Thank you Sal and thank you CVK for joining us for this session. Vimel shared our point of view. I'm going to go through a few areas. First is just the context we talk about a little bit on what your customer thinking are. How is your offering changing? How's your business model changing? What are some of the competition you expect to come in? And most important, what kind of companies are you willing to buy, looking to buy? A lot of here the people have companies which they're willing to sell to you. Right? So those are some of the areas you want to focus on. Start with both of you were in Davos a few weeks ago and AI truly has become a boardroom conversation there. CVK, you talked about how physical AI is going to be a trillion dollar plus opportunity by 2030 and you're already working on some of those areas. And Sal, you talked about 90% of your top 200 customers already using AI, you're running over 4,500 AI initiators for these customers. Seems like a lot of things are happening. However, when we speak to our clients, be it in the Bay Area, the way they are leaning into AI, almost they're betting the companies on AI. And we talk to customers in regulatory industry, be it BFSI or healthcare and so on, seem they're taking a more cautious, measured approach. They've been hurt by this in the previous waves, right? So you both have been meeting with customers on a regular basis. I know Sal, you've been last two weeks you've been on the road meeting customers. Give us perspective on what are you hearing from your clients? We talked with Salil. What are you hearing from clients? What are the different variations?
So first, thanks for having me and Infosys here. It's great to see so many people here for this event. I think the session that was just presented was incredible because in many ways that's what we see. We a couple of weeks ago shared an investor AI day where we essentially laid out six areas more or less overlapping with the five that were presented here where we see the growth. So what we're seeing from our clients to your point is first, you know, we are working with the Global 2000, so it's a smaller set of companies. They have large, complex tech landscapes and they are going now from not, they've already done the pilots and the proofs, they're into doing scale projects on AI. From what we can see in financial services, those clients we find are the ones who are the most ahead in our industry makeup. And there, as an example, of our large 25 financial services clients, in 15 they've announced an AI partner of choice for services and we are playing that role. What they're doing is for any of their functions, so take things like AML, KYC, look at pricing, look at credit risk, everywhere either we are building agents or they are also doing depending on which foundation model and platform that they're working with. And there's tremendous need for more and more of that work. This morning, for example, I was with a client where they're looking to add literally 500 more people on one of the foundation models if we had skilled and certified people in the good part of that model activity. And the conversation is like that everywhere going on. Now of course, overall it's not a big part of our revenue. So we shared publicly it's just over 5% of our revenue, but that piece which is this, in our case the six value pools, what you showed five, is growing quite massively.
All right, CVK, what about you? What are you hearing from a client? So, you have a slightly different type of customers compared to Infosys as well. A lot more manufacturing. You have a strong engineering practice. You're building as well for customers AI compared to just executing on that.
Yeah. So if I look at industries, tech is a big vertical for us. It's almost 15% of our revenue and we see very strong, intense AI adoption whether it is software development life cycle and mostly around that, right, product development. I think the intensity is very high, maybe 90% plus, very deep usage. And I would think financial services is again a strong area. I mean basically industries which had a lot of data intensity like financial services, healthcare are good. And we think, I mean of course while generally we tend to approach it with more IT use cases, clients seem to be a lot more prioritizing business use cases like fraud detection and algorithmic trading, personalizing experiences, all of that in financial services, seeing good adoption. Healthcare again, it's so data intensive and drug discovery is an area where I think clients have invested in a lot of AI infrastructure. Like if you see the GPU bought by some of these big life sciences companies, all of them are going into drug discovery. But having said that, still even after two years, three years, we don't have any drug which is really got approved, which is an AI discovered drug. That's a reality. A lot of them in our clinical trials and probably maybe in a year or two you'll have something which is coming out. Specifically manufacturing, I think there are strong use cases in the shop floor like vision and computer vision and predictive maintenance, those type of use cases seems to be and they're quite mature and that kind of really lends itself to physical AI and things like that. But within the enterprise layer in manufacturing, I think it's still very lukewarm. That's what I would say.
Got it. And Salil, you talked about the investor day. You were one of the first ones to do an AI focused investor day. I did listen to Nandan's and your keynotes. So very impressive and the kind of growth and traction. You had real case client examples in each of the scenarios. The one question though, when you talk to investors is some of the areas which is going to give you growth, right, the legacy migration area, process automation, all of that is also the ones which are creating compression on the other side. So how do you see what gives you confidence that some of these offerings which are getting compressed, we talked about appdev, UI/UX, versus some of the newer areas, the newer areas will grow much faster to make up for what is getting compressed?
No, I think that's the key point, Par, as you bring up. I think we see clearly and we shared a lot of detail on the areas where we see the growth and the type of growths with examples. And equally we also shared that we see the compression. Now what we have to, and we've not shared publicly the data on what those numbers are, but there are many public estimates that you can see. For example, one of the ones I've seen with some analyst notes is a view that around 1 to 3% revenue compression is what some external analysts seem to be talking about. My own sense is really like how quickly, for example, we at Infosys, how quickly we will pivot into these six areas. So one of the points mentioned in that session before is very much what we are focused on, reskilling and building that capability and that will need some investment. And as you know, investment for like Infosys or services companies is really from the operating line unless we do acquisition. There are no scale acquisitions today on AI services that's available at least. So my sense is if you can pivot fast and if there's one to three is what industry people are saying, if that holds, then we will continue to see growth. And really the test will come, you know, very quickly in April we'll give a guidance, so you will see, the world will see where that looks like at least for this year and then as the next few years come.
So you're confident that the newer services will to large extent make up for some of the compression you're seeing?
So for the purposes of the guidance, there's no sort of specific comment, but what we've shared publicly is financial services and energy utilities, we see both of them growing. Financial services is a lot of it is coming on AI. The rest of it, we'll come back to it. In the medium term, we definitely see that that will hold.
Got it. I wouldn't push you too much. I know you have to, you're the investor calls. CVK, one of the things HCL is known for, like you, in the infrastructure business. You're one of the pioneers in building the infrastructure business. This is a several billion dollar business for you buying software. I know there is so much of push came from the market. Hey, why are you buying software especially legacy software from IBM and other companies? You went leaned into it. That's a huge nonlinear business you have built. You're already $15 billion in revenue right now last quarter run, impressive performance over the last, you know, last 30 plus years. What is the big bet are you taking in the AI wave, right? One of the things I've seen you in the recent Fortune article you spoke about moving into outcome based model. So can you talk us a little bit about the big bet you're taking in operating structure and so on.
So Par, two years ago, I mean we were the first to have invested in AI and I called out very specifically what we think is going to happen. I mean because we truly believed AI is the biggest disruption moment for services industry and we need to reinvent ourselves which means don't be afraid of cannibalizing your revenues. And I said this to the investors, I've said it to all my sales teams. I'm sure a lot of us are telling this to our sales teams, but I've gone a step forward to say that if you don't meet your numbers, I am happy to adjust your numbers as long as that's due to you passing on the AI benefits and delivering to it.
I've never heard in HCL somebody says it's okay to lose.
But that's real, right. I mean I went, I've met every one of our sales person eye to eye and have told him it's okay if you don't meet your numbers due to AI, it's perfectly fine. Because it's very easy to say that we're okay to cannibalize our revenue, all that, but end of the day the salesperson or the whatever the teams, they're very focused on meeting their goals. How do you change their mindset, right? So I think we started with changing the mindset. And whatever assumptions that we had on how it'll play out in software development, in IT operations, in BPO are largely played out. And based on our portfolio, we have kind of come to a conclusion there'll be a 2 to 3% deflation. And HCL Tech is a very different company compared to most IT services firms. One is we're always courageous to challenge the status quo, right? Like we built the largest infrastructure business and my friend Shri Krishna who's here, he was a big part of that whole momentum. So today we are the largest infrastructure services provider in the world, right? Not in terms of revenue which may not really matter because you have data centers and assets, but in terms of devices that we manage, we are the largest. So we can kind of take a bet which is completely unconventional and make it big. And software was another bet, right? And I knew going into it markets will punish us, it'll take us several years to recover from the market sentiments on that. We went all in, we put a lot of energy to really reinvent. And today we have $1.5 billion product business, but more than creating a product business, it has created a product mindset in our company. So the way we led AI is to really build platforms like AI Force is a platform which now we've deployed in 60 clients and lot of our new wins are just completely the differentiation is coming from the platform. So we, I think our hypothesis is to lead with IP, lead with more platform based services and deliver outcomes. Now outcome based is becoming a little difficult to kind of migrate the clients into outcome based. It's very easy, it's relatively easy in BPO to really focus on getting to an outcome based. In software development, even from an input based time and material to a fixed price, that itself has been somewhat challenging. And IT ops is more than outcome based. It's really how do you really drive a platform based delivery and agent take, platform based, human in the loop. I think that's where we are focused on.
And Salil, you think there is going to be a nonlinear between the revenue not directly linked to number of people you're going to employ? Is that going to start to happen in the industry over a period of time?
Industry, I don't know. I think the outcome base is definitely there. So we are seeing, I think some stats also mentioned, we're not seeing that level of percentage on the last deal, but we are seeing significantly more than in the past. So definitely there's outcome based. But what I find is most clients want the outcome base, but the upside is still a little bit capped for, like for Infosys. So I find it's got outcome in it in that the downside is a little bit more protected for the client. So there's a little bit more risk that comes onto us and there's slightly better margin if the execution is good. But you know, typically, at least from the past I've seen, fixed price has always been more difficult to execute because typically you end up sort of taking more commitments. So we'll see how outcome plays out. Today it's not a big percentage of our revenue. So it's not like moving the needle there, but we'll see how it plays. But definitely it'll come in more ways. The other thing which we're already doing again on a smaller footprint, there are like teams where we'll have agent plus human. So there'll be a different agent pricing, there'll be a different human pricing and depending on where we get the agents, like we have our own platform Topaz, if we build agents in that, but we also use third party agents. Our own agents I think will be a bit more nonlinear with third party agents depending on the pricing comes too.
Got it. So the agent pricing, both you build something on ServiceNow versus you have your own Topaz based agents and so on. So coming into these platforms, Vimel talked about competition, right? One, you look at this software companies, most software companies are selling on licenses, subscription based revenue and now they are getting into, hey, I'll charge by number of tickets resolved or not by number of seats, but the actual outcome. And more and more which means that they want to replace the humans who are using their tools, be it Salesforce, you look at ServiceNow, ITSM solutions, all of them are coming into the model. So that's one type of competition. The other kind of competition is customers saying, hey, now appdev is so easy, so can I just do it myself? Can I bring that in inside? And the third is this whole AI native newer companies. We have had Turing come here, they built $300 million revenue in like few years. There are companies like Quantify and several other companies which are AI native services companies which are coming in. How do you see this play out? Maybe start with the software companies because you compete with them. You're partnering with them now. Will you see them as competition?
Okay. Software companies, of course, they have been, if you take the last 10 years, I mean the software SaaS companies had a strong pricing power within the enterprise, right? They kept increasing the prices and that did squeeze out a lot of services kind of spend.
Yeah, whatever, right. So but now I see that pricing power getting diluted for sure, right? Just today I was with a Fortune 100 CIO and where we were doing something on software asset management and we were talking about how can we get to an outcome based model and they were absolutely fine, said maybe don't touch my SAP and Salesforce, all other spend you can come back with a proposition with an outcome based, you can take 30% of the savings from that. So I think today all the SaaS companies are definitely under pressure. Their pricing power is eroding slowly even though many of them are our big partners. But the reality is AI native workflows and applications is where there is going to be some value shifting for sure. And that also means a very meaningful revenue streams for service providers like us because the context is something which we understand very well. Our ability to kind of migrate them, not necessarily migrate the entire SaaS, but even if you can chip away a few workflows and create AI native workflows, that kind of dilutes the pricing power and I think there's going to be some pressure.
You're already starting to see clients okay and so your TAM some level has increased.
Absolutely. I do believe this opens up, I think the TAM between software companies, service providers and AI native frontier companies, all of them are now addressable by everybody. So it's a playing field which is maybe two to 3x or maybe 2x of what services companies had. But how do you really evolve into delivering more vertical specific AI native applications? And I think that's relatively easy. You can create a number of vertical specific applications. So we have an offering called industry specific AI solutions and we're kind of targeting seven or eight workflows within each industry, maybe five or six industries. And they are all IP led. It's all going to be IP led and we will get subscription revenues. So while we are a services company, we think we will have at least 500 million ARR software products in the next 3 years. So that's the direction that we're taking.
Just going to add, I think the addressable market is definitely larger from the points that were mentioned. And what we see there is the edge products are already in play for development with agents that we are building. In fact, one of the things that was shared in that earlier presentation of actual software build, if you look at the current activity of software build, that will compress but the addressable expands because there's this new activity that's showing up. So even, and I think many of the SaaS estates will not disappear, but the pricing power as CVK said is definitely gone because everyone has got a view that they can build at the client side. I mean they can build the largest of the SaaS, even if they don't build anything, they will be able to negotiate better price. And some of the smaller apps, I mean smaller apps, you're already in discussions of building on agent based. And some of the larger apps, SaaS, the functions which are more on the edge, so to speak, so that's already in place. So my sense is the overall addressable market therefore is larger. And what was also mentioned earlier, which even CVK was mentioning, the domain piece is where we have the depth. So as long as we keep that, we have that advantage because to build, you know, most SaaS as you know has been massively customized in the Global 2000. There's no such thing as a standard implementation. And so today when you do some edge replace, a lot of that is domain knowledge which you're going to put into the agent. So I think there's enough activity in there.
And to do all of this, I think great that the time is going to be higher. There are a lot of newer offerings which is, you know, $300, 400 billion or new AI offering which is possible. So these are great, right? But both of you have very large companies and driving change in a large company, it's incredibly hard. I know that skilling is something you've been both investing in, but the structure is very hard. If you look at Accenture, it went through a massive restructuring so that they compress all the horizontal into one easy to service the customer. What are structural changes has to be done in the enterprise? Other one is strong CTOs. You're talking about competing with product company, then you need strong CTOs and able to hire the talent, right? Even if you look at the talent pool, the product companies seem to hire even in global locations like be it Mexico and India, the product company tend to hire from a different pool, services company hire from a different pool. So you don't see that talent diffusion between those two areas as well. So how are you driving the internal change? The opportunity is large.
On the change, you're absolutely right. I think for us, we learned a little bit when we did the change in digital where we started with about 20% then we, most recent statistic we shared was something like 65% digital. And the change that we drove there, not that it's similar, but the approach to change will have some elements. So my experience is it's a huge ship and the change has to be very simple. So we have to find, and as we have done through the six areas we have identified, there are two or three which are absolutely just exploding with growth. Make sure that in each of our areas, industry service lines, that comes through. Second, on the restructuring, we've taken a view of reskilling everyone. We do see, you know, there'll be some dips because the utilization will not hold in that time. At this stage at least, we're not looking at any of the restructuring. And that reskilling gives us huge momentum into the company that people want to do something new. In terms of the quality of talent, my sense is we have our training which is incredible. And so we hire straight from college. You know, we've, our plan for this year, we've done 20,000, next year financially we're doing 20,000. So we will continue with that. And the training is now fully, we do, you know, training without foundation model and then training with foundation model because the people have to learn both sides. So that will be the playbook of the transformation and it is a huge, huge change. So really it's an execution activity. The opportunity doesn't, you know, look, there are pluses and minuses, but it doesn't look like everything is zero, but the execution is where the action is.
Yeah, I think definitely in large organizations this is a formidable challenge. The way I look at it is if you have clarity on what you want to achieve and go about it with a lot of conviction, it can be done. And the biggest thing is the mindset, mindset of the entire organization. So we have a vision which I've stated in many forums and to really double our revenue with half the headcount, right? I would really love for every one of our employees to be a super user of AI and deliver maybe 4x productivity. And that kind of compelling hypothesis has really shaken everyone. I could have very well said same number of people, 4x revenue, but it's quite important to pass on the message that several roles may not exist. So I think it's a mindset change. It really makes everybody to really kind of stand up and think how they can really be a super user of AI, right? It could be in coding. It could be more platform based delivery. And I don't look at us like a $15 billion company. I constantly think of like 10 one half billion dollar companies and how do you really enable and provide the agility, mindset, speed within a smaller cohort? And I think that's starting to show some kind of difference. And if you're very clear what you want to achieve and drive that clarity and don't really make it very prescriptive and really get every team with the objective of how can I deliver 4x more productivity, that I think changes the equation. And it's going to take time but it's already kind of, we can see measurable metrics.
Okay. So it's a lot of skill development, mindset, culture change, then an org structure change is what you're driving. One of the other mention, Vimel mentioned is around consolidation, right? Any industry goes through the chain, you see a consolidation. Do you expect that type of thing play out in the tech services industry the way it is today?
I don't think it's going to consolidate while the popular belief is there's going to be a lot of consolidation.
The customers seem to have lot more power in terms of price negotiation compared to the service providers, right? That's why you start to see this negotiation where 10, 15, I even heard 30% plus.
Okay, you were talking about, I was thinking of industry consolidation. Client consolidation, absolutely, yes. I do think clients are looking for one strategic AI partner who can really, whom they can put everything on and really build a strategic partnership. Two of the large deals that we announced last quarter, we had multiple providers, everything got consolidated with HCL Tech with AI platform.
You're saying the clients will consolidate whom they buy from but not the providers itself.
