New Delhi, Feb 8 The upcoming ‘India-AI Impact Summit 2026’ is being organised through seven Chakras or Working Groups, structured around seven interconnected thematic areas, and each Chakra focuses on a core area of AI impact, and translates the Sutras into concrete areas of action across policy and real-world applications, an official statement said on Sunday.
Each Chakra fosters multilateral collaboration on AI's societal impacts, from building skills to ensuring ethical deployment. These are: Human Capital; Inclusion for Social Empowerment; Safe and Trusted AI, Science; Resilience Innovation and Efficiency; Democratizing AI Resources; and AI for Economic Development and Social Good.
“Through these Chakras, India aims to shape global AI norms while addressing local challenges. The outcomes of the Summit will guide policy makers, investors, and industry leaders in the years ahead,” said the statement.
Over 100 countries worldwide have engaged through these Working Groups to shape a future of responsible and inclusive AI. The India-AI Impact Summit 2026, from February 16-20, has attracted significant high-level engagement, with 15–20 Heads of Government, over 50 international ministers, and more than 40 global and Indian CEOs expected to participate.
According to the statement, the Summit is guided by three foundational pillars, referred to as Sutras, which articulate the core principles guiding global cooperation on AI: People, Planet and Progress.
The India–AI Impact Summit 2026 strengthens India’s role as a key platform for shaping the global AI agenda. Anchored in the Seven Chakras and the Three Sutras of People, Planet, and Progress, the Summit advances a development-oriented framework for artificial intelligence.
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The Summit positions India as a convenor and partner in global AI cooperation, supporting shared standards, collaborative frameworks, and scalable solutions for public good. It marks a transition from dialogue to delivery, reinforcing India’s commitment to responsible, inclusive, and development-focused AI pathways.
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