At the India AI Impact Summit 2026 in New Delhi, policymakers signalled a major shift in how India plans to govern artificial intelligence, showcasing a principle-based governance model rather than pushing for a new, comprehensive standalone AI law. Instead of drafting rigid legal codes specifically targeting AI, the government unveiled a framework anchored in broad guiding principles designed to steer AI development and deployment across sectors like health, education, finance, agriculture and public services. This approach emphasises innovation, trust, accountability and fairness — aiming to balance technological advancement with safeguards against misuse.
The new governance framework, released ahead of or during the summit, rests on seven core “sutras” — trust as the foundation, people-first design, innovation over excessive restraint, fairness and equity, accountability, transparency and safety. These principles are intended to provide flexible guardrails applicable across varying risk levels of AI use, allowing the technology to be adopted responsibly without stifling innovation or economic growth. Rather than creating a discrete AI act, India relies on existing laws (such as IT rules, data protection statutes and criminal codes) for enforcement and plans periodic review and targeted amendments as AI evolves.
This model also proposes institutional mechanisms to coordinate policy and oversight, including an AI Governance Group, a Technology & Policy Expert Committee, and an AI Safety Institute to handle standards, risk assessment and capacity building. Developers and deployers of advanced AI systems are expected to produce transparency reports, label AI-generated content, and set up mechanisms for grievances or harms. For applications with significant impact on safety or rights, stronger oversight and mandatory human control are emphasised.
India’s choice of a flexible, principle-based AI governance model reflects an ambition to position itself as a global leader in inclusive and human-centric AI policy, particularly for the Global South. By avoiding a heavy-handed law and instead embedding ethical and democratic norms into a broader regulatory ecosystem, the approach seeks to foster innovation while ensuring responsible AI use across society. Critics, however, argue that without binding legal safeguards, rights protections might be weaker and rely too much on voluntary compliance rather than enforceable standards.
