Context:

• The global AI race is intensifying, with the US making massive semiconductor investments and new open-source models challenging proprietary AI dominance.
• India has significant potential to become a leader in artificial intelligence (AI), backed by a robust digital infrastructure and a skilled workforce.

India’s Strengths in AI:

• Enabling ecosystem:
  • India has an ecosystem that allows both public and private innovation to flourish.
  • For example, 14 million businesses registered on GST, 863 million internet users, and an expected 13.42% digital economy growth rate.
• Growing AI workforce and market:
  • India has 4,20,000 AI professionals, one of the largest AI talent pools.
  • With a 92% AI adoption rate, India leads global enterprise AI integration.
  • The $17 billion AI market potential positions India as a major player.
• Government initiatives and startup ecosystem:
  • The IndiaAI Mission reflects strong government commitment.
  • India has 240+ Generative AI startups, with 70% focused on industry-specific solutions (e.g., healthcare, education, BFSI, agriculture).
  • Examples:
    • Sarvam AI - Developing foundational models in Indian languages.
    • Niramai - AI-powered breast cancer detection.
    • BHASHINI - Breaking language barriers with support for 22+ Indian languages.

India’s Digital Public Infrastructure (DPI) as a Model:

• Financial inclusion and digital payments:
  • Bank account penetration increased from 30% to 80% in seven years.
  • The cost of opening a bank account reduced from $23 to 15 cents.
  • India processes 49% of global real-time payments (UPI transactions worth $568 billion/month).
• Tech-driven economic growth:
  • 108 unicorn startups emerged in the last decade, leveraging DPI.
  • Expansion into sectors like health-tech, lending platforms, and e-commerce.
• Crisis response and social welfare:
  • During COVID-19, $4.5 billion was instantly transferred to 160 million people.
  • Enabled leakage-free, real-time financial assistance to marginalized communities.

Challenges and the Need for AI Hardware Development:

• Dependence on foreign AI hardware:
  • Graphics processing units (GPUs - key AI components) are controlled by the US.
  • The US AI diffusion rule places India in Tier II, restricting access to advanced GPUs.
• Strategic need for indigenous AI hardware:
  • India must develop its own AI hardware to ensure technological sovereignty.
  • Investment in AI hardware will create jobs, attract capital, and drive innovation.
  • India can position itself as a critical global supply chain player.

Recent Global Developments in AI:

• US:
  • The US committed billions to semiconductor investments with the Stargate initiative, laying the groundwork for its technological future.
  • The aim was to create 1,00,000 jobs and secure pole position for the US in AI.
• China:
  • An open-source AI model emerged in DeepSeek, shaking the foundations of proprietary systems with its unmatched cost-efficiency and performance.
  • DeepSeek developed an open-source product in less than two years with 200 employees and less than $10 million in capital.
  • In comparison, OpenAI boasted 4,500 employees and had $6.6 billion in funding.

Roadmap for India’s AI Leadership:

• Innovation with cost-effectiveness: Inspired by ISRO’s frugal engineering, AI development must be energy-efficient and cost-effective.
• Open-source AI development: Encourage an open-source AI ecosystem with strong software-computing convergence. Develop AI solutions for key challenges in education, healthcare, and governance.
• Sovereign AI models: Build AI models that are based on Indian datasets, free from external biases. Develop end-to-end AI ecosystems, not just application layers.
• Multilingual and multimodal AI models: India’s 22 official languages and regional dialects require AI models that ensure linguistic inclusivity.
• Global AI leadership and policy advocacy: As a Quad partner, India must negotiate for Tier-I status in AI diffusion. Push for unrestricted access to AI computing resources.
• Mission-driven urgency: AI leadership demands a mission-driven approach, with clear policy and regulatory support.

Conclusion:

• India must transition from a service provider to a global AI innovator.
• India has the necessary foundation to catalyse both the pace and scale of a new wave of digital transformation.
• India must take decisive steps to build and fortify the hardware backbone powering AI systems, ensuring that they deliver unmatched efficiency, reliability, and scalability.
• Strategic investments in AI infrastructure, talent, and policy will define India's role in shaping the future of AI.
• This decade could mark India's transformation into a technological superpower.