arm as opposed to third-party arm. So -- and many a times, the account managers tend to take a slightly defensive posture to conversational sales because the immediated KRAs are slightly still old tuned. So how are you straddling this conversational sales, deal shaping, sole-sourced with account manager KRAs, which are the last milestones or potentially the first milestones for those interactions to happen?

So, [indiscernible], I'll start, and I'll request Ravi to add. I just want to talk about the timing when you can get sole-sourced deal done. And I think we are in that time. The timing of sole sources you'll get is when the environment is uncertain, there is no homogeneous view of productivity available in the marketplace, and you are able to pitch a compelling solution to a customer, which he feels yes, let me bet on these guys because you can do it. Now if you are in a market where the technology outcome is very homogeneous, that will lead to competitive bidding and 5 rounds and eventually, you are hammered down on price and pick up the deal. That happened, for example, in classic old infrastructure services, which was data center plus desktop management between 2012 and 2018. We are no way close to that opportunity right now. So it's possible. Now, I'll let Ravi talk about how our account management really leverages this opportunity.

I think it's a very good question on account management. How do you tie them to long-term incentives versus short term. I mean, look, if I was an account manager, I'm holding on to it, saying, "I will not give it away until somebody cannibalizes it." But we also have now created a mechanism to know, which are the clients where we know we have a compelling proposition. We have a seat on the table. We have trust. We have a trusted relationship where we should double down on. And I think we have to work on the KRAs. We have -- I don't think we have fully got there. But I'm also seeing a different thing now, just going back to 1 part of your question, which is -- if I look at deals we have done with you, deals we have done with Charlotte, we have taken you to those deals versus you bringing us to those deals. And when you were bringing us to those deals, it was called out by the client. And when we are taking you to those deals, it's called out by us. And why are we bringing you in? Because they still need an agnostic party to vet it. I mean, I've gone to 1 client with Charlotte where they basically said, "Look, this is fantastic, but let's do an RFP." And I said, "Okay, it will cost you this much to do an RFP. I'll get you an independent party, which will validate, which we have done with one of the deals with you." So I think it's going to become -- the roles are going to change. They're going to blur when we sole source it. And I'm seeing that -- I mean, the partnership we have with ISG, the partnership we have with many of you in the room, we are excited about taking you to those deals. And we feel confident to win. Therefore, we can bring a third party in saying, evaluate, it's okay. But don't go and do an RFP.

Jonathan Lee from Guggenheim. Given we're nearing quarter end, can you talk through what you're seeing today with heightened uncertainty and how that looks relative to your near-term outlook?

So Jonathan, thank you for, first of all, wearing Cognizant jacket.

Maybe we should -- next time, we should get one for everyone.

Yes, but as you can imagine, we are in quite picked. I would not comment specifically on the quarter. If we are okay, I can't comment. Your question was on the Q1 quarter, right? Yes. I mean it's just too close for me to make a comment.

It's [ Puneet ] from JPMorgan. So Jatin, in your presentation, you talked about that 50% of cash will be allocated to M&A. Should we expect like a continuation of deals like you did in 2024, like the large deals that help you gain capabilities in underpenetrated markets, whether it was aerospace, defense or ServiceNow, through those acquisitions? Or should we expect like different type of assets like the assets to address this larger TAM that you talked about through, Services-as-a-Software? Like what does your current pipeline for M&A look like?

So, I think, Belcan was a big bet. And, therefore, it was very, very -- we had to really think through whether we take that bet. I don't think if you look at last 5 years, that was a slide on my deck, where we have covered. I think what we have taken is calculated bets in high-growth areas, which fit nicely into a part of our portfolio where I can tuck it in and grow quickly and disperse it as its offering within our market access channels. So that would be the -- that would be more of our deals as we move forward. Of course, if there is a great opportunity on horizon, as I mentioned even in my presentation, we'll look at it. But I don't think every year, we are trying to do a Belcan equivalent of deal.

Surinder Thind with Jefferies. When I think about the growth of GCCs, it would suggest that clients are trying to do a lot more themselves. How do you fit into that equation when you think about going after that TAM that's beyond just the IT spend if clients want to do more? And as we think about the evolution of technology and their ability to do more, what is their willingness to share? And how do you fit into that? Are you becoming much more of a product company then that's servicing clients? How do we think about that evolution?

It's a great question actually, 1.5 million people work in GCCs in India. So it's a fairly sizable market. It's in 3 areas: engineering, ops, and technology. And initially, it was technology in our tops and it's also engineering. In fact, ops is actually moving where technology is. So they're kind of going there. So I think there is a different value proposition there, which system integrators like us have a unique role to play to grow the GCCs. I have no interest in telling them it's not the right thing. First, it's a labor market where we are a dominant force. I mean, if you're a Tier 1 global enterprise, you still have an opportunity to go to those labor markets. But not every company can go in those labor markets and [Audio Gap] enterprise, you still have an opportunity to go to those labor market. [Audio Gap] for a period of time of platforms, productivity tools and everything else. So I think the opportunity after the GCC is established, there's more than the opportunity of establishing the GCC. Establishing GCC has the things, which Surya spoke about, which is the micro-services, we can sell Learning-as-a-Service, Recruiting-as-a-Service and all of that, which is lending our value chain. And doing a build-operate-transfer means I am actually now standing up multiple GCCs in my premises in India, in my premises. So they are actually building the GCC in my premises where lock stock and barrel, we're taking care of everything. But that's not the opportunity I'm excited about. That's the opportunity -- that's a good short-term opportunity to connect and create the glue. The bigger opportunity is because there's a runway on AI, runway on productivity, runway on automation, we will be better than any -- we will be better than our clients, which -- who are not -- this is not their core business. So they will actually ask access to the tooling and the infrastructure, which we can price them actually, constantly keep giving them. Because if we don't do that, their productivity will be lower. And subsequently, the business case will fall off. Because today, the whole opportunity of arbitrage is not labor. The opportunity of arbitrage is labor plus technology. And if they can't create the technology arbitrage, we want to create the technology arbitrage and rent it to them or partner with them. So that, I think, is a bigger opportunity. I mean, clients are starting to see this. Look, I'm going to set it up in India or in Philippines or in any of these labor markets, but that's only going to be a labor arbitrage. What about the technology arbitrage? That has to come from us. So we want to partner with a long-term view of giving the productivity back to them. So more GCCs has put -- I'm actually feeling excited about the size of the opportunity. Engineering spend was completely insourced. One of the reasons why engineering spend is outsourced now is because of the advent of GCCs in the last 2, 3 years. And they are an opportunity for me. I mean the automotive client I'm referring to, I met them in Bangalore. They want me to provide software engineers to write code for cars in Bangalore because they can't find them. And once they do that, they will ask for productivity tools. They will ask for platforms, and we want to be in that journey with them. So it's an evolving space. We -- with a flexible model of how we co-create with our clients, with the platform approach, I see this as an opportunity. I don't see this at all as something, which is going to take away our services. I mean you look at it in the short term, it does look like that way. But on the long run, we can build great strategic partnerships.

Thank you. Over here, actually. Lou Miscioscia, Daiwa Capital Markets. So the presentations on AI were really good, so I appreciate that. On that concept and on the different waves we've seen over the last 10 or 20 years, any time a new wave comes in and it's big and we can actually say that this one is pretty massive given that we're seeing hundreds of billions of dollars this year, next year coming into the data centers. Now I understand that for this year, you have got guidance, and I'm really looking for guidance. But at some point, wouldn't you see a massive step-up in demand that could give you then a massive step-up in your revenue growth, 10%, 20% sort of going back to the old days? Because if all this money is going into hardware, you could just look at NVIDIA is over $100 billion in GPUs last year, $150 billion in 2025. Somebody wants applications and somebody wants solutions. And obviously, that seems like it would be right up your alley for the future.

Absolutely. I think your observation is right. I'm pretty sure...

Then if you -- it would be helpful.

I'm pretty sure that the value will move to the front. I mean it has to. Infrastructure will get commoditized. It will -- I mean, look at the AI scaling loss. Every 6 months, every metric on compute on efficiency is doubling. Every 6 months, the AI scaling loss have completely beaten the Moo's Law. So as that happens, the back end of the value chain will not be where the money will be spent. It has to be spent on the front end of the value chain, which means system integrators like us will be the ones who will monetize on it. Finally, enterprise-grade AI is a lot of heavy lift. And because there is a lot of heavy lift, system integrators will have a role to play. Now if you look at my 3-vector strategy, the first vector is not about additional spend. It's about optimizing existing spend of enterprises. So it can never give you this huge growth, which everybody is looking for. The first vector will give you relative growth more than your peers if you have the magic wand, I mean, the productivity tools, which the others don't. The second and third have to give you revenue-generating opportunities, growth-generating opportunities, new products, new services. And the foundation for that is also going to be a lot of heavy lift. I mean I don't -- I can't predict when the external economic situation will get to a point where the spend on AI is this double-engine thing, it's more on productivity today, but we'll get to innovation pretty soon. And in fact, some of the clients who are navigating this are asking for productivity to underwrite the savings to their innovation. And that's why we are finding some traction, which is 1,200 projects and all of it. But for those bold bets, I mean I hope the economy -- the economic -- there is more certainty around the future and the economy and that will happen. And when those 2 vectors start to accelerate, we want to go back to the heydays of the growth, which this industry had. And that's not far off. I mean, frankly, I can't think about enterprises without AI anymore. I can't even think about it because I just think it is imminent. It is real. It has to happen at some point of time.

One more question, if anybody wants the honors.

Ted Schadler from Forrester. It may not be a fair question for the last one, but I'm just interested in how you're thinking about the risk that you're taking on when you're doing -- you're building platforms, you're doing sort of risk-based pricing deals. Does that change your capital structure at all?

Look, I've always believed that free cash is not just for M&A. It should also be invested into the CapEx cycles of clients. I mean, that's an aspirational way of looking at being on the front of change and betting along with your clients and mitigating the risk your clients are taking. Are we at that point today? I don't think so. But do we want to be at that point? Absolutely. I mean, the amount of bets we are taking on these platforms, I'm bundling the platforms with the services, and I'm creating a multiplier on the services. We are not monetize the platform. At some point in time, we have to start to think about monetizing the platforms. We are monetizing the services underneath that, we can monetize the platform. Subsequently, we can -- like I spoke about the digital health, digital nurse example where we are not an engineering -- we're not an engineering partner, we are actually a go-to-market partner. I'm working with 1 another tech -- a high-tech company, where all the digital infrastructure inside the car, we are building for them, which is the digital cockpit and the chassis and all. But we are actually getting paid for OEMs for a number of cars getting sold as a percentage. We don't have a lot of examples of that kind. I mean everybody has some examples. We think we have the appetite to do more because we already invested into the platforms. And the pricing will also be a catalyst for adoption of more Vector 2 and Vector 3 opportunities. So it's a good thought to take a go-to-market in a way that can actually be a trigger for growth. But how much we can do? I mean, we are a company, which has done more M&A. We are a company -- in the past, we've used the free cash more efficiently for growth. For a long period of time, we've used the cash to generate more growth and a flywheel of growth. So it's a good idea to think in those lines of partnering with our clients on the go-to-market. Thank you so much. I know it was a long day, and thank you so much for listening to us. Thank you so much for being a part of this journey of what we are going through, and we look forward to continued feedback. And I've actually learned a lot from the questions today to figure out the ways to focus on in the future, but we're excited about our journey. I mean we do think we're very confident about being in the Winner's Circle.

Thank you.