Cognizant Technology Solutions (CTSH) investor relations material

AI impact and business transformation

• AI is driving efficiency in traditional IT services, causing some contract-level deflation, but overall industry and company revenues remain stable with continued organic growth guidance of 3%-4% this year.

• AI enables both modernization of legacy work (e.g., mainframe modernization) and creation of entirely new opportunities, expanding the total addressable market (TAM) from $1 trillion to potentially $5-$6 trillion.

• The business is evolving toward a model combining human skills, AI agents, and proprietary platforms, with platforms like TriZetto now accessible to agentic workflows for broader monetization.

• Platform and IP-led offerings are expected to drive higher gross and operating margins as they become a larger part of the portfolio.

• New AI-driven agentic workflows (Vector 2 and Vector 3) are a small but rapidly growing revenue stream, with significant future growth potential.

Revenue models and client engagement

• Clients are experimenting with various AI consumption models, including human effort billing, blended inference, and outcome-based fixed pricing, with transparency on token usage becoming important.

• Optimization of AI costs is achieved by deploying both large and small language models, tailored to specific enterprise needs, reducing unnecessary token spend.

• The company adds value by integrating deterministic systems with agentic outcomes, ensuring optimal delivery and cost efficiency.

• In the next 3-5 years, enterprises are expected to operate with a mix of 70% deterministic and 30% probabilistic (AI-driven) systems, with a flatter organizational structure to deliver value.

Market demand, client behavior, and sector trends

• Rapid technological change and macro/geopolitical uncertainty are causing some client indecision and delayed decision-making, especially outside BFSI.

• BFSI leads in AI adoption and discretionary spend, followed by healthcare; manufacturing is impacted by geopolitical factors, while communications/media lag.

• Most current demand is productivity-led (Vector 1), with growing traction in infrastructure readiness (Vector 2) and early adoption of agentic workflows (Vector 3), especially in simpler organizations.

• Clients that have implemented agentic models report significant reductions in human effort, faster turnaround times, and improved quality.

• Discretionary spend is expected to return as clients seek ROI from AI investments, with ACV growth as a key indicator.