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

Okay. Perfect. I'll start off this next session. My name is Adam Wood, I look after European tech research from Morgan Stanley here in London. It's a great pleasure to welcome Ravi Kumar, the CEO of Cognizant, to London with us. Ravi, thank you so much for taking the time and joining us.

So maybe let me kick things off. I think you took over as CEO of Cognizant January '23. So just coming up to 2 years ago. Could you maybe just remind the audience of some of the changes you've made within Cognizant over that time frame and how those initiatives and those changes have progressed?

Sure. Thank you. Thank you for the opportunity. When I was coming in, one of the things I reflected in Jan of 2023 and I saw Cognizant from outside as a peer and a company, which was for a long period of time, very successful. In the 30-year history of Cognizant, I would say we were in the winner's circle for more than 25 years. So the strength of Cognizant was it sensed what was coming on the way on technology waves over the last few -- every technology wave. It incubated those technologies for downstream innovation. It built the tooling. It built the capability. And it created significant value for clients. So clients were excited about the fact that we could do this ahead and keep them differentiated. Investors loved us because we created a flywheel of opportunities. And of course, our employees loved us because we did cutting-edge work ahead of others. So the changes I made was to pivot back to that heritage, which I believe was the key for differentiation. So we've now put up a leadership team, which kind of cuts across the whole spectrum of capabilities needed for tech services company, all the way tech services to BPO services, to infrastructure services, which is a new capability set, and now engineering services because over the last 35, 40 years, tech services company is focused on enabling businesses. Now there is a unique opportunity to embed technology into core products and services. So that's one change I've made. I took the focus back to India. So we now have a new Chief Operating Officer in India. We have established a leadership team in India. And 2/3 of my workforce is in India. We now have a new CFO. We have a new CHRO. We have had huge presence in health care and financial services. We progressively moved into communications and technology, so we have a new leader for communications and technology. We have bought a company called Belcan, which gave us the engineering capability. And what I've actually done is I'm using that as a beachhead to move into industrial and manufacturing. So I've got a new manufacturing head coming on board. So a whole bunch of changes. In fact, a large portion of our business comes from the United States. I think we are understated in Europe and Asia Pacific. So we established a structure for capturing opportunities in Europe and Asia Pacific. So we have 2 new leaders there. So effectively, I've gone back to the roots of who we are and I put a structure which will allow us to capture those opportunities and seize those opportunities for the market. Very early on, I have called out an investment on AI. We are investing $1 billion on AI. And I think there's a unique opportunity for the tech services industry. And I've kind of created AI labs, which can sense what is coming and then I've catered a structure to industrialize it inside. So I think we're excited about the progress we've made in the last 2 years. I would say it's a phase of stabilization and we adjusted that inflection point of starting to be in the phase of growth.

And so maybe, if you look back at what you've achieved, what's gone well, what's gone badly, I mean, in terms of getting Cognizant back to its roots, do you feel as if that work's done now or is there still work to do?

I mean, quite a bit done. And that's why I said we are at the end of that phase of stabilization. I mean, my attrition rates are at an all-time low. I have 13,000 returners coming back into Cognizant over the last 2 years. My client attrition rate has gone down significantly. I mean, it's nonexistent. Our large deals bookings is on a historic high. We've built a muscle on large deals. Last year, we did 17 large deals, more than $100 million. This year, in the first 3 quarters, we have done 19 large deals and I have a quarter to go. So I'm excited about the fact that we've made all this progress. There is always work in progress. I mean, I'm not -- we have still not capitalized on the opportunities outside of financial services and health care. We have still not capitalized on the opportunities outside of Americas. We have set a structure up, and we're hoping that in the next wave, we're going to see the growth coming in these new areas where we've invested. We have invested in ER&D, which is a new space for us. I mean, we now have a $2 billion portfolio. We are probably the top 5 players in the market with the addition of Belcan. It's an extraordinary opportunity because engineering services is not about building systems for enterprises, enabling businesses. It's actually embedding technology into products in an era where every industry is going to be a tech industry. So only $150 billion -- actually $250 billion has got outsourced so far in engineering services, but the total spend is almost $2 trillion. So we do think there is headroom there. So there is things to do, but we are set for a phase of growth.

That sounds -- I mean we've written a lot on that whole idea of the operations side, the factory, the software coming together in products. I mean, could you -- could we dig in a little bit on that as an opportunity area for you? You've made an acquisition there. Could you talk a little bit more about that business and how you see it?

Yes. I mean engineering services historically was not a big space for tech services companies because tech services companies as enterprises were globalizing, focused on helping enterprises enable it. Engineering now is embedding technology into products. And we are living in the age -- in a golden age of technology where software is the new alchemy. So let me give you an example, let's take automotive. Tech services companies in the past were enabling the business of automotive like building HR systems, building finance systems, building sales systems. Now we have uniquely 2 additional opportunities. You could put technology into the car for the infotainment inside the car. You could actually write code, which is the core, which takes out the internal combustion business to a software business. That is an unlimited opportunity. Embedding technology into medical devices. Belcan, which we bought is embedding technology into the aerospace industry. I mean they do wing design, they embed technology into it. Embedding technology to industrial products. I think there is so much to do, so that's almost an unlimited runway. It's also countercyclical to tech services. Tech services has a different spend pattern and engineering services has a different spend pattern. So now for a $20 billion company Cognizant is, we are in all the 4 vectors of the business: technology services, engineering services, BPO services and infra-led services.

That sounds a great way to both get into new industries and sort of smooth the cycle.

Yes, absolutely. Absolutely. It also gives resilience to the platform because you just have a much bigger spread.

That makes perfect sense. Now you alluded to the big investment, billion investment, in AI and I guess this is for a lot of investors that we see these huge opportunities that we can automate much more with Gen AI than we could with RPA and traditional coding. But there's potentially a risk at the low end of the pyramid, those jobs either get automated or certainly maybe we don't recruit as much as we did. But for you, maybe it's an opportunity to break the link between head count and growth that's been there in the past. How do you see Gen AI as a pro or a con for Cognizant?

So we made very early investments, pretty much like how Cognizant did in every technology wave: invest ahead of the curve and monetize all the opportunities coming on the wave. I will actually put this in 3 broad segments. The first segment is today and now. One of the biggest use cases for generative AI is tech for tech, applying technology on technology. In fact, this is such a mainstream use case that many analysts feel is this sector going to shrink because you want to cannibalize your own self. Remember, every technology wave this question came up. When offshoring happened, we thought this technology sector will -- the tech services sector will shrink, it didn't. It actually grew. When cloud happened, we flipped the model. We've flipped the plumbing-to-building ratios. Plumbing was 70%, building was 30%. The cloud flipped it on its head. We do 30% plumbing, 70% building. And interestingly, the elasticity of spend on technology just made technology create more spend. Right now, as machines write code, and in our earnings last quarter, I spoke about 2 million lines of annualized code written by machines and it is roughly around 13% to 14% of the code, which we write. And in fact, many other companies have also started to code, not in our group, but in the software sector like Alphabet said 20% of their code is written by machines. Your first impression it creates is it takes away your business. The reality is you could use that as a tool to create more opportunities. You could unlock modernization spend. I mean, there is $1 trillion of technology that's sitting on balance sheet, $0.5 trillion is actually spent on addressing that spend every year. You could unlock it because you don't need the tribal knowledge, you have the human capital and you don't need the financial capital needed to unlock it. You can take the backlog off. I mean, some CIOs I've met have actually said, "I want to do more for less. So take the backlog off." So we have used this as a unique opportunity to win more business and increase our wallet share by actually consolidating and taking over portfolios of our peers in the same client base. And if you're ahead of the curve and if you have the tooling and the techniques to do that, you could commit that productivity and get it. But it is going to give you a runway of cannibalizing, but equally creating opportunities to consolidate and do more. So it is the first vector of growth. It's going to have marginal growth because there is cannibalization. And this is an improving technology, which means this number of what -- the machine is writing code is only going to go up as a percentage. Now let's come to the second vector. We do 1,000 projects on Generative AI. Half of them are tech for tech and in the category of writing code. The other half are business related. They're revenue related. They're innovation related. The categories are content aggregation, customer experience, employee experience, content creation -- net new content creation. These are the categories we are seeing projects. Now this you could argue and say, wait a minute, aren't the foundation models generating the output? So what does a tech services company do? The foundation models are generating the output, but that is not business grade. That is not enterprise grade. That is consumer grade. To make it enterprise grade, you have to run the last mile. You have to put the checks on the hallucinations. You have to make it responsible enough. You have to create traceability of it. You have to modernize the data and modernize the cloud underneath it. And more importantly, in recent times, the output coming out of these models is not ready because you need to put the reasoning layers and the cognitive layers to make it move from what they call system 1 technology to system 2 technology, which is you don't take pretrained output. But you take pretrained output and then you take it through a scenario building and a decision support process and a reasoning process. And already, I mean, a lot of these generative AI models are starting to put that reasoning template, but it needs the heavy lift from a system integrator to agentify it. So that opportunity is unique. It is net new. That spend didn't exist. Then the third segment to this, which is the most interesting segment, is how do I take this agentification of all the work we do and take the labor pools, which we didn't address and start to actually agentify it. Let me give you an example. If you are, say, implementing Workday, the spend of $1 on Workday software has $2 to $3 of services for us. That was our total addressable spend. Now imagine if I start to take the spend around it because once I agentify it, I can take onboarding of employees, recruiting, engaging employees. All those labor pools are ready for agentification. So if you take HR software to be set a $20 billion market, services was $40 billion to $50 billion. But the size of HR organizations and the compensation and the salary, the labor pools attached is $250 billion. So the labor market just -- the labor pools, which I can address is much more. If I take another example like Salesforce, right? I mean, Salesforce is a $35 billion company. The services underneath it is probably $70 billion to $100 billion. But imagine the number of things salespeople do around it. They punch in opportunities, they punch in leads, they do forecasts. They do sales compensation. They do reporting. All of that is a $1 trillion. That labor pool is my new addressable spend. So the point I'm making is tech spend of enterprises is no longer the budget I'm looking for. That was the traditional budget I was looking for. The new budget is operations spend of enterprises. Anything below the cost of goods sold is available for the agentification. So in my third category from the first, I'm writing software -- machines are writing software. The second is I'm agentifying it. The third is I'm taking the labor pools, which did not -- wasn't my total addressable spend and I'm actually going to make that an addressable spend for us. So this progression as it goes makes tech services, and at least companies like ours who have invested ahead of the curve, to be the beneficiaries of the process. And I'm keeping engineering services aside. Engineering services is a completely new runway. It's a runway where you are embedding technology into products and it is going to have a different flywheel. So if you put all of this together, AI is going to be a huge beneficiary for IT services companies like us. It will actually differentiate the losers from the winners. But with the framework I just established and the stuff we are doing, we do believe we'll be in the winner's circle.

If we think about those 3 areas, I mean, the one that sounds to me the biggest is that area of you being able to attack the labor pools around Workday and Salesforce.

That takes the longest decision period as well.

Yes. That makes sense. I mean, apart from you being ahead of the curve, is there any other specific advantages for Cognizant to be able to attack those labor pools ahead of other people?

Yes. So let me go back to, again, the history of the company, heritage of the company. We always had 2 categories of firms. There were companies, which were built with the industry domain expertise, and there were companies which were built with technology. Cognizant's birth happened way later than the first wave of outsourcing. The first wave of outsourcing was the Y2K boom. Cognizant was born literally after the Y2K boom. It was born in 1998, just when the Y2K boom was over. So Cognizant was built for the application outsourcing space, where the domain expertise and the technology expertise and the confluence of these two was the strength of the company. So I would believe that strength is now more relevant than ever before. So the ability to tap on to the third pool, which I spoke about, the third category, needs operations strength and industry domain coming with deep engineering. I think we sit at that intersection. And in fact, in places like health care, we have manifested that into a platform play because Cognizant has a platform in health care where we manage health care operations for companies. 2/3 of the insured population in the United States goes through our platforms. So we think that operational knowledge will help us to tap into that third pool because it is a confluence of those 3 things I spoke about.

We could talk about Gen AI for hours, but I'm going to get told off if I don't move on and talk a little bit about macro demand and so on. So maybe if we could just talk a little bit about, I guess, clients are starting to prepare and think about budgets for 2025. In terms of your conversations with customers, what are you hearing from them in terms of how their planning is going?

So I would say at the same time in 2023, we had less visibility into 2024 as much as we have now into 2025. So we have improved significantly since last time. There is an unlock in some areas. I mean, financial services have started to come back. Discretionary spend has started to come back. I mean, we were doing large deals. Discretionary was the challenge. Discretionary has started to come back in financial services with the 2 rate cuts, which have happened, and some of that uncertainty out. I mean, look at it, last year, by this time, we had uncertainty of elections, geopolitical situation, interest rates, inflation. Some of it is gone. The elections is out of -- I mean it's out of our way. Inflation is much more tamed down. Interest rates, we have made good progress. So I would believe the discretionary will start to build up from here. It will be interesting to see in January and February how the budget shape up. But I'm also excited about the fact that budget is only one piece in the puzzle now. There are more things, which are happening beyond the traditional IT budgets. So I'm excited about the fact that it is starting to come back and it's much more stable, but there's more work to do. And I mean, by January or February, we'll start to see more visibility into the year, but it is looking much better than what it was last year.

And that improvement in financial services and discretionary, is that quite U.S.-centric or are you seeing that in other...

I mean, it's more U.S. And I think it will kind of have a ripple effect to other parts of the world. But most of the business exposure is also to the U.S. in a much larger way.

And on that financial services side, I mean, that's been an area of strength for you for a couple of quarters even if we haven't had those green shoots. I mean, have there been things that you've been doing specific at Cognizant to address that market to improve things that are in your hands and...

So in 2023, when I started, we had both market was soft and Cognizant by itself did not take off on financial services. I think we have now established a strong leadership team. We have put in measures to seize those opportunities. Now that the market has started to come back, in fact, spend on generative AI is one of the highest in financial services. They are the ones who are doing the most experimentation. The regulatory -- there's a hope that the regulatory spend will start to go down and that will unlock dollars for innovation, unlock dollars for discretionary spend for future work. So I think it's a combination of the two, which has helped us. I mean we have structured better offerings. We have created a bundle with software-led offerings. We've also expanded into regional banks, which are doing end-to-end IT outsourcing. Fintechs have unlocked more outsourcing than before. I mean, fintechs had a free runway on EBITDA. Now that the cost of capital has gone up, they're starting to look for ways to scale at a more economically viable cost structure, which means they are starting to outsource. So we're seeing a lot more traction in financial services because of this.

And I mean, I think our own CIO polls and actually we had a couple of people from the Morgan Stanley tech department in our Barcelona conference a few weeks ago, they were saying that to date, the Gen AI has been -- the spend has been cannibalistic of other areas of budget. Are you starting to see that?

We're starting to see that get diverted.

Yes, interesting.

In fact, in many places, banks are also starting to think about can I shrink the run and underwrite the savings to the build. I mean, there is a relook at how much you want to spend on the run side to the build side. Can I underwrite those savings so that I can actually generate that momentum? Some banks have started to consolidate as well the provider base, which gives us unique opportunities. In fact, financial services is also the largest sector for mainframes. So if you really look at it, I can show you live a mainframe code, which I can take -- put it into an AI algorithm, and with no human intervention, I could translate that to Python code or an Angular code. And just look at the possibility of taking all of that technology debt and translating that to real value. So there is so much exciting action, which is up there. I mean, the thing is there is still some uncertainty around the geopolitical situation around the world. But if the trajectory of interest rates and the trajectory of inflation continues to go the way it is going, we hope to see more.

Perfect. I'm aware of time, I just thought I'd open it up to the audience. Are there any questions we can take from the floor? Maybe I'll carry on then. Just maybe turning to margins, could you talk a little bit about the levers that you have to manage margins and profitability as you look into '25 and beyond?

Yes. So early on in 2023, we started this process of program called NextGen, where I wanted to take cost out. And that was structural cost below the gross margin, which is primarily SG&A. Now structural cost takeout is always a once-in-a time opportunity. I mean, it doesn't happen every time. And the idea of doing that was to go back to the roots of who we are, take the money out, invest back into the future and that's how we could invest into AI. I also invested $1 billion dollars into ServiceNow. We bought this company called Belcan, I had -- there was margin dilution because of Belcan, so I had to compensate for that. So that was a structural program to do that. So we put this in 3 vectors. First, how much do you put that back into the margins? How much you invest into the future? And how much do you share the productivity because large deals when you do, they have an investment window because the money comes later because there is a productivity improvement plan and you invest upfront on the transition costs and everything else. So we put all 3 into the mix: how much we enable the business, how much we put into the margins and how much we invest into the future. So if you have noticed, since I've come on board, we improved our margin to 15.1% last year. And when I started, it was much lower. And we gave a 20 to 40 basis points increase for 2024. And we bought Belcan, it diluted us, but I've got back to the same number for 2024 as a forecast. We think we can keep the expensive plan of margins for the future, keep the investments going and continue to stay focused on sensing what is coming. Now on gross margins, we did 3 or 4 things. In the last 3 quarters, you would have noticed -- in fact, in the last 2 quarters, we sequentially grew but our head count has gone down. So we grew by 2% sequentially, but our head count went down. Now that is reflective of how operationally we are running, which contributes back to the gross margin, and how much of AI-led productivity we are saving and how much we are sharing with clients. I mean, sharing with clients gives us the right to win. Keeping it back is about how much you can do ahead of your peers so that benefit remains with you. So we are able to actually do more for less and improve the margin. So we have now -- in 2025, we have a tailwind from the NextGen program we have done in 2024 as well as the operational efficiencies and the AI-led productivity and sizing the pyramid, we think we have a runway on it. So I'm aspirationally wanting to keep the expansion on an ongoing basis, but keep an eye on investments in the future so that growth is the driver for the change in -- for the growth in EPS.

Yes. Top line is the most important thing and the investments need to happen to keep that.

So it's a combination of the 3 we're doing.

Yes. Perfect. Appreciate we maybe have time for one last one just on pricing. I guess we've seen cycles before where some competitors have been very aggressive on pricing to win volume. I mean, in terms of what you're seeing competitively and are we starting to see pricing stabilize, improve as discretionary comes back and things improve?

So I mean, right now, the pricing is -- there is very little to look at. In pockets, there is pricing. Like if you look for deep engineering, there is pricing -- you will get a pricing premium. That's also because the talent pool is much smaller. But if you look at pricing in context to traditional work, there isn't so much. In fact, on the contrary, a lot of our clients are looking for productivity to be shared with them because they know that AI is nonlinear. It is not labor linked, it is nonlinear. So I mean, it's hard to say when pricing -- we will get a pricing uplift, I mean, mainstream pricing uplift. We should potentially wait for more discretionary to come back till you see that. But I'm a believer that it will kind of move into an equilibrium when the demand and the supply start to fall in place.

Perfect. Well, we're bumping up against time. So I'll close it there. Again, thank you very much for joining us. Thanks for joining the conversation. Thank you.