Blitz Bureau
NEW DELHI: The Centre released a white paper titled “Strengthening AI Governance Through Techno-Legal Framework”, outlining India’s approach to building a trusted, accountable, and innovation-aligned artificial intelligence (AI) ecosystem. The White Paper, released by the Office of the Principal Scientific Adviser to the Government, emphasises the contours of a “techno-legal” AI governance framewok that aims to mitigate risks while preserving flexibility and innovation. It highlights India’s pro-innovation approach to AI governance, which integrates baseline legal safeguards, sector-specific regulations, technical controls, and institutional mechanisms.
“Developing a robust and responsive governance framework is not just a regulatory necessity but a prerequisite for sustaining the momentum of technological progress. The techno-legal approach offers a viable pathway by embedding legal, technical, and institutional safeguards into AI systems by design,” PSA Ajay Kumar Sood said.
The White Paper defines the techno-legal approach as a practical and ecosystem-wide model that embeds governance directly into the design and operation of AI systems by default. Key focus areas covered in the White Paper include understanding the techno-legal approach to AI governance; enabling safe and trusted AI across the full AI lifecycle; technological pathways for operationalising techno-legal governance; implementation considerations for India’s AI governance framework; and the development of techno-legal tools and compliance mechanisms.
This publication is the second in the White Paper Series on “Emerging Policy Priorities for India’s AI Ecosystem”, an initiative by the OPSA that aims at deepening understanding and fostering informed discussion on critical AI policy issues. The first White Paper in the series, released in December 2025, focused on “Democratising Access to AI Infrastructure”, highlighting the need to treat AI infrastructure as a shared national resource and identifying key enablers such as access to high-quality datasets, affordable computing resources, and integration with Digital Public Infrastructure (DPI).
