Is India ready for Agentic AI?

The agentic shift: From tools to autonomous teammates

The move from assistive to Agentic AI marks a critical inflection point. These systems plan, act and adapt independently, operating as digital teammates that can handle repetitive tasks while humans focus on creativity and strategic decision-making. This evolution challenges traditional workforce structures. Hybrid pods of humans and AI Agents now collaborate, combining precision and scale to expand capacity without adding headcount. Human oversight means the technology remains transparent, accountable and aligned with enterprise ethics.

India’s corporate ambition and urgency in scaling AI

Indian enterprises are advancing rapidly in their AI implementation journey, with deployment speed becoming a clear differentiator. Yet, challenges persist: 64.5% cite data governance and security as “very severe,” and 78% struggle with system integration. Despite these barriers, enterprises are finding value by scaling beyond pilots. Across sectors, the GenAI impact is tangible, driving productivity, enhancing decision-making and enabling sustainable growth. The shift from experimentation to execution shows that AI success depends not on perfect conditions but on continuous adaptation and learning.

Sovereign AI and the rise of SLMs

India’s Sovereign AI strategies focus on self-reliance and inclusive innovation. The IndiaAI Mission, supported by over INR10,000 crore and 40,000 GPUs, aims to build an independent ecosystem where India can develop and deploy AI using domestic data and infrastructure. Analysts estimate this could add up to US$1 trillion to the economy by 2035.

Alongside this, Indian enterprises are investing in Small Language Models (SLMs), which offer localized and efficient solutions. Unlike massive global models, SLMs require less compute power, can be designed to support Indian languages and have predictable costs. They also enhance compliance and data control key pillars of the Sovereign AI ecosystem. Together, these initiatives strengthen India’s position in the global AI universe.

Responsible AI 2.0: The new trust mandate

As AI gains autonomy, accountability becomes critical. Responsible AI 2.0 shifts the focus from trust claims to verifiable assurance. Enterprises must implement transparent governance through active monitoring, proper documentation and third-party validation. The RBI’s FREE-AI framework, for example, mandates board-approved AI policies and oversight.

Balance between innovation and discipline is also needed to realize ROI. Clear goals, measurable results like productivity or retention and structured scaling from assistive to autonomous systems allow AI adoption to stay ethical, sustainable and aligned with business objectives.