India AI Governance Guidelines Enabling Safe and Trusted AI Innovation
The India AI Governance Guidelines provide a comprehensive, balanced framework aimed at promoting AI innovation and inclusive development while mitigating societal risks. Structured across four parts, the guidelines establish seven foundational sutras, detail recommendations across six pillars covering enablement, regulation, and oversight, set forth a multi-stage action plan, and offer practical guidance for industry and regulators. The document advocates a pro-innovation, techno-legal approach utilizing existing laws and Digital Public Infrastructure rather than creating a separate standalone AI statute.
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, AI developers, and researchers seeking to understand India's strategy for safe, trusted, and inclusive AI innovation.
What the document contains
The document covers a strategic national framework for artificial intelligence governance in India, addressing infrastructural enablement, capacity building, policy and regulation, risk mitigation, accountability, and institutional oversight. It outlines specific measures for data and compute access, digital public infrastructure integration, content authentication, copyright considerations, risk assessment, and incident reporting.
The text does not prescribe a new dedicated overarching AI statute, nor does it contain binding legislative text or specific punitive monetary fines for non-compliance at this stage.
- India's AI governance framework prioritizes inclusive development, innovation, and trust, anchored by seven core sutras.
- A separate standalone AI law is deemed unnecessary at this stage, as existing statutes combined with targeted amendments can adequately address current risks.
- The framework integrates AI development with Digital Public Infrastructure (DPI) to ensure scalability, affordability, and local relevance.
- An institutional architecture including the AI Governance Group (AIGG), Technology & Policy Expert Committee (TPEC), and AI Safety Institute (AISI) is proposed to oversee implementation.
- A graded liability system and voluntary frameworks are encouraged to foster responsible innovation without imposing compliance-heavy burdens.
· Preface · Foreword · Introduction · Executive Summary · Part 1: Key Principles · Part 2: Issues & Recommendations · 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
screening score · 2026-10-23
Fairness
4/5Non-discrimination and equitable treatment
Promote inclusive development and avoid discrimination.
Part 1
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
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
Part 2
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
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
screening score · 2026-10-23