Infosys is helping clients optimise AI investments

Enterprise AI is driving business transformation, with over 50% of AI use cases delivering impact, according to Infosys. Success is highest in professional services and tech, while financial services face regulatory hurdles. Satish H C, EVP, chief delivery officer, Infosys, tells Padmini Dhruvaraj, that the company is investing in small language models, Agentic AI, and workforce transformation to enhance AI-driven automation. Excerpts:

ALSO READBessemer Venture launches $350-million India fund According to Infosys study only 20% of AI (artificial intelligence) use cases fully meet business goals, with 31% nearing success. What key challenges hinder AI deployments?

Achieving transformative change requires recognising complexity and organisational readiness. While incremental value is possible, true transformation comes from re-imagining processes with an AI-first approach, not just augmenting existing ones. This shift depends on workforce engagement, change management, training, and budget support. Expectations also vary by AI type. Generative AI excels in chatbots, question and answer, and document summarisation, while AI for business value relies on traditional models, BI queries, or statistical methods for accurate predictions. Achieving this requires agentic frameworks, interconnected models, and significant investment.

How is Infosys helping clients optimise AI investments to ensure sustainable cost reductions without compromising performance?

We are helping clients optimise AI investments to ensure sustainable cost reductions without compromising performance through several strategic approaches. To name a few – AI tooling leveraging AI foundry, AI factory, Agentic AI for enterprise transformation, product centric operating model and setting up value office. AI foundry and AI factory to experiment and incubate new technologies, develop new patterns etc. The AI factory then turns these learnings into products and platforms. Together, they form the hub of AI innovation, experimentation, building and training customer models and then eventually leading to value realisation, workforce engagement, and governance at scale. With our Responsible AI 3S framework (Scan, Shield, Steer), we are ensuring innovation is safe for adoption for our customers. Agentic AI for enterprise transformation involves creating multiple small AI agents, each playing a specific role or carrying out a specific task including taking decisions, plan actions, and learn from experiences, enabling end-to-end processes.

Are there any Infosys-led AI implementations that have significantly transformed business outcomes for clients both in terms of efficiencies and return on investment?

In the US CPG (Consumer Packaged Goods) sector, our Media Mix Optimiser slashed implementation time significantly and boosted accuracy by 10-15%,

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