The focus here in Davos continues to be on AI adoption, but more importantly from an India standpoint, what AI is going to do to transform the Indian IT services industry. If last year there were question marks and some amount of gloom and doom around the India IT story and what AI could potentially do as a disruption, today the mood has changed. In fact, Indian IT services companies now talk about AI as being a big tailwind. One of the companies that's at the forefront of saying that, and in fact calling it out independently by way of revenue as well, is HCLTech. In fact, let me just throw some numbers your way. The fastest growing large cap tech services company for the fourth year running reported $148 million in advanced AI revenue, one of the first companies in the Indian IT services pack to do so. CVK, always great to have you join us here in Davos. Thanks very much for your time. You're speaking to me after a very strong performance, not just for the last quarter, but for the year. You continue to be industry leading in terms of growth. How confident do you feel about being able to better that?
Yeah, first of all, thank you Shireen for taking time to talk to us. Of course we are very happy with the performance, but what we are truly excited about is the opportunity that's ahead of us. While AI is a big inflection point in the industry, we've been very proactively looking at how to transform our services without worrying about any potential deflation or cannibalization of existing revenue streams. I think that proactive approach has helped us really land very well with our clients in transforming the existing services. But what's even more exciting is a lot of completely new opportunities. For example, in the tech vertical, there is close to a trillion dollars of capex, some of which is already done, some of it is on the anvil. Every one of these big programs will need significant services in terms of planning out data centers, the professional services, the GPU infrastructure, and the managed services around that. I think that's what we call the AI factory. That's a very big opportunity. It could easily be a billion-dollar revenue stream for us in the coming years. And there are many such revenue streams that we've identified. It's still early days, but we have some head start, and that's why we're calling out our advanced AI revenue.
So let's double down on that. You said that these could potentially be a billion-dollar revenue opportunity for you in the coming years. Could you give me a more definitive timeline? And you also said that you've identified a bunch of these opportunities. What would those be?
Yes. So I started with talking about the AI factory. It's a very small service line within the $150 million, which is about $600 million annualized revenue. It's probably less than $100 million. We think it can get to a billion-dollar revenue stream in three to four years. And similarly, physical AI is again a very big theme. While a lot of things have been talked about in agentic AI and AI in software development operations, physical AI is all about AI's ability to understand, sense, and act with respect to physical objects, whether it's warehouse management, port management, vision, all of that. That's what we call physical AI: robotics plus AI-infused workflows. I think it's well placed into our engineering heritage because we've been working with many companies on their mechatronics and other areas. Now it logically extends itself. Physical AI is actually a trillion-dollar industry by 2030, according to analysts. But if I take the services, the places where we can play, that can also be another billion-dollar opportunity. So I think we are identifying completely new areas that are not where traditional IT services were constantly focused. While existing business will see some deflation, you can grow your wallet share and continue to offset that. These new opportunities are really exciting.
So you know this $145 million revenue number for advanced AI that you've reported, based on what you've just explained to us, what could this number look like a few years down the line? Because it's still very small as a proportion of your overall revenue.
I think we are thinking at least in the next two to three years we should get to $2.5 billion in size on these completely new service lines. These were not existing, not about modernizing existing services through AI. These are completely new discretionary spend areas.
Okay, so $2.5 billion over the next few years. It's an aspiration, but of course we have to see where that goes. You're working toward it. So I want to understand from you how things are also changing from a commercial model point of view, how things are changing when you talk about pricing as you bring more AI into the fold. Between humans and agents, how does the pricing model change?
I think it's still evolving, and there is no one silver bullet as to how you price it. But at a conceptual level, moving all the work to outcome-based engagements is where the value is. Instead of looking at time and material or even output-based, can we focus on an outcome? For example, a simple thing like if you're really focused on a business operation such as employee claim settlement. Someone puts in a claim, it gets reimbursed after a week or so. But everything can be completely automated: the receipt can be read automatically, it can figure out if it's for food or hotel or any other expense, put it in the system, validate it, and the payment can be done the same day or next day. So you're focusing on the end-to-end value chain and on an outcome. If you can commit to a client that you will deliver all their claims within the same day or next day, that takes out so much clutter from the entire system. So I think it's more about outcome-based constructs.
In this pivot and transition to outcome as a service, what does it mean in terms of the kind of capabilities you need to double down on? What does it mean in terms of hiring? And I also want your view on the impact of the labor code and whether this is a one-time impact or we will continue to see some impact as it plays out.
Specifically on the labor code, a significant part of it is a one-time provision. On an ongoing basis, it will have a hit into our cost structures. We called out about 10 to 20 basis points impact on an ongoing basis. Coming to your earlier question on outcome as a service, here it's not just the technology capabilities, not just about agentic AI or infusing AI. It's also about understanding the business process and really reimagining it so that it becomes seamless and truly leverages AI capabilities to deliver a superior experience and much better cycle time. So a good amount of process and business understanding, in addition to technical understanding and capabilities, is what will help.
Speaking of capabilities, will you now be looking more actively at acquisitions to try to bolster the capabilities that you believe will be required in this new world?
Certainly, in areas like physical AI, agentic AI, and some of the AI-led services, we are always on the lookout for either hiring the top talent or acquiring capabilities that will strengthen our overall offering. Both are likely. There are enough things to be done, and this whole space is about speed. How can you get maximum speed in scaling up your AI talent and capabilities? There's really no time limit; it's urgent, and we're always looking at it.
So what happens from a workforce point of view if Indian IT services companies move up the so-called value chain? What does it do to the kinds of people you're going to hire, the specialized workforce you'll perhaps need, and what does it do to entry-level jobs?
I think the emphasis is shifting from quantity to quality. This year, in the nine months, we've hired over 10,000 fresh talent, and we're really focused on more elite engineers who have much higher aptitude, learn much faster, and are ambitious about using these technologies. So we're looking for high-aptitude, elite engineer cadres. That's where there will be a lot more traction.
Let's talk about some of the risks. Global uncertainty and geopolitics continue to be a concern that weighs on investment decisions. But what we've seen happen, not just for you but for the sector at large, is that the deal wins have been very strong for every company. What do you make of that? Is it because we're seeing this pivot and transformation to AI? What do you attribute the strong deal wins to?
I think AI is significantly accelerating the urgency with which our clients and enterprises need to look at what they want to do. Even in traditional services like application development and modernization, if they can significantly reimagine their application landscape using AI, they have to do it as soon as possible. So we are seeing large opportunities where we take over a large application landscape and completely modernize it with an AI-first approach. Those kinds of opportunities are there. In fact, we announced a mega deal with a global apparel retailer where we become the AI technology partner for them in completely modernizing their landscape.
So what are clients asking of you when we talk about outcomes? What are they asking you to do for them with the use of AI?
I think the most common ask is in software engineering: how can you deliver it 30 to 40% more efficiently? There are tools available today, like coding assistants, that help deliver some level of efficiency. But if you look at software development, there are many elements. How can we give them confidence that we deliver value in every part of the software development lifecycle, from requirements to coding to testing to deployment and sustenance? The existing tools don't necessarily address the end-to-end lifecycle. That's where our AI Force 2.0 platform, which we've launched, can underwrite 30% efficiency in the entire software development lifecycle. We feel pretty confident there are very good use cases. Some of the deals we've won are very large, and the key differentiator has been our AI Force 2.0 platform.
So help me understand when we talk about large deals. As you pointed out, we're seeing much more of that. What can we anticipate in terms of deal size and frequency changing in the foreseeable future?
Very large deals tend to be a little more driven by cost optimization and efficiency. But transformative deals, I would think, range from $50 million to $200 million. That's the space if you're focused on G2000 or even G5000 companies. If you want to take over a landscape and fully transform it with AI as the primary driver, that's the kind of deal sizes we should be looking at.
You were talking about coding. How much of the coding within HCLTech is now being done by GenAI?
I would put it somewhere between 25% and 35% of all the development work we do.
