India AI Governance Guidelines Enabling Safe and Trusted AI Innovation
The India AI Governance Guidelines provide a comprehensive framework balancing AI innovation with accountability and safety, structured around seven foundational sutras. The document establishes recommendations across six pillars including infrastructure, capacity building, policy and regulation, risk mitigation, accountability, and institutional oversight. It outlines a whole-of-government approach to operationalize these recommendations through bodies such as the AI Governance Group and the AI Safety Institute. Furthermore, it details practical guidelines for industry actors and regulators to ensure responsible AI implementation and innovation aligned with India's national priorities.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
This document is for policymakers, regulators, industry actors, researchers, and public sector bodies seeking guidance on safe and trusted AI innovation in India.
What the document contains
The document addresses comprehensive AI governance strategies across infrastructure access, capacity building, policy and regulation, risk mitigation, accountability models, and institutional frameworks. It covers the application of existing laws, copyright issues, content authentication, deepfake mitigation, and the integration of AI with Digital Public Infrastructure.
The text does not provide binding statutory rules or immediate punitive penalties for AI non-compliance, leaving detailed enforcement mechanisms to future sectoral regulations and legislative amendments.
- The framework is guided by seven core principles known as sutras, emphasizing trust, human-centric design, and responsible innovation over cautionary restraint.
- India's approach relies on empowering existing sectoral regulators rather than creating a separate overarching AI law, leveraging existing statutes alongside targeted amendments.
- The guidelines integrate AI development with Digital Public Infrastructure (DPI) to ensure scalability, affordability, and inclusive development.
- An AI Governance Group (AIGG) and an AI Safety Institute (AISI) are proposed to coordinate cross-sectoral policy, institutional oversight, and technical safety testing.
- A graded liability system and a national AI incidents database are introduced to monitor real-world harms and ensure proportionate accountability.
01 Preface 02 Foreword Table of Contents Introduction Executive Summary Part 1: Key Principles Part 2: Issues & Recommendations · 2.1 Infrastructure · 2.2 Capacity Building · 2.3 Policy & Regulation · 2.4 Risk Mitigation · 2.5 Accountability · 2.6 Institutions Part 3: Action Plan Part 4: Practical Guidelines for Industry & Regulators Glossary Annexures References
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
4/5Clear responsibility for AI outcomes
Adopt a graded liability system based on the function performed, level of risk, and whether due diligence was observed.
Part 2 - Key Recommendations: 05 Accountability
screening score · 2026-10-23
Fairness
4/5Non-discrimination and equitable treatment
AI systems should be designed and tested to ensure that outcomes are fair, unbiased, and do not discriminate against anyone
Part 1: Key Principles
screening score · 2026-10-23
Human Dignity
3/5Respect for the inherent worth of persons
Human-centric design, human oversight, and human empowerment.
Part 1 - Key Principles: People First
screening score · 2026-10-23
Human Oversight
4/5Humans remain in control of consequential decisions
Require human oversight and other safeguards to mitigate loss of control risks especially in sensitive sectors involving critical infrastructure.
Recommendations
screening score · 2026-10-23
Privacy
4/5Protection of personal data and private life
The Digital Personal Data Protection Act (DPDP Act) which governs the collection and processing of all digital personal data in India
2.3 Policy & Regulation
screening score · 2026-10-23
Transparency
4/5Openness about how AI systems work and are used
Provide disclosures and explanations that can be understood by the intended user and regulators.
Part 1 - Key Principles: Understandable by Design
screening score · 2026-10-23
Enforcement
4/5Consequences and compliance mechanisms with real force
Applicable laws should be enforced, while guidelines can assist organisations in meeting their obligations
Part 2 - Key Recommendations: 05 Accountability
screening score · 2026-10-23