Genpact Limited (G) Earnings Call Transcript & Summary

Thanks, Crystal. Hello, everyone, and good afternoon. We're glad you could join us for this call covering our second quarter results, discussing the period that closed on June 30, 2023. Hopefully you've already had an opportunity to look through the earnings release we put up in the IR area of genpact.com. Joining us today are Tiger Tyagarajan, who serves as our President and CEO, along with Mike Weiner, our Chief Financial Officer. Here's how we'll proceed: Tiger will start with a summary of how we performed and where our strategic initiatives stand; after that, Mike will guide you through the quarter's financial results and share what we're currently thinking regarding the outlook for the entire 2023 year; Tiger will return for a few final comments; and following that, we'll open things up for your questions. We anticipate this call running roughly 60 minutes. A portion of what we cover today constitutes forward-looking statements and carries various risks, uncertainties and other factors that might lead actual outcomes to diverge materially from what those statements suggest. Those risks and uncertainties appear in our press release. Also, on this call we'll be citing specific non-GAAP financial measures, which we feel offer extra insight into how management understands the operating performance of our business. A reconciliation connecting those measures to GAAP is available in the earnings release issued today and posted in the IR area of our website. So with all of that said, I'll hand things over to Tiger.

Thank you, Roger. Good afternoon to all of you, and thanks for being with us on this call covering our second quarter 2023 results. Before I discuss how we performed financially this quarter, I'd like to point out that we carried strong momentum in bookings into the second quarter. At this point, we anticipate bookings growth for the full year 2023 in the range of 25% to 30%, fueled by sizable deals and wins with new logos. That sets us up well for robust top line growth in 2024 and beyond. In addition to an excellent quarter for bookings, our adjusted operating income margin, adjusted diluted EPS, and cash flow from operations all came in above what we had expected. Although cost reduction and digital transformation remain top priorities for our clients, more and more they are asking us to assist in speeding up their data journeys, which have been set off by a wish to take advantage of Gen AI. That lets us bring greater value to them via AI-augmented end-to-end services. To be specific, during the second quarter of 2023, on a constant currency basis, we delivered total revenue of $1.106 billion, which rose 3% compared with a year earlier. Revenue from Data-Tech-AI services reached $501 million, up 3% versus the prior year, while Digital Operation services revenue came to $605 million, an increase of 2% year-over-year. We also posted an adjusted operating income margin of 16.8%, which declined 10 basis points from a year ago, along with adjusted diluted earnings per share of $0.72, a gain of 3% year-over-year. Our top line revenue in the second quarter fell short of what we had anticipated. This mirrors the present environment, in which clients throughout industry verticals keep giving priority to large transformations centered on structural cost reduction and replatforming operations, while simultaneously facing added pressure on discretionary project spending in areas tied to marketing and short cycle advisory work. We additionally experienced certain volume decreases from our high-tech clients as a result of macro headwinds. Because of these near-term difficulties, Data-Tech-AI services, where we design and build solutions that transform our clients' business, rose 3% on a constant currency basis, whereas Digital Operation services, where we digitally transform and run our client operations, increased 2% on a constant currency basis. Given these trends, we now anticipate total revenue for the full year to rise 5.5% to 6.5% year-over-year on a constant currency basis, versus our earlier expectation of 6.5% to 8% growth. Mike will give you more detail on our revised full year outlook. Even with the near-term revenue pressure, demand for our services continues to be strong. The amazing deal momentum we witnessed earlier in the year carried on, as we achieved a new record for bookings in both the second quarter and the first half of the year. Most of our deals are long term in nature, with roughly 70% being annuity based, which shows how resilient our business model is. Win rates during this period were far above historic averages, exceeding 60%. In quarter 2, we signed 6 large deals, all above our total contract value of $50 million, after the 5 deals we signed in quarter 1 of this year. Both figures are above historic levels. We also saw healthy growth in our customer base, bringing on 24 new logos in the quarter, and that included 3 significant deals. With strong new business coming in, our pipeline hit yet another record high, and that includes a number of fresh large deal possibilities. More and more, we're noticing clients want to get their data consolidated, make it higher quality, and then migrate and orchestrate it in the cloud. That sets them up to take advantage of Gen AI, large language models, Predictive AI and machine learning so they can deliver much stronger business offerings. With our record bookings so far this year and a strong pipeline, we now anticipate bookings growth for full year 2023 of 25% to 30%, which is above the $3.9 billion we saw last year. We haven't previously provided a bookings outlook, but because of the steady strength we're observing, we felt it was important to share one now, and it reflects how clients are approaching positioning themselves to use Gen AI going forward. Let me give you some detail on the 6 large deals we signed this quarter. For a big global insurance company, we'll handle all of their technology — infrastructure, applications and platforms — as we move their data to the cloud and bring together all their disparate systems and processes from acquisitions. For one of the biggest global technology platform providers serving financial institutions, we'll operate and transform their deposits, lending, collections, fraud chargebacks and fraud alert management operations. The entire contract uses transaction-based pricing and will be a genuine win-win, since over time we'll apply Gen AI and other digital technologies to run their operations. Our domain depth is what won here; we're partnering with an e-commerce company to run all of their corporate technology security operations, financial accounting and customer care services. Our goal is to modernize the technology apps, shift them to the cloud and dramatically enhance customer experience. The endgame is to build the capability to use Gen AI to run these services; we broadened our relationship with a global food company to standardize and transform their finance operations in EMEA, replicating how we executed the highly successful North America journey. The next goal here is to use Gen AI and predictive analytics from all this streamlined data to drive competitive advantage in their markets; and lastly, for a large industrial client, we'll apply digital technologies, advanced analytics and Gen AI to deliver real-time critical decision insights that grow their business, cut costs and improve cash flow; we also expanded our relationship with a global financial institution to help build and launch an all-digital savings account option for their customers. Our experienced team, our banking experts and digital technologists combined to design and build the front-end user interface as well as customer service, fraud detection and other back-office functions, which we now run. During the quarter, we kept making great progress on our 5 strategic initiatives. To start, priority account revenue rose 2% compared with the same quarter last year, making up roughly 62% of all revenue. The money we've put into these customers is delivering returns, since about 70% of bookings in the first half came from priority accounts, and we still anticipate this portfolio will outpace the overall company growth rate over the long run. Next, we keep strengthening ties with the cloud technology companies alongside which we co-innovate and develop joint IP solutions. As an illustration, together with o9 solutions, we introduced a supply chain as a service product that draws on Gen AI and assists businesses in dealing with persistent supply chain disruption. This offering delivers real-time scenario planning, enabling clients to lower supply chain expenses, remove surplus inventory and generate top line growth. Thanks to our fresh collaboration with Microsoft, Genpact's worldwide talent can tap into Microsoft's Azure OpenAI service, allowing us to create and roll out Gen AI solutions woven into our services; alongside Google Cloud, we are assembling a Gen AI practice team to speed up cloud-based AI solution deployment for enterprises throughout our selected verticals, with especially strong emphasis on financial services. Working hand in hand with AWS, we are developing and preparing to launch a Gen AI-driven regulatory reporting solution for a major global pharma company.

Our collaboration with ServiceNow keeps getting stronger as we deliver extensive domain expertise and process know-how, which enables ServiceNow to become the preferred workflow across many buying centers beyond the IT department. Next, we keep putting money into additional operating centers located in Tier 3 Indian cities, which gives us access to bigger and more varied talent pools; during July, we launched our third new facility this year. Then, we're experiencing strong momentum in our shift toward commercial models not based on FTEs, including pricing tied to transactions and pricing tied to outcomes. Such models currently account for 16% of our revenues. Even more significant, one-third of our bookings in the first half came from non-FTE pricing, and we're now confident that we'll reach our initial target of 20% revenue penetration considerably ahead of 2026. Greater adoption of our AI-driven solutions has contributed to this as well. Lastly, our recent spending on our large deal team is producing excellent outcomes in both bookings and pipeline. As anticipated, our attrition has leveled off and now stands at 25% for Q2, much lower than 38% recorded during the equivalent period a year ago. When we adjust for involuntary attrition and staff with under 3 months of tenure, our attrition figure dropped to just 20%. Allow me to take a few minutes now to discuss our methodical strategy for applying Gen AI throughout our operations. As I mentioned during the previous quarter, our AI efforts began over 5 years ago, and from that point onward, we've invested in, built, and honed our AI capabilities with offerings suited to every one of our services and industries; we've directed our resources and Gen AI initiatives across 3 main areas: first, we're applying Gen AI to shake up areas where our penetration has been lower and that remain wide open for fresh service models. We refer to this as our offense strategy. Strong illustrations of these services encompass customer care, FP&A, and sales and commercial digital marketing support. This should let us capture market share and fuel growth. Second, we're focusing on services where we're already seen as a leader, like financial accounting, financial crimes and risk services, and supply chain services, where embedding Gen AI can serve as a catalyst for step function improvements in outcomes that go past mere productivity. And third, we're quickly implementing Gen AI inside our own organization in functions including HR, training, knowledge management, and internal software coding; this should boost our margins and generate use cases for our clients. Let me illustrate this with several examples. For one of the biggest worldwide consumer brand companies, we've transformed their revenue forecasting process, using AI and machine learning models at the SKU level that dramatically raised forecast accuracy from a 70% range to a 90% range while simultaneously reducing cycle time from weeks down to minutes. For a global automotive manufacturer, we're leveraging Gen AI to collect and condense competitive product features in real time, fostering agility in how they respond to the market. When it comes to a worldwide insurer whose household-goods claims operation we handle from start to finish, Gen AI is what we're applying to gather and examine product and pricing details, so that the pricing behind claims reimbursements gets determined more precisely, which means settlements arrive quicker and are more accurate. At a digital financial institution, we're applying Gen AI to pin down what suspicious keywords and customer transaction notes actually signify, which cuts down on false positive alerts tied to potentially fraudulent transactions within our KYC and AML offerings. At a worldwide media and entertainment firm, customer care agents get help from Gen AI in swiftly settling customer disputes, using ideal responses generated by examining online chat data that reads customer sentiment in real time; for a worldwide media and entertainment firm, customer care agents get help from Gen AI in swiftly settling customer disputes, using ideal responses generated by examining online chat data that reads customer sentiment in real time. At a worldwide medical devices firm, the procurement team was given a Gen AI engine delivering real-time answers on questions about contract clauses and payment terms, so vendor disputes get addressed with suggested actions. At a big Japanese technology conglomerate, we handle charging and translating of customer e-mails for fast replies, which lifts customer satisfaction along with sales. Though these remain early days, it thrills me that over 60 distinct Gen AI solutions exist, whether being piloted with clients or used in-house. Those have produced 500-plus client conversations spanning verticals, aimed at building a Gen AI strategic roadmap for each of them. Our belief is that we hold a unique position to craft frameworks and playbooks for clients via 5 5GL large language models combined with client-specific data and industry domain data, thanks to how deeply we grasp the domain and the data. A further edge comes from our long-standing emphasis on comprehending processes from end to end and delivering outcomes; that lets us join forces with clients on deployment, change management and adoption of these fresh AI solutions. All this has swiftly generated numerous new deal inflows with Gen AI embedded, unlocking fresh possibilities for long-term growth and margin expansion. As I've noted previously, every enterprise struggles with getting clean data and orchestrating data into the cloud so AI models and large language models can be leveraged. Our view is that this will grow our total addressable market, just as each technology wave before it did. Across the coming 3 years, we intend to put in roughly $600 million, through both organic and inorganic means, to keep expanding our AI capabilities. That covers investment in our own innovation R&D teams, client co-innovation programs, data tech and AI skills training and building deep expert groups, plus acquisitions centered on data analytics and IP and frameworks for using data models. With that, I'll hand the call over to Mike.

Thank you, Tiger. Good afternoon to all of you. In today's session, we're going to walk through the results for our second quarter, and after that we'll share our most current view of the financial outlook for the full year 2023. Revenue in total came in at $1.106 billion, which is a 2% rise compared with a year ago, or 3% when measured on a constant currency basis. Revenue from Data-Tech-AI services, accounting for 45% of the total, was up 2% versus the prior year, or 3% in constant currency terms, mainly fueled by continued demand for supply chain offerings and by our work automating the core finance and accounting operations of clients. That result fell short of what we had anticipated, owing to weaker short-cycle discretionary spending on technology, mostly within our financial services vertical. Digital operations services revenue, representing 55% of our total, grew 1% year-over-year, or 2% in constant currency, chiefly because of deal ramps tied to existing and recently won business, partly offset by volume declines among our high-tech accounts. We anticipate that digital operations will perform better in the back half of the year, linked to significant deal ramps from the large bookings Tiger mentioned in his earlier comments. Looking at verticals, financial services rose 4% compared with a year ago, mostly from insurance client deal ramps and sustained strong appetite for our Digital Solutions, partly offset by reduced discretionary project spending on legacy technology by current clients. Consumer and Health care fell 1% year-over-year, mainly because of the lengthening large deal cycles we observed in last year's second half, along with the recent divestiture of businesses we had previously classified as held for sale. That decline was partially offset by demand for our tech-enabled finance and accounting process improvement solutions. Hi-Tech and manufacturing was up 2%, primarily from supply chain engagements, ramp-ups and new logo wins. Partly offsetting that was the effect of lower volumes in Hi-Tech accounts, which I referenced earlier. Over the 12-month period that ended June 30, 2023, we raised the count of client relationships generating annual revenue above $5 million from $154 million to $180 million. Client revenues above $25 million grew from $34 million to $38 million, while clients above $100 million went from 3 to 6. Adjusted operating income margin stood at 16.8%, a decline of 10 basis points versus a year ago and a gain of 40 basis points quarter over quarter, thanks to stronger gross margin and operational efficiencies. Let me remind you that our second quarter results a year ago benefited from classifying a nonstrategic asset as held for sale and did not include a $39 million restructuring charge tied to steps we took to lower our run rate cost basis. Gross margin in the second quarter widened 90 basis points year-over-year to 35.3%, largely from revenue mix, operational leverage and the absence of the restructuring charge that was partly reflected in last year's cost of goods sold. SG&A as a percentage of revenue improved 60 basis points year-over-year to 20.8%, since the absence of the prior year restructuring charge more than offset greater investment in sales and marketing during the second quarter of 2023. Our adjusted earnings per share came in at $0.72, which is a 3% rise compared to the same time a year ago, when it stood at $0.70 in last year's second quarter. The $0.02 gain came mostly from stronger adjusted operating income, plus a favorable effect of $0.01 from fewer shares outstanding. We saw an effective tax rate of 22.7%, which is lower than last year's 24.8%, mainly because the second quarter of 2023 had a bigger share of discretionary tax benefits than the prior year. In the quarter, cash generated from operations reached $171 million, compared with $102 million in the equivalent period a year earlier. That improvement stemmed largely from sequential gains in our DSOs during the second quarter of 2023, in contrast to an increase in the same period last year. Looking year over year, our DSOs got better by 2 days, reaching 82 days; we still anticipate DSOs staying within the low 80-day range through the rest of the year. Cash and cash equivalents came to $491 million, versus $552 million when the first quarter of 2023 ended, mostly because we returned $145 million to shareholders. Our net debt-to-EBITDA ratio across the trailing 4 quarters stood at 1.3x. Thanks to our undrawn debt capacity and the cash balances we hold, we still have plenty of liquidity to chase growth opportunities and carry out our capital allocation strategy, which covers reinvesting in our businesses, strategic capability acquisitions, and giving capital back to shareholders. We still expect our net debt-to-EBITDA ratio to stay within our preferred 1x to 2x range. In the quarter, we kept executing our share repurchase program, buying back roughly 3.2 million shares at a total cost of $120 million, with an average price per share of $37.68. To date, we have repurchased $150 million of our shares, which matches what we set out for the full year of 2023; through this activity and our projected full year dividend, we will return 50% of our expected operating cash flow. Capital expenditures as a percentage of revenue was about 1.4%; we expect a greater level of investment activity in the second half of the year tied to large new deal wins and to opening new operational centers in Tier 3 cities. Now let me bring you up to date on our full year outlook. As Tiger mentioned earlier, clients have grown more cautious about growth when it comes to discretionary spending, since they are focused on their cost-based agendas, and that affects our short-cycle advisory project work. Meanwhile, they are putting priority on large transformational deals; this dynamic led to less near-term revenue because bookings mix has tilted toward large deals whose revenue is recognized across a multiyear period. Consequently, we now expect total revenue in the range of $4.59 billion to $4.64 billion, which represents year-over-year growth of 5% to 6%, or 5.5% to 6.5% on a constant currency basis. Our projection for the adjusted operating income margin across the entire year remains at about 16.8%, which factors in AI-related investments consistent with our approach of achieving margin growth more rapidly than in past periods. Because a number of our sizable recent bookings include onshore delivery at the outset, we still anticipate that gross margin for the whole of 2023 will be roughly level with or marginally below what we saw in 2022. For the entirety of 2023, we continue to anticipate an effective tax rate toward the upper portion of the 24% to 25% band. In light of this revised forecast, our expectation for adjusted earnings per share across the full 2023 year is now somewhere between $2.91 and $2.94, which equates to growth of 6% to 7% versus the prior year. That figure incorporates a favorable effect of $0.04 per share stemming from share repurchases made so far this year. Allow me to bring you up to date on how we're viewing the cadence for revenue and adjusted operating income in the latter six months of the year. Owing to ramp activity on our recent large bookings, we anticipate building as the year progresses, and with simpler comparisons ahead, we foresee revenue growth measured year over year in the back half coming in a bit above what we see in the front half. As a result, we look for quarter-over-quarter expansion in the mid-single-digit range for Q3, widening to high single digits in Q4; meanwhile, our adjusted operating income margin should now rise somewhat as sequential revenue gains are accompanied by our absorbing greater investment amounts during the back half. Finally, we still anticipate cash flow from operations for the whole year of roughly $500 million. As Tiger mentioned previously, in view of record bookings so far this year and a strong pipeline, we look for bookings across full year 2023 to increase 25% to 30% compared with the $3.9 billion posted last year. With that growth expected, we presently foresee a return to double-digit organic top line growth during 2024. Having said that, I'll hand the call back to Tiger.

Thanks, Mike. Even as we navigate what's happening with this tough macro backdrop, our confidence stays high that we can deliver organic revenue growth of 10%-plus along with adjusted operating income margin expansion, and do so more quickly than we have historically, all the way through 2026. There are a couple of developments from our first half bookings that I find really exciting and want to highlight. Technology bookings have risen 80% year-to-date, and the pipeline for technology services deals looks strong. That demonstrates how much clients want us standing beside them as a tech partner—one that grasps what drives business outcomes. The second exciting development: 51% of the deals we've signed have data analytics, tech and AI built into the solution, which makes plain the strength in domain and data-led work that gives us a distinctive position in the market. As clients push for more productivity out of their tech stack, we're seeing chances to apply Gen AI for writing code, optimizing how resources are allocated, troubleshooting systems, assisting with network configuration, and also analyzing enormous volumes of information to surface unique insights that meaningfully improve decision-making. In our view, that widens the total market available to us. It's obvious that the chance to pick up new skills in digital and Generative AI, and to work somewhere recognized for nurturing an innovative culture, is what helps us bring in and keep excellent talent. Sitting at the center of what our Gen AI offering promises is a foundational team of deeply skilled data scientists, domain experts and engineers—the people who form our AI center of excellence. Under our data bridge certification program, we've put more than 70,000 employees worldwide through contextual data literacy training across the last 3 years. That positions us well for our Gen AI journey, and we recently kicked off a new AI training program that right now has over 20,000 enrollments, with 12,000 people in our workforce having finished it. On top of that, we've trained roughly 10,000 team members in prompt engineering. While we're facing certain near-term pressures tied mainly to discretionary spending, the future ahead of us is still very bright. Our record year-to-date bookings, together with a quality pipeline that keeps growing, leave us well positioned to return to top line growth of at least low double-digits for 2024. With that, I'll hand the call back to Roger.

Thanks, Tiger. At this point we want to turn the call over to your questions. Crystal, would you mind giving everyone the instructions?

Let me start with the revenue revision. I'd like to understand the revenue revision and perhaps how it breaks down between the decline in short-cycle work and the lower volume you experienced. Also, in your second half outlook, are you factoring in any rebound in either of those areas? Or is the second half outlook really just about a big deal ramp?

Yes. Great question, Tien-Tsin. First, we aren't factoring in any rebound for short cycle, since you'd need a crystal ball to reach that kind of conclusion. So that's not what we're doing. Most of what we'll see in terms of growth during the second half comes from the large deal ramps, along with carrying on with the Data-Tech-AI journey and consulting technology advisory, et cetera, work that's happening right now. We aren't anticipating a rebound during the second half. As for the earlier portion of what you asked, the drop in volume we saw with Hi-Tech clients was probably responsible for around 40% of the revenue change, while advisory work would make up the remaining 60%.

To follow up quickly, my question concerns momentum on large deals. Clearly, things look strong there. Could you say anything about the margin profile on some of those deals, any rebadging tied to them, and how timely the ramps are? Compared with what you normally see, how do these look?

Yes, Tien-Tsin, another excellent question. First, roughly 40% of those deals involve rebadging, though that is just one piece of each such deal, while the rest have none; that mix is what we typically get. So it isn't wildly different. And with large deals generally, you always see some blend of rebadging plus the usual ramp. That's the first point. As for margin profile, these deals aren't any different, except for one notable distinction I mentioned: over 1/3 of first-half deals use transaction-based pricing and non-FTE pricing as the commercial model; that's something, as you're aware, we've pursued quite aggressively across many years. We believe the momentum we're witnessing in the market regarding AI solutions, Gen AI solutions, and our capacity to start weaving those into what we offer lets us build value propositions that make it a win-win for our client and for us. So how I'd frame the margin profile: the base case margin profile shows no change, yet in truth the genuine opportunity is that margin profile will expand as we deliver greater value to our clients.

Let me just tack something onto what you said there, Tiger. When you look at our strategy and the way we're pushing margins upward annually at a quicker rate than before, nothing about that has shifted as we move through 2024 and past it.

Two questions come to mind, and they're connected. First, Tiger, I'm attempting to piece the narrative together. You mentioned double bookings expansion between 25% and 30% against a base of 3.9. So with 25% to 30%, let's simply take 25% to keep it simple, alongside top line growth in the low double digits for 2024. That struck me as quite an interesting remark, clearly conveying assurance about your staying power. But where's the gap? My assumption is that one piece involves bookings needing time before they show up in revenues, yet it appears baked into that is also some degree of presumption that short cycle work is going to be fairly soft. I was just hoping you might connect, say, that 25% to 30% against low double-digit revenue growth? Then I have a follow-up.

Yes. I think you've partly responded to it yourself, Keith. Whenever you have a bigger, longer deal and a long-cycle deal, an annuity deal that gets signed, you're clearly structuring that as a 5-year contract. And when that occurs, while simultaneously short-term smaller advisory work and the deal momentum in that area moves more slowly, then what you're really witnessing is a rotation of the booking portfolio away from those short cycle deals toward larger annuity ones. Consequently, that 25% to 30% growth is unable to translate automatically into matching growth during the subsequent immediate year. So that covers part of the answer. The second piece is that you'll observe that arriving across the years. And the initial reflection of that is the fact that we're stating we will return to double-digit growth in 2024. If you look back at our history, you'll notice many years where this has unfolded precisely this way, where you have a bookings year, and I could think about 2018, which was a great booking year that then proceeded very strong revenue year, but the difference between the bookings growth and revenue growth mirrors the kind of numbers we're talking about here.

Yes, yes. All right. My follow-up is connected to that, Tiger. I'm attempting — and I pose this same query to numerous service provider firms — but what's your vision for this supply chain interruption or the efficiency improvements tied to Gen AI? More specifically, I believe Genpact holds a substantial customer service footprint. I'm unsure of the revenue percentage, yet plenty of prominent experts highlight major efficiency boosts and seat-based pricing structures, especially for customer service. Consequently, there will be — and the bulk of that labor is structured around an FTE model. So seat counts will drop; and I'm just considering how you, first, would you agree with that assertion? And second, what's your method to counterbalance it? I'm aware you mentioned success-based models becoming a bigger piece of your approach. I'd guess that factors into your response. Yet simultaneously, a CFO would prefer to spend less money once AI gets deployed across customer service operations. So I'm just attempting to weave together the different — truly, what's your perspective on Gen AI? Which areas face the greatest likelihood of disruption? And second, how does relying on success-based models allow you to counterbalance those efficiency improvements from Gen AI?

So Keith, every point you raised, we concur with, aside from a single data point, and just to set the record straight, customer care, customer service work represents under 10% of our business. As you may recall, financial accounting stands as our biggest portfolio, insurance claims, insurance underwriting, lending underwriting, risk services, I could continue listing supply chain, naturally, sales and commercial support. Thus customer care is a very tiny share of our business when measured against typical comparable very large providers focused solely on customer care, which in turn actually gives us an opening that I mentioned in my script, essentially stating customer care will be disrupted, so I fully concur with you; for us, consequently, it turns into an offense strategy in Gen AI. So what we're doing right now is developing solutions and bringing them to customers right now, where we don't handle customer care work on their behalf. And we're informing them, here's a new model, and this is how you ought to approach it. So you're completely correct. It's among the areas destined for disruption. We're already witnessing that in pilots we're conducting. The share of that work for us is modest. Incidentally, even the customer care work we perform is complex, high-value customer care; we don't handle what you'd typically label commoditized, simple customer care, which is less susceptible to instant disruption or elimination from Gen AI. But we possess the skills and the capability and that's precisely what we're doing, which is why we labeled it the offense portion of our strategy. Another point I'd tack onto that, and it's how I wrapped up my comments: when you consider run-of-the-mill application development and basic coding, the story in the market is quite plain — that's yet another area, again, that's bound to be upended. Our own firm has conducted pilots for the internal coding tasks we handle, and we're seeing a potential disruption range spanning a low 40% up to 70%. Once more, it isn't a large portion of our portfolio. Once more, it's something we're bringing to our clients as part of our offense strategy, telling them, "We can deliver this for you in a manner different from how it's currently being done, whether by the providers you already use or by your own team."

Perhaps regarding outcome-based pricing, as that came up in the previous subject. Could you share a bit more detail about which kinds of engagements are experiencing a greater rise in this outcome-based pricing? And then any trends concerning which sector, how long the relationship has lasted, or similar factors regarding what clients are adopting outcome-based pricing?

Maggie, once more, an excellent question. I'll begin my response by noting that the broad category to keep in mind is non-FTE pricing, meaning pricing tied not to headcount, since beneath that umbrella, I would begin with transaction pricing along with overall fixed pricing, and after that outcome-based pricing, roughly in that sequence. The reason I put it that way is that much of the transactional work performed within our type of services suits transaction-based pricing quite naturally. A straightforward illustration would be — let's begin with accounts payable and accounts receivable, which fit well. After that you shift to financial services transaction work in insurance or the financial services, technology provider clients we mentioned, where we handle real customer service responses not via telephone, but rather in a more sophisticated manner. You are performing Fraud Alert Management, you are performing underwriting responses, you are performing insurance claim responses, insurance claims management. Whatever is transactional suits transaction-based pricing extremely well. The sector most receptive to this is financial services, since they grasp transaction-based pricing, they possess volume, they possess velocity and frequency of throughput. So we're witnessing a genuine — and I believe that's something that has shifted in the marketplace literally over the past 6 months but likely more across the last couple of years, because we've been advancing this agenda for 5 years — which is an openness to the model and a recognition that it actually generates a win-win, since it lets us invest and build solutions that embed AI and Gen AI and machine learning and all digital technologies that then deliver excellent value for the customer and for us, yet also for the end customer, because when we execute this really well, the consumer of the bank or the customer of the bank is the one most delighted throughout this journey.

That's very useful, Tiger. And we've also seen steady strong activity on big deals. So I'd like to know how you'd describe the competitive landscape at this point, and then how pricing looks for deals that are competitive?

Well, Maggie, the competitive landscape isn't all that different from how it's actually been for a good number of years. There are 2 things I'd point to that have always mattered and have likely become even more important. And my guess is that both the digital transformation journey coming out of the pandemic and now the Gen AI journey that people are working through are a major driver of what's shifting. I believe there's a strong awareness of how important it is to understand my industry, my data, my processes — something we've always thought was among the most critical elements in the journey. I think a majority of our clients are starting to see that. And where it truly hits home is when you begin deploying intelligent solutions with intelligence embedded in them through these AI models. You really need to be certain that the data being used for that intelligence is completely understood. And then when you put guardrails in place around responsible AI, around ethics, around InfoSec and privacy, again, I think the finest people to actually surface all of that, put it on the table, and work out the right road map and playbook and journey are those who grasp the domain and process and the data. And we stand out in those conversations. So I'd say the competitive landscape, not all that different; we are standing out. Our win rates have consequently risen. That's quite evident. We're standing out and prevailing in every deal. The first thing we hear when we win is that you guys stood out in your domain and data understanding. And I think that's the world we're in, and we're genuinely thrilled about that world.

Okay, so here's what I'd like to know — could you take your 2 segments, Data-Tech-AI and digital ops, and give us a breakdown of how much of each one is typically discretionary, meaning the stuff clients have flexibility to move around on timing? The thing is, your prepared remarks did mention that it's the near-term, more optional work getting deferred. And when I compare your 2Q numbers against what consensus was expecting, Data-Tech-AI actually came in right where people thought, while digital ops fell short. So a breakdown along those lines — plus some sense of which parts and which functions are discretionary — would really help.

I do have the answer on which piece of each of those segments is discretionary, but let me first react quickly to how the 2 items we flagged hit revenue. We flagged advisory and that front-end kind of work. Nearly all of it sits inside Data-Tech-AI and hits Data-Tech-AI; however, we also flagged the volume decline at a couple of Hi-Tech clients. Every bit of that lands in Digital Operations. So without the Hi-Tech volume decline, Digital Operations would have grown even more, with the weakness instead sitting in Data-Tech-AI relative to what we expected, caused by the advisory work. So when you separate out the effects, the Hi-Tech piece affects Digital Operations, and it's a one-off. The Data-Tech-AI piece reflects advisory work of a far more widespread nature, where clients are redirecting their discretionary spend. Mike?

Sure, let me unpack that a little, and your instincts there are on target. Everything really traces back to Data-Tech-AI within Digital Operations — that volume you mentioned. If you break it down, our work there falls into 3 sizable groups: first, legacy technology projects. That one took a hit largely in our financial vertical as well. Then digital marketing plus our experience business, which more or less tracks the broader market. And finally, the piece Tiger just referenced — the advisory services we provide, covering a great deal of operational advisory, blueprinting, supply chain, and procurement engagements that simply aren't landing where we expected them to earlier in the year; for that, we're keeping our outlook fairly flat — precisely flat — across what's left of the year.

However, Ashwin, there's one fascinating piece I'd like to mention. If we zoom in on particular customers where major transformation efforts are starting to be launched — be it agreements we've closed or those we're currently engaged in — one of the most fascinating observations we're making is this: once such a customer chooses to embark on a major transformation effort, they essentially halt every kind of smaller initiative taking place in those areas. They stop that activity since they don't wish to direct those additional funds there, because they're now starting to embark on a major transformation effort; so a portion of this amounts to a rotation. Even when it comes to where our customers direct their spending — not toward 10 minor items but toward a single major one — because they want to gain control of their data so that AI models can then consume it, which allows them to deliver far greater value. And they'd better act on this now, since otherwise they'll be at a comparative disadvantage.