ExlService Holdings, Inc. Citi’s 2026 Global TMT Conference

Yeah. EXL, we've been in business for 27 years. Actually this year we complete 20 years of being a public company. We started out as a business process outsourcing company. We made an early pivot in 2006 to move into data analytics. Today we are a data and AI company. I think when we think about the journey over the last few years, the last several years we've been investing in building up our capability around data management and really beefing up our credentials out there, which I think has played out quite nicely.

Now we've started to focus in a lot more on the model. We just acquired a company called iMerit, which allows us to do model evaluation, red teaming, rubric creation, chain of thought reasoning, and start to kind of really play around both with foundational models and frontier models, but also start to bring that same technology and that architecture down to the enterprise clients.

Yeah, so look, the biggest thing that's happening right now is how do you make AI work effectively in the enterprise? What that requires is using some of these new capabilities that are being spawned out by AI and applying that in an enterprise environment. That sounds very simple, but it's not easy. Our approach to that is that we lean in by having a very strong understanding of our client's business. So we go deep into the domain, and we have very strong contextual understanding of our client's business, their workflows, and how they use their customer data, how they think about leveraging capabilities across the enterprise. That's the starting point. The second is, we've got this capability built up around data management, which really allows us to help our clients have a clean data estate that can be usable for AI.

Finally, using AI, when you first apply, the first time you apply the model, the outcome is actually pretty bad, and the quality results are pretty poor. So you have to work on it iteratively to improve the accuracy and bring down the cost of using AI. By bringing together this domain knowledge and contextual understanding of our client's business and workflows, having a mastery over data, and knowing how to correctly apply AI into the workflow, that's what allows us to be successful with our enterprise clients. Our AI services, we track the efficacy of that, and we are at a 94% success rate in terms of enabling AI in the enterprise.

The industry statistic on the same dimension is closer to 30%, which means a lot of clients are trying to use AI, but only 30% of them succeed in terms of actually getting to the business outcome and being able to deliver this at cost and get the ROI associated with that investment.

Yeah. The first thing I would start off with is enabling AI in the enterprise is not really a technology solution that you are trying to build in. It is actually a business problem that you are trying to solve for and be able to get to a business outcome. Frankly, the work starts from the business side first, and most of our relationships are with the CEOs and the COOs and the heads of businesses, and those are the people that are driving this change going forward. Technology is an enabler, and it is a necessary part of making the transformation and the change, but the entire initiative in terms of that transformation is being led by the business. It is not like previous technologies, it is not being led by the technology or the CIO function.

I think that gives us a big edge because our knowledge and understanding of operating workflows and understanding our client's business, that gives us a huge advantage. The second part is our portfolio. Today, 61% of our portfolio comes from what we would categorize as data and AI-led services. That part of the business for us is growing very rapidly. In the second quarter, that grew at 30% year-on-year. So it is a large part of our portfolio, which has got rapid growth and a huge amount of demand associated with work that we do out there. Then finally, our operations management business and our digital operations that we run. When you take a look at total operations, which means it includes the piece where we are embedding AI into the operations, that is growing at 10%.

Frankly, we are seeing a lot of demand on the operations side as well as on the data and AI side, and everything seems to be kind of working well for us. We are also fortunate that we don't have specific client situations or specific geographies or specific types of work that we do that we don't have a grow-over problem. Essentially for us, this is a great time for us and a great position to be in, where we can be adding a lot of value to our clients and continue to build and grow our business.

Yes. What's become really important in the AI era is business outcomes are really important. Having companies that are going to stand behind their commitments and their promises is really important, and just the size and the brand itself is not going to carry the day. Today, we are able to compete very effectively against some of the much larger players, against some of the IT players who have deep relationships for decades with the CIO and with the CDO. But we are able to make a headway out there because of our demonstrated ability to deliver results.