India to Showcase AI Impact, Sovereign Models and Safety Frameworks at AI Impact Summit

On the sidelines of the World Economic Forum Annual Meeting 2026 at Davos, Union Minister Ashwini Vaishnaw highlights India’s comprehensive strategy on artificial intelligence, semiconductors and deep-tech innovation, ahead of the upcoming AI Impact Summit.

Objectives of AI Impact Summit

• Focus on Impact: The primary objective of the AI Impact Summit is to demonstrate how AI models, applications, and ecosystems can improve efficiency, enhance productivity, and generate a multiplier effect for economic growth.
• Accessibility for Global South: The second objective is accessibility, particularly for India and the Global South, drawing inspiration from India’s success with UPI and Digital Public Infrastructure (DPI) and exploring whether a similar scalable and affordable AI stack can be developed.
• Safety and Guardrails: The third objective is AI safety, with emphasis on building guardrails, guidelines, and safety frameworks, and developing an AI regulatory and safety stack within India.

India’s Startup and Deep Tech Ecosystem

• Scale of Startup Growth: India now hosts nearly 200,000 startups, ranking among the top three startup ecosystems globally.
• Chip Design Startups: 24 Indian startups are engaged in chip design, one of the most complex domains, with 18 already receiving venture capital funding, reflecting investor confidence.
• Shift Towards Deep Tech: Over the past decade, there has been a clear shift towards deep tech innovation.

Five-Layer AI Ecosystem Framework

India’s AI strategy is structured around five interlinked layers: applications, models, semiconductors, infrastructure, and energy.

• Application Layer: The first layer focuses on real-world use cases, ensuring AI applications address practical challenges across sectors.
  • The application and usage layer offers the highest return on investment, with India leveraging its IT services sector to rapidly deploy AI across enterprise workflows.
• Model Layer: The second layer involves development of AI models tailored to enterprise and societal needs.
  • Nearly 95 percent of AI workloads are currently handled by small models, with 50-billion-parameter models sufficient for most enterprise needs.
  • India is developing a bouquet of around 12 focused AI models, capable of running on small GPU clusters at low cost for large-scale deployment.
• Semiconductor Layer: The third layer consists of chips and semiconductor manufacturing, which enable computational capability for AI systems.
  • India is prioritising manufacturing 28nm to 90nm range segment before advancing to cutting-edge nodes.
  • Nearly 75 percent of global chip volumes fall within this range, used in electric vehicles, automobiles, railways, defence, telecom equipment, and consumer electronics.
• Infrastructure Layer: The fourth layer covers digital infrastructure, including data centres and computing facilities.
  • India has established a common compute platform through public-private partnership, providing access to around 38,000 GPUs.
  • Infrastructure Investment: Around USD 70 billion of AI infrastructure investment has already been confirmed and is under implementation.
  • For Instance, Google Cloud is deepening its engagement with India’s AI ecosystem, including a USD 15 billion AI data centre in Vizag, Andhra Pradesh, and partnerships with Indian startups.
• Energy Layer: The fifth layer is energy, identified as a decisive factor for sustained AI growth and the emerging fifth industrial revolution.
  • Recognising energy as vital to AI growth, India has opened nuclear energy to private participation through the Shakti Act, supporting the full AI ecosystem.

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