Morning, everyone. My name is Puneet. I'm from J.P. Morgan'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 in audience. I don't know why. I'm gonna ask only margin questions now. Wonderful. I love that. But, 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- Thanks ... joining us. I appreciate that. Thank you. So, let's start with, like, it's been, like, a few months, like, into your new job, new role, like a CEO. Discuss, like, what will change at Genpact. Like, you recently talked about three plus one strategy. Yeah. Explain that to us. Absolutely. Thank you, Puneet, and thanks so much for having me here. 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 two decades, and therefore know many nooks and crannies of Genpact. And as I got this opportunity into the new role, clearly knew some of the areas where we need to execute better. And what three plus one is our execution framework, and three of those initiatives are client-facing, and one of them is facing Genpact. The three 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 the solutions through which we approach the market, and it is—it represents nearly 44%-45% of our revenues, or $4,500,000,000, give or take. Increasing our impact in data technology and AI is our second initiative. The third one is really simplification, and simplifying the organization so that we are far more accountable organization, far more agile organization, and are able to engage with the clients in far more proactive way. So those are the three client-facing initiatives, and the plus one 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 one, we have already launched 50 use cases, be it in technology, in finance, in procurement, which are more internal facing, and we announced our Chief Technology and Transformation Officer, who she leads the entire mandate on that. So that's what three plus one is about. Gotcha. 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 high pace. So, like, data and tech, part of Data Tech AI, like, you've been doing those things for a while. Mm-hmm. Can you talk about, like, how large, like, individual pieces are, if possible, if it's possible to break it out? Mm-hmm. And then, what does it mean with clients trying to embrace AI for your data and tech services? Yeah. So, Puneet, we do not break the Data Tech AI into the three 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 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 and AI solution. Obviously, as you mentioned, data and technology have been ingrained in 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- Yep ... where we run mission-critical processes for our clients, be it supply chain process, like I mentioned, or a finance process, or a 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, a data solution or a 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? Like, whatever, like, the systems of record or- Mm-hmm The 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, it's always based on the client need. But what we are attempting to do is integrate AI into the business process of the company. So 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 are deep domain in insurance. And for their closed book of business, which they typically do a lot of acquisitions on. So we have inserted now 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 in to 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 business process of this particular company. These are the typical ways. Now, there are also examples where a large company, actually a technology company, they wanted to set up a AI center of excellence- Yeah ... for their finance operations. And, you know, we have set up the Responsible AI Center of Excellence for them. So it's 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- Yeah -to give them the specific use case or center, setting up centers of excellence. Why is, like, Genpact best positioned to when, like, to bringing 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- Sure -like a BPO company versus IT services company bringing in AI to- Yeah 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, you know, be it the current systems, or if you want to take technology from Microsoft or OpenAI or, you know, from Google or Amazon, on Bedrock or Llama, you know, 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- Mm-hmm ... technology is the enabler. Technology is not be all, end 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 morphed 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 their pitch? 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. Speaking of, like, the continuing on that competition theme- Mm-hmm ... 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 done, can be managed with fewer employees. Mm-hmm. So can it drive, like, a wave of insourcing? 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, 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 insourcing? ... So I'll say three comments, Puneet. First, no, we are not seeing any insourcing 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 the 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 is 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 a CPG or if you think of insurance, as I mentioned, about how do you pay the claims in an appropriate manner and in a 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 a 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. 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. The last point I'll make, in terms of insourcing, we have only seen acceleration of journeys. We typically work with the large enterprises, many Fortune 500 clients, and we only see acceleration of that, of conversation. Even from productivity standpoint, they want to leverage models like Genpact more and more. Yeah. And how should we think about, like, outsourcing penetration rates, like- Mm-hmm ... 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 view was penetration rates were low, but 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, with AI and GenAI. You mentioned RPA. With RPA, further expanded. Yeah. But this is another turn, which is a far more significant technology turn, and we are seeing early, early signs of expansion again. 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, you think of claims operations or underwriting operations for insurance companies. So even in our chosen verticals, the penetration levels are still abysmally 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. Give us, like... final question on GenAI? Okay. Like, give us, like, a overall view, like, where is, like, the demand for GenAI solutions? Last year, like, there was so much hype. Excuse me. It was still early days- Mm-hmm ... 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, Puneet, 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. You know, think of banks, think of insurance companies. And in different processes, you know, they will approach in a different manner, you know, because regulators are involved, and you need to be responsible. Responsible AI is an integral part of AI. So where the explainability of data should be there, you know, or the results should be there, traceability of data needs to be there. What is the security around that? Yeah. 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, you know, overall, in our conversation, in our pipelines, you know, 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. Yeah. 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 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, like, that's been weak for almost two years now. So is it the issue completely cyclical, or could there be any structural drivers behind that? No, I don't see any structural issues behind that, Puneet. Look, I think, so first, I'll just respond to the macro question as I am observing it, as I talk to many, many clients. Now, you think of where the world is from a geopolitics standpoint. Two years ago, we were not there. And then you think of the interest rate and the inflation environment. You know, yes, the last print was a tidy bit better. But overall, the inflation and the interest rate environment has been reasonably brutal. And then we certainly have elections in the 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. Just coming in now from a Genpact standpoint, as I mentioned, in our roughly $4,500,000,000 revenues, about 70% of our revenues are annuitized- Yeah ... because of our long-term contracts. But yes, and 30% of our revenues, you know, we need to con- Mm-hmm has some dependence, not absolute, has some dependence on this discretionary spend, especially in Data-Tech-AI- Yeah - when we design and build these solutions. But overall, I think given the geopolitics and the macro environment, then I think as we progress through the year, possibly things will settle down more. Understood. Speaking of large deals, like you've been very successful in winning many large deals, so talk to us about the pipeline. You see the activity—like the pace of movement, like of those deals in your pipeline. Yeah. Thanks for that. And, our pipeline, across cohorts of deals continues to be at the record level. Even in Q1, we booked, and we announced, 3 large deals. Large deals is anything greater than $50,000,000. They could also be $100,000,000, $200,000,000 dollar deals. And, our pipeline, even after that booking, continues to be fairly strong. You know, at this point in time, again, we are many... many of these conversations, that we are progressing with, with our clients, both on large deals, medium-sized deals, or smaller deals. What's driving this strength in large deals? Not just now, like over the last two years. The cost and productivity, again, a lot of Fortune 500 companies continuing to engage, as they want to harness and standardize their business processes. Clearly, at least a year and a half ago, and I think that continues even today, it was almost a very clear tale of two cities, where discretionary spends were just tightly controlled, and large deals, you know, people wanted to progress much faster. I think that has continued into the conversations as we sit today. Is your pitch, like for cost and productivity, is like you can run that process better, more efficiently, or you can bring like a tool like that... I'm assuming, like, you're winning these deals from clients' in-house operations for the most part. Sometimes in-house operations, sometimes, they themselves haven't even consolidated it. And there are instances when we've, when they have already outsourced to somebody, and, we win it, when that's not a massive portion. But, largely our, our solution, our presentation is around, yes, we can, run and transform your operations much better, with latest technologies, latest, latest data, infusing AI. But also it is not just the cost side of the equation, it is also value side of the equation. How, you know, working capital can be better, how your on time in full can be better, how your claim, where are you losing? Where's the leakage in your claims, payment process? And I think we have developed those data routines, is, is integral part of the solution. Got it. Got it. So let's take a step back. Like, when Genpact went public, like you, most of the work, not most, like large part of work used to be F&A, around F&A. Like then over last 15, 16 years, 17 years, you diversified, like, supply chain, pharmacovigilance, insurance, like you got into other areas. What's next? Like, if we talk to you 5 years from now, what will... like the Genpact service mix, like the- Yeah ... especially the business processes or the, verticals, what will change? It's a great question that you're asking, Puneet. Look, I think where our thesis is when we work with these large enterprises, including Fortune 500 clients, in the sectors that we work with, we want to drive most relevance, and we always call it internally inch wide, mile deep as to how your solutions are mile deep so that you can drive relevance, front to back transformation for your clients. So for a typical CPG company, like you mentioned, we started with finance, then we graduated to sales and to supply chain. Then we graduated to sales and commercial and order management and enabling their sales team. And therefore, we look at how do we enhance their top line growth? How do we enhance their gross margin, and how do we enhance their operating margin? So it is front to back, be it in the banking scenario, be it in the insurance scenario or all the verticals on manufacturing. You know, in each of these operations, we are constantly advancing the agenda. And then, in a very disciplined manner, at defined frequencies, we also see, do we need to expand the verticals? Do you have, like, the right headcount to service—like, the right skill sets within your headcount to service this opportunity, and the right culture to make that pivot? You know, I think it's a great question again, and fundamentally, always an evolution, okay? So today we are about 125,000+ people globally. And whenever we think of the talent, we also think of not just buying the talent but building the talent. Building the talent has been integral part of Genpact for all of its 25 years or more of existence. And when I say building the talent, so over 100,000 of our people, you know, we have an internal training platform called Genome. So over 100,000 people have gone through level one of data and AI training, a number of them are now in level two. We have close to about 40,000+ data scientists, data engineers, AI. They are going through far more advanced level of training. Even top 100 people within the company, including a few people sitting in this room, and me, you know, we are going through a structured, certified, certification program on AI from institutes like MIT or Stanford or others. So I think there is an integral part of build that has been core DNA of Genpact. That's how talent is always... You know, we are very, very proud of the talent that gets harnessed in Genpact. And then you continue to add to that talent as well. So it's a continuous evolution, I would say that. Got it. And so- Next question. Go ahead. Yeah, I mean, what you're describing sounds really compelling, right? You have a big opportunity, very little outsource penetration. At the same time, you trade at, like, 8 times EBITDA, right, and I think part of the reason for that is the fear that AI is a big negative for pricing. You have a headcount-heavy model, right? So does it take to reduce the number of heads, right? And so what do you say to that, and what do you say to AI being this cloud, AI as this cloud over your business? Yeah. So look, I think I'll say it's a great question. I'll tell you, I think yes, 8x EBITDA, I hate that number. You know, and there are two reasons for that. One is exactly what you said, which is, that there is, apprehension out in the marketplace that Gen AI will eat everything up. And I will call it nothing more than that, which is, it is apprehension, okay? When cloud came in, think of cloud. Again, what did cloud do to, the entire world? When cloud came in. Actually, cloud came in in 2002, 2003, took shape in 7, 8, 9, 10. Really took shape in 11, 12. We are sitting, even from that time, 15 years later. 15 years later, no more than 40% of workloads have transitioned to cloud in the world, okay? So yes, we can get caught in many apprehensions. When you mentioned, Puneet, about RPA, when RPA came in, you know, a number of us, series of our companies, that's what we were experiencing, that's what we were articulating, this is what I'm articulating even today. That this is a total addressable market enhancer. But if you go back, again, the many of these took a little bit of a dip before everybody understood as to what it is. So it is nothing more than an apprehension, and I think over a period of time, it'll get proven, point number one. I think the second one, why we have a little bit more gravitational pull on our multiple is, our say-do ratio suffered specifically in 2023. And, I think that is, you know, the execution piece that I mentioned early on, which is the 3+1 framework that we have put in place. And we are, again, regaining and rebuilding our momentum that has been integral part about Genpact, and, it's, it's always been an execution machine, and, I think, we paid a little bit of a heavy price in 2023. What's that ratio? Say-do ratio. what we told the street- Oh. and we did not deliver on that. So how do you plan to like... Like, what changes will need to be made, like, for you to deliver on, like, the targets? Like, Genpact, I think a few years ago, like, you set out, like, the targets, low double-digit revenue growth, slight margin expansion. Is that, like, still a realistic target, one? And then what changes you plan to make in how you guide? And, and we love more disclosures, like your last two quarters, so thanks for that. But other than that, like-... and has anything changed in the way you guide in your guidance mechanism? Look, I think what has changed in our guidance mechanism is I think we are being more prudent as we rebuild the momentum, Puneet. And fundamentally, as I mentioned, you know, I've been part of Genpact for 25 years. Genpact is an execution machine, and I think we are bringing that back, that execution muscle through our 3+1 framework, so that we have again transparently shared with each one of you. And there are, you know, again, more disclosures on metrics that we have also started sharing. And internally, we track a lot more metrics, but they are obviously all laddered up to what we share with the overall in the public domain. I really do feel confident that we will. There isn't any structural issue, and we will be at or above market rates as we progress. And on margin overall trajectory continues. We have increased the margin over a period of time, if you see over the last four, five, six years. So I think that trend will continue. We obviously, as we continue to invest for growth, you know, we will balance those decisions as we go along, but the trend is not changing. Any more questions from audience? Let me ask one more, like, on... So how do you balance, like, the need for growing revenue faster, like investing in the business, growing revenue, with margins, like, or returning capital to shareholders? So talk to us, like, about, like, those different, like... Can you achieve both, grow revenue at above industry average, expand margins, and return capital to shareholders? The simple answer is yes, in a broader time horizon, Puneet, and you have seen that in the past. As we grow our top-line revenue, that automatically provides the operating leverage. Then with GenAI, we are further wanting to become a far more, as Genpact itself, far more efficient organization. And as far as returning capital to shareholders is concerned, I think we have a very clear and stated goal of 50% be in form of dividends or buybacks that we have always maintained. M&A continues to be an integral part of our strategy, but whenever... But we are very disciplined about M&A. In case, take an example, last year or last couple of years, when we didn't do any M&A, we returned more capital back to the shareholders. How should we track progress, like, of that, like, beyond revenue and margins? Or maybe how do you track progress of, like, the changes you are making, 3+1, internally? Like, what metrics do you watch? Where should we see change first before, like, we see re-acceleration in revenue growth? So two-part answer, Puneet. One, internally, we have many lead indicators, we call it. So take an example in three plus one, when we talked about investment in technology partners. Our partner inflows were about 2.5-3X in Q1 relative to the corresponding Q1 last year. Okay? This is kind of internal tracking- Yeah ... you know, that we do. And there are similarly many leading metrics and leading indicators that we have that tell us all of these initiatives that we have put in place, are they working? Are they not working? What tweaks do we need to make? And so on, so forth. I think we have point number two: we have clearly shared with you the laddered metrics, and we'll continue to stay disciplined with that. All right. On that note, we'll wrap it here. Thank you. Thank you so much. Thank you. Thank you, Puneet. Thank you. Appreciate it. Thank you. Thank you, all.