The Centre on Thursday moved to formalise India's approach to artificial intelligence with the constitution of the AI Governance and Economic Group (AIGEG), signalling a more coordinated policy framework.
The newly formed group will bring together key arms of government to address the increasingly complex and cross-sectoral nature of AI. Its mandate spans coordinating policy across ministries and regulators, ensuring compliance with existing laws, and overseeing governance issues that cut across industries. At a time when AI adoption is accelerating, the government is seeking to balance innovation with accountability.
The panel is chaired by the Minister for Electronics and IT, with the MoS serving as Vice-Chair, and includes the Principal Scientific Adviser, the Chief Economic Adviser, and the CEO of NITI Aayog. Key secretaries from departments such as Telecommunications, Economic Affairs, and Science & Technology are also part of the group, along with a representative from the National Security Council Secretariat. The Secretary of the Ministry of Electronics and Information Technology will act as Member Convener, anchoring the group's work and coordination.
A central focus of AIGEG will be to promote responsible AI deployment while identifying emerging risks and regulatory gaps. The group has also been tasked with examining whether current legal frameworks are sufficient, and where amendments may be required. Importantly, it will help shape India's broader strategy and position on global AI governance debates.
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Beyond regulation, the group will work closely with industry and stakeholders to develop a roadmap for AI deployment over the next decade. This includes a granular assessment of how AI will impact jobs, mapping roles that may be automated, augmented, or newly created, and analysing the geographical spread of these changes.
Recognising the potential disruption to the labour market, AIGEG will also design mitigation strategies and transition plans, factoring in India's large informal workforce, diverse skill levels, and regional variations. It will classify AI use cases into categories such as "deploy", "pilot", and "defer", based on readiness across data, skills, and legal frameworks.
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