Genpact Limited (G) Earnings Call Transcript & Summary

Thanks, Gigi, and good afternoon, everyone, and welcome to our Q1 earnings call, where we'll discuss results for the period that ended March 31, 2023. We hope you've had an opportunity to look over our earnings release, which was posted to the IR section of our website, genpact.com. On today's call, our speakers are Tiger Tyagarajan, our credited CEO, and Mike Weiner, our Chief Financial Officer. Here's how today's agenda will go: Tiger will give an overview of our results and an update on our strategic initiatives. After that, Mike will take you through our financial performance for the quarter, and he'll also share our current thoughts on our outlook for the full year 2023. Tiger will then return for some closing remarks; after that, we'll take your questions. We expect this call to last about an hour. A number of the matters we'll discuss today are forward-looking and involve a number of risks, uncertainties and other factors that could cause actual results to differ materially from those in such forward-looking statements. Those risks and uncertainties are set forth in our press release. Also, during today's call, we will refer to certain non-GAAP financial measures that we believe provide additional information to enhance the understanding of the way management views the operating performance of our business. A reconciliation of these measures to GAAP can be found in today's earnings release posted to the IR section of our website. With that, let me turn the call over to Tiger.

Thanks, Roger. Hello, everyone, and good afternoon — appreciate you being with us for the Q1 2023 earnings call. During today's remarks, I'll walk you through what we posted financially in the first quarter of 2023, and also explain why we think our position is unique when it comes to partnering with clients as they take advantage of generative AI, Large Language Models, or LLMs, plus AI and machine learning technologies more broadly. To begin, the results we turned in for the Q1 came in solid and underscored the strong interconnection linking our Data-Tech-AI and digital operations services — an interconnection that opens up plenty of fresh chances to keep delivering value to clients and growth for our company. The highlight was the record Q1 bookings we booked during the quarter, along with the near record pipeline we carried into the sec ond quarter. During the Q1 of 2023, on a constant currency basis, total revenue reached $1.089 billion, which was up 4% year-over-year; Data-Tech-AI service revenue came to $485 million, up 6% year-over-year; and digital operations services revenue was $604 million, up 3% year-over-year. On top of that, adjusted operating income margin came in at 16.4%, which expanded 140 basis points year-over-year, while adjusted diluted earnings per share were $0.68, up 13% year-over-year. Across the past 60 days, I've gotten the chance to talk with 150+ C-suite executives at large global enterprises, and the themes I keep hearing are consistent. Every one of them confronts the reality that they must accomplish more with less, and they stay focused on taking out cost and improving cash flow. Meanwhile, they're eager to direct resources toward their most critical long-term transformational programs, which includes beginning to explore how generative AI, LLM, and AI more broadly can be used in their business. That's the backdrop for the net new record we set in our Q1 bookings, which included five large deals whose total contract values exceeded $50 million. Although close to 3/4 of our bookings came from our priority accounts, we brought in 17 new logos during this quarter, with an average contract value of roughly $6 million, versus the $3 million level for the full year of 2022. Let me share some color on those five large deals, since a few consistent themes run through them. For a leading technology platform provider in the automotive industry, we're modernizing their application stack, shifting all of it to AWS Cloud, and redesigning their finance, sourcing, procurement, and customer service operations to boost efficiency and, more importantly, to access clean data that can be orchestrated for AI-based solutions. Cost reduction is the strategic objective, along with better end-to-end dealer and customer experience that will drive growth. For one of the largest global consumer goods companies, we'll redesign, transform, and run their full order to cash and source to pay services end to end across 100 plus countries, dramatically cutting costs and improving working capital. And what's really key here is that with Cora AP — our AI-driven, cloud-based platform — we're going to bring standardization and automation to master data management and contracting. That opens the door to applying AI for smarter decision-making around purchasing, selecting suppliers, and sustainability, plus customer segmentation and customer credit. Take a large industrial equipment maker whose technology environment is highly fragmented across more than 50 countries. We're going to re-engineer and operate their global finance processes from end to end, which lets them complete a full separation into 2 publicly listed companies. They'll pair digital partner technologies with the domain depth and process expertise we bring, and that lets data be harnessed for AI and generative AI, producing savings and commercial gains. Then there's a leading global med tech company that, after many years of running its own global captives, switched its strategy to partner with Genpact. What drove them was wanting to tap the newest AI, generative AI, and LLMs — but first they needed clean data available consistently across more than 80 countries. So we're taking over their global captives, aiming not just to lower costs but to give them a commercially competitive edge that fuels growth. And lastly, a global beverage company: we're assuming control of their European capture operations, since they also chose to change strategy and draw on our process and domain know-how so they can embed AI solutions, quickly modernizing the processes that generate AI-driven insights to enhance cost, experience, and outcomes. A lot of these deals build in non-FTE-based commercial models — transaction-based pricing especially — which lines up everyone's goals toward fast adoption of new technologies like generative AI, machine learning, and LLMs. Our Data-Tech-AI services, where we design and build solutions that transform client businesses, posted 6% growth in constant currency; the driver was continued momentum in emerging services — supply chain, sales and commercial, and risk — which together rose 9%, partly offset by an expected slowdown in the discretionary side of our shorter cycle advisory work. Digital operations services, where we digitally transform and run client operations, kept delivering steady results in the Q1, up 3% in constant currency. Across all five of our initiatives, we've made strong progress toward our long-term objective of 10%+ organic top-line growth and expanding our AOI margin through 2026 at a more meaningful pace than we've seen historically. To start, revenue from priority accounts rose 3% in the quarter and made up roughly 62% of total revenue. Even with some near-term macro pressure, the investments we've made in these clients are paying off, since most of our Q1 bookings came from priority accounts. Next, we keep strengthening ties with our cloud technology partners, co-innovating with them and building joint IP and AI solutions. With ServiceNow, for instance, we've embedded our domain and data depth to help transform and automate manual processes in areas like procurement, accounts payable, and risk management. Our alliance's power shows in the fact that we are co-sponsoring ServiceNow's flagship gathering, Knowledge '23, which happens next week, and there we'll showcase our procurement-as-a-service solution. Together with Kinaxis, we've broadened our preferred partner designation, adding capabilities across Europe and Asia so we can better help clients with essential supply chain solutions worldwide. Number three, we are putting money into new operating centers located in tier 3 cities, especially in India, which gives us strong talent pools; 2 of these centers are completely up and running, while a 3rd is being prepped for a quarter 3 debut. Number four, we keep advancing outcome and transaction-based commercial models, which currently account for 13% of total revenue as we aim for 20% by 2026. In fact, non-FTE pricing applied to 28% of our bookings in quarter 1. Finally, we've grown our large deals team to capitalize on a rising count of large deal opportunities, and that's reflected in large deal bookings plus a robust pipeline for large deals. As anticipated, our attrition keeps falling, sitting at 24% in the Q1. This favorable trend appeared throughout the company across every level, skill set, and geography. When we adjust for involuntary attrition and staff with under three months of service, attrition came in even lower, at 19%. Over the quarter, we brought on board 8,000 new team members worldwide.

What draws people to us, plainly, is the ability to gain new capabilities and answers while working with digital, generative AI, and machine learning tools on such a wide range of client projects — and that same factor is driving our attrition numbers down. Let me step back for a moment and talk about the pace at which generative AI has changed during the last 5 months, along with the reasons we believe we rank among the industry's best positioned companies to capture this coming AI wave. For years AI has been central to who we are, and yet generative AI and the latest breakthrough amount to an exciting next wave that our existing strengths will support. If we rewind over the last five years, one thing deserves real emphasis: the role AI has played in how well we serve our clients. Over that stretch, we've developed and refined what we can do with AI, and that's what allows us to design creative, sector-tailored offerings for the people we work with. Our view is that this has positioned us among the top players in AI within our field, giving us an edge that supports growth and margins over the long haul. Here are several of the important steps we've taken along the way: back in March 2017, we took a major step into AI by buying Rage Frameworks. Through that deal, we added natural language processing along with natural language generation into what we offer. With this, we're able to roll out our financial-services AI products, which rely on tech that interprets financial statements—something we later put to work in our lending operations and financial reporting services, cutting loan cycle time by 60% and costs by 40%. For the CPG industry, we created and implemented AI-based demand forecasting and inventory optimization tools, which brought down stockouts along with inventory holding expenses. A trio of years ago, for several sizable manufacturing customers whose operations we manage, we introduced AI-powered predictive maintenance, which produced a 30% decrease in maintenance expenses and better equipment effectiveness. Back then, we additionally established our AI Center of Excellence, aimed at advancing innovation, cultivating talent, and developing fresh solutions at scale alongside industry partners. Our range of AI offerings grew to encompass natural language understanding, or NLU. That enabled us to deliver chatbot-based customer service driven by AI for banking, insurance, and high-tech sectors within our comprehensive services. Better customer experience lifted our clients' retention and renewal numbers, and it also boosted their cross-sell and upsell results. Across all of those 150-plus C-suite conversations I mentioned earlier, generative AI came up every single time — our clients keep asking where to begin, how to rank their priorities, which moves to make, and how to get the most value. What most enterprises eventually grasp is that scattered, fragmented data and processes stand in the way of even getting started. That's precisely what we witnessed 7 years ago, when RPA and low-code workflow on the cloud hit prime time. We brought these technologies in, built up expertise with them, and integrated all of them into both our offerings and our internal ways of working. Right now, we have about 8,000 bots running across our operations, deployed at customer sites on our behalf. Beyond that, more than 250 customers run operations supported by Genpact's Cora platform — our cloud-based AI digital platform — which generally handles over 20 million transactions per month. We're now seeing similar co-innovation efforts focused on AI emerge, with the goal of bringing processes and data together, tidying them up, making them consistent, and then providing services that have these AI solutions built right in. This is clearly one of the biggest things driving the surge we're seeing in inflows and bookings — that sense of urgency clients have about getting to the point where they can actually put these technologies to work and create value. Often, before they can put AI to use, they have to fix the basics first — their legacy technology, their processes, and their data. As their transformation partner, what sets us apart comes down to 5 pillars of strength. The first is domain expertise. Because we know so many industries deeply, we've been able to develop AI solutions built for specific industries that address their unique challenges and handle every exception and edge case. The second is scalable AI solutions. The AI solutions we build can easily be tailored and expanded across industries and functional areas. Third, continuous innovation; we hold the view that rapid, ongoing innovation cycles are essential to preserving an edge in AI and generative AI. We put steady investment into R&D so that we are always testing AI and generative AI use cases alongside our clients. Fourth, talent development. A gifted group of data scientists, engineers, and domain experts staffs our AI Center of Excellence. Last year, 70,000 people earned certification through our DataBridge reskilling program, now three years old; that supplies the underlying talent pool for deepening our expertise in a market where talent is scarce. Finally, strategic partnerships. We have formed strategic partnerships with top technology providers to strengthen our AI capabilities. Thanks to what we know about our domain, our processes, and our data, we're set apart as a strategic partner unlike any other for a lot of them. Let me give you two specific examples of how those five pillars, along with our history of results, have positioned us as the go-to partner for finding ways to put AI to work. For one top-tier software-as-a-service business, we built and launched a churn prediction model powered by AI. This model uses machine learning algorithms to look at customer behavior data, patterns in how products get used, and other relevant factors, which lets it predict how likely a customer is to churn. Consequently, we spotted at-risk customers and have since put targeted retention strategies into place within our operations, producing a 30% reduction in churn and a substantial rise in customer lifetime value for our client; for a different client, we reached back into 10 years of customer sentiment data that had been collected to construct a highly effective net promoter score prediction engine, which we then applied to power specific tailored marketing campaigns, using generative AI to assist with customer service. When it comes to one of our global manufacturing clients, we applied predictive analytics powered by AI within our FP&A offerings to produce revenue and expense forecasts that were more accurate, factoring in a range of internal and external elements like market trends, economic indicators, and historical financial data; because accuracy improved, that business can now make strategic decisions with better information, allocate resources more effectively, and in the end reach a 25% decrease in forecast errors, which drives greater operational efficiency and stronger financial performance. This present surge of use cases involving generative AI is still at an early stage, and with our clients we remain in a mode of rapid prototyping and experimentation. Help desk, customer service, and research work—especially within unregulated industries—are where the first set of opportunities is clustered. Just as we've shown with things like RPA, dynamic workflows, and even prior versions of AI, each technology wave widens our total addressable market and lets us take on more intricate work for our clients. Having said that, I'll hand the call over to Mike so he can walk through our Q1 results in detail.

Thanks, Tiger. Hello everyone, and good afternoon. In today’s session, I’ll walk through the results for our first quarter, then give you an update on how we see the full year 2023 financial outlook. Revenue came in at $1.089 billion, which is a 2% increase compared with a year ago, or 4% when measured in constant currency. Data-Tech-AI services revenue made up 45% of total revenue and rose 4% versus the prior-year period, or 6% in constant currency, mostly because of ongoing expansion in our cloud-based data and analytics offerings within the areas we focus on, such as supply chain, sales and commercial, and risk services. Digital operation services revenue accounted for 55% of total revenue and was flat compared with last year, or up 3% in constant currency, mainly from deal ramps tied to existing and recent wins. Looking at things by vertical, financial services was up 9% versus a year earlier, mostly from sustained strong demand for our risk management services that use data, analytics, and AI. Consumer and healthcare fell 4% compared with last year, mostly because of longer large deal cycles, reduced Data-Tech-AI services revenue, and the effect of a recent divestiture involving a business we had classified as held for sale back in 2Q 2022. In high tech and manufacturing, we saw a 3% increase, driven primarily by new deal ramps, though that was partly offset by a notable reduction in the operational scope of a priority high tech account. Throughout the year, we grew the number of client relationships bringing in over $5 million in annual revenue from 150 to 175. The count of those above $25 million rose from 31 to 36, and that includes a recently expanded relationship that brings the total of clients with more than $100 million in annual revenue from 3 to 5 during the same period last year. Our adjusted operating income margin came in at 16.4%, up 140 basis points from a year ago. The main reason we beat expectations was the timing of when we spent on sales and marketing, which we expect to increase during the remaining portion of the year, plus overall operating leverage. Keep in mind that our adjusted operating income margin for Q1 2022 included the effect of the business classified as held for sale that was divested not long ago. We posted a 34% gross margin this quarter, down from 35.8% during the equivalent period last year, driven primarily by unusually high severance expenses related to cutting headcount in the discretionary side of our short cycle advisory work, as well as greater travel spending and outlays backing new deal activity. Taking out that severance expense I mentioned earlier, our gross margin this quarter would have landed much nearer to what we posted in Q4 of 2022. SG&A came to 19.9% of revenue, down 230 basis points year over year, driven mainly by when our investments fall — we anticipate those picking up pace across the rest of the year — along with broader G&A leverage. Adjusted earnings per share reached $0.68, up 13% from $0.60 in the first quarter a year ago. That $0.08 gain came mostly from adjusted operating income being higher by $0.08, plus benefits from a reduced count of shares outstanding and $0.01 less in net interest expense, though those were partly offset by a $0.02 hit from FX remeasurement shifts between years. Our effective tax rate landed at 23.4%, essentially matching last year's 23.5%. Now moving to cash flows and the balance sheet. In the quarter, operations consumed $34 million in cash, versus $114 million consumed over the equivalent stretch a year earlier. Part of that stemmed from a big jump in DSOs during Q1 of 2022, as clients went back to their historical payment patterns to capitalize on interest rates. Compared with a year ago, DSOs rose by 1 day, reaching 83 days. For the rest of the year, we anticipate DSOs will stay within the low 80-day range. Cash and cash equivalents came to $552 million, down from $647 million at the close of fourth quarter 2022, which mirrors our annual incentive compensation payouts made in the fourth quarter along with $55 million returned to shareholders. As the quarter ended, our net debt to EBITDA ratio across the trailing 4 quarters stood at 1.4x, matching our preferred range of 1 to 2x. Given the undrawn debt capacity and the cash balances we already hold, we enjoy plenty of flexibility to chase growth opportunities and carry out our capital allocation strategy. Throughout the quarter, we kept up our practice of repurchasing shares on a more regular cadence, buying back 631,000 shares at a total cost of $30 million, or an average price per share of $47.57; on top of that, we distributed $25 million in dividends. Capital expenditures equated to roughly 1% of revenues in the quarter. We expect a greater level of investment activity over the rest of the year tied to new large deal signings and the opening of additional operational centers connected to our hybrid delivery model. Finally, let me bring you up to speed on what we expect for the entire year. Our revenue projection remains between $4.64 billion and $4.71 billion, reflecting growth of 6% to 7.5% compared with last year, or 6.5% to 8% when measured on a constant currency basis. For full year 2023, we're still expecting an adjusting operating income margin of about 16.8%, which aligns with the plan we've described of growing margins faster than we've done historically. I'd like to take a moment to add some detail regarding gross margin for 2023. Our underlying gross margin should improve by about 30 basis points in 2023, driven mainly by scaling our Data-Tech-AI services, plus the impact of off-cycle pricing increases we secured last year. That said, those gains will be offset by the impact of the sizable contracts we recently secured, since those deals use onshore delivery and thus come with a lower gross margin by nature in the early years of the engagement. So for 2023, we anticipate gross margin will be roughly flat to modestly lower compared with 2022 levels. These new big wins do naturally come in below the company average on gross margin, but as we digitally automate solutions and leverage resources over time, we expect profitability on them to improve throughout the life of the contract. Looking at what these agreements specify, we anticipate that adjusted operating income margin overall will be in line with the total company level, since supporting delivery requires less SG&A investment. Our full year 2023 effective tax rate is now projected to come in at the higher end of the 24%-25% range we gave previously, as the overall jurisdictional earnings income mix leaves fewer discretionary tax benefits available than we first assumed. Based on the outlook I just provided, our expectation for adjusted operating income per share for the full year 2023 remains between $2.92 and $2.99. I'd like to offer some thoughts on how expected revenue and adjusted operating income margin should cadence over the rest of the year. Our full-year revenue outlook is now skewing toward the back end to a greater degree than we originally anticipated. The reason is ramp activity on deals connected to sizable new engagements, and that more than makes up for the deceleration in advisory work, which we expect to persist over the near term. For the second quarter, we're still targeting modest single-digit sequential improvement, and that should widen into mid-to-high single digit gains as we move through the later portion of the year. Looking at it year over year, we still expect the second half of 2023 to show growth relative to the first half, driven by how the recently won deals ramp and by a simpler comparison. Thanks to the solid adjusted operating income margin from Q1, we think we're better set up to grow that margin to 16.8%. Built into this forecast is our plan to take on greater R&D spending as well as higher sales and marketing costs for the rest of 2023, while putting the money saved from Q1 cost actions toward backing new deals. As for how the year unfolds, we still anticipate adjusted operating income margin will follow our usual trend of rising quarter by quarter alongside revenue, though the climb during the back half will be gentler than what we'd projected before. Looking ahead to the whole year, what we can see for the back half of 2023—where bigger contract signings should speed things up—along with a strong pipeline, makes us feel good about hitting our long-term plan: keeping organic revenue growth at 10% or better on a sustainable basis while pushing adjusted operating income margin up at a more significant rate than before, all the way through 2026. That said, I'll hand things back over to Tiger.

Thank you, Mike. When we consider how 2023 has begun for us and the momentum that's evident, it's obvious that the skills we developed internally and brought in through acquisitions across the years matter even more to our customers now. Each fresh technological leap that has emerged has simply heightened the demand for partners such as ourselves to assist our customers in harnessing these technologies so they can deliver value to them at scale. We've already witnessed stronger urgency and appetite among our customers and new prospects to shift toward new operating models, to get a solid handle on their data — data that is clean, clearly defined, and properly understood — which can then power these models to generate exceptional value. To sum up, all of the more than 150 target meetings I attended during the past 60 days voiced both interest in and intent for Genpact to serve as their partner in adopting and deploying AI and generative AI. Our AI path began when we acquired Rage in 2017, and that gave rise to numerous AI and machine learning services and solutions. Third, we see AI as an opportunity both for internal efficiency and margin improvement and for expanding services to customers within a growing TAM. Following the launch of ChatGPT and other generative AI, the intensity of our pipeline has increased. We're already engaged in a number of genuine use cases with customers in our operations and in theirs too. That's the reason that, notwithstanding certain near-term pressures affecting the small portion of our advisory business that leans more discretionary, overall demand for what we offer could hardly be stronger. I'm happy to report that we just released our 2022 sustainability report, which you can find on our website, detailing the continued progress achieved through our ESG initiatives that underpin our long-term financial targets. Simultaneously, we are assisting numerous customers in advancing their own ESG objectives through our solutions; with that, I'll hand the call back to Roger.

Appreciate that, Tiger. At this point we'd like to open things up for your questions. Gigi, would you mind sharing the instructions?

Hi there, and good afternoon, everyone. Tiger, it sounds like you've spoken with quite a few executives, which is fantastic. Yes, that's a great deal of conversation. I suppose that's positive for business. Regarding those 5 big deals, I do need to ask about them. You provided solid detail there. As far as the ramp goes, it seems like a portion of this will ramp during 2023. What length of time will be required to reach complete ramp? Does risk exist within any of these transitions? It sounds like there may be some rebadging and assuming control of certain captives. I'm simply attempting to gain a clearer picture of both the effect on the P&L near term and the risk that might accompany it. Overall, it sounds excellent, clearly.

Yes, indeed. Thanks, Tien-Tsin. Just a quick response regarding those 150 clients; that's a great deal of conversation, I realize. The current environment makes it beneficial to converse in order to gain complete insight and also engage, since everybody is attempting to work out solutions. As for your inquiry about the 5 deals. Structurally, these deals closely resemble ones we've previously completed. A few of them, which I specifically mentioned, do contain significant rebadge elements. These are businesses that have taken strategic steps where they acknowledge that, "In fact, we require a partner to assist us, despite having previously believed we didn't." Throughout our history, we've completed more than 25 of these rebadge deals. I'd say without exception, they've turned out very well. That's no shock, since we were carved out of GE, I believe 18 years ago now, yet that DNA persists; we perceive no risk tied to it. Clearly, these are complicated deals. The ramps are complicated. We understand this business; we understand how these deals get structured; we've been through this previously. Nothing out of the ordinary exists in any of them; we anticipate a normal cadence of buildup. Regrettably, none of these deals truly contributed meaningfully to anything during Q1. They'll begin ramping at some point in the second quarter and, in fact, more so in the year's second half. A number of them will tail up. I mean, the tail ramp will extend into next year's first half, since these are big and complicated. No, I mean, there's nothing further to mention beyond that; clearly, we're quite thrilled about how quarter one unfolded on that front.

All right. Excellent. I suppose, you know, it's good that you covered generative AI, since both my colleagues and I keep fielding questions about that topic. Tiger, throughout the years we've discussed numerous technology trends and waves. You brought up RPA, as I recall. Is there anything you'd liken this generative AI chance to, compared with earlier waves — whether in scope, in opportunity, or simply in the effect on enterprises that you've observed up to now?

Let me begin by saying this is extremely, extremely thrilling. You know, I'll repeat a point I've made previously in fairly public settings: my view was always that RPA would never prove to be the final solution. My view was always that RPA is an extremely straightforward, simple answer sitting at the base of the food chain; we've consistently maintained that AI sits at the top of the food chain. This is AI; this is the thing every one of us in the sector, every one of our clients, and anybody who has examined work, knowledge creation, and service usage has been requesting while saying, "Someday we'll arrive there." Well, at last the breakthrough came about in language; we're extremely thrilled. In fact, during the fourth quarter we began developing solutions alongside our clients, since, you know, GPT 3.0 had become available, and our staff and our teams have been developing those. Our AI Center of Excellence developed those. It differs from RPA, yet plenty of parallels exist. I believe it matters to grasp that although the chance is enormous and the value creation chance is genuine, the difficulty each enterprise confronts is, first, where should I begin? What should I prioritize? What value am I able to obtain, which subsequently dictates where I begin. The second is, whichever area you pick to begin with, because that's the greatest value and you can obtain it quickly, you'd better have your data prepared. If you examine standard big enterprises, which have existed for a great many years and are tremendously successful, it's the single item they've been progressing on, and that progress carries on. Each of the five deals we closed in the Q1, each of the deals in our pipeline that we're enormously excited about, centers on assisting our clients to gain control over data, meaning standardize, consolidate, pull it all into one place, cleanse the data; that's a progression. Who's positioned best to accomplish that? Firms such as ours. So I believe this is a genuine chance and a tailwind for us, precisely what we witnessed with RPA. I recall 2016, late 2015, 2016, I think all of us read truly expert reports claiming RPA would wipe out BPO. I recall us saying, "No, RPA is going to expand TAM." That's precisely what occurred. In our view, generative AI along with AI more broadly represents a genuine chance to grow TAM and deliver value to the clients we serve.

Thank you for sharing that, Tiger.

Thanks, Tien-Tsin.

Hello, and thanks. I'll pick up where Tien-Tsin left off. Tiger, throughout many, many years, you've consistently offered a considered viewpoint. Essentially, your argument regarding generative AI is that although it boosts the productivity of every one of your staff members — meaning they become more efficient — and under either the FTE model or the P times Q model applied to people, it will reduce revenue growth, yet you'll pick up additional work that still results in overall growth, correct? That has held for your entire strategy toward AI for some time now. Still, I wanted to dig deeper. When you consider that, there are a few factors I'd like to tease out as generative AI moves increasingly to the forefront and quality gets better. Could pricing face a greater risk of being eroded during this, potentially in a way unlike other areas of AI? Or do you view every one of those pressures as alike?

In fact, Keith, excellent question. Incidentally, the manner in which you opened that question made me feel old.

So that simply proves I’m getting older as well.

I appreciate that.

Since I've been following your company for some time now.

No, no, I appreciate that. By the way, that's an excellent question. The manner in which we approach this, there are two components to my response since your question has two components. First, precisely as you noted; we observe and have observed this not solely with RPA, but also with the shift toward cloud computing. In fact, if I look back 15 years, RPA did not exist. We witnessed this with Lean and Six Sigma. You enhance productivity, you remove labor, consequently you decrease the volume of tasks requiring completion, yet you receive additional work. We have consistently maintained that this sector, our sector along with the services we provide, remains under-penetrated. Meanwhile, we have introduced additional services within those same industry verticals and throughout our client base. RPA, identical situation. Although we have 8,000 bots operating, the truth is that for those very same clients, in fact, I believe if I run a regression analysis, something we have performed, to determine where those bots deliver the greatest impact, the clients achieving the most are those where we possess the bots and we have expanded alongside the client. It resembles the two occurring nearly simultaneously since you are genuinely delivering value to the client, and subsequently you are enlarging the total addressable market and seizing a greater portion of it. When you accomplish that, you obtain improved pricing. What is fascinating currently in our business model compared to 2016, when the RPA wave commenced, is that our alternative commercial models, commercial models constructed upon transaction-based or outcome-based or value-based pricing, which was extremely, extremely low during those times, remains at just 13%, yet it is on a growth trajectory. We mentioned 20% for 2026. I would not be astonished if we in fact surpass that significantly sooner. The bookings for this quarter alone signals at 28% of total TCV being alternative commercial models that we are going to achieve that. When we secure alternative commercial models, it is a win-win. The client gains enormously, and we do gain as part of it because that is how a complete win-win is generated. We anticipate in this journey margin to be accreted, which is partially why Mike and I stated in the long-term plan that this is going to occur.

Correct. Correct. Apologies, Tiger, I just want to dig into this further. You believe this alters the character... What I mean is, could your project work, if you will, rise as a proportion of your overall revenue due to AI, rather than simply performing time and materials?

Keith, I wouldn't characterize it as project work, I think. Actually, nearly every example I provided, whether in the deals or in the solutions, nearly all of them are AI solutions embedded into the services we provide. In certain instances, it's services we already provide, and in that situation we approach the client, we assemble a proposal and a solution, then we collaborate with the client since occasionally we require data from them. Occasionally we already possess the data since we handle the operations; then we embed that into our operations, deliver the value and receive a portion of that value, and then obtain additional growth.

Right.

Simultaneously, we do come across genuine chances in which a client asks, "How about you step in as well and handle X, Y, and Z across my operations, leveraging your AI technologies?" That's what we did when it came to RPA. Of those 8,000 bots, roughly 1,500 are in fact deployed at client sites. The remaining 6,500 sit with us. We're seeing the same thing unfold with AI. My sense is the ratio won't shift. I believe that proportion will stay exactly where it is. The reason is that AI's true strength, from our standpoint, shows up when we put together a major proposal on a large deal — it incorporates AI-driven solutions, much like RPA is already built into it today.

Understood. All right, so that I don't take up too much of my colleagues' time, I'll hand things over now. Thanks very much, Tiger.

Thanks, Keith.

Yeah. Hi, everyone. Thanks a lot. Strong bookings this quarter.

Thanks, David. Appreciate it.

Yeah, yeah. Could we sort of walk back through this? From what I'm hearing, you'll finish this year at roughly the usual rate of 10% or better. There's this stretch of 4 quarters running closer to mid-single digits. I realize the cause is somewhat softer Data-Tech-AI, which began around Q4. Could you connect the dots between the typical 10%-plus expansion in the business and the reason that, across 4 quarters, we get mid-single digits? Is it only 1 or 2 customers? That's really where my question comes from, so we aren't sitting here anxious that something is turning somewhat disruptive inside the business.

I'll begin, and after that Mike can chime in. Let me just say, right as we came into the year, at the point we began discussing the year during Q1 of TEUP, when we issued guidance for the year, I believe both Mike and I stated the year would show some gap between the first half and the second half, since we anticipated the first half would grow more, and the second half would grow more than the first half, because, as you know, the year before, the comparison would pit the first half of 2022 against the second half of 2022. That expectation was set by us. Coming into the year, we also observed discretionary spend on advisory work, especially around items such as digital marketing or experience and so forth, declining during the fourth quarter; we anticipated that would persist; we built our plan around it, and it has flowed through. Mike likewise pointed out during his remarks the smaller operation scope for one of the bigger high-tech clients. That too has been accounted for; it arrives in full. In fact, the bulk of it arrives in Q1; clearly it arrives across the first half. The deals, the big deals, we truly anticipated, if you recall, that we would sign a few of them in the final days of the fourth quarter. They slipped into Q1; sign them we did, yet we signed them near the close of Q1. At this point the ramp is genuinely, for want of a better phrase, quite a meaningful ramp as we move across the year into the third and the fourth quarter. I'll bring in Mike next.

Sure. The one point I'd tack on there is that you brought up the shrinking scope for that client, and yes, that was baked into the guidance we gave before. What I'd say is this: as we examine our business, we keep evaluating it against rolling averages of 12 months, 18 months, and 24 months, correct? Those big deal wins get factored in. Once everything shakes out, we're quite confident we'll land at that blended 10% rate across these 2 years. As we've consistently noted, certain years come in a bit stronger. 11+% was where we landed last year. For this year, our estimate runs somewhat under that. When you put all of it together, my sense is we'll be back on a path to perform even better than that.

Good. That's really nice to hear. OK. So for my second question, it seems there was a cash flow line item — you divested that business. I believe you brought that up during, say, the prepared remarks. Could you repeat how large an effect on revenue that divestiture had?

Sorry, could you say that again? I wasn't able to hear you. Cash flow.

Oh.

I heard it.

Yeah, I apologize. Regarding that divestiture, what kind of revenue effect does it carry?

What's the revenue figure? Right, we aren't giving that out. It accounts for a sizable portion of the gap between our typical trajectory and our growth rate, as well as where we're projecting for this year, if you'd like to sort of work backward to figure it out.

Understood. Fine, thank you.

Once more, the other significant swing factor, just like Tiger mentioned, is when everything lands, correct? Specifically, those substantial contract victories arrived right at the close of the period; we had expected them somewhat earlier. That big agreement wound down, if you will, during the earlier portion of the period. We expect it all to even out.

Gotcha. Thanks, guys. Appreciate it.

Thanks, Eric.

Thank you. It's clear you've gained momentum with the big contracts, yet you also noted that decision timelines for those major agreements remain stretched out. What I'd like to know is how you see signings unfolding for the rest of the year.

Maggie, that's a terrific question. No decline has appeared in the large deal cycles, as far as we can tell. For a couple of quarters now, they've stayed at raised levels, and right now that pattern holds. What's encouraging is they aren't climbing any higher. I won't pretend to predict the future, so my sense is we shouldn't anticipate additional increases. At this point, I also wouldn't claim they'll decline. As conditions calm and everyone finds a rhythm, and if inflation and supply chain hopefully become somewhat more settled, my expectation is that some portion of this extended cycle time will ease somewhat, since it is elevated and has remained so. Through this year, we've built in the assumption that this persists. No other assumptions have been made on our part.

Yep.

Excellent. Thanks. Regarding the outcome base, you set a target, I believe, for 2026. What's required within the company to move toward that goal? It seems like perhaps the possibility exists that it would be margin accretive as well. Is that right?

Yes. The latter portion of my response is straightforward, Maggie. What we've seen historically is that whenever we sign an agreement containing that element — and it can come in different shapes, depending on which service it is, and so on — we usually generate a win-win situation all around. Everybody comes out ahead. In fact, the third win I mentioned: a client comes out ahead, we come out ahead. The people doing the work, they get genuinely energized since they can see genuine value being generated, and so on; it's a genuine possibility. As we keep moving along that road, getting our clients to accept those kinds of commercial models has always proven difficult. It has required time through the years to actually bring a number of clients to that point. These sorts of things tend to build momentum. We feel that momentum is starting to build, and among the forces behind it are items such as AI and generative AI. When you do that, what you're truly after is exceptional value creation. On that exceptional value creation path, you genuinely require a real partnership with the client organization, along with access to the data they hold. Bringing together the standardization of that data with our domain knowledge, process knowledge, technology, digital knowledge, and analytical insights — all combined to make it operational and produce value; we've witnessed that with insurance claims, we've witnessed that with insurance fraud, we've witnessed that with sourcing and procurement. We've witnessed that with order to cash. We've witnessed that with financial planning. We observe it repeatedly. Customer service; we believe there's a genuine possibility in customer service. What's most intriguing about customer service is that we aren't a major participant in customer service. Consider what we might accomplish; we could shake up the customer service market by actually creating solutions and bringing them to our clients throughout financial services, high tech, and several other customer service areas.

Thank you, Tiger.

Thanks, Maggie.

Thanks. Hello Tiger, Mike. It's a pleasure to talk with both of you. I'd like to begin with bookings. Clearly, as has been noted several times during this call, those bookings look strong. What I want to ask about concerns how bookings turn into revenue — not so much the projected schedule, but how sure you are that this schedule will be met, since across the industry we've witnessed quite a few firms announcing, well, here's an enormous bookings figure, and afterward it never truly ramps up at the pace you'd expect based on history or norms. So how confident are you about that, and turning to the other side of the same coin, broadly speaking, which areas are converting into revenue more easily for you? Which kinds of items are being deferred, from a functional standpoint?