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. Today we're really excited to talk about the long term opportunity that we see ahead and our strategy to get after it. Before we get started, I have the privilege of providing the best update of the day, which is the legal disclaimer behind me. 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.
Non-GAAP reconciliations to the numbers that we're referencing today will also be available and are also available in the 8K that we filed this morning. All right, 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. You are going to hear from leaders from our unique platforms and engineering services, as well as some of our cloud and data practices.
If you could scroll down a little bit, after that we're going to have.
Some more partnership or 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. Finally, Jatin Dalal, our CFO, is gonna bring it all together to talk about our financial results and how our financial roadmap is expected to drive long term shareholder value. 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. We have a lot to cover. 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, so grateful that you chose to come here. You know, every time you come for a Cognizant event, I'm very grateful I chose this point of time in my journey with Cognizant. You know, I spent two years in Cognizant. I joined 2023 January to tell you this story. Our journey after we have rebuilt a 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.
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've 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. I'm so grateful to my board who has been kind enough. Five of my board members have also been a part of the audience. You should be able to interact.
With all of them during the day.
We have some showcases there. It is a tiny space. If you want to see more of it, please write to us. We are going to send you more information and hopefully engage. That is broadly what I had to start with. Thirty years of heritage engineering, modern businesses. You know, in these 30 years we have had an era of globalization. Enterprises across the world used technology to scale. It was a peaceful era of globalization. As they scale, they used technology and they used providers like us. In some ways in the 30 years there were cost budgets allocated for tech transformation. The last 10 years there was a different new swim lane of tech disruption happening through digital transformation. We had access to the revenue budgets, the growth budgets of our customers.
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. We did this so well that we made the next wave because of the current wave. 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. 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 one 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. We think we are so uniquely poised. You want to hear from some of my colleagues on the AI disruption around us? There is a lot on these slides. 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. You know, 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 + years. I have 70,000 people in the company who are more than 10+ years and they know the craft well and they traverse the reskilling infrastructure of the company and moved to the next disruption in an economically viable way. 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 inner circle, the expansive margins, you know, we 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 expensive margins for the future and invest into the future so that we stay resilient. We also capture the opportunity ahead of others. We went from 14.6% in quarter one of 2023 to 15.7% in quarter four 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 source 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 healthcare. We're very strong in healthcare. By the way, we did 10% growth YoY on healthcare financial services. We actually expanded ourselves to all the other industries. Now we have industrial, comms, retail, and CPG. We expanded our large deal engine from U.S. to Europe. We now operate on four pillars of tech services all the way from tech services to BPO to infra-led transformation to engineering-led transformation. We do believe that irrespective of the times around us, we are more.
Resilient and more durable because of the.
Spread of services and 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. You know, every time I go and see a client, I ask them what is so special about Cognizant associates.
They tell me, you know, 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. They probably created incremental value and incremental projects. 14,000 people have returned. My Head of HR is going to talk to you later, Kathy. She's going to talk about 20,000 more people are waiting on the wings. 5%-7% of what we hire today is actually returners who are coming back to Cognizant. You know, 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 have shared with our clients, we have 12,000 more releases where we have created incremental productivity. In Q4 of last year, we did 2% organic growth with more than 15,000 people less. Less than 15,000 people from the previous year. That is the power of AI productivity, which is like kind of going like, you know, 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. We kind of have taken the trajectory all the way from minus 2.4% to 6.7% YoY in quarter four, the highest NPS score and the highest employee satisfaction two years in a row. We are back to the winning heritage.
We have built resilience and durability and we are prepared to lead the next wave. I actually think we are very, very well positioned for the next big opportunity in front of us. What is the future of IT services? How do we see it? There are a number of things, but I'm going 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. 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, a big opportunity for tech services companies. 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. We want to see a ton of opportunity there. We are excited about the future of ER&D, as you call it, which we see 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 want to hear from my colleague Prasad. You know, 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, you know technology is evolving. There are always going to be gaps, gaps to make it enterprise grade. As they get productized, you're going to see those gaps. We build intellectual property on the edge. I call it fast software. We are one of those companies who has 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 generation 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 built 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 built labs, we built investments on IoT, IT and OT. We built investments on, you know, investments on intelligence on the edge, smart manufacturing.
The spend we are going to see now is multi trillion dollars. Embedded engineering is going to go from insourced to outsourced. Cloud and data, which was happening for the last 10 years, will get catalyzed. There is $2 trillion of tech debt sitting on balance sheets which will get unleashed. In fact, I was talking to a bank last week. They have a lot of legacy infrastructure. They do not have the tribal knowledge, they do not have financial capital to pull it out and they do not have legacy skills. It is a unique, unique opportunity with the power of AI and operations are going to be digitized. You are going to see some of the things we are working on. We are 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're building connected pharmaceuticals and connected health care using them. Financial services, deep free fintech is still a huge opportunity, network engineering. In fact, I was talking to an automotive client a month ago. You know, 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. That's the power of what embedded engineering capabilities can do. Of course with Belcan. Our CEO of Belcan is here today.
You know, we have the same opportunity on aircraft, embedding software into the aircraft ecosystem. This is the three 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. You know 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. 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 six months. They're doubling in every six months. Cost reductions, compute efficiency, increased accessibility.
We are unlocking thousands of use cases at 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'm going to talk about it. It just changes the TAM on what we can address. Let's see the first vector. It is today and all the way in 2024. All our large deals, a good number of them, we sold sourced based on AI productivity. You know, 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 the top line bumped up.
When you share productivity, your top line goes down. It's managed, you know, it's called managed re-baselining. When you do managed re-baselining you have to consolidate. 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 number of lines of code written by machines. 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, a bigger opportunity for ourselves. 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 have 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. You know, this is something we're doing grounds up. We want to change the universe.
We want the 2,000 plus clients of Cognizant to have managed services work with us so that we can share those benefits. Vector 2, you know I call this industrializing AI and I call this industrializing AI because it is a unique heavy lift. You need to re-plumb the existing stack. You have to re-plumb the existing stack all the way from the data, the cloud foundation. Naveen, 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 that customizes 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're going to build. I mean that's the user interface. The existing user interface is out of the window. 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 healthcare client recently and I was looking at what a customer service agent does and if you want to replace that with a AI agent, you need to know the work dynamic behind it.
They picked data from different places that they consolidated and push it to client, push it to solve queries. You need to know what's happening behind it. I and my financial services had met one of our clients and we wanted to identify a teller. You need to know what a teller does. The work graphs are equally important. 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 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, you know, 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 change the pace at which this embraces, reduce the cost, reduce the risk in doing AI embrace in enterprise landscapes. Remember, enterprise landscapes are so heterogeneous. I mean, technology of the past, you first had governments, then big enterprises, then small enterprises, then consumers absorb it. In the last 10 years, consumers get it first and enterprises get it at the end of that cycle because it is heterogeneous and complex. These platforms are last mile infrastructure, intellectual property, which we own and we bundle it to the services. A lot of it is now AI led. In fact, we have business platforms which Surya is going to talk about. Our TriZetto platform is completely AI enabled. You're going to hear from one of our clients talk about it as well.
The third vector which is agentifying AI. You know, software's newfound ability is to go after labor spent 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? You know, we can actually tap into labor pools around software, identify it. The question is, will that be up for identification? The question is, will that be up for outsourcing? We are building a capability set which compels customers to view it in a very different way than how they see it today. We also connecting with the AI native startup 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 the estate. We want to be that bridge, that value added bridge between startups and large enterprises. This is an unlimited TAM, an unlimited totally addressable spend you can tap into untapped human services. We call this service as software. I am going to talk about two 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. If you look at a traditional SI, for a dollar of software, there was probably $2 of services. If I am implementing CRM in 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 trillion dollars. Here is an example of a client you can see it in our showcases who is actually doing an RFP by agentifying and Cognizant is actually helping them do 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 two weeks ago and they do all systems work with us.
They build compact medical devices which sit at people's homes and people 50%-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 hour of the possibilities all the way from horizontals to verticals. Surya will talk about an underwriting example. He has 100 odd agentification 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 agentification work or will they give you the combination of the two? 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. We have to pick and choose what we think we will uniquely win in the market. This is not just IT spend, this is labor pool spend. This is about labor pools which do not exist today. 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 $500 billion of claims going through our books. What is 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. 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 increase in share repurchase authorization and we committed to add $500 million more to share repurchases this year in addition to the $600 million we were planning to do, underscoring our conviction in the strategy and the opportunity we have ahead. You are going to hear from Jatin, in fact, his presentation is the last so that you can see all the numbers and we do not go away. A new set of strategic imperatives are evolving from the past.
Amplifying more on talent, you know, the learning infrastructure, scaling innovation, more platforms, more of grassroots innovation, accelerating growth using AI, both on productivity and on the new opportunities, on identification. We want to be in the winner's circle by 2027. Our definition of the winner's circle. Our definition of the winner's circle is to be a top tier player. You can see that 10 players at the bottom.
Amongst the 11 players we want to be in the top tier, which is top three or four 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 they 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. We want to be in the winner's circle. The winner 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 between our EPS growth and is going to be higher than our revenue growth. 10-30 basis points in our outer years, remember in 2025 we've already said we'll do 20-40 basis points in 2025, in 2026 and onwards, at a minimum we want to do 10-30 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%-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 to my colleague Prasad who's going to talk about unique IP-led differentiation using platforms and digital engineering. You are going to hear from Vibha about the embedded engineering story of ours. Thank you for listening to me today.
Thank you.
Thank you, Ravi. Very good afternoon to everyone. I want to start by introducing myself. My name is Prasad Sankaran. I've been here for two 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 a Senior Managing Director, did a lot of global leadership roles. 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. Ravi touched upon both.
What we want to be able to do after, at the end of the session is really leave you with a good view of, you know, what we're talking about. 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, you know, 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 appliance 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 huge amount of hyper productivity.
We use that through a lot of the new AI that's available, copilots, LLMs and so on. We will get into the last slide, which is going to really be about the kind of results that we're seeing. Let me talk about how, you know, when we talk about platforms, what do we really mean by platforms at Cognizant? 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. It has been a combination of legacy as well as, you know, cloud as well as digital technology. This requires a lot of talent and budgets that they are, they're short of.
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. You know what to pick up and the time to implement is significant. What we are doing is two things. We are offering what we call repeatable software solutions, but at an enterprise scale. That's what a platform essentially is. 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 a sense, high quality, and most importantly it's going to drive hyper productivity for us. What I'm going to talk about, a lot of these things around platforms really drive Vector 1 that, you know, Ravi spoke about. Now let's look at how they fit into our client's ecosystem. This is pretty, it's a simple picture, but it's characteristic of any sort of client that you look at. Right. The left hand side is all the legacy technology that's there. You know, 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 and a half 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. The middle part denotes the data silos that exist. There's lots of fragmentation. My colleague Naveen is going to talk about the data challenge because there is no AI without data. 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 is helps them with innovation. How can you quickly drive innovation? 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. It's how can we get there quickly, how can we give 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 is what our modernization platform, Skygrade, and I'll talk about it a little bit, and Ignition, which Naveen will talk about, help us do. They do two things. One is they hollow 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, you know, able to make that work with, you know, 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.
One of the things that we've done with our platforms here, Neuro IT O perations, WorkNEXT, et cetera, is how can we take out that manual effort? How can we autonomously manage that estate? 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. It is also great for our clients because it helps and it shifts the shift where the people are. I'm now going to talk about Flowsource. Ravi touched upon it. It's a full stack platform for software engineering.
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 are doing now through Flows ource is bringing this cross functional team together and they are able to now have a similar unified experience. All of the tools that we are talking about are subsumed under this Flows ource platform. By the way, if you get a chance, I can show you a Flows ource demo during the break. It is very impressive. It uses LLMs, it uses whichever code companion you want to use. You want to use GitHub Copilot, that is fine. You want to use Gemini, it does not matter. What it does is it generates 20%-50% productivity and already we are seeing that 20% of the code where it is applicable is now being written by machines.
That number is only going to go up. What does it do for us? In the one 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. This has been a huge area for us. We've got great feedback from analysts and advisors 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.
That makes a direct difference immediately and we can drive that very, very quickly. The second is a healthcare payer client where we use Skygrade. We move them from the mainframe to the cloud. We did it at 30% lower cost as well as migrating 2 billion claims that were 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 are 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.
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 and 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. Surya, I'll 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. 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. 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. 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. It's for our health clients and our banking clients. It's the core of what we do and have been doing.
We're going to talk about engineering and IoT, which is all about building software for physical devices, which we've all covered in detail. When I switch over to this part, I have three parts to 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. Some of this we do independently. 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 have 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. It's a three 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 two shore. In lots of cases we do three 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. We brought all of that together and we have a unified model.
It is not that you deal with just one acquisition and those people there, but really bringing that whole thing together. The other thing that we are able to do is really look at proximity of our clients from a Central and Eastern Europe standpoint. Manoj will talk about some of the benefits, but there is a language benefit, there is a time zone benefit for LATAM to the U.S., for Central and Eastern Europe to our Western European clients and so on. It is really a question of bringing this together in that global footprint. Platforms I will not go into, but it drives nonlinear productivity. Then there is the modern talent approach that Kathy will touch upon. 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.
You know we used to talk about developers and testers, but now we are focused on full stack engineers and SDEVs. We are trying to completely shift to the new archetypes because that is what is going to drive growth and drive our leadership in this space. 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. It is very, very important to what I do because we participate with partners who understand their roadmap to get our people certified, to go to market jointly and to be able to just give them feedback on what our clients are looking for. Very important part of what we do.
Lastly, I'm going to cover a couple of slides on digital engineering, which is that first part that you saw. This is all about building new products. 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 build that in an agile manner. We make sure that it's AI infused. We build it with the business first in mind. It's all about building new stuff. The other thing is the $2 trillion point that Ravi spoke about.
There is a ton of legacy out there and even as we get more productive, there is going to be all of this work still to be done because we have to take this backlog out, we have to take this to the cloud, we have to make this modern. This is a huge part of what we do. It is technology and business led. We are taking that tribal understanding as Ravi said that we have, and then being able to convert all of this to the new. Let me bring it alive with an example. We have been working with a leading bank in the U.S. It has 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.
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 number one 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. That's what we came to do. That's the left hand side of what you saw before, that is building the new product. 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.
That's all motion two, which is all about the legacy to cloud, to modern, and we've been able to do that. What does that do for us? Results for us. We've had a 22% three-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. It's all driven by our platforms as well as our engineering ability. At this point, I'm going to pause and invite Vibha to talk about advanced engineering and IoT.
Thank you.
Thank you.
Good afternoon everyone and good to talk to many of you before. I'm 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. 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. 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. 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. 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. 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. We are aligned with the market mix, we are aligned with the industry spend. What we're doing here is we're covering this market with four 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 are you, Lance? You can talk to him afterwards in the back.
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 lifecycle. 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. We have 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 to beyond the car. 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 in 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. 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 make the spaces highly efficient, whether these are buildings or factories or warehouses.
In each of these industries, we are providing sustainable solutions for better outcomes. 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. Some of these categories in smart products, for example, one of our clients 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. 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. We are executing a very highly technical and complex work which is driving the future of EVs. EV chargers and in the space, we are implementing this solution across 35,000 units.
Now, in the automotive space.
Did you know that 30-100 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. 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 is Firmware On- The-A ir and Software On-T he-A ir. 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 the 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. 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 five 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 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. Now you're efficient and you're doing all the processing at the edge. The third one is enhancing privacy and data security. This immediacy of real time edge processing is very critical in some industries like automotive, in industries like AMD, in industries like medtech or manufacturing or retail. 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.
This is for manufacturing plants and factories that are connected, that are intelligent and is done through simulations and modeling. This enables us to drive 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 a contemporary next generation player in this industry. This is what gives us the right to win. I want you to remember five 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.
What is important here is it is also being spent in the regional markets. We are leveraging our global talent pool across all the regions, across EMEA, across India, APAC, across the Americas for providing these capabilities across all of our clients. The second, the third one is our global network of labs. You see the digital infrastructure, this is much more than IT infrastructure. This is labs that have products, manufacturing labs, automotive labs, garages, studios. There is a lot of infrastructure that is going in from a physical standpoint. The fourth one of course is our strategic M& A.
I spoke about a few, but here 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. I spoke about the cutting edge solutions, assets and process frameworks, we are accelerating the time to market. Speed, speed, speed. I know you heard that. 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.
Combined with what Prasad talked about on the engineering platforms, Cognizant 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. I would like to invite Naveen Sharma to the stage next.
Thank you, Vibha. That was good. Thank you, Prasad. Thank you, Vibha, for setting that up. 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. 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. Been here 16 years, and I'm going to walk you through the journey of where we stand with data in the cloud. Let's first look at the market to the left. You see the numbers, right? $840 billion TAM that we estimate exist 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 these solutions that we've built. 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.
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, helps you detect it, helps you stop the transaction in near real time. Similarly, we've built models in healthcare. I'll talk about one of those in subsequent slides. The thought here being healthcare is a complex business. To review claims in healthcare, you need folks that have had a certain amount of medical education. How do we take those folks, those highly expensive, paid, highly expensive folks specialize in their area and how do we take their effort away from doing paperwork review to something that is higher value? We'll show you that in a few minutes.
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 one or two 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 the insight at the bottom right of the slide you can see some of the recognition that we've received from analysts, industry analysts that review the space for a living. In each of these analyst content collateral that is published, we end up in the top right.
You know, in 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. We feel very proud about our position in here. Bringing it back to what Ravi touched on, the three vector strategy, right? This is every client that we work with is executing on all three vectors. Some are further along on Vector 1, some are starting vector two, some have already made the leap into vector three. Does not 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 is what we call out on the right. I am going to walk you through this. I am going to start at the bottom and work my way up.
Once I do one or two 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 the work that happens within BPO, it's the 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.
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 click stream that comes in from their website, from their mobile apps. 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. Those are the two layers that I'm going to talk about. To realize value, you do need to look at the other three layers as well.
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 number three. Identifying the enterprise. That's the multi-agent orchestration.
If 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 over there, is going to walk you through that demo. 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 his team on rewiring that whole experience.
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. Those are the five layers of the new technology stack that we think you need to realize. I'm going to focus on these bottom two. Let's start very quickly with those two layers on the left of the slide. You'll see, the work that we do within the space of enterprise data 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. Sometimes you 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's 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 defined it as anything that was built in the last 10 years. 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. What was 10 years ago, Hadoop was modern. Today we do a significant amount of work modernizing clients away from Hadoop. 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 conversational AI.
Ask a question, get an answer, do it quickly without making me click through 10 steps. 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. That's the stack on the data side. Let's shift to the cloud. Remember, this is my expanded definition of the cloud. It's cloud and SaaS and cyber and all of those things that go together in that foundation. Every client's at 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. 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.
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? That optimization, that securing is what happens in this second offering for the cloud. 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? 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. I touched on this. I'm going to do a very quick drive by. I've got examples of five different solutions, right? Over 120 exist, but we've called out five.
Look at the first one in here.
For our life sciences clients. Life science companies go through a large multi-year 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 helps them improve site activation by over 57%. If you're a quick service restaurant, that's where OrderS erv 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? Order Serv helps our clients reduce the cost for building up that scalable architecture by 30%. Something that a QSR can deploy quickly and manage costs. This next one is something that I touched on already.
If you're a healthcare payer, you get thousands of claims that come in where people are saying, I should have been given this treatment, why was I declining 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 fax machines and then turn around and answer. We have short circuited that whole process, built a solution that uses generative AI to look at the inbound claim, review it, turn around with a decision very quickly. Currently running at 86% accuracy. This improves every single implementation that we do. 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? 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. 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?
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 onto wherever I want to go? X to Y sort of migration sitting on Teradata.
Today I want to go to a.
Databricks, a 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? How do I start to drive meaning out of it? Those are the five 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. 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 one to platform two, we use a fair bit of no code and low code capabilities within this platform. 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. Look at the outcomes.
Over 12 PB of data that have been moved using this platform. Over a million 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 use this asset to speed up their data migration and modernization journey. That is an example of the kind of work that we do with these platforms. How do we build these platforms? One, not in isolation. We have 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 in sizes, revenue, sometimes in number of trained resources, sometimes in a joint go to market, sometimes just having the data and analytics practice of the year consistently. These are all companies that we work with over the years. This 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 is a hilarious video. I'd love to show it to you. If you're interested in seeing that, stop by in a break and I'll show.
You know what that is.
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. 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. That's how we build this stuff. I shared all of this. What does that mean for a client? What does a client do with any of this?
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. 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.
As they moved into their roadmap of cloud first data management, how do we make sure that 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 three months, harmonize all of the records, have the Salesforce 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.
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 unlocks something in the third tower. When we unlocked something in the third tower, that actually created this flywheel of now I need new capabilities in my first tower. 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. To summarize, our right to win, we go to market by domain, we build domain specific solutions that obviously leads to these things, right?
You get a faster deal cycle, you get higher client retention. We are able to deliver fast. I 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 generate for the client. If we don't save them anything, we.
Don't walk away with anything.
If we do, we get a certain percentage which leads to long term stickiness for us. 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 and building in this space. To summarize, the market's 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.
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. 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's 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 Gomari. I'm with Cognizant for more than 25 years. I joined the firm 25 years ago from college and over the years I have moved around the firm, worked in business development, sales, presales, a bit in 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. I managed a couple of business units including Healthcare, 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.
You know, since this afternoon we have heard strategy from our CEO Ravi, and we have heard about our investments in AI from Prasad and Vibha , and we have just heard about our data and cloud strategy. Now I would like to take this opportunity to, you know, 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 did you tell the client in the room?
It was not by design, by the way. Amy, you have been the CIO for KeyBank for almost a decade.
Yeah, a little bit more.
A quick intro of yourself, please.
Yeah.
Great to be here. 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. I have a little bit of experience in financial services. At KeyBank, I'm responsible for all of our technology organizations. From front to back I also have the privilege of running all of our shared service back office operations. Think loan servicing, deposit processing, collections. I also run our intelligent automation center and our contact center. 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, Cyber Security, all the things that keep you up at night.
On top of that, I have the joy of running all of our real estate portolio. Just add a little bit to it, but keeps me busy and I love it.
That's very, very short intro, I guess. Actually, let's start our conversation with the same question that Ravi got this morning in CNBC from Sara Eisen. 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. How are you or how is KeyBank navigating this volatile environment? What does it mean? What does it mean to your priorities and spending patterns and things like that?
Yeah, I wish I, like Ravi, had a crystal ball and how all this is going to end up. Look, I think we in general in 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 that we 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. If you are not in one of our geographies, you may not have heard of us. We are one of the largest regional banks in the United States. Regional banking has been a little difficult the past couple years.
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. We are seeing clients came into the year with optimism, a little bit of caution right now in executing transactions, but they believe that there is kind of a light at the end of the tunnel. 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. We remain optimistic for the year ahead, but it is going to be a year unlike. I mean, not unlike, just like the last five years with a lot of uncertainty. I think most of us have become very good at being agile and adaptive and changing in the marketplace.
We're all having to do that.
AI continues to be your number one priority?
I wouldn't say it's the number one, but it's up there.
It's up there,
it's up there.
How are you industrializing AI into the enterprise? How are you redoing your plumb lines across your tech stack, leveraging AI, GenAI, and agentic AI?
Look, I think everything you have just talked about for the last hour or so I kind of smiling going well we do that with Cognizant.
We do that with Cognizant.
We do a little of that with Cognizant. We have 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. When I think about the priorities, first you have to modernize, constantly have to modernize your system. There is always a portion of our investment that is going towards that and you are helping us with that. We will not get off of all of our legacy systems probably in my lifetime, but there is a goal to get there, right. You are constantly having to do that. Second, you are constantly digitizing. 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. 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. Constantly investing, trying to figure out how do we make those investment products stickier. That is all done through technology making it easier for our clients. 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 help us run our data foundation as you just heard Naveen talk about. 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 the fuel for taking the robotics work that we started together eight years ago and now thinking about how do we identify that work. I think there's so much more ahead of us to do.
I will also say though 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.
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. We have about 20 proof of concepts going on right now with generative AI. 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, 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's 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 CEOs then going to come around and say, hey, your tech costs are going up and my revenues haven't kept pace with that. So you're constantly having to evaluate that and we're being very disciplined to make sure that that happens.
Yeah.
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 they are making. In AI, one dimension is the benefits that it serves them or it serves a client like you, or 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.
Right.
How do you.
Yeah, I would say now this is KeyBank's position and I would say, you know, 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, we moved our data to the cloud in 2019. We moved off of Hadoop in 2022 with your help, and moved to Google Cloud. So our data's there, we have the speed. 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.
While you do that, how are you managing change or how are you doing the change management with your workforce?
Yeah, I mean that's a huge investment. We 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. We absolutely have to invest in reskilling our people, whether that be technologists 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.
You know, you have heard this afternoon and in fact you are very aware that Cognizant has spent or pledged about $1 billion of investment into AI over the last couple of years. We are continuing to invest.
we. Plan on taking advantage of that.
We have built, you know, the infrastructure, as you have seen, the AI labs and you know Babak very well. We have more than, you know, 25 PhDs doing constant research, we have 54 patents and we have built these platforms and you know, we are building these industry specific solutions. As a client. As a client. How would you see this? What's your reflection on?
You know, I think one of the things when I first saw Babak, and you all get to meet him in a moment, but when I first saw him and he talked about identifying your enterprise, he did it. One, you can tell he knows what the heck he's talking about, he's brilliant. Two, he did it in a way that the average enterprise user could consume the information. What really sparked my interest was we have about 400 bots running today who have IDs as employees in our system. Right. They are doing tasks every day somewhere in my enterprise. A large amount of them are in our operations team. 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 the intelligent people like Babak and others to help us build from where we are to that next level. How do we make ourselves smarter? I think there's a great opportunity there.
I mean, thinking, talking about agents and bots, last week Jensen at NVIDIA Tech Conference, he was referring to the IT organizations of the enterprises potentially morphing into semi HR roles. It's interesting he said that, he said that, you know, these IT leaders will have to select agents, train agents, manage agents and pay agents like, you know, any HR organization would do. How are you envisioning this? Agent centric.
True.
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 agent? That is not insignificant as you deploy all of this. 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. 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. By the way, you have to have 99.99% availability 24 hours a day, seven days a week.
That has to get smart too.
Right. Any AI conversation is not complete without talking about the risk and the guardrails that one needs to. How is KeyBank managing that? What's your perspective on that?
I think we're learning. Again, I go back to, I think certain industries maybe have an advantage where they're not 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? I think we're trying to walk our way into it without sprinting and getting ahead of those groups as well. We've all got to learn together.
Thank you, Amy. You know what? Since you mentioned Babak, and he knows what he does, here is the deal for you. He's gonna create agents on the fly for KeyBank for a business problem that you're gonna give him.
I'm getting this for free.
Are you getting it for free? Amy, it's always a pleasure talking to you and thank you for the long standing.
Hello everyone, my name is Babak. I am the CTO of AI for Cognizant. My background is in AI. I got into AI in the late 1980s. It's all I've done, all I know, it's all my career wasn't as cool.
As it is today.
Today for a while. And it's, you know, 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. 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. Let's dive right into it. Let me first talk about the investment that we're making into innovation.
There is a process, there is 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. There is a method to this madness. I'm sure you've seen this through my colleagues' presentations up until now. There is 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. I'll talk and I'll demo some of those in a moment. Of course we have a number of AI studios around the world where we showcase these. Sorry, I have to unlock my laptop.
Here.
It's asking for a password. Sorry, just went.
So.
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. 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. What is an agent after all? Is it just the latest reincarnation of AI or LLMs or GenAI, or is it what's real about it? 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. 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 microservices is it representing, what kind of data is it representing? It's engineering, it's customization.
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. You want these agents to work together. That is a multi-agentic system. 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 will 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. Everybody's got their agents now, plus plugging them interoperably into this multi-agency 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. 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 is 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. 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, code coverage and adds unit tests. It's a team that's building a software. That's what we're looking at. Of course that third multi agent system, if set up properly, is beating all of our coding benchmarks.
Okay.
Gartner believes the future is in multi agency. 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, it's out of scope. Go see if there's another agent that can do it for you. You want these agents to be talking to each other. When you do that, you're breaking the silos. When you break the silos, you're reducing costs, you're improving efficiencies.
Okay, so let's enough slides and let's actually build a system here. If we could go to my.
Laptop.
There we go. Okay, 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 identifying this and we can actually use various different entry points to talk to this system. 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. What I want to do is show you the behind the scenes of this and the actual agents. Let's go to our NeuroAI platform. This is the platform that we use to build individual agents, actually identify and scope them. I'll do that right now and then put them together into a multi agent. Before I actually build an agent, let me show you the intranet agent, the one Cognizant Intranet. 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. Once this loads, I will be able to show you.
There we go.
Here is one of our multi-agentic systems. It's rather small, so I'm going to.
Blow it up just a little bit.
I mentioned our intranet. 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. Of course it is human in the loop. Of course it is augmented, but it is growing incrementally and organically. That is how we set it up for our clients. We allow our clients, 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. If I ask it a query such as a life change event, I just had a baby, what do I need to do? I used this on purpose, I showed this to an analyst and they are 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, you know there's some benefit changes. 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. 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. What I'm going to do is I'm going to use agents to help me build an agent. It's a bit meta. We're using agents to build agents.
I have a number of agents that are human in the loop agents that we're going to interact with. Amy's standing there. 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, what the system's going to do is it's going to. This is obviously not implemented at Q1. I don't have the data of KeyBank. It's going to do a 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. 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 mortgage finance decision making. We could do any one of these. Amy, are any one of these interesting for me to build for you, or should I do a different one? Up to you.
I choose.
I choose. Okay. Okay. How about we do SBA loan eligibility and would that.
Yeah.
yeah, 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's nodding her head. I think I'm on the right track here. It's giving us these outcome objectives. You can think of them as KPI. 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 spent a lot of time here going back and forth as they threw like, oh, but this is different here, or 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.
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. Finally, when it's done writing the code, we're going to have some agents build it and that's the last step. 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. We are 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 onto the cloud and running against that. 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. We're going to be able to. This is a rather large one that we're going to use and it's again breaking all the silos. 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. 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 there's a lot of engineering and custom making. 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. 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.
You.
Sam. It. Sa.
Panel. Ravi, you want to come up.
Introduce
Paul, you want to come?
Yeah.
[I'm gonna].
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 healthcare space for many, many years. Dedicated his career to transforming healthcare. 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 way back in 2007 with development and support, custom work. Since 2015, we have been working with Paul and his team on the expansive opportunity we had with TriZetto Facets. Now we are involved in the transformation on the cloud data. Very grateful to you for coming over for the investor day all the way from the West Coast.
Thank you so much.
Pleasure to be here.
Paul, very quickly, you know, 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. You know, I always ask 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 the partnership for such a long period.
Maybe what I'll do is start with the context of where we're trying to go and I think it'll be clearer how the partnership helps us get there and why it's valuable to us. Everything for us starts with our nonprofit mission to create a healthcare system that's worthy of our family and friends and sustainably affordable for everyone. God forbid one of your loved ones needs to access the healthcare 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 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 healthcare 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. 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. 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. We've developed the approach that we want to take to get there.
There is 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 and unless you're truly taking advantage of the latest in what technology makes available. There are certain core things you need to do every day. You need to do this also while you're, you know, the proverbial, you got to be able to change the tires while you're driving kind of notion because we're still processing a lot of claims every day, we're still answering the phone. How do you move from this legacy world to this future world? To me this is where it's just incredibly valuable. Like 15 years ago it was around we started the journey to migrate to fast.
It's 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. What we've structured now is this movement to the cloud.
This is our new version of TriZetto.
Right.
Taking the customization out of the system 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. 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. It is really fundamental to us getting to the vision that we have in mind, really achieving the mission that I described at the beginning.
One of the things you 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? Yeah, I mean we figured out a while ago that it was not 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 two to three times that to really drive the agenda at the level that we want to. To avoid having that put undue short term pressure on our rates, just need more scale to do that. I went out and basically tried to negotiate non profit mergers for about five years.
With other Blue plans.
It's not easy to get that, to get that done. What I realized is that all the Blue plans loved the business case, but always balked at the potential changes in control. It's just a common phenomenon in nonprofit conversations. The idea was, why don't we create this new entity called Stellaris? It's one of the sister companies to Blue Shield, and Ascendiun's the parent of Blue Shield and Stellaris. We'll figure out, like, how do you get the value of a merger and scale without merging?
How can I go to the other nonprofit blues and say you can keep your board, you can keep your CEO, you do not 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. We can do it a lot faster than we otherwise would. A part of what we were doing, and again a part of the reason why this partnership is valuable, is that we are not just trying to get it to perform for Blue Shield, we are creating that platform and that vehicle that allows, that can be multi tenant and multi plan. Yeah, it is pretty exciting.
We are excited also because this is one of those unique opportunities to create a distribution network for our healthcare assets using a Tier 1 strategic partnership of a client. As much as we do it directly, we now find a client to actually take it to other clients, which is fascinating. Paul, one of the other questions which is around in the U.S. for the last couple of years is the healthcare costs in the last 20 years have gone up by 200%. The only two sectors which have significantly gone up on costs over inflation for the last 20 years is education and healthcare. We've used a lot of technology, but it hasn't actually manifested into productivity gains for the sector. 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 healthcare.
It can be and it needs to be. I mean, healthcare 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's unsustainable, it won't last forever, and that's healthcare costs. We simply cannot afford to keep paying more in healthcare 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? Is the public, you know, are the politicians going to come and solve this thing for us in terms of affordability? This is really our obsession. Like the biggest challenge we have with our mission is getting to affordability.
Healthcare 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 the rest of inflation. Macro quality scores do not budge. Macro satisfaction scores naturally do not budge. We just keep throwing more money at it and not getting any better outcomes or output. That is just absolutely negative productivity. 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—a year and a half ago I had my own little sports weekend warrior injury. I went and got an MRI. I went to an orthopedist, I go to the MRI, I get done, they hand me a CD-ROM.
You know, I go to my orthopedist and he hands me, proudly hands me the printed fax that he sent to refer me to a physical therapist. By the way, all these people know who I am. 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 this is.
Investment platform, sometimes
we're a next generation company.
Okay, okay.
You know, we just have so many opportunities to do it. 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. People don't understand, sometimes they jump into healthcare 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. 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. 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. I think folks tend to overlook that. You've seen a lot of technology get thrown at the healthcare 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. There's just, I mean there's opportunities, I think abound, whether it's in ambient dictation for physicians, which we've been using. I mean we've got physicians that are seeing two to three 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 and 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 like 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 eight use cases which include the things I mentioned, real time claims, real time prior authorization, real time calculation, of course, quality scores and care gap interventions, and the list goes on basically. That drives huge administrative and productivity savings. It enables pay for value and the alignment of incentives with physicians. Hospitals and potentially gets to much better quality of care as well.
In fact, on the TriZetto platform, we now have integrated OpenAI interfaces, we have an AI assistant, we have auto adjudication of claims which has gone through significant jump. In fact, I was actually in one of the customer service functions of one of the payers 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 we, which is going to happen in healthcare for sure I think is vertical integration payer providers so that the incentives are aligned. We think it's a unique, big opportunity for transformation for companies like us because you have to integrate the systems of 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, unless that's the case. It can't possibly come like you're not going to have a whole bunch of Kaisers nationally because it's just, it's too expensive and too intense to go out and just buy physician practices. I mean, these are highly paid professionals. They don't tend to stick around. They'll walk with their feet if they're not or, you know, let their feet do the talking. I don't see a whole bunch of like big cons, consolidated ownership of physicians.
You do see pay up, provided.
That's what I'm saying is you have to integrate. You're going to have to have that ability to say, you know, 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. I should be able to just when I walk out of the physician's office, my claims should be settled. I should just be able to do, touch a button and pay whatever I owe in terms of out of pocket. All these things that I talked about before, quality scores, claim settlement, pardon me, 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.
Absolutely. 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. That might actually be a good, good inflection point to change the way the industry works. You know, 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?
I think a great way to be wrong is to make political parts predictions with this administration. You know, I just take this with a massive grain of salt. 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. I think you're seeing that right now in the sense that
will it.
Come back in some other form? Medicare?
Here's the thing, 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. The House basically said we're going to put a placeholder in and save $880 billion in Medicaid expenditures. We're not going to touch Medicare. The Senate, they had to reconcile the bill. Senate did nothing. The Senate was zero and the House was $880 billion. 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 reconciliation, 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. They seem to be based on that, unlikely to touch what people call FMAP, which is the percentage of amount the federal government pays. They're far more likely to be in the $100 billion-$200 billion range in terms of savings rather than $880 billion. Now again, to go back to my first statement, making political predictions is just, I think in this world, I think that's where it stands right now. I think that there's too many, there's too many Republicans that are in states and districts where there's a large number of negative impacts for really big cuts.
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. You know, a guy like that is like, yeah, he's seen this movie before, right. I mean, his whole district is something like close to 70% Medicaid coverage.
Right.
We're really excited.
He's in a Biden plus something district. I look at that and say, I don't see like mass. There's going to be changes
good for technology.
I mean, technology is going to be an enabler for change.
The fact is, yeah, 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. I think the private sector needs the government and the government needs the private sector. I don't see Medicare fee for service saving Medicare from a cost standpoint.
Long term.
That does not mean the Medicare Advantage program does not need to be restructured and changed or there might even be changes in Medicaid. The fact is we, I do not 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 getting shorter term as costs keep going up the way that they are and they all come back to how do you drive improved productivity? You cannot drive improved productivity without the application of technology.
In fact, we are very excited. It's our largest industry vertical. We have the large. We are the largest. We are the largest tech services provider in health care in the United States. $500 billion of claims go through our platforms. Two thirds of the insured population of the United States is on our platform. So we've got 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 question from any one of you to Paul? Yeah,
H. Yeah, yeah.
Did you hear the question?
Yeah, I did hear the question. It was about whether the transparency is going to jumpstart some of this change, right? I sure hope so. That said, I've also watched as entities have actively thwarted. 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. 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 one plan's rates versus another. They sort of intentionally made a complex thing more difficult to track. Ostensibly abided by the transparency requirement. I hope so. I think I would love to see way more transparency. The system is entirely too opaque.
I think it has the potential to have that driving force, if you will. I'm also mindful of how active self interest can undermine it sometimes.
Yeah, but in that example, if we just use the agent that was just.
Shown to us about an hour ago.
We could actually, you know, parse through that complexity pretty quickly.
It also bursts the silos. You know, AI is one of the biggest silo busters.
Yeah.
They sort of also.
Yeah, yeah, I hear you. There are 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 anyway, I won't get into too much technical detail, but it's amazing the creativity that can go into trying to block transparency. I agree with you, artificial intelligence and policy can really help.
I mean even agentification is going to be huge productivity. I mean the number of areas we are thinking we can tap into is by agentifying. I mean there are tens of thousands of people who just process claims in every. So Paul, thank you so much. Thanks for spending time with us. Thank you for coming here all the way from California and we are very excited about this strategic partnership and the ability of Blue Shield of California to take the treasure of platform to other, you know, to other other players and create a network for us.
Thank you again.
It's my pleasure.
Thank you, Ravi.
Thank you.
We're going to cover our markets and geographies. We are primarily going to cover three things. An overview of our market, our performance highlights, and our go forward priorities. I'm going to cover Americas, 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 prior 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. 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 US 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, constant 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 the segment products and resources. This is 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 much faster rate. Historically, as you all probably realized, Cognizant has been heavily indexed towards financial services and healthcare.
Over the last two years we have invested in products and resources and we have accelerated the growth 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 eight quarters. I just want to double click on the performance highlights in the last eight quarters. 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 advisors and partners. Third, while doing [the other two] , we also focused on enhancing our delivery muscles 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 commercial communication and engagement with our clients all the way from CEOs like Paul and Ravi himself. He has done 400-500 meetings in the last seven eight quarters and 40% of those meetings are with CEOs and it's just not at CEO level. We have established high touch engagement at various levels on the client side and with many of you partners, with analysts and advisors. 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. 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, and acceleration of our products and resources, communications, media and tech, highest ever NPS scores. As Ravi said, two years in a row. 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?
We are going to focus on five 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. 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 sub segments 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. Third, we just spoke about TriZetto as a platform. We have platforms in some of our businesses. We have the world's largest claims administration platform in the TriZetto based on our analysis.
We also have the third largest clearinghouse and we have a shared investigator platform for clinical trials. We want to lead into the market with platform-centric solutions and we want to expand these platforms into adjacencies and into global markets. The next large deals. There is elevated activity on large deals in the market primarily driven by two things, the vendor consolidation and cost optimization agenda of our clients. 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 megadeals, which is mixed winning billion dollar plus teams. 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.
We have focused strategy to capitalize this GCC opportunity. I'm quickly going to double click each of these on converting AI mindshare to market share. We have explicitly quantified the market opportunity in three vectors: enabling hyper 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. The second dimension of that playbook is new selling skills. 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. The fourth dimension of that playbook is new partnerships. We have extended our traditional partnership ecosystem to AI natives so that we can leverage their expertise and build joint go to market solutions. This four dimensional AI GPM playbook is already put to use, so we are executing it across all those three vectors of opportunity today. I'm very glad to let you know that we have conquered the first vector in many ways enabling hyper productivity.
We are engaged with almost all our clients, almost all our clients across the markets that we serve and are helping them unlock the trapped productivity in the first vector. We have 1,200 plus active engagements in the second vector, which is industrializing AI. We are having more than 100 plus active conversations as we speak on the third vector, which is agentifying the enterprise. 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 healthcare context or in an insurance context, it has five or six steps, starting from data gathering, data generation, data validation, profiling, applying the networks and all that. There are five or six steps in the process. Historically, clients have outsourced only one or two steps of the underwriting process.
They have kept the remaining four 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. This is a value pool that we never had access to before. This is the value pool that clients are willing to engage in conversations right now as an example. We are having 100 plus such conversations to identify 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 clearing house. Our TriZetto platforms serve two-thirds of US insured population today. We have a clinical trials platform over the last eight quarters or 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 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 our TriZetto platforms. We are also looking at property and casualty insurance space where if our platforms can be customized into that space, the health insurance platforms can be customized. The second thing that we want to do with our platforms is to take them global.
Today our platforms are catered to the U.S. market. Now we are beginning to see the demand for our platforms globally. Almost all seven emirates of UAE have shown interest in TriZetto platforms. We are trying to customize our platforms and build an Arabic wrapper to take our platforms globally. With this strategy we will continue to invest in our platforms and lead with platform centric solutions. You have seen the progress that we are making on the right hand side. We will continue to grow, we've been growing these platforms business. The third thing is the large deals and GCC's large deals, as I said, there is an elevated level of activity. We have done really well and we have done well by doing three or four things. We were laser focused on industry solutions. We were extremely agile. We were extremely agile.
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 toolkit that we have built. We have leveraged our AI productivity 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. 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. Now GCCs. As I said, there is a lot of activity in GCC's market.
Almost every single client of ours either already have a GCC or is contemplating to have one or at least thinking of one, having discussions to have one. We want to address that market, both the clients who already have GCCs and the clients who plan to have GCCs. For the clients who intend to or who are contemplating to have a GCC, we have incubated a global capability center service line within Cognizant and we have launched a catalog of microservices, 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.
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 partner. We started executing on this strategy and we have seen initial results. We have won six deals in the last few quarters and we have more than 20 active conversations with the clients who are planning to set up GCCs. Finally, the fifth priority, focusing on underpenetrated market segments. We have identified four of those: aerospace and defense, energy utilities and oil and gas, communications, and healthcare provider. Aerospace and defense is a complete white space for Cognizant. Completely underrepresented. We did not focus on this value pool ever.
We have invested heavily both organically in building the capability and we have also invested in a strategic acquisition of Belcan. Similarly, energy 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 healthcare provider and communications. Though we serve in these markets and segments today, we are heavily underrepresented. Most of our healthcare business today is on the healthcare payer side and biopharma side, but we are underrepresented in provider. We are investing to accelerate growth in the provider space by focusing on adjacencies like RCM and other channels, and same thing with communications and media.
We were heavily indexed on tech, now we are focusing on to accelerate on the communications and media. Bringing it all together over the last eight quarters we have successfully executed on winning in the market, building trust with the clients, with all the stakeholders, clients, advisors, analysts, partners and enhancing our delivery muzzle that becomes the bedrock of our execution engine. On that bedrock we are going to execute on these five priorities that I outlined and we are confident that on successful execution of this we can continue to deliver the market leading growth and help Cognizant pivot to inner circle while expanding the margins. We are committed to doing that. Thank you. I would request my other colleague Manoj to cover the geography across the ocean.
As you can see,
let me assure you this business is not limping back to growth. Pardon me while I sit down. I sprained my foot last week.
Oops.
My name is Manoj Mehta.
I live in Amsterdam.
I've been with Cognizant for 20 years and you know, 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, right? There is this incumbency of a lot of these European players. That is, you know, 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, right? Europe and EMEA, typically the complicated market, right? We've got over 100 countries. The most important thing when I.
Took over this role six quarters back.
Was focusing our spend. How do we actually focus our spend? How do we focus our SGA in certain key markets? That is what we will talk about, right? I see massive opportunity in Europe as long as we are able to capture the opportunity. The other thing that is very interesting is the macro situation today. While others see uncertainty in Europe, I actually see a lot of opportunity. I actually see a lot of first.
Time outsources coming in.
There are still a lot of Vector 1 deals that Ravi spoke about. 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? I think that's where a lot of our focus has been. The clicker works.
Right?
First is what are we focusing on? Right? I think markets U.K. has traditionally been 40% of our business. I personally believe there will be massive opportunity in continental Europe and the other parts of Western Europe. I think we're focusing very hard in the short to medium term in Nordics, in Germany and certain parts of the Middle East. Right. Also, Middle East, we're seeing certain spaces like healthcare Surya spoke about, because I cannot take TriZetto to Western Europe because of the way European healthcare systems are set up. 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. Invest in Europe, 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, right? 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.
Right?
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 U.K. and I think it's amazing, right? In the last few quarters we've ramped up to over 51,300 associates purely on site. They are helping improve citizen lives in central government, in defense and healthcare. 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 two quarters in the public sector space. Second is we spoke about platforms, right? Think a little bit around how we are getting positioned in Europe. Going back, right? Markets changing up, 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 four or five years now.
ESG Mobility, Mobica, Third era, 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, changed dramatically. The last part is, you know, how if, how do I demonstrate how is it working?
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. 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, right? 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. I think we are seeing a massive uptick in the pipeline.
A large number of big deals coming and almost half of the business is net new deals coming in. Here are three examples of clients we wouldn't have won in the recent past. Right, 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 three days. Our Cognizant positioning into creating that business was massive. Second, Schiphol, I think I live there, I live in Amsterdam, so I think this is home. 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.
Right.
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. I think we brought in a lot of that skills from nearshore which we would not 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. That brings me to my final slide. Right. What is our right to win? That is 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 end to end, our ability to go deep and establish trust in each of the geographies, that we can deliver locally with similar cultures, with data requirements that Europe comes in along with a global delivery approach. I am quite confident about the kind of opportunities we have. Let me end here. I am going to invite Sandra up to stage, but before that, as she will talk about our partnerships, we have a video with one of our partners coming up.
I couldn't be more excited about the.
Powerhouse combination of Cognizant and ServiceNow. At ServiceNow, we emphasize what it means to be elite. That's exactly the partnership we have built over the years. Cognizant is our global elite partner, the highest level of partnership within ServiceNow. This showcases a strong relationship built on trust, the ultimate human currency. We have a common dream to fundamentally revolutionize industries through collaboration, innovation and AI driven automation. Last year we took our partnership to even greater heights. Ravi saw that AI is the opportunity of our generation. It will have a nearly $20 trillion global impact by 2030. It's delivering unparalleled ROI to our customers. For every $1 spent on AI solutions and services, they will generate nearly $5 in value to the global economy. AI is only as good as the data that fuels it.
That's why we applaud Cognizant for being the first partner to bring to market Workflow Data Fabric, a solution that delivers autonomous data orchestration across enterprise systems. Because Cognizant leads by example, they already implemented Data Fabric across 350,000 of.
Their associates for their own business transformation and having more than 70 use cases.
They're enabling our customers to build the data foundation for AI-driven productivity, efficiency, and growth. Cognizant and ServiceNow are working in lockstep to position Workflow Data Fabric as an enabler for AI-powered workflow automation.
We're only just getting started, so let's stay hungry and humble and do our best work right now.
Cognizant and ServiceNow all in.
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 two years ago after 15 years at Gartner as an IT services analyst. Before that I was a sell side analyst, always covering the IT services industry. 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 jumpstart 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. 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. 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 things here. 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, 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 sense incubate and scale framework that Ravi mentioned. Obviously a very important way for us to pivot toward where the demand is coming.
As Bill mentioned in his video, trust and advocacy is so incredibly important with our partner universe because as they advocate for us in the marketplace, it gives us the 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. 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. In 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. From a workforce perspective, the expertise that we have, industry proprietary domain, all of that makes for much better client experiences and client outcomes. That's another advantage or value that we bring to our partner organizations. What have we done over the last two years? 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.
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 offer that Naveen talked about in his presentation and the other hundreds of co developed solutions that we have in the marketplace. 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.
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. What do I mean by that? I'll give you a couple of examples. Microsoft, just a couple of years ago we were number five, number six global system integrator driving Azure consumption revenue. In two years we've been able to go from that mid single digit global system integrator to number two globally and number one in the United States. Of course, you know, migration is a very important strategic growth initiative for Microsoft. 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, healthcare as well as there's some very domain specific as well. 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 are number two when it comes to certifications in data cloud which is obviously very important 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.
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 and what he said. We're a global alliance partner to ServiceNow. What that means is that there are six 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. We're gaining share in ServiceNow and I can tell you that just a couple of years ago we were number 15 when it came to selling ServiceNow licenses in the marketplace. We're now their number one salesperson, sales company, I should say, on that ServiceNow platform. 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. Really making a bigger impact in data and analytics. Last week at NVIDIA we have actually taken this partnership essentially from zero to, we'll 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 eight solutions. One of which was around our healthcare LLM where we're actually addressing some of the things that Paul mentioned around the excess costs that are associated with healthcare.
This Healthcare 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 I mentioned earlier this morning. We are launching our technology startup 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.
You know, 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. Very good, strong performance over the last couple of years. How 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 partnership supported TCB.
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 with $6 billion of partner supported TCB, 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 the GSI.
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. 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. 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. 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 partner 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. I thank you very much for your time. I went over a little bit. Right now I'd like to bring Kathy Diaz onto the stage. Kathy is our Chief People Officer.
She brings a tremendous amount of expertise, leadership in running our 340,000 person organization. Kathy, I'll transfer it over to you.
I have been asked to bring us to the Q & A a bit further. I am going to spend a few minutes with you talking about our talent strategy and our people and then I will invite my good friend Jatin up to talk about our financials and then we will get to Q& A. I also wanted to offer up that I will be in the reception. If anything I touch on, you want to expand on, please catch me. It is great to be here with everybody. I have been here at Cognizant coming up on five years and I have been in the Chief People Officer role for just about two 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. I've known Cognizant for over 20 years as a client and I got to see firsthand the value and the capability that Cognizant brings to its clients. It's one of the things that attracted me to the job to begin with, to see how I can do that at scale. 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, as a people company, you know, talent is our strategic asset. At Cognizant we've really figured out what I call the secret sauce of making that happen. In the last two years, we've made significant progress in our very bold ambition to be an employer of choice. I'm happy to say, and I'll talk a little bit more about what we've done to do just that. It really started with going back and harnessing the deep, 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. That's what puts us ahead. During other periods of technical transformation, we've been able to sense ahead and skill ahead. That's what I'll talk about.
Turning all of that into a strong talent strategy that positions us to win. Win. It's a simple but very powerful combination. You know, we have become a magnet for talent now, and we're ready for the future. You'll hear some of the executive committee talk about the mojo of Cognizant is back. 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 startup together in one company. Cognizant's engagement scores are significantly above global and industry benchmarks. In fact, last year, we gained on our lead ahead of the industry. There's a couple of things about that engagement score that I want to talk about.
In the last two years, we've improved in three 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 and innovate in our company. Learning and growing is in the DNA of this company. 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 in the fact that we actually empower all of our organization at all levels of the company to innovate. 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. This is probably the thing that I'm the most excited about, is that we have the highest return, higher rate in our industry. 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. What's fascinating is we interviewed thousands of them to find out, you know, why did you choose to come back? The answers. We have, you know, 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. 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 mention. Tomorrow we will be announcing that we're on Fortune's most innovative companies list once again. I'll talk a little bit about sort of our future and how we're thinking about the future. You heard all day today or all afternoon how my colleagues are talking about the next wave of transformation and Ravi talking about getting into the winner 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. A couple of examples on the left, and that is how we're evolving roles. If you think about it, an AI ethics expert didn't even exist a few years ago. 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. For example, people in our Cognizant Moment who are in design or experienced people, they are 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 a 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 roles with digital assets. I 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. 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 Learn, 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 My Skills, 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 onto this program. Why is that important? We're able to get people onto projects 60% faster. We're able to have much more efficient pricing models. 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. I'll just touch on a couple of takeaways. One is technology does not drive change alone. Technology and people do.
That is why it is so important to focus on your talent strategy. For us, it is our entrepreneurial culture with our learning strategies, which is unparalleled. I talked about psychological safety. When you take that with customer centricity, it is a key ingredient for innovation. I will just say that this is what has enabled Cognizant through multiple waves of transformation in the past and what will also position us in this new wave. That is the Cognizant difference. With that, I am going to say thank you for your attention time. Please find me in the reception and I am going to invite my good friend Jatin to talk about our financials. Thank you.
Okay.
Thank you.
Yeah, for a CFO, it's a good trade off if you are getting two cocktails faster by sacrificing a tea bread. I hope it is for you too. Okay. Thank you very much for being here. Very good to see some of the familiar faces in this room. 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.
You know, this is what we have really invested in. And this is a 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 charts, you will see a clear positive progression. Our bookings growth is significantly ahead of our revenue growth. Our TCD, both in number terms and value terms, has increased significantly since 2022. And we are running this business with significantly higher book to bill than we used to do in past. So strong bookings and excellent customer retention gets you to the next chart. This tells a story. This tells you a story where we have increased our aggregate revenue growth by 900 basis points across last four quarters of which 500 basis points have come organically. And let me remind you, 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 a time when the industry was either shrinking or sluggish. This is what we have been.
Able to push through all the things.
That we have described since morning. If you see our Q1 guidance either side of the range organically, you will continue to see this progression. If this slide does not tell you about or give you comfort of our progress, probably no other slide would. Even as we have executed on revenue, we have executed on margins. There are two things that we have done in the last two years. The first is the next gen 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 SGN. The second one is what I call 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.
If I leave 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 2024 and Q4 of 2023.
Second.
Which is even more heartening to me as a CFO, it's almost like eating a dessert that.
We grew our.
Revenue between these two 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. That is operational excellence in my mind to shrink the input as you continue to push on the outcome. As a result, as you can see, we delivered 20 basis point higher.
Operating margin.
For 2024 after investing 30 basis points of margin dilution in Belcan, which is a great strategic asset for us. That's not enough. All the work that we did on left side also helped us invest. You know, this is a very nice picture of a balanced portfolio.
Where we have invested.
The first and foremost is AI. You know, the whole sense, incubate and scale model in AI has come to life. It is one big investment we have spoken about.
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. In last two years we have really invested in data, cloud and infrastructure.
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 infrastructure. You can't win it and hence.
That's a great data point.
I'll give you. On the portfolio side, you know, 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 help.
I'll tell you and I'll give you.
A reason for you to add one more which is CMT. You know, 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. I'll give another data point: it's 40% of our top 10 customers' revenue. 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.
You know, so far I have spoken.
About the progress we have made and the portfolio that we have created.
That takes us to the slide that.
Ravi spoke about which is our ambition to get to the winner circle by 2027. I skipped a slide in 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. Ravi spoke about briefly what we will achieve but I will also add how we will achieve. I think it will.
The most crucial for us would be.
To achieve the GenAI opportunity which is in front of us. The IToT opportunity which is in front of us. If we can. You know, 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 five years. You can go back and check. Let's say 2009 to 2014, it was infrastructure services, 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. The numbers will tell you that story. The next few years belong to GenAI as all of us know it. We believe that we have a great story there and capturing that is essential for us to get there. I think we are very well convinced of that. Second is continue to win large skills. Third, which is underpinning all of this, is excellent delivery and execution and customer satisfaction. I think we have done a great job about that in the last two 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 five or six CIOs with whom we are working today on a large scale. I think we have done that. Even as we grow our revenue, we want to expand our operating margin for 2025. We have mentioned 20-40 basis point margin expansion. That I would like to remind you is after absorbing eight months of additional dilution coming out of Belcan. Even if you take, you know, for four months it was 30 basis points. You take 50 basis points. That is a large expansion that we have already committed as part of 2025 guidance range. For outer years we believe we can deliver another 10-30 basis point of margin expansion. There are four levers of which one of them is enabler and I'll come to it in the end.
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.
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. 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. 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. Therefore that whole pyramid optimization is just not a cosplay. 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. The one 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 the last two years we expanded this by two and a half percentage points. Number looks small but you are talking on a base of $20 billion. It's not easy but it will improve. As it improves, our ability to deploy this lever improves. Last, let me talk about cash. You know we are a very healthy business. We can generate 90%-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 dividend, 25% on share buyback and 50% being earmarked for M& A. I have 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 two more data points, one which Ravi referred to. 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 billion as of this morning. We will do $500 million more of share buyback in 2025. This is specific to 2025, otherwise we will 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.
If there are opportunities which are.
On the horizon which make eminent sense for Cognizant, we can always leverage it to go after it. Our balanced capital allocation is built on a foundation of healthy balance sheet where we can take a calculated bet.
Bet if we want to, if we.
Saw a great opportunity in front of us. You know, this is really the summary of our financial roadmap which we believe will create shareholder value as we move forward. Top year revenue growth by 2027, annual adjusted operating margin expansion of 10-30 basis points that supports EPS growth ahead of revenue growth. I want to remind you that for last year years for 2023 and 2024, our EPS growth indeed has been ahead of our revenue growth. We are committing to continue that journey and finally making sure we convert our cash well and we follow 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.
You know there is a great market opportunity in form of Vector 2 and Vector 3 on AI and whole IToT convergence on the other. Cognizant has a clear strategy that you heard since morning. We have 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. That is all I had to say this afternoon. Thank you very much. We will be very happy to take your questions.
All right. Yep.
Rod Bourgeois here with Deep Dive.
Very big picture question.
You have been executing a transformation in.
Talent and culture, which seems one 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, is.
There is 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?
Thanks,
that's a great question. I mean, we are a human capital company. The first thing I did when I came on board is to have employees on my side. Then I had clients on my side and now I'm hoping investors are on my side. 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 presidents of the company, like Surya is. We have 70,000 people who have 10+ years in Cognizant. 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 research infrastructure to get ready at scale at economics, which our clients loved it. We've got back to that. We're hiring 20,000 school graduates. We are 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 comes from entrepreneurial spirit, high on innovation. I mean, I test bedded 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 this park, they show me new innovation ideas, and they feel empowered to go back and tell their managers to invest into it. 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 this 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 tell me two things. Either you have breadth of capability or you have the agility of a small company. On the client services teams, we actually had both. We had breadth of a big company and we had agility of a small company. We were this big, small company which Kathy was mentioning.
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. 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. That culture, I think I am, I mean, it's progressively got to a point where we now have the differentiation, we have the gold standard. I'm going to keep stepping that up. Our Blue Bolt Innovation Initiative. 250,000 ideas written by associates inside the company. More than 50% of them are AI led. 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 two years in a row. I mean, the first year there's a little bit of novelty value for a new CEO. The second day it actually dips. Mine didn't dip. It actually went up both at NPS and on employee satisfaction. I am 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.
It's a journey.
I think I'm pretty close to saying that we've got back to that mojo. I mean, more to do. Always.
Thank you.
Over here in the corner, Ravi Ramsey El-Assal from Barclays.
Thanks for taking my question and thank you for the analyst day. It's been a great deal. 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 structure of pricing remain somewhat static?
You know, it's a great question. You know, when I first wrote about lines of code written by machines in quarter three 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 want to change the model when you get productivity back. So wherever we could, we are managing that re baselining wherever we could. I mean, if I don't do it, somebody else will do it. The challenge with managing re baselining 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 20 $900 million deals and remember, the company was coming back into stabilization, so I had to fight that out to get there. 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.
If I'm securing the contract, then I can add more. That's how we got the 12,000 releases in addition to what we gave away to clients. Clients are already rebaselining and I think we are leading the path and that's why we're winning those deals. 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. Wherever we have been able to, I think we have, we've been able to manage to secure it. Before I do that, you know, 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 2023 and 2024. And we will do the same in 2025 as well. I mean we will go and proactively sole source and create deals. 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 grows. If you have a compelling proposition, it will grow.
Thank you, guys.
Jason Kupferberg from Bank of America. Really appreciate the day.
I was curious just to ask.
About the winner's circle, right. The aspiration to get there. Top three or four out of the.
10, what are maybe the top one or two drivers of making that happen?
Because we heard a lot about Cognizant's differentiation today. 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 do not see any other player who can do that. I am pretty confident. Show me the portfolio, I am going to give you productivity, which is better than what I did before and better than anybody else can do. 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. That is 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. 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 run. That is why the capability set we have to build for the future. We have to be careful about what we choose and go behind it. I am actually super excited about it. The underpinnings of both are the investments we are 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 an AI journey. If I wait for a couple of years, most of the software will have this. I am talking about today and today that is 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.
These are the two 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's 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 two years $50 million deals, $100 million deals. We've put them together on a bid versus dead program. Jatin reviews it every week, I review it every month, the board reviews it in the quarter and we are on track. I am 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 beating my peers and going up. The growth rates could be different depending on the velocity and the swim lanes you activate. In a 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.
Good afternoon. 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 of 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. Thanks.
I think that's true. Your observation is right. More and more things services companies do will actually get productized. As they get productized, we actually look for new frontiers. That's what I'm doing with Vector 3. I mean, you know, look at it. When the cloud happened, when the cloud happened. I was doing investor days then as well and you know, the plumbing to building ratios changed. Everybody said stuff, 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 the trash 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, 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. I actually believe this is only, it's a paradox. It is going to actually create more spend. The more for less formula I truly believe will give us more elasticity. The spend is now going to be not just in technology, it's actually going to be at the intersection of technology and ops. I mean, look, if I have to go back to that example of underwriting, I have a very different profile of capability needed.
You know.
Recently I heard one of the banking institutions talk about writing an IPO with agents. It went from three, four weeks to three 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? 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. 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. I think we have to start to look for new addressable pools. 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. 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.
You know, today 20% of the code is written by machines. There will be more and more and more code written by machines. As that happens, I just think the addressable spend is only going to be increased because technology will be embedded into everything we do. That is the lens we are taking and that is the lens on which we are investing into the future. We see this TAM as a much bigger TAM than how we traditionally saw it. Do we need deep programmers? We would need deep programmers to write the AI algorithms. 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.
It's just the, I mean the way you see it,
you know, I.
Just want to add in short term in, in Vector 2 Ravi covered the Vector 3. 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 Agentforce to do. I'll give you an example. As a CFO, I want to know, you know I remember this opportunity. What happened? Did we collect the cash? Did we pay the vendor? Say easy question, but the moment I say opportunity you go and go to the agent of Salesforce. 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.
You need this multi central coordinator in a multi agentic framework which can talk to each of these individual ecosystem and give you an answer. Even today there is a role of, 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 transforming the experience in the world of AI. That's going to be billions of dollars. We are really looking at the future stack and then starting to think about what the opportunity is.
Good afternoon.
Jim Schneider from Goldman Sachs. Thanks for the great presentations. Since you've been at the helm, Ravi, the turnaround in the financial performance is apparent to most people and certainly to investors. I think as you go forward, maybe talk about, you've been very clear about the areas you're focusing on. 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. Maybe share with us some of the things you're deciding to put to the side or de-emphasize, whether that is certain types of verticals, certain service types or deal size or smaller deals, et cetera.
You know, that's a great question.
Actually, traditional BPO services, which are, say, FNA, ProcurePay, all of them, I wouldn't take them in the traditional way. I would actually take them in the new way of delivering it. Those, I mean, call centers. Let's take call centers. Call centers are up for disruption. I'm so glad we are not in that space. You have to see it with the context that I can go and disrupt it. If there is traditional call center work that comes my way, I will probably, you know, just to run it, I will not take it. If I have to run it and transform it, I will definitely do it. What else? I mean, you know, 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 is 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? It's a good question actually. I have to start to think about. Look, in a low velocity market 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.
Hey guys, thanks.
It's Darrin Peller from Wolfe.
When we think about the winner's circle.
Growth profile obviously depends on the market's growth rate itself. When we first of all consider organic versus inorganic, I know you kind of moved a little quickly through some of those 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, you know, larger base. 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. Maybe just a little bit more on the intended mix in terms of offshore, outside offshore, you know, if you looked at a couple of years.
Thanks guys.
Yeah, our going in hypothesis is really the growth is powered by organic growth. 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. When we say we want to reach winner's circle, 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. That will have an addition of inorganic, but that will not 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 is a three year journey we are talking about.
We are already speaking 20% of the code is coming through something like is coming through AI. This is an evolving world. Difficult to say how much it will come. I think one thing is going to be certain, that every incremental outcome that you are generating, you are going to generate it with less and less human effort than what we are traditionally used to saying. 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. In a high growth discretionary LED scenario it is more on site centric growth and in more cost based growth is essentially through offshore. It depends how each of the year pans out. Again, that's difficult to call out today.
Hi, excuse me.
Hi.
Thank you.
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 as you think about.
As well as the clients adopting solutions.
Do the contract structures have to change?
Y ou know.
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. We haven't actually almost gone to outcome based pricing as an industry. I think we have a unique opportunity, 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. 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. They do not want me to be an engineering partner.
They actually want me to be a partner who can share the benefits of a digital nurse. I think we've got close to that point. 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. Now the next model for TriZetto is to look at spend which is flowing through versus transactions because if you're auto adjudicating claims, you have fewer transactions. 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 cost up.
I'm actually thinking we could be ahead of the curve on that. It is also about how much appetite you have to bet on those kind of models. That's what our platform play is all about. We are actually investing ahead of time on platforms in anticipation that we are going to win business in the future. It takes you a little more on that risk profile as we go forward. 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.
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. I think pricing, you know, pricing will become much more exciting as we go forward and it will be more risk weighted.
Yeah, please go ahead.
Thanks. First of all, a very well laid out, very briefly packed, I mean succinctly packed event. Thank you for that. The question, and this could be either one of you playing ball.
On.
The sole source, the deal incubation. Clearly that is evolving and that's where the TCV is, the profitability. It is a lot of conversational sales, which also means multiple cycles as opposed to advisor orchestrated RFP, which is timelines, time bound, etc. The question is, with that context set, how are you navigating the deal shaping universe with many a times the conversational sales selling is on the shoulders of account managers, including things like GCCs, which you spoke about, which is becoming a second arm as opposed to third party arm. Many times the account managers tend to take a slightly defensive posture to conversational sales because their immediate KRAs are slightly still old tuned.
How are you straddling this, you know, 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.
Sadak, I'll start and I'll request Ravi to add. I just want to talk about the timing when you can get sole source deal done and I think we are in that time. The timing of sole source deal 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 five 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 nowhere 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 onto it saying I will not give it away till somebody cannibalizes it. 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. I think we have to work on the KRAs. I don't think we have fully got there. I'm also seeing a different thing now. Just going back to one 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. 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. Why are we bringing you in? Because they still need an agnostic party to vet it. I mean I've gone to one client with Charlotte where they basically said, look, this is fantastic but let's do an RFP. 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. I think the roles are going to change, they're going to blur when we sole source it.
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.
Hey, thanks for asking today.
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?
Jonathan, thank you for first of all wearing Cognizant jacket. We appreciate it but you know,
next.
Time we should get one for everyone.
Yeah, we'll get one. As you can imagine, I, I, we are, we are in quiet period. I would not comment specifically on the quarter if you are. Okay, I can't comment. Your question was on the Q1 quarter, right? I mean it's just too close for me to make a comment.
It's Puneet from JP Morgan. Jatin, in your presentation you talked about that 50% of cash will be allocated to M&A. Should we expect like 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. What does your current pipeline for M&A look like?
I think Belcan was a big bet and therefore it was very, very, you know, we had to really think through whether we take that bet. I do not think if you look at last five years that was a slide on my deck where we 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. 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 will look at it. I do not 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 do share.
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?
You know that's a great question actually. You know 1.5 million people work in GCCs in India. So it's a fairly sizable market. It's in three areas, engineering, ops and technology. Initially it was technology in ops and it's also engineering. In fact ops is actually moving where technology is.
They're kind of going there.
I think there is a different value proposition there. Which system integrators like ours 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 are a tier one global enterprise, you still have an opportunity to go to those labor markets. But not every company can go in those labor markets and compete. For a period of time of platforms, productivity, tools and everything else. I think the opportunity after the GCC is established is more than the opportunity of establishing the GCC.
Establishing a GCC has the things which Surya spoke about, which is the microservices 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. They are actually building the GCC in my premises where lock, stock and barrel we are taking care of everything. That is not the opportunity I'm excited about. That is the opportunity. That is a good short term opportunity to connect and create the glue. The bigger opportunity is because there is a runway on AI, runway on productivity, runway on automation. We will be better than any, you know, we will be better than our clients who are not. This is not their core business.
They will hold, they will actually ask access to the tooling and that infrastructure which we can prize and 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. I think that 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. That's only going to give me labor arbitrage. What about the technology arbitrage that has to come from us. We want to partner with the long term view of giving the productivity back to them. More GCCs are 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 two, three years. 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 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.
It's an evolving space. We, with a flexible model of how we co-create with our clients, 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.
Over here actually. Louis Miscioscia, Daiwa Capital Markets.
Presentations on AI were really good. I appreciate that on that concept.
On the different waves we've seen.
Over the last 10 or 20 years.
Anytime a new wave comes in and it's big and we can actually say.
This one is pretty, pretty massive.
Given that, you know, we're seeing hundreds.
Of billions of dollars this year, next.
Year coming into the data centers.
Now understand that for this year you have got guidance and I'm really looking for guidance. 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?
You know, 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's, you know, over $100 billion in GPUs last year, $150 billion in 2025. Somebody wants applications and somebody wants solutions. Obviously that seems like it would.
Be, you know, right up your alley for the future.
Absolutely. I think your observation is right. I'm pretty sure, 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 laws. Every six months, every metric on compute on efficiency is doubling every six months. The AI scaling laws have completely beaten the Moore's law. 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 three vector strategy, the first vector is not about additional spend, it's about optimizing existing spend of enterprises. 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. The foundation for that is also going to be a lot of heavy lift. I mean, 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 it.
Will get to innovation pretty soon. In fact, some of the clients who are navigating this are asking for productivity to underwrite the savings to their innovation. That is why we are finding some traction, which is 1,200 projects and all of it. You know, for those bold bets, I mean, you know, I hope the economy, the economic, you know, there is more certainty around the future and the economy and that will, that will happen. When those two vectors, you know, start to accelerate, we are going to go back to the heydays of, you know, the growth which this industry had. That is not far off. I mean, you know, frankly I cannot think about enterprises without AI anymore. I cannot 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.
Thank you.
This 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 it change your capital structure at all?
Look, you know 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. Do we want to be at that point? Absolutely.
I mean the amount of bets we are taking on these platforms, I am bundling the platforms with the services and I am creating a multiplier on the services. We are not monetizing the platforms. At some point of time we have to start to think about monetizing the platforms. We are monetizing the services underneath that. We can monetize the platforms subsequent. Frequently we can, you know, like I spoke about the digital health digital nurse example where we are not an engineering, we are not an engineering partner, we are actually a go to market partner. I am working with one another tech, high tech company where all the.
All.
The digital infrastructure inside the car, you know, we are building for them, which is the digital cockpit and the chassis and all. We are actually getting paid by OEMs for number of cars getting sold as a percentage. We do not 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. It is a good thought to take a go to market in a way that can actually be a trigger for growth. 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 our cash to generate more growth and a flywheel of growth. It is 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 our thank you so much for being a part of this journey of what we are going through and we look forward to your continued feedback. I have actually learned a lot from the questions today to figure out the ways to focus on in the future. We are excited about our journey. I mean we do think we are very confident about being in the winner's circle.