Cognizant Takeaways from AI Forum - Harness, Context, and New Growth Opportunities Across IT and Ops; Front-Footed To Bridge the AI Value Gap

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Cognizant Takeaways from AI Forum - Harness, Context, and New Growth Opportunities Across IT and Ops; Front-Footed To Bridge the AI Value Gap

$150–200B TAM, and commoditizing slowly), 4) AI models

(custom LLMs and SLMs, $50–75B TAM, medium commoditization pace), and most

importantly 5) the interface and application layer (agentic apps, enterprise AI agents,

agentic workflows, contact center transformation, and vertical applications which

management estimates at $600–900B TAM and sees as the slowest to commoditize,

making it the highest-value and most defensible layer over time).

Cognizant's stated ambition is to compete across all of these layers, with particular

emphasis on the application and data layers where domain expertise and context

engineering create durable differentiation.

3 Vector Strategy Reiterated

Vector 1- AI led productivity

Application Modernization. Application and core modernization emerged as a central

AI-driven spend catalyst: enterprises face $1.5–$2.4T of tech debt and legacy

applications are increasingly a bottleneck, pushing modernization of applications, data

foundations, cloud infrastructure, and AI operations in parallel. Management’s message

was that AI is making modernization economically viable by compressing timelines and

lowering cost (cited ~65–75% improvement), with particular emphasis on mainframe

modernization (including MFaaS or Mainframe as a service-style approaches) and AI-

led enterprise package transformation. The commercial framing also shifted from labor-

based delivery to outcome-based models (AI-infused rate cards, “agent cost estimators,”

and underwriting operational outcomes), positioning modernization not as isolated re-

platforming, but as workflow reimagination that combines technology change with