As AI moves from assistance to execution, enterprises must rethink workflows, traceability, and governance while services firms shift towards more outcome-led roles.

AI is no longer just a productivity layer sitting beside enterprise teams. In some workflows, it is beginning to take decisions, trigger actions, and alter how execution itself is organised. That makes this conversation with Muthu Kumaran timely. As Operating Partner and Head of India Operations at Recognize, Kumaran brings a services-led view shaped by deep operating experience, including a long career at Cognizant. Recognize, co-founded by former Cognizant CEO and Vice Chairman Frank D’Souza, has been building its thesis around the future of digital services. In that sense, this conversation is not only about enterprise AI adoption, but also about how the services model itself is being forced to change as AI moves from support tool to execution layer.

We are at an inflection point. AI is no longer just a co-pilot sitting beside human workers. It is increasingly making the call. In enterprises, that shift is already visible in procurement workflows, customer service pipelines, financial reconciliation, and supply-chain decisions.

The enterprises that will lead the next decade will be the ones that redesign workflows around AI’s decision-making capacity instead of simply bolting AI onto existing processes. That means rethinking approvals, exceptions, and accountability at every layer. This is not incremental change. It is a structural transformation.

The deeper shift, and one that forward-looking enterprises are beginning to harness, is intent-driven development. When a business leader can state what they want a system to do, and AI can translate that intent into architecture, workflows, data models, and code, the entire development model flips. It becomes top-down, outcome-first, and far more powerful. This is not just a productivity gain. It changes who can build software, and what software building itself may come to mean.