Transcripts

Cognizant Technology Solutions Corporation's management answers for the business every quarter. These are the exchanges that explain it best — verbatim, from the call transcripts preserved in Sources. Each link opens the full transcript at that page in a new tab.

Q1 FY2026 Earnings Call — Q1 FY2026

The fullest account of the AI-builder economics: token-metered rate cards, Project LEAP, and how pricing is shifting from labor to outcomes. · Open the full transcript →

The strategic reframe: from systems integrator to AI builder, and why AI forces it.

Ravi Kumar (Chief Executive Officer): With AI, the fundamentals are shifting. Software is penetrating deeper into enterprises and our clients now expect more value and measurable outcomes. The old fundamentals are still relevant, but there must be a reforge for a new reality. Cognizant has already embarked on this transition, which demands four significant shifts that redefine the role of IT services firms. First, we are evolving towards owning the full stack of capabilities required to design holistic bespoke AI systems from a systems integrator to an AI builder.

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On AI price pressure the game shifts from unit price to how few units deliver the same outcome.

Ravi Kumar (CEO); question from Jason Kupferberg (Wells Fargo): The way I see it is, unlike in the past, where pricing was determined by the unit price, which is billing equivalent, the race now is about the number of units and how well you can deliver with a lower number of units for the same output and the same outcome. That is based on how much productivity you can derive out of AI usage in your software development cycle. So we feel very confident because 40% of our software development cycle is assisted by AI. We have infused AI into our rate cards. So when we are up for a consolidation opportunity, we seem to be in the winner's spot because we are able to share the productivity and also keep some for ourselves.

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How AI-era pricing works: token metering and an A0 to A3 human-to-autonomous rate card.

Ravi Kumar (CEO); question from James Schneider (Goldman Sachs): Token metering is a reality, both at a project level and at an individual level. We have token metering for fixed-price programs as well as for time-and-materials. For fixed-price programs, we have the opportunity to reduce the cost and keep the margin with us. For new deals, we actually have the opportunity to outpace the productivity we give to our clients and therefore keep some of that benefit. […] On time-and-materials and tokenized rate cards, we are starting to see a pattern. I'll give you an example of a rate card template we're taking to the market: A0 is completely human effort; A1 is effort done by humans verified by AI; A2 is effort delivered by AI, verified by humans; A3 is autonomous digital labor. […] But clients have started to see that they are not able to optimize the digital effort themselves, so some clients are coming back and asking us to take care of both the human and digital effort. They want us to open the tap on compute, manage the model usage, and deliver the service end to end so they don't have to manage the economics.

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Capital allocation: strong free cash flow, ~$2B returned, and fuel in the tank for AI-aligned M&A.

Jatin Dalal (Chief Financial Officer); question from James Faucette (Morgan Stanley): And just from a capital allocation standpoint, we generated $2.5 billion of free cash flow last year. We returned close to $2 billion to shareholders and roughly $500 million to $700 million was invested into three-cloud acquisitions, which technically closed at the beginning of this year but were announced in 2025. This year, again, we generated strong free cash flow. We have committed $1.6 billion to be returned to shareholders — $1 billion via share buyback and $600 million in dividends. Of that, we have now used about $600 million for the repurchase so far. We therefore have fuel in the tank and a very healthy balance sheet to leverage for attractive opportunities. We'll remain disciplined, but we have the capacity to act on the right opportunities.

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Project LEAP: resizing the pyramid with early-career talent and funding the shift to outcome-based models.

Ravi Kumar (CEO); question from Tien-Tsin Huang (JPMorgan): We have a clear frame of what our future operating model looks like, and Project LEAP is designed to get us there faster. It's our opportunity to resize our pyramid with a broader base — that's why we're hiring more early-career talent and shortening the path to expertise. This model is margin-accretive because the more we broaden the pyramid with AI-native skills, the more services we can deliver efficiently. Second, it allows us to invest in platforms, AI enablement, tokenization and automation. We have measured the savings: in 2026, we expect $200 million to $300 million in savings, recognizing that this year is partial since we're already mid-year; the full impact is larger in 2027. So not only are we right-sizing the pyramid, but we are also accelerating our move to outcome-based models.

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Q4 & Full-Year 2025 Earnings Call — Q4 FY2025

The victory-lap annual call: winner's-circle reached two years early, plus the clearest explanation of why AI is a tailwind for services and BPO. · Open the full transcript →

Three eras of IT services and why AI lets Cognizant own the stack again.

Ravi Kumar (CEO): In the nineties, we were bespoke systems builders. We wrote custom software code, and we owned the outcomes. In the two decades that followed, our role evolved into orchestrating classical software owned by various software providers. But classical software was written around the microprocessor, was deterministic, and built on rigid logic and fixed rules. Today's AI-led software, which is written around the frontier models, is probabilistic and contextual. This shift allows us to own the stack again and deliver outcomes.

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The bear case answered: AI does not self-deploy; enterprises need a bridge, and that is the business.

Ravi Kumar (CEO); question from Jason Kupferberg (Wells Fargo): this has happened over tech revolutions before. When a new technology comes, we kind of think the old technology will go away, but the new technology will actually provide more opportunities. I see this as an increase in our total addressable spend. […] any tool, any technology will not magically generate value on the other side. You need a bridge. And that bridge is what companies like Cognizant do.

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Fixed-price economics: Cognizant underwrites the productivity and carries the delivery risk.

Jatin Dalal (CFO); question from Keith Bachman (BMO Capital Markets): there are various types of fixed price engagements, but essentially, I mean, they have one thing in common is that the larger component of delivery risk resides with the service providers like us. And, essentially, we underwrite the productivity in the beginning of the contract and we deliver to that productivity to the customer irrespective of whether we are able to achieve that outcome from a cost standpoint or not. […] we deliver on aggregate of the portfolio very close to the expected margins that we had planned, which means we are in aggregate not having any overrun or also not significant underrun.

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Q4 & Full-Year 2024 Earnings Call — Q4 FY2024

The pivot-to-growth call where the three-vector AI framework and the TriZetto/Belcan portfolio were first laid out in full. · Open the full transcript →

TriZetto, the healthcare moat: a platform that processes about two-thirds of US healthcare claims.

Ravi Kumar (CEO): This included continued strength in TriZetto, our differentiated software platform that is used to process about two-thirds of US healthcare claims. As a recent example, we entered an agreement in 2024 to enhance healthcare operations for Blue Shield of California with our TriZetto Facets platform as a service solution.

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The three-vector AI strategy laid out: productivity, integration, and software as the worker itself.

Ravi Kumar (CEO): We see the AI-enabled opportunity playing out in three distinct vectors with the first already here. First, the most mainstream use case of AI is tech for tech for its application in software development cycles with the help of code assist platforms. […] In the fourth quarter, we estimated that 20% of our code accepted by developers was generated by AI, allowing us to do more for less and unleash a wave of hyper productivity. […] The Vector 2 opportunity will be about modernizing the data and cloud foundation for integrating AI into enterprise landscapes. […] Finally, Vector 3 is about untapped and newer service pools that we believe will be unlocked by agentification. Our view is that, software may no longer be mainly a tool for organizing work, but can become the worker itself, capable of understanding, executing, and improving services traditionally delivered by humans.

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Is the software edge defensible? Ravi on fast software, Flowsource, and staying ahead of replication.

Ravi Kumar (CEO); question from Surinder Thind (Jefferies): The software layer we've developed, which I refer to as fast software, provides essential tools for our clients to accelerate their progress, bridge gaps, or create micro industry vertical templates that existing software lacks. […] For instance, our platform Flowsource acts as an orchestration layer over code assist platforms like GitHub. We created this layer because we recognized the need for a developer workbench that can synchronize the efforts of machine-written code and human-written code to enhance productivity. […] While some existing platforms may eventually replicate this functionality, by that time, we will be tackling more complex challenges. The gaps we face today will persist, and it will be the responsibility of system integrators to address those, with some eventually becoming products.

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Q2 2023 Earnings Call — Q2 FY2023

Ravi Kumar seven months in: the turnaround plan, the $1B GenAI bet, and the bookings-to-revenue puzzle at the start of the story. · Open the full transcript →

The turnaround plan at inception: accelerate growth and a $1 billion, three-year bet on generative AI.

Ravi Kumar (CEO): Our next priority is to accelerate revenue growth which is the absolute focus of the entire management team. We are differentiating Cognizant and large-deal opportunities by scaling our capabilities for cost take-out and optimization and focusing more on managed services. […] Given the groundswell of interest in generative AI, the number of projects we have underway focused on cognitive and generative AI, we see this technology generating a new wave of opportunities for us. Accordingly we expect to invest approximately $1 billion in our generative AI capabilities over the next three years.

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The two swim lanes framing of demand: transformation vs. cost-takeout, then skewed to cost.

Ravi Kumar (CEO); question from Ashwin Shirvaikar (Citi): there are two swim lanes on large deals. One is related to transformation. One is related to efficiencies, productivity, cost takeout. I think it’s fair to say that at this point of time the deals we are seeing in the market are over-indexed to efficiency, cost takeout, consolidation kind of deals.

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Why record bookings were not converting: longer-duration, larger deals push revenue out.

Jan Siegmund (Chief Financial Officer); question from Ashwin Shirvaikar (Citi): the duration of the deals that we signed up in the last year has very meaningfully lengthened, basically. So we have been signing up longer-term deals, on average, with a higher deal value. […] the actual contribution of this book in volume just to give you an example for the rest of year revenue is actually lower than it was in the comparable quarter. So we really have built a pipeline for longer type of revenue streams in the future, which obviously gives us good comfort into the quality of revenue stream going forward, but it also explains why and we’re not seeing immediate uptake on our revenues as these bookings will take time to translate into revenue.

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More calls

Q3 2025 Earnings Call — Q3 FY2025 · 12 pages · The last quarter before the winner's-circle declaration: continued beat-and-raise, financial-services strength and building large-deal momentum. · Open →

Q2 2025 Earnings Call — Q2 FY2025 · 13 pages · A mid-2025 read on the recovery in discretionary spending and how the large-deal book was converting into growth. · Open →

Q1 2025 Earnings Call — Q1 FY2025 · 11 pages · The first call after the March 2025 Investor Day, where management framed its 2027 winner's-circle target and margin roadmap. · Open →

Q3 2024 Earnings Call — Q3 FY2024 · 12 pages · The first quarter with the Belcan engineering (ER&D) acquisition consolidated, reshaping the Products & Resources portfolio. · Open →

Q4 & Full-Year 2023 Earnings Call — Q4 FY2023 · 21 pages · Ravi Kumar's first full-year results as CEO: the stabilization year and the NextGen cost program that funded the later pivot to growth. · Open →