Genpact Limited (G) Earnings Call Transcript & Summary

All right. Let's start day 2 of the conference. Morning, everyone. My name is Puneet Jain. I'm from JPMorgan's Payment Processing and IT Services team. Glad to have here with us BK Kalra, new CEO of Genpact. And Mike, like who's in somewhere very audience, I don't know why. I'm going to ask only margin questions now.

Wonderful. I love that. I love margin.

So the format of this presentation is going to be fireside chat. I'll start with like a few questions, and then we'll open up like the floor for questions from audience. So thank you, BK. Thanks so much for joining us.

Thank you. I appreciate, man. Thank you.

So let's start with like it's been like a few months like into new role like a CEO. Discuss like what will change at Genpact, like you recently talked about 3+1 strategy, explain that to us.

Absolutely. Thank you, Puneet, and thanks so much for having me here. I really appreciate that. Look, I think as I've been with Genpact for a long time, let's just say that, because it's over 2 decades. And therefore, no many nooks and crannies of Genpact. And as I got this opportunity into the new role, clearly new, some of the areas where we need to execute better. And what 3+1 is our Execution Framework. And 3 of those initiatives are client-facing, and 1 of them is facing Genpact. And the 3 client-facing initiatives are, the first one is around partnerships, more focused on technology partners, and how do we engage with them, how do we build data and our own IP on top of partner products. That's the first one. The second one is really engaging into Data-Tech-AI conversations with our clients. Data-Tech-AI is one of these solutions through which we approach the market and it is -- it represents nearly 44%, 45% of our revenues of $4.5 billion, give or take. And increasing our impact in data technology and AI is our second initiative. And the third one is really simplification, and simplifying the organization so that we have far more accountable organization, far more agile organization, and are able to engage with the clients in a far more proactive way. So those are the 3 client-facing initiatives. And the plus 1 is what we call client zero. We ourselves becoming the best credential for the world of AI and GenAI and data, and that's where we are focused on. And in that plus 1, we have already launched 50 use cases, be it in technology, in finance, in procurement, which are more internal facing. And we announced Chief Technology and Transformation Officer, who -- she leads the entire mandate on that. So that's what 3+1 is about.

Got it. No, it makes sense. So let's disaggregate like Data-Tech-AI, like it's like a business, like there is a lot of potential like it has grown at such a high pace. So like data and tech part of Data-Tech-AI, like you've been doing those things for a while. So can you talk about like how large like individual pieces are, if possible, if it's possible to break it out. And then what does it mean with clients trying to embrace AI for your data and tech services.

Yes. So Puneet, we do not break the Data-Tech-AI into the 3 parts. But overall, Data-Tech-AI represents nearly 45% of our revenues. And it grew at a rapid pace and again, coming back to its growth journey. And what it represents is think of when we are delivering, in a CPG industry, as an example, we work in a finite number of sectors, CPG is one of the larger ones or banking or insurance. But in the CPG industry, when you have to think about delivering cloud data solutions for supply chain to make the supply chain far more predictive and proactive for the retailer. So that is an example of a data solution combined with AI, combined with the latest technology is an example of a data tech AI solution. Obviously, as you mentioned, data and technology have been grain of Genpact for a very, very long time. We have, over the last couple of years, more importantly, last year, we started investing in AI as well in a significant way. We invested in a company called Rage Frameworks back in 2017, that was all about AI, and that set us the foundation back in the day, but we have accelerated our investments and therefore, infusing AI in many of our solutions in Data-Tech-AI. I think the second piece I'll say, the second way we approach the market is through digital operations where we run mission-critical processes for our clients, be it supply chain process, like I mentioned, or our finance process or our core operations for a bank or running claim operations for an insurance company. And a lot of our digital operations also starts at tip of the spear with Data-Tech-AI, our data solution or tech solution or AI solution or a combination thereof and then translates to digital operations.

Got it. Got it. You talked about like the infusing AI in clients' processes. So tell us like, like do you add like an AI layer on top of like the current systems, whatever, like the systems of record or software that Genpact employees are using to do transaction processing? So do you add like an AI layer on top of it? Or like the software vendor or you like integrate like AI within the system? Like who's responsible for adding AI layer or AI capabilities into that software.

What we are always attempting to do is always based on a client need. But what we are attempting to do is integrate AI into the business process of the company. So -- and now then there are sometimes client need certain specific use cases. But our approach always is to integrate AI into the business processes that we are running for the client or even if we are not running, but we have deep domain expertise in that space. So if I give you an example of a large life insurance company. So we have deep domain and insurance. And for their close book of business, which they typically do a lot of acquisitions on. So we have inserted our AI and GenAI capabilities in reading or in figuring out what is the product information, what is the pricing information, so that when the due diligence is happening for acquisition of a new block of a book. It is far more easier for our teams and the client's team to do the due diligence or do the acquisition. Similarly, take an example of a large med devices company. And for this med devices company, they have many products in the hospitals. So we manage their field service operations. So calls come into engineers that manage the contact center from hospitals. And now there are service manuals, user manuals, so we have again integrated GenAI into the operations of the -- or the business process of this particular company. So these are the typical ways. Now there are also examples where for a large company, actually a technology company, they wanted to set up an AI center of excellence for their finance operations. And we have set up the responsible AI center of excellence for them. So it's a combination of integrating in the business processes that we run or our clients run where we have deep domain or where the opportunity exists based on client needs to give them the specific use case or setting up centers of excellence.

And why is like the Genpact best positioned to win like to bringing in AI to business processes? I understand like you -- because you've been managing those processes, so you know processes better than most companies. But like IT services companies might say that, hey, we understand this technology. We understand like the client's IT architecture. So like tell us like the relative pros and cons of like a BPO company versus IT services company, bringing in AI to a business process.

Look, I think our thesis and what we see with our clients all the time is unless until technology is all pervasive. Technology is available, whether you be it the current systems or if you want to take technology from Microsoft, OpenAI or from Google or Amazon or Bedrock or Llama, whatever be the models. These are all available. Unless until you understand the business process, the underlying data and have conversations with the right CXOs, technology is the enabler. Technology is not all and all. Technology is there to solve a business problem, okay? And given our genesis has been in running mission-critical business processes and then later, we worked on bringing in data technology, AI, which is more the design and build portion of solutions. We are very well positioned. We see that in our pipeline. And we certainly -- now is there an opportunity for technology companies too, for making [indiscernible] the answer is yes. But we actively see a lot of technology companies actually also wanting to collaborate with us, which we didn't see in the past.

And Speaking of like the -- continuing on that competition theme, like can it also drive like this wave of AI, clients willing to embrace AI which will make them more productive? The business processes can be managed with fewer employees. So can it drive like a wave of in-sourcing clients might in the past, the process might have taken 100 people, now if I can do with 20, I can hire 20 people or I can build like a tool or own a tool. So are you seeing any trends at all that the clients could be looking to do more in-sourcing?

So I'll say three comments, Puneet. First, no, we are not seeing any in-sourcing trend at all. If at all, we are seeing the reverse and more of the clients wanting to engage in standardizing the business process, having right data because unless until you have that AI is not a magic dust that you can just go apply, point number one. Point number two, I think there is a cost side of the equation like the productivity that you're talking about. There's also a value side of the equation in any function that you take, even if you took a finance function, there's a working capital component in there. How do you close the books faster component of value apart from the productivity. If you took off -- think of supply chain on time, in full and how your product is available on the shelf for our CPG. Or if you think of insurance, as I mentioned about how do you pay the claims in an appropriate manner in the timely fashion or underwriting or due diligence and so on and so forth. So there is a cost side of the equation. Yes, which gets a lot of attention. There's also value side of the equation. And a lot of times, we talk to customers, both on the cost side as well as on the value side. And this is early days, but you will see that as the trend of AI and this is not a trend, actually, this is a fundamental shift, a lot more value conversations will also happen. And the last point I'll make in terms of in-sourcing, we have only seen acceleration of journeys that we typically work with large enterprises, many Fortune 500 clients. And we only see acceleration of that. Our conversation even from a productivity standpoint, they want to leverage models like Genpact more and more.

Yes. And how should we think about like outsourcing penetration rates like for your services, like we saw this movie like 8 years ago -- 7, 8 years ago, when RPA was picking up, and that ended up driving more clients to adopt outsourcing, right? And the [indiscernible] penetration rates were low. But how do you -- how should we think about penetration rates within like large clients, like do you have more processes that can be outsourced or going after like a newer clients, new verticals or regions.

So penetration rates continue to be quite low and the total addressable market instead continues to expand with AI and GenAI. You mentioned RPA. With RPA, further expanded. But this is another turn, which is a far more significant technology turn. And we are seeing early signs of expansion again. And to the point that you are making penetration even in more mature markets like finance is still very low. Then you think of supply chain, you think of procurement, you think of core operations of banks, and you think of claims operations or underwriting operations for insurance companies. So even in our chosen verticals, the penetration levels are still dismally low. And therefore, it is a great runway for companies like us and then technology waves like GenAI are further enhancing the total addressable market.

And give us like -- a final question on GenAI like give us like an overall view, like where is like the demand for GenAI solutions? Last year, like there was so much hype, it was still early days. But it seemed like a lot of those projects like are still in pilot or POC stage. Like why is that? Like what is like the constraint to some of those projects moving into production?

So a lot many projects have moved into production for me, point number one, relative to last year. I gave you a few examples that we have moved -- I gave you the field service example or the example for the life insurance company. And there are many, many other examples. Now we also need to bear in mind that many of these sectors that we work in are also regulated sectors. Think of banks, think of insurance companies. And in different processes, they will approach in a different manner because regulators are involved and you need to be -- responsible AI is an integral part of AI. So where the explainability of data should be there or the results should be there, traceability of data needs to be there, what is the security around that, what is -- so all of that is an integral part, and I think the world is learning about how to leverage responsible AI. But we are seeing increased momentum. We are seeing that overall in our conversations, in our pipelines, we never had just over last year, these many conversations on AI.

Are there any questions from audience? All right. I'll keep going then. So let's talk about like the current state of demand environment, like it seems like things like especially as it relates to project-based work or short-term work has been weak for a while now, like clients have been pushing back new projects for a couple of years. They're doing large deals, which is driving growth. But like the short-term work -- short cycle work, that's been weak for almost 2 years now. So is the issue completely cyclical? Or could there be any structural drivers behind that?

No, I don't see any structural issues behind that for me. Look, I think as you -- so first, I'll just respond to the macro question as I am observing it as I talk to many, many clients. You think of where the world is from a geopolitical standpoint. Two years ago, we were not there. And then you think of the interest rate and the inflation environment, the last [ sprint ] was tidy better. But overall, the inflation and the interest rate environment has been reasonably brutal. And then we certainly have elections in U.S., and elections in many parts of the world going on. So I think there is clearly, a macro environment that has possibly restrained that discretionary spending. And -- what -- just coming in now from a Genpact standpoint, as I mentioned in our roughly $4.5 billion revenues, about 70% of our revenues are annuitized because of our long-term contracts. But yes, 30% of our revenues, we need to -- has some dependence, not absolute, has some dependence on this discretionary spend especially in Data-Tech-AI when we design and build these solutions. But overall, I think given the geopolitics and the macro environment, and I think as we progress through the year, possibly things will settle down more.

Understood. And speaking of large deals, like you've been very successful in winning many large deals. So talk to us about the pipeline. Do you see the active -- like the pace of movement like of those deals in your pipeline?