The Government of India has released the India AI Governance Guidelines, which intends to lay and shape a robust national framework for how Artificial Intelligence (AI) is to be developed, deployed and supervised in the country. The objective is clear: To encourage innovation and economic growth and ensure individuals, communities and national interests are protected.
Core Principles
The guidelines rest on seven governing principles. Trust must form the basis for all AI innovation and deployment. AI systems should be designed around human oversight and human welfare using a people first approach. The framework promotes fairness and equity by mandating that AI systems should avoid bias discrimination and be inclusive. Innovation is prioritized, balanced with responsibility. Accountability is to be assigned to those who build and deploy AI systems. Disclosures should be provided to users and regulators to explain and understand systems. Finally, AI must be safe, resilient and environmentally sustainable.
Key Recommendations
The framework provides a structured plan through six focus areas-
- Infrastructure: India seeks to expand access to compute resources, datasets and digital public infrastructure. India’s AI Mission is to build national compute capacity, data-sharing platforms and sovereign large language models. Access to compute and representative datasets is considered critical to encourage adoption, particularly among start-ups and small enterprises.
- Capacity building: Widespread skilling is essential for adoption. Training programs are to be expanded for students, researchers, government officials and law enforcement agencies. The goal is to create AI literacy, build confidence, and ensure institutions understand AI risks and opportunities.
- Policy and regulation: The main idea here is to adopt a flexible framework with the aim to support innovation and mitigate risks of AI. The current assessment is that most risks associated with AI can be addressed through existing laws relating to information technology, data protection, intellectual property and criminal law. Targeted legislative amendments may be introduced, for example in copyright and platform liability. Standards will be developed for areas like content authentication, fairness, data integrity and cybersecurity.
- Risk mitigation: The framework recognizes risks such as deepfakes, bias, lack of transparency, systemic risks, national security threats, harm to vulnerable groups and possible loss of human control. India plans to build an AI incidents reporting system to document real world harms to understand AI-related risks in the Indian context. Voluntary measures, human oversight and techno-legal safeguards are encouraged to prevent harm.
- Accountability: A graded liability model is recommended. Responsibility will depend on the role and level of risk. Industries should provide grievance redressal channels, maintain transparency about data and model usage, and demonstrate compliance when required by regulators. Transparency reports, self-certification through auditors, internal policies, committee hearing, peer monitoring and techno-legal measures are to be adopted into voluntary frameworks at the organizational and industrial level.
- Institutions: The guidelines outline an institutional structure to coordinate governance. A high-level AI Governance Group (AIGG) will steer national policy across ministries and regulators. A Technology and Policy Expert Committee (TPEC) will provide specialized guidance on matters of national importance in relation to AI policy and governance. The AI Safety Institute (AISI) will lead research, risk assessment, promote adoption of AI safety tools and development of safety standards, and will interface with international AI safety networks.
Action Plan
Identifies implementation of these guidelines into three phases-
- Short term actions include creating governance institutions, drafting India specific risk frameworks, expanding compute and data access, adopting voluntary frameworks, suggest legal amendments, develop liability regimes, launch awareness programmes and expand access to infrastructure and safety tools.
- Medium term actions include operationalizing the incidents database, issuing common standards on content authentication and fairness, amending laws where necessary and piloting regulatory sandboxes.
- Long term actions include continuous monitoring, foresight research, drafting new laws on emerging risks and ensure sustainability of the digital eco-system on global AI governance.
Practical Guidelines for Industry and Regulators
Industries are expected to comply with all Indian laws, adopt voluntary frameworks, publish transparency reports, and create grievance mechanisms. Regulators are expected to support innovation, use flexible instruments, avoid unnecessary licensing burdens, and prioritize real harms. Techno-legal solutions are encouraged so that safety and accountability are built into system design.
Conclusion
The India AI Governance Guidelines reflect a future ready and pragmatic approach to AI governance. It is a hard balance of pro innovation competitive economic growth balanced with safe-guarding individuals and public risk at large. It is the first attempt at handling AI governance and certainly ambitious since there are many actors and regulators at play. To keep pace with a fast-moving technology will certainly be a challenge within India and globally. However, by combining infrastructure development, capacity building, risk management and modern regulatory thinking, India hopes to position itself to lead in building an AI ecosystem that is safe, trusted and globally competitive.
The India AI Governance Guidelines can be accessed here:
https://static.pib.gov.in/WriteReadData/specificdocs/documents/2025/nov/doc2025115685601.pdf