AI Governance Framework for India 2025-26

⚡ Quick Summary

The AI Governance Framework for India 2025–26, developed by the National Cyber and AI Center (NCAIC), presents a robust, risk-based approach tailored to India’s unique socio-technical landscape. Grounded in principles of human-centricity, inclusion, and risk proportionality, it introduces a structured taxonomy for AI risks, lifecycle controls, and an assurance system aligned with global standards like ISO 42001 and NIST AI RMF. It outlines 100-day, 12-month, and 24-month roadmaps for rapid adoption, supported by templates, evaluation harnesses, and sector-specific blueprints for government and enterprise. The framework positions India not just as a regulatory responder, but as a proactive global leader in responsible AI.

🧩 What’s Covered

This 36-page national policy report integrates strategic vision with implementation pragmatism:

• Foundational Design Principles (p.5): Human-centricity, inclusivity, privacy and security by design, fairness, and explainability.
• Regulatory Alignment (p.6): Synchronization with India’s DPDP Act, CERT-In directions, sectoral regulations, and the IndiaAI Mission.
• Governance Model (p.7): A multi-tier structure with roles for boards, AI Risk and Ethics Committees (AIREC), and Chief AI Risk Officers.
• Risk Taxonomy (p.8): Defines prohibited, high-, medium-, and low-risk AI use cases—explicitly banning social scoring and emotion inference in employment.
• Lifecycle Controls:
  • AI System Inventory & Data Governance (pp.9–10)
  • Secure Model Development & Pre-deployment Evaluations (pp.11–12)
  • Deployment, Monitoring, and Decommissioning (pp.13–15)
• Technical Control Catalogue (p.16): Includes prompt injection defenses, fairness audits, and C2PA-based provenance tools.
• Assurance Framework (p.17): Supports tiered certifications—Basic, Enhanced, Premium—backed by independent testing and ISO 42001 alignment.
• Sector Blueprints:
  • Public Sector (p.18): Emphasizes transparency, AI sandboxes, and civic engagement.
  • Enterprise Sectors (p.19): Tailored approaches for BFSI, healthcare, telecom, and manufacturing.
• Implementation Plans:
  • 100-Day Plan (p.20)
  • 12-Month Maturity Development (p.21)
  • 24-Month Strategic Excellence (p.22)
• Reporting & Enforcement:
  • Performance Metrics Dashboard (p.23)
  • Enforcement Mechanisms & Safe Harbors (p.24)
  • Incident Response Protocols (p.25)
• Case Studies (pp.26–27): Real-world applications in payments and healthcare diagnostics.
• Tools & Templates (p.28): AIPIA, Model Cards, AIBOM, Evaluation Harnesses.
• International Alignment (p.29): Harmonization with ISO, NIST, and EU AI Act standards.
• Cultural Considerations (p.31): Focus on multilingualism, sustainability, and digital inclusion.
• Role of NCAIC (p.32): As the central coordinating body with national and international responsibilities.
• Future Outlook (p.33): A roadmap for India’s leadership in global AI governance through 2030.

💡 Why it matters?

India is projected to be one of the largest adopters and exporters of AI-enabled solutions globally. However, its vast linguistic diversity, socioeconomic inequalities, and high-stakes digital infrastructure (from Aadhaar to UPI) make AI failures not just risky—but potentially destabilizing. This framework ensures that governance is not an afterthought but a precondition for safe deployment. It also makes India one of the first major economies outside the EU to operationalize ISO 42001 at scale, signaling credibility to global partners, investors, and civil society. Its modular design—applicable to startups and ministries alike—offers a replicable governance template for other democracies navigating similar challenges.

❓ What’s Missing

• Enforcement Authority Clarity: While enforcement tools are listed (p.24), it’s unclear which bodies beyond CERT-In and sectoral regulators hold binding powers.
• SME Applicability: Though public and large private sector guidance is detailed, support for SMEs is minimal—particularly those without CARO-level resources.
• AI Lifecycle for Generative Models: Despite mentioning RAG security (p.16), LLM-specific development lifecycle controls are not deeply elaborated.
• Ethical Framework Integration: There is limited treatment of values-based AI dilemmas, especially those beyond bias (e.g., manipulation, autonomy erosion).
• Open Evaluation Tools: While it mentions evaluation harnesses, open-source tools or repositories are not detailed.

👥 Best For

• Public Sector Leaders tasked with deploying or regulating AI in citizen services.
• Chief AI Risk Officers & Governance Professionals implementing enterprise AI assurance.
• Regulators & Policymakers seeking harmonized compliance models.
• AI Vendors targeting government or regulated sectors in India.
• International observers interested in non-Western governance leadership models.

📄 Source Details

• Title: AI Governance Framework for India 2025–26
• Published by: National Cyber and AI Center (NCAIC)
• Date: September 1, 2025
• Website: www.ncaic.in
• License: Open license for adoption across India and internationally.

📝 Thanks to

The National Cyber and AI Center (NCAIC), the Ministry of Electronics and IT, IndiaAI Mission, CERT-In, and the diverse public-private contributors who made this benchmark governance framework possible.