Cognizant Technology Solutions 2026 Q3 Earnings Call

Please go ahead, sir. Thank you, operator, and good morning, everyone.

Welcome to Cognizant's third quarter 2026 earnings call. I am joined today by Ravi Kumar, Chief Executive Officer, and Jatin Dalal, Chief Financial Officer. By now, you should have received a copy of the earnings release and investor supplement. If you have not, copies are available on our website, cognizant.com. Before we begin, I would like to remind you that some of the comments made on today's call and some of the responses to your questions may contain forward-looking statements. These statements are subject to the risks and uncertainties as described in the company's earnings release and other filings with the SEC. Additionally, during our call today, we will reference certain non-GAAP financial measures that we believe provide useful information for our investors.

Reconciliations of non-GAAP financial measures, where appropriate to the corresponding GAAP measures, can be found in the company's earnings release and other filings with the SEC. With that, over to you, Ravi.

Thank you, Tyler. Good morning, everyone. Thank you for joining us. We delivered a solid third quarter while advancing our AI Builder strategy. Revenue was in line with our expectations, and adjusted operating margin reached its highest level in four years, reflecting continued execution in a rapidly evolving market. We maintained strong momentum in financial services, where clients are increasingly using AI to accelerate modernization and address new areas of demand powered by AI-led innovation cycles. We are building the deployment capacity and differentiated capabilities that we believe can help clients move AI into production at enterprise scale and capture more of its value, and we see an opportunity to capture more of that value through platforms as well as deployment services. Looking at the quarter's highlights.

Revenue grew 4.8% year-over-year in constant currency, led by strong performance in North America, including contribution from our recent 3Cloud and Astreya acquisitions and our integrated offering strategy. Financial services accelerated to 12% year-over-year constant currency growth, its third consecutive quarter of double-digit growth. Communications, media, and technology also grew double digits, driven by inorganic contributions from Astreya and strong spending from technology clients. Trailing 12 months bookings increased 4%, with the mix of new versus expanded business growing over 10 percentage points year-over-year to 60%. We signed three large deals with TCV of more than $100 million each, while the combined trailing 12 months TCV of large deals increased 9% year-over-year. Adjusted operating margin increased year-over-year to 16.3%, the seventh consecutive quarter of year-over-year expansion. We also continue to see indicators that AI is changing our operating model.

Revenue and adjusted operating income per associate, excluding GenC trainees, increased more than 3% and 5% respectively. To the end of quarter 3, we estimate more than 50% of our software development was AI-assisted, and we have over 8,500 AI engagements. We achieved these results in a complex demand environment. Although macroeconomic conditions were largely stable in the third quarter, we are seeing the macro uncertainty weigh more on discretionary spending in the fourth quarter, particularly in healthcare and consumer-facing sectors. We have reflected these factors in our updated full-year guidance, which Jatin will cover in more detail. Despite these factors, we are still delivering revenue growth that ranks among the top of our peer group.

Against this backdrop, our strategy and actions are aimed at building the necessary capacity to deploy AI at enterprise scale, capturing more of the value between AI intelligence and the enterprise, and applying these capabilities to the areas where we see the greatest growth opportunities. Historically, major technology transitions required capacity to deploy new technology at scale. We are building that capacity across our talent engineering platforms and partner ecosystem with leading frontier AI companies, hyperscalers, and enterprise technology providers. More than 45,000 Cognizant associates have earned more than 95,000 certifications across frontier AI platforms, and another 65,000-plus are in progress. We recently expanded our Google Cloud partnership with a new Gemini Frontier Capability Group, bringing together more than 18,000 dedicated Cognizant associates focused on legacy modernization, developer experience, autonomous business processes, and Frontier Cyber Defense.

We are also proud of the strong momentum created through our Gemini partner event, where more than 55,000 associates completed Build with Gemini, the largest Gemini partner workshop to date. With this deployment capacity in place, we believe our larger opportunity lies in helping enterprises turn AI intelligence into differentiated business value. As AI moves into production, that value increasingly comes from reimagining how work gets done, providing the enterprise context AI needs to operate effectively and build the trust and governance required to deploy it at scale. Our AI Builder strategy is designed to bridge this gap between AI capability and enterprise value through four connected areas. First, reimagining how work gets done. This starts with redesigning business workflows, operations, and roles around what AI now makes possible in new Cognizant proprietary methodology in agile pods engaged in reimagination and reinvention of business landscapes.

Work once handled by software systems and human teams will increasingly be performed by a new combination of systems, people, and AI agents. We have pioneered the discipline of context engineering to develop our associates' expertise in this discipline. We believe we are building the specialized engineering capacity needed to build agentic systems at scale. Second, engineering enterprise-grade AI. Putting reimagined work into production as bespoke agentic systems requires enterprise-grade systems, meaning governed, trustworthy, safe, and grounded in the enterprise context. This is an area where we believe our platforms will play a critical role. This allows us to embed our capabilities and IP directly into delivery, scale them across clients, and increasingly bend the cost curve. Our platform opportunity rests across two pillars. First, engineering platforms support the end-to-end engineering life cycle through AI-led engineering and modernization.

Second, business platforms apply to repeatable business processes, particularly bounded workflows where AI can increasingly perform and improve the work. The third area of our AI Builder strategy is building the capacity to help clients absorb AI. Effective enterprise AI adoption requires the right skills, tools, and ways of working. We are putting into this practice inside Cognizant through Skillspring, our AI-native learning platform, which is now used by approximately 315,000 associates. We are also making the platform available to clients and are building an active pipeline of opportunities. Finally, compounding and protecting institutional intelligence. As AI is embedded in more workflows, enterprises need greater visibility into and control over how AI is used while protecting their institutional intelligence and sovereignty.

We recently launched Cognizant AI Nexus, a modular multimodal operating layer that helps enterprises govern AI quality, manage spend, coach in real time, compound repeatable patterns, and connect AI consumption to business outcomes across teams. It illustrates how we aim to help clients manage AI as an enterprise capability while learning from its use and making that institutional intelligence more valuable over time. Together, these four elements of our AI Builder strategy are designed to help clients turn AI capabilities into enterprise value while positioning Cognizant to capture more of that value. Now let me discuss how our AI Builder expands the opportunity for Cognizant in three areas. First, AI-led productivity and autonomous software engineering, which is increasingly becoming the baseline for how we deliver our traditional work.

Second, old things in new ways, which is using AI to perform existing work in fundamentally new ways, changing the economics of modernization and enterprise workflows. And third, new things in new ways. AI creates enterprise new services, platform, and operating model opportunities that were not previously possible. Together, they increase our total addressable spend and create expansive opportunities on enterprise landscapes, yielding new avenues of growth for Cognizant. To capture these opportunities, we are evolving how Cognizant operates by reshaping our organization, talent, and commercial model for an AI-led market. Notably, we have aligned our software engineering group portfolio around AI-led software engineering and modernization. This shifts the group's focus from engineering disciplines to client outcomes, industry context, and frontier capabilities. We expect this shift will improve how we build and deploy AI-native capabilities while giving associates clearer paths to develop frontier expertise.

In parallel, we are evolving our workforce, building frontier roles around the capabilities needed to design, deploy, and operate AI-native solutions. These roles combine engineering, AI fluency, and business expertise with greater accountability for client outcomes, and they are complemented by our investments while leading frontier AI partners I discussed earlier. We are also adding capabilities through targeted acquisitions. Last week, we announced our intent to acquire Australia-based DyFlex Solutions, an SAP Platinum Partner, to deepen our SAP expertise and strengthen our ability to help clients across Australia and New Zealand modernizing their core platforms. Our commercial model is also evolving. As human and digital labor increasingly converge in delivery, we see more opportunities for outcome-based pricing, AI-infused rate cards, and platform monetization. More broadly, our mix of fixed price and transaction-based work is steadily increasing.