What’s in India’s first AI rulebook? – Crypto News

With this, India joins a long list of countries that are drafting and adopting national strategies, ethical frameworks and regulatory tools for AI. Mint decodes India’s approach to AI governance and what it means for the industry.

What do the guidelines say?

The guidelines are structured around six governance pillars: infrastructure, capacity building, policy and regulation, risk mitigation, accountability, and institutions.

• Under infrastructure, they advocate expanding access to foundational resources.
• Capacity building emphasises developing skills, training, and awareness among citizens, public officials, and regulators, particularly in underserved areas.
• In the area of policy and regulation, the guidelines recommend reviewing existing laws and introducing targeted amendments where necessary.
• To support oversight, standards, and safety research, the guidelines introduce an AI Safety Institute, a Technology & Policy Expert Committee, and an AI Governance Group.

They also outline seven guiding principles, or sutras – trust, people first, innovation over restraint, fairness and equity, accountability, understandable by design, and safety, resilience, and sustainability.

What’s the government’s action plan?

The guidelines mention an action plan mapped to short-term, medium-term and long-term goals.

• The short-term plan includes forming governance bodies, drafting standards and India-specific AI risk assessment and classification frameworks with sectoral inputs, preparing the groundwork for AI incidents database and grievance redressal mechanisms, and launching public awareness and training programs for citizens and regulators on AI capabilities and risks.
• The medium-term plan includes piloting regulatory sandboxes, publishing standards, amending laws as needed and expanding national datasets.
• The long-term plan involves integrating AI safety testing, continuously updating sectoral laws, preparing for future risk and opportunities, and participating in global AI governance efforts.

Do other countries have such guidelines?

Many countries have introduced AI governance guidelines, ethical frameworks, or regulatory initiatives in the past couple of years.

For instance, in 2024 the European Union passed the EU AI Act, one of the most comprehensive AI regulatory frameworks worldwide. China has introduced and updated rules for generative AI services, content labeling and algorithm registration in the past two years as part of a more centralised governance model.

Singapore published its ‘Model AI governance framework’ back in 2019 and updated it for generative AI in 2024, while Canada has drafted the Artificial intelligence and Data Act (AIDA) to regulate ‘high-impact’ AI.

Which laws will govern AI in India?

The Indian government isn’t proposing a single comprehensive AI law at this stage. Its guidelines recommend applying and strengthening existing sectoral laws to govern AI systems. These include the Digital Personal Data Protection Act, 2023 for privacy and data-use compliance, and the Information Technology Act, 2000 for accountability, content moderation, and cybersecurity obligations.

Other relevant legal instruments include the Copyright Act, 1957 to address ownership of AI-generated content, and consumer protection, competition, and criminal laws that can be invoked for harm, fraud, or malpractice.

MeitY said these laws already provide a foundation for responsible AI deployment, but amendments or new rules may be introduced in the future as AI technology and risks evolve.

What does this mean for the industry?

For India’s technology and startup ecosystem, the AI governance guidelines mark a shift toward a more organised but still innovation-friendly regulatory setup.

Rather than impose a heavy compliance burden, the framework focuses on ‘innovation over restraint’, encouraging companies to follow voluntary best practices, stay transparent, and build ethics into their design.

It also creates space for regulatory sandboxes and graded accountability, providing room to test and experiment safely. For the industry, this means clearer rules around data use, model transparency, and risk management, along with greater policy stability that could boost investment and global partnerships.

However, while the guidelines mark a strong starting point for ensuring responsible AI deployment, they don’t yet spell out how enforcement or accountability will work, leaving much to depend on future interpretation and institutional capacity.