Indian enterprises are moving agentic AI from experimentation into production and must now prove measurable business value. According to IDC, India’s AI spending is projected to reach USD 6 billion, growing at a CAGR of 33.7% through 2027. Leaders need frameworks that go beyond cost reduction or productivity claims. Feedback comes in two forms: explicit signals such as thumbs-up or thumbs-down and implicit signals drawn from outcomes, for example, whether a resolved incident stays closed or a workflow finishes without further intervention. Implicit feedback often better reflects real business value. Metrics should match the agent’s role and be refined over time. Deployments typically start under close human supervision. Low-risk tasks can later run with greater autonomy, while high-impact actions involving finance, critical infrastructure, or sensitive data should still require approval. Continuous evaluation and clear governance will decide which programs scale with confidence.
Indian enterprises are moving agentic AI from experimentation into production and must now prove measurable business value. According to IDC, India’s AI spending is projected to reach USD 6 billion, growing at a CAGR of 33.7% through 2027. Leaders need frameworks that go beyond cost reduction or productivity claims. Feedback comes in two forms: explicit signals such as thumbs-up or thumbs-down and implicit signals drawn from outcomes, for example, whether a resolved incident stays closed or a workflow finishes without further intervention. Implicit feedback often better reflects real business value. Metrics should match the agent’s role and be refined over time. Deployments typically start under close human supervision. Low-risk tasks can later run with greater autonomy, while high-impact actions involving finance, critical infrastructure, or sensitive data should still require approval. Continuous evaluation and clear governance will decide which programs scale with confidence.