India’s Office of the Principal Scientific Adviser (PSA) has released a white paper that sets out how India intends to govern artificial intelligence through what it calls a “techno-legal” framework. Rather than proposing a standalone or omnibus AI law, the paper argues that governance must operate inside AI systems themselves, through technical controls applied across the system’s lifecycle and anchored in existing legal and regulatory instruments.
Instead, the paper advances a “law-plus” model. Under this approach, sector-specific rules, subordinate legislation, regulatory guidance, standards, and technical enforcement mechanisms fill gaps in AI governance on top of existing laws.
Notably, this model distinguishes India from jurisdictions pursuing comprehensive AI Acts and reframes AI governance as a responsibility that begins at the design and deployment stage, rather than as a post hoc compliance exercise.
Why this framework has been proposed
In the foreword, Principal Scientific Adviser Ajay K. Sood writes that while AI offers significant transformative potential, unmanaged risks and harms could undermine trust and slow adoption. Against this backdrop, the paper situates India’s approach within a global environment where governments continue to experiment with risk-based regulation, principles-led frameworks, and standards-driven governance models.
Building on the India AI Governance Guidelines, the paper outlines a pro-innovation approach that combines baseline legal safeguards, sectoral regulation, technical measures, and institutional mechanisms to enable what it describes as “safe and trusted AI.”
Importantly, the framework prioritises proportionality and flexibility. It explicitly rejects uniform obligations across all AI systems and instead calls for context-sensitive regulation shaped by institutional capacity and ecosystem diversity.
What “techno-legal AI governance” means
At the core of the paper lies a shift in how it conceptualises governance itself. The white paper defines the techno-legal approach as the integration of legal instruments, rule-based conditioning, regulatory oversight, and technical enforcement mechanisms directly into AI systems by design.
In this framing, governance does not function as an external constraint imposed after deployment. Instead, it operates as an intrinsic feature of AI systems that can respond to evolving risks.
The paper positions this approach as a way to support responsible innovation while aligning AI systems with India’s legal, technical, and ethical norms. It identifies transparency, explainability, provability, and enablement for innovation as core characteristics and explicitly links them to constitutional values and developmental priorities.
Rather than relying on a single regulatory intervention, the framework adopts a layered structure. It moves from law to rules framed under law, regulatory guidance, standards, and…
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