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India AI Governance Guidelines
Enabling Safe and Trusted AI Innovation
Posted On: 15 FEB 2026 11:12AM by PIB Delhi
Key Takeaways
India adopts a principle-based AI governance framework anchored in seven Sutras to enable safe,
trusted, and inclusive AI innovation across sectors.
The guidelines recommends establishment of new national institutions including the AI Governance
Group, Technology & Policy Expert Committee, and AI Safety Institute.
AI governance guidelines prioritises innovation over restraint, positioning AI as a catalyst for
inclusive growth, competitiveness, and the vision of Viksit Bharat 2047.
Introduction
Artificial Intelligence has emerged as the defining force of the Fifth Industrial Revolution, and India has
articulated a clear, ambitious vision: to build the full AI stack, anchored in national priorities. India’s AI
strategy is not confined to technological prowess alone; it is rooted in democratisation, scale, and
inclusion. The objective is to ensure that AI is not concentrated in a handful of firms or geographies,
but diffused across agriculture, healthcare, education, governance, manufacturing, and climate action. By
focusing on “AI for All,” India seeks to combine sovereign capability with open innovation—leveraging
public digital infrastructure, indigenous model development, and affordable compute to drive productivity
and inclusive growth. This approach aligns AI development with the broader aspiration of Viksit Bharat
2047, positioning AI as a catalyst for economic transformation, social empowerment, and strategic
autonomy.India’s achievements reflect this deployment-first philosophy. Under the IndiaAI Mission, over 38,000
GPUs have been onboarded through a subsidised national compute facility. AIKosh now hosts more than
9,500 datasets and 273 sectoral models, strengthening indigenous model development. The National
Supercomputing Mission has operationalised 40+ petaflop systems, including AIRAWAT and PARAM
Siddhi-AI. On the capacity front, IndiaAI and FutureSkills initiatives are supporting 500 PhDs, 5,000
postgraduates, and 8,000 undergraduates, while 570 AI Data Labs and 27 IndiaAI labs across states
are expanding grassroots innovation. With nearly 90 per cent of startups integrating AI in some form,
India is embedding AI deeply into its innovation ecosystem.
The India AI Governance Guidelines, releasing in AI Impact Summit 2026, arrive at a critical juncture
to consolidate these gains. Anchored in seven guiding sutras, the framework adopts a principle-based,
techno-legal approach. By establishing new institutions such as the AI Governance Group, the Technology
& Policy Expert Committee, and the AI Safety Institute, India is institutionalising a whole-of-government
model that balances innovation with safeguards. The guidelines strengthen India’s ambition to lead not
only in AI adoption and capability, but also in responsible, inclusive, and trusted AI governance
globally.
India’s AI Governance Philosophy
India seeks to harness the transformative potential of artificial intelligence for inclusive development and
global competitiveness, while addressing the risks it may pose to individuals and society. To advance this
objective, the Ministry of Electronics and Information Technology (MeitY) constituted a drafting
committee in July 2025 to develop a framework for AI governance in India. The Committee was
mandated to draw on existing laws, review global developments, examine available literature, and
incorporate public feedback in framing suitable governance guidelines.
Based on its deliberations, the Committee presented the AI governance framework in four parts. The
first part sets out the seven sutras that ground India’s AI governance philosophy. The second part
examines key issues and offers recommendations. The third part presents an action plan, and the fourth
part provides practical guidelines for industry actors and regulators to ensure consistent and responsible
implementation of the recommendations.
Part 1: Key Principles
The key principles of the AI Governance framework have been carefully designed to ensure cross-sectoral
applicability and technology neutrality, enabling relevance across diverse use cases and stages of
technological evolution. Together, these principles provide a flexible and future-ready foundation for
responsible AI development and deployment.
1. Trust is the Foundation 2. People FirstTrust is essential to support innovation, adoption, AI governance should place people at the centre.
and progress, as well as risk mitigation. Without AI systems must be developed and deployed in
trust, the benefits of artificial intelligence will not ways that strengthen human agency and reflect
be realised at scale. Trust must be embedded societal values. From a governance standpoint,
across the value chain – i.e. in the underlying this requires that humans retain meaningful
technology, the organisations building these tools, control over AI systems wherever possible,
the institutions responsible for supervision, and supported by effective human oversight. A people-
the trust that individuals will use these tools first approach also emphasises capacity building,
responsibly. Therefore, trust is the foundational ethical protections, and safety considerations.
principle that guides all AI development and
deployment in India.
3. Innovation over Restraint 4. Fairness and Equity
AI-led innovation is a pathway to achieving Promoting inclusive development is a central
national goals, such as socio-economic objective of India’s AI governance approach. AI
development, global competitiveness, and systems should therefore be designed and
resilience. Therefore, AI governance frameworks evaluated to ensure fairness and to avoid bias or
should actively encourage adoption and serve as a discrimination, particularly against marginalised
catalyst for impactful innovation. That said, communities. At the same time, AI should be
innovation should be carried out responsibly and actively used to advance inclusion while reducing
should aim to maximise overall benefit while risks of exclusion and unequal outcomes.
reducing potential harm. All other things being
equal, responsible innovation should be prioritised
over cautionary restraint.
5. Accountability 6. Understandable by Design
To ensure that India’s AI ecosystem progresses Understandability is fundamental to building trust
based on trust, AI developers and deployers and should be a core design feature, not an
should remain visible and accountable. afterthought. Though AI systems are probabilistic,
Accountability should be clearly assigned based they must have clear explanations and disclosures
on the function performed, risk of harm, and due to help users and regulators understand how the
diligence conditions imposed. Accountability may system works, what it means for the user, and the
be ensured through a variety of policy, technical, likely outcomes intended by the entities deploying
and market-led mechanisms. them, to the extent technically feasible.
7. Safety, Resilience and Sustainability
AI systems should be designed with safeguards to minimise risks of harm and should be robust and
resilient. These systems should have capabilities to detect anomalies and provide early warnings to
limit harmful outcomes. AI development efforts should be environmentally responsible and resource-
efficient, and the adoption of smaller, resource-efficient ‘lightweight’ models should be encouraged.Together, these seven principles establish a coherent and balanced AI governance framework that
enables innovation while safeguarding trust, equity, and accountability. They reflect India’s
commitment to a people-centric, inclusive, and future-ready AI ecosystem. By aligning technological
progress with societal values and developmental priorities, the framework provides a strong foundation for
responsible AI adoption at scale.
Part 2: Key Issues and Recommendations
Using the seven principles or sutras as guidance, the Committee recommends an approach to AI
governance that fosters innovation, adoption, and scientific progress, while proposing measures to
mitigate the risks to individuals and communities. Effective governance includes not just regulation, but
also other forms of policy engagement, including building capacity, infrastructure development, and
institution building. The Committee has made recommendations across six pillars.
1. Infrastructure
India’s AI governance framework seeks to promote innovation and large-scale adoption while mitigating
societal risks. Under the India AI Mission, significant progress has been made in strengthening core
infrastructure, including improved access to compute and datasets, development of foundational models,
and deployment of AI applications, building on Digital Public Infrastructure (DPI), enhanced data sharing,
and safety testing. To sustain this momentum, continued investment in scalable infrastructure,
equitable access to compute and data, and strong institutional capacity will be essential.
Foundational AI Infrastructure Ecosystem The Committee Further Recommends:
38,000+ GPUs onboarded under IndiaAI Mission Empowering the India AI Mission and
(target: 100,000), subsidised access via IndiaAI governments to expand AI adoption through
Compute Portal. infrastructure and compute access.
AIKosh hosting 9,500+ datasets and 273 sectoral Improving data availability and sharing
models. through strong data governance and portability
National Supercomputing Mission (40+ standards.
petaflops machines) including AIRAWAT & Promoting locally relevant datasets to develop
PARAM Siddhi-AI. culturally representative AI models.
Ongoing AI integration with Digital Public Ensuring access to evaluation datasets and
Infrastructure (DPIs). compute for AI deployment and safety testing.
Integrating AI with DPI to enable scalable and
inclusive deployment.What is Digital Public Infrastructure?
Digital Public Infrastructure (DPI) refers to foundational digital systems that are accessible,
secure, and interoperable, supporting essential public services. For example: Aadhaar, UPI,
DigiLocker, Government e-Marketplace, UMANG, PM GatiShakti, among others.
2. Capacity Building
India has launched multiple AI capacity-building initiatives, including IndiaAI FutureSkills,
FutureSkills PRIME, and higher education programmes, laying a strong foundation for an AI-ready
workforce. As AI adoption accelerates, further scaling these efforts will help meet the demands of
inclusive growth and broader access. Expanding AI exposure for small businesses and citizens, alongside
strengthening technical capacity within the public sector, will support effective procurement, risk
management, and responsible deployment of AI systems.
Existing AI Human Resource & Innovation The Committee Further Recommends:
Capacity
Ongoing initiatives such as IndiaAI, FutureSkills Enhancing public awareness and trust in AI
are supporting 500 PhDs, 5,000 PGs, 8,000 UGs. through regular training programmes and
AI Data Labs Network consists of 570 labs across awareness campaigns.
Tier-2 and Tier-3 cities to build grassroots AI Training government officials and regulators to
capabilities through training in data annotation, support informed procurement and responsible AI
curation, and applied AI skills use.
AI-linked curriculum is integrated under National Building capacity of law enforcement agencies
Education Policy 2020 to detect and address AI-enabled crimes.
27 IndiaAI Data and AI Labs established + 174 Expanding AI skilling initiatives in vocational
ITIs approved across 27 States/UTs. institutes and tier-2 and tier-3 cities.
YUVA AI for ALL free foundational course
launched for mass AI literacy.
3. Policy & Regulation
The objective of the AI governance approach is to promote innovation, adoption, and technological
progress while ensuring that risks to individuals and society are mitigated across the AI value chain. A
review of the existing legal framework—comprising constitutional provisions, statutes, rules,
regulations, and guidelines across domains such as information technology, data protection,
intellectual property, competition, media, employment, consumer protection, and criminal law—
indicates that many AI-related risks can be addressed under current laws.
At the same time, there is an urgent need for a comprehensive review of relevant laws to identify
regulatory gaps relating to AI systems, including issues of classification and liability across the AI value
chain, application of data protection principles to AI development, misuse of generative AI and challenges
around content authentication and provenance, use of copyrighted material in AI training, and sector-
specific risks in sensitive domains. While some of these issues are already under deliberation through
inter-ministerial consultations, rulemaking, and expert committees, the rapid evolution of AI—including
increasingly autonomous systems—poses challenges for regulatory frameworks to remain timely,
coherent, and future-ready.Policy Foundations for Responsible AI The Committee Further Recommends:
IndiaAI Mission (2025) for AI sovereignty, Adopting a balanced, agile, and principle-based AI
democratisation of compute access, governance framework that builds on existing laws.
indigenous model development, and Reviewing the current legal framework to identify
responsible AI capacity building. AI-related risks and regulatory gaps.
IT Rules, 2021 & Amendments to provide Introducing targeted legislative amendments to
the baseline intermediary liability structure clarify issues of classification, liability, data
and enforcement backbone for AI-related protection, and copyright.
harms within existing digital regulation. Developing common standards and benchmarks for
Digital Personal Data Protection Act, 2023 content authentication, data integrity, cybersecurity,
(DPDP Act) to support accountability and and fairness.
lawful AI deployment by regulating personal Enabling expert-led guidance through the AI
data processing, consent, and fiduciary Governance Group (AIGG) with support from the
obligations. Technology & Policy Expert Committee (TPEC).
Information Technology (Intermediary Using regulatory sandboxes to test emerging AI
Guidelines and Digital Media Ethics Code) technologies in controlled environments.
Rule 2026 for AI-generated and deepfake Strengthening international and multilateral
content. engagement on AI governance issues.
Conducting horizon-scanning and foresight
exercises to keep regulation responsive to future AI
developments.
4. Risk Mitigation
Risk mitigation is central to translating policy and regulatory principles into practical safeguards
that prevent or reduce harm from AI systems. Given that AI systems are probabilistic, generative,
adaptive, and agentic, they can introduce new risks or amplify existing ones across individuals, markets,
and society. These risks include malicious uses such as AI-enabled misinformation and cyberattacks; bias
and discrimination arising from inaccurate or unrepresentative data; transparency failures in the use of
personal data; systemic risks linked to market concentration and geopolitical instability; loss of control
over AI systems; and threats to national security and critical infrastructure.
Vulnerable groups face heightened exposure to these harms, particularly children—through
exploitative recommendation systems—and women, who are disproportionately targeted by AI-generated
deepfakes. Despite global and domestic efforts to classify and assess AI risks, India needs a profound
context-specific risk assessment framework grounded in empirical evidence of real-world harms. The
presence of a structured mechanism to systematically collect, analyse, and learn from AI-related
incidents would equip policymakers, regulators, and institutions to anticipate emerging risks, design
proportionate safeguards, and ensure accountability across sectors.
Existing Risk Mitigation The Committee Further Recommends:Indian Computer Emergency Response Team Developing an India-specific AI risk assessment
(CERT-In) is a national agency for cyber incident and classification framework with a focus on
response, coordination, and real-time threat vulnerable groups.
advisories. Establishing a national, federated AI incident
The Indian Cyber Crime Coordination Centre reporting mechanism to track harms and inform
(I4C), established to combat cybercrime in a oversight.
coordinated and comprehensive manner Encouraging proportionate voluntary risk-
National Critical Information Infrastructure mitigation frameworks through standards,
Protection Centre (NCIIPC) is a Nodal body for audits, and incentives.
safeguarding critical information infrastructure Embedding transparency, fairness, and
across strategic sectors. security by design using appropriate techno-legal
Reserve Bank of India, Securities and measures.
Exchange Board of India, Insurance Mandating human oversight and safeguards to
Regulatory and Development Authority of mitigate loss-of-control risks in sensitive and
India etc. are sectoral regulators enforcing critical sectors.
domain-specific technology, cybersecurity, and
risk management norms.
National Cyber Coordination Centre (NCCC)
strengthens real-time cyber threat monitoring and
situational awareness, while the Data Protection
Board of India (under the Digital Personal
Data Protection Act, 2023) serves as the
statutory enforcement body for data protection
compliance and accountability.
5. Accountability
Accountability is the backbone of AI governance, yet ensuring it in practice is challenging. Many AI-
related risks can be addressed under existing laws, but their effectiveness depends on predictable and
timely enforcement. Firms need meaningful pressure to comply, while regulators require visibility into
organisational practices and the AI value chain. Current voluntary frameworks lack legal enforceability,
and there is insufficient clarity on how liability should be attributed across developers, deployers, and end-
users. Users often lack accessible and effective grievance redressal mechanisms, and transparency in AI
system design, data flows, and organisational decision-making remains limited. AI systems’ probabilistic
and adaptive nature may also generate unexpected outcomes, requiring a governance approach that
balances enforcement with space for responsible innovation.
Existing Accountability & Compliance The Committee Further Recommends:
MechanismsIT Act, 2000 provides the foundational legal Clarifying applicability of existing laws to AI
framework governing digital intermediaries, cyber across the value chain through guidance notes or
offences, and platform liability across the AI value master circulars.
chain. Implementing graded obligations and liability
Digital Personal Data Protection Act, 2023 proportional to function, risk, and due diligence of
establishes consent-based data processing, AI actors.
fiduciary obligations, and accountability standards Strengthening enforcement and accountability
for AI systems handling personal data. mechanisms including transparency reports,
IT Rules, 2021 & IT Amendment Rules 2026 audits, and self-certifications.
provide grievance redressal mechanisms and Mandating accessible grievance redressal
expedited takedown timelines for AI-generated mechanisms with clear feedback loops and timely
and synthetic content harms. resolution.
Improving transparency of the AI value chain
to enable effective regulatory oversight.
6. Institutions
India’s AI governance framework would benefit from a coordinated “whole-of-government” approach to
strengthen coherence and effectiveness. At present, responsibilities are distributed across multiple
agencies, creating opportunities to enhance cross-sectoral coordination and strategic alignment.
Establishing a permanent inter-agency mechanism could help oversee national AI strategy, assess
emerging risks, guide implementation, and promote responsible innovation. While institutions such as
MeitY, CERT-In, and the RBI play vital sector-specific roles, closer integration of technical expertise on
AI policy, safety, and ethics would enable more robust risk assessment, guideline development, and
informed engagement with industry, while ensuring alignment with India’s domestic and international
strategic priorities.
Existing Institutional Architecture for AI The Committee Further Recommends:
Governance
Ministry of Electronics and Information Establish an AI Governance Group (AIGG) to
Technology is an apex ministry for the coordinate overall policy development and align
development of AI policy. AI governance frameworks with national
NITI Aayog anchor institution for the priorities and strategic objectives.
development of India’s National AI Strategy, Constitute a Technology & Policy Expert
providing strategic vision, policy advisory Committee (TPEC) to provide expert inputs to
support, and cross-sectoral coordination on AI the AI Governance Group on matters of national
adoption and innovation. and international importance relating to AI
governance.
Provide adequate resources to the IndiaAI
Safety Institute to conduct research, develop
draft standards and their evaluation metrics and
testing methods and benchmarks, collaborate with
international bodies, national standard making
bodies and provide technical guidance to
regulators and industry.Whole-of-Government Approach
A coordinated framework where all relevant ministries, sectoral regulators, standards bodies, and public
institutions collaborate to develop, implement, and oversee AI policy. This ensures alignment of
strategies, avoids duplication, and promotes cohesive governance across sectors.
Part 3: Action Plan
The Action Plan sets out a phased roadmap for the institutionalisation of AI governance, risk mitigation,
and sustained adoption across sectors. It aligns short-term priorities with medium- and long-term reforms
to translate governance principles into responsible, scalable, and inclusive outcomes, while remaining
responsive to technological advances and emerging risks.
Short-Term Medium-Term Long-Term
Establish the key governance Publish common standards (e.g. Continuously review and monitor
institutions such as AIGG & content authentication, data the governance framework and
TPEC. integrity, fairness, activities under this Action Plan.
cybersecurity)
Develop India-specific AI risk Operationalise national AI Adopt new laws to account for
assessment and classification incidents database with emerging risks and capabilities.
frameworks with sectoral localised reporting and
inputs. feedback loops.
Conduct regulatory gap Amend laws, as may be Expand global diplomatic
analysis, suggest appropriate needed, to address regulatory engagement and contribute to
legal amendments and rules & gaps. standards development.
adopt voluntary frameworks to
promote responsible innovation
and mitigate risks.Publish a master circular with Pilot regulatory sandboxes in Conduct horizon-scanning &
applicable regulations and best high-risk domains. scenario planning to prepare for
practices to support future risks and opportunities.
compliance.
Prepare the groundwork for AI Support the integration of DPI
incidents database and with AI with policy enablers
grievance redressal
mechanisms & develop clear
liability regimes.
Expand access to foundational
infrastructure for AI.
Launch public awareness
programmes and operationalise
Safe and Trusted tools.
The AI Governance Guidelines are designed to deliver practical impact by strengthening institutions,
managing risks effectively, and enabling responsible AI adoption, while fostering innovation, trust, and
accountability across sectors. In the short term, coordinated institutions, India-specific risk frameworks,
incident reporting mechanisms, voluntary compliance, and public awareness initiatives will build trust and
governance capacity. Over the medium term, common standards, regulatory sandboxes, updated laws,
and DPI integration will support safe innovation and smoother compliance. In the long term, India will
establish a balanced, agile, and future-ready AI governance ecosystem with strong accountability,
resilience to emerging risks, and enhanced global leadership in responsible AI governance.
Together, these outcomes will ensure that India’s AI ecosystem remains innovative, inclusive, and
resilient, advancing technological progress while safeguarding societal interests.
Part 4: Practical Guidelines for Industry & Regulators
To enable consistent and responsible implementation of the AI Governance Framework, the Committee
sets out practical guidance for industry participants involved in developing or deploying AI systems,
alongside principles to guide policy formulation and enforcement by government agencies and sectoral
regulators. These guidelines are intended to support innovation and adoption while ensuring that risks are
addressed in a proportionate and context-appropriate manner.
The Committee recommends that any The Committee suggests the following principles
person involved in developing or deploying to guide policy formulation and implementation
AI systems in India should be guided by the by various agencies and sectoral regulators in
following: their respective domains:
Comply with all Indian laws and regulations, The twin goals of any proposed AI governance
including but not limited to laws relating to framework is to support innovation, adoption and the
information technology, data protection, distribution of the technology’s benefits to society,
copyright, consumer protection, offences while ensuring that potential risks can be addressed
against women, children, and other vulnerable through policy instruments.
groups that may apply to AI systems.Demonstrate compliance with applicable laws Governance frameworks should be flexible and agile,
and regulations when called upon to do so by such that it enables periodic reviews, monitoring, and
relevant agencies or sectoral regulators. recalibration based on stakeholder feedback.
Adopt voluntary measures (principles, codes, When using policy instruments to mitigate risks,
and standards), including with respect to regulators should prioritise those where there is real
privacy and security; fairness, inclusivity; non- and present harm or a threat to life, livelihood or
discrimination; transparency; and other well-being
technical and organisational measures
Create a grievance redressal mechanism to Proposed AI governance frameworks should avoid
enable reporting of AI-related harms and compliance-heavy requirements (for example,
ensure resolution of such issues within a mandatory approvals, licensing conditions, etc.)
reasonable timeframe. unless deemed necessary
Publish transparency reports that evaluate the The appropriate regulator or agency should
risk of harm to individuals and society in the determine which type of policy instrument is the
Indian context. If they contain any sensitive or most useful, relevant, and least burdensome to
proprietary information, the reports should be achieve the desired objective (for example, industry
shared confidentially with relevant regulators. codes, technical standards, advisories, binding rules).
Explore the use of techno-legal solutions to Regulators should encourage the use of techno-legal
mitigate the risks of AI, including privacy- approaches to meet policy objectives around privacy,
enhancing technologies, machine unlearning cybersecurity, fairness, transparency, etc. where such
capabilities, algorithmic auditing systems, and policy measures have already been put in place.
automated bias detection mechanisms.
These practical guidelines are intended to support consistent, lawful, and responsible development and
deployment of AI systems in India. By clarifying expectations for industry and guiding proportionate
policy action by regulators, they aim to enable innovation and adoption while strengthening trust,
accountability, and effective risk management across sectors.
Conclusion
The India AI Governance Guidelines present a pragmatic, balanced, and agile framework that promotes
safe, trusted, and responsible development and adoption of artificial intelligence in the country. Rooted in
the seven guiding sutras — Trust is the Foundation, People First, Innovation over Restraint, Fairness &
Equity, Accountability, Understandable by Design, and Safety, Resilience & Sustainability — the
guidelines ensure that AI serves as an enabler for inclusive development, economic growth, and global
competitiveness, while effectively addressing risks to individuals and society through proportionate,
evidence-based measures.
Enabled by coordinated institutional leadership — including the Ministry of Electronics and
Information Technology as the nodal ministry, the AI Governance Group for strategic coordination, the
Technology & Policy Expert Committee for expert advisory, the AI Safety Institute for technical
validation and safety research, and sectoral regulators for domain-specific enforcement, this framework is
designed to foster innovation, build public trust and position India as a responsible leader in the global AI
ecosystem.Through this structured and forward-looking architecture, India aims to realise the vision of AI for All,
ensuring that the transformative potential of artificial intelligence contributes meaningfully to the national
aspiration of Viksit Bharat by 2047, with benefits reaching every citizen in a safe, inclusive and
sustainable manner.
References
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