{"id":156,"date":"2026-09-14T10:10:00","date_gmt":"2026-09-14T04:40:00","guid":{"rendered":"https:\/\/www.wininfosoft.com\/insights\/agentic-ai-roi-india-why-projects-stall\/"},"modified":"2026-09-14T10:10:00","modified_gmt":"2026-09-14T04:40:00","slug":"agentic-ai-roi-india-why-projects-stall","status":"publish","type":"post","link":"https:\/\/www.wininfosoft.com\/insights\/agentic-ai-roi-india-why-projects-stall\/","title":{"rendered":"Agentic AI ROI in India: Why Projects Stall Between Pilot and Payback, and What to Measure Instead"},"content":{"rendered":"\n
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Quick Answer:<\/strong> Agentic AI projects in India stall between pilot and payback for ordinary, fixable reasons. KPMG in India found 88% of enterprises surveyed are investing in agentic AI, yet published returns are rare, and Gartner predicts that over 40% of agentic AI projects will be cancelled by the end of 2027. The usual culprits are no measured baseline, a pilot run on clean data, integration debt, nobody owning exceptions, and governance added late. None of them is a model problem. Measure cost per completed task against a baseline, plus work finished without human touch, handoffs, cycle time, error cost, review minutes and compute cost.<\/p>\n<\/blockquote>\n\n\n\n

An agent demo tends to stop just before the part that decides the return. The agent reads the form and books the refund, and nobody asks what happens when the form is a skewed phone photo or the refund goes to the wrong account. Those cases are where the money is made or lost. The operations head wants to know who picks up the work the agent cannot finish. The board just wants a number.<\/p>\n\n\n\n

The published Indian evidence is thin, and it says more about spending than about returns.<\/p>\n\n\n\n

What the Indian figures say, and what they leave out<\/h2>\n\n\n\n

KPMG in India reported in July 2026 that 88% of Indian enterprises surveyed are investing in agentic AI<\/a>. The figure tells you money is moving, and nothing about whether any of it has come back.<\/p>\n\n\n\n

An EY-CII report from November 2025<\/a> found that 47% of Indian enterprises have multiple AI use cases live in production. Live in production is a higher bar. It covers AI in general, though, and ‘live’ is not the same as ‘profitable’. Subtracting one survey from the other is tempting and wrong: they asked different questions, and only one of them is about agentic AI.<\/p>\n\n\n\n

Then there is the warning. On 25 June 2025, Gartner predicted that over 40% of agentic AI projects will be cancelled by the end of 2027<\/a>, due to escalating costs, unclear business value or inadequate risk controls. It is a general forecast rather than an Indian count. Its three reasons matter more than the percentage, because each one can be tested before signing.<\/p>\n\n\n\n

Why agentic AI ROI is harder to prove than chatbot ROI<\/h2>\n\n\n\n

A chatbot answers questions; its value shows up in deflected calls, and a wrong answer usually costs a follow-up. An agent is given a goal and permission to act. It reads a document, checks a system, updates a record and, in some deployments, moves money. That changes the calculation in five ways.<\/p>\n\n\n\n