India is taking a measured, "no rush" approach to AI governance. The strategy is to first leverage and adapt existing legal frameworks—like the IT Act for deepfakes and data protection laws for privacy—rather than creating new, potentially innovation-stifling AI-specific legislation.

Instead of competing to build sovereign AI stacks from the chip up, India's strategic edge is in applying commoditized AI models to its unique, population-scale problems. This leverages the country's deep experience with real-world, large-scale implementation.

India is leveraging its upcoming AI Impact Summit to establish itself as the voice for the Global South in AI policy. By championing inclusive AI and showcasing successful development applications in healthcare and agriculture, India aims to create an alternative to the Western-centric AI narrative.

The India AI Impact Summit is framed by three principles: people, planet, and progress. This philosophy aims to democratize AI, ensuring it's accessible and beneficial for developing nations, moving beyond the typical safety-focused narrative of Western summits and championing Global South inclusion.

The current movement towards impact-focused business is not just a trend but a fundamental economic succession. Just as the tech revolution reshaped global industries, the impact revolution is now establishing a new paradigm where companies are valued on their ability to create both profit and positive contributions to society and the planet.

Indian startups are carving a competitive niche by focusing on the AI application layer. Instead of building foundational models, their strength lies in developing and deploying practical AI solutions that solve real-world problems, which is where they can effectively compete on a global scale.

India's Ministry of Electronics and IT (Meti) acts as a promoter and facilitator for the AI sector, not a traditional regulator. It uses "policy nudges" and strategic programs like the India AI Mission to coordinate and foster collaboration between private companies, academia, and research organizations.

For India, "leapfrogging" with AI means overcoming systemic resource shortages. AI acts as a horizontal productivity multiplier, enabling, for example, a limited number of doctors to deliver better healthcare outcomes through AI-powered diagnostics, thus enhancing sectoral capacity without massive infrastructure investment.

The discussion highlights the impracticality of a global AI development pause, which even its proponents admit is unfeasible. The conversation is shifting away from this "soundbite policy" towards more realistic strategies for how society and governments can adapt to the inevitable, large-scale disruption from AI.