Reforms 3.0: Building an AI-Powered India for Economic Growth & Technological Leadership

GS III: Indian Economy and issues relating to planning, mobilization of resources, growth, development, and employment

Context: India’s next phase of economic reforms should focus on building an AI-powered nation, leveraging Artificial Intelligence (AI) to achieve sustained high economic growth, technological leadership and national transformation.

About Reforms 3.0

• AI-Led Growth: Artificial Intelligence (AI) is presented as a transformational opportunity comparable to the 1991 economic liberalisation, capable of driving the “Bharat rate of growth” of 8% and above.
• Leapfrogging Model: India has previously leapfrogged traditional development pathways through Aadhaar, UPI and Jio, demonstrating its ability to build large-scale Digital Public Infrastructure (DPI).
• Strategic Opportunity: India’s AI transition represents another “WhatsApp moment” where timely reforms can fundamentally reshape the economy.

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India’s Digital Success Story

• Aadhaar: India created the world’s largest biometric identity system, covering over 1.38 billion people.
• UPI Revolution: Unified Payments Interface (UPI) processes nearly 250 billion annual transactions, accounting for around 50% of global real-time digital payments.
• Affordable Data: Reliance Jio dramatically reduced mobile data costs, making internet access affordable and enabling digital inclusion.
• Replicable Model: India should replicate the Aadhaar-UPI-Jio model for AI through open models, diversified computing infrastructure and low-cost AI tokens.

Need for AI Investment

• Low R&D Spending: India spends only about 0.65% of GDP on Research & Development (R&D), significantly below countries like China, the United States, South Korea and Israel.
• Subsidising Cognition: India should gradually shift from subsidising calories, chemicals and carbon towards subsidising AI-powered knowledge creation.
• Affordable Investment: Providing free AI tokens to leading universities, R&D institutions and schools would cost only around 0.06% of GDP.
• Human Capital: Free AI access can transform scientists, students and researchers by making AI an everyday productivity partner.

Proposal for Free AI Tokens

• Institutional Access: Free AI tokens should initially be provided to the top 100 national R&D institutions, 100 universities and 5,000 schools.
• Public-Private Partnership: India should collaborate with AWS, Google and Microsoft to secure AI inference capacity through mutually beneficial agreements.
• Cross-Subsidisation: Enterprise users can finance free AI access for educational and research institutions.
• Regulatory Enablement: Like the telecom revolution, the government should create enabling regulations rather than directly subsidising AI usage.

Sovereign AI Infrastructure

• Domestic Hosting: India should host major Large Language Models (LLMs) on sovereign infrastructure rather than relying entirely on foreign APIs.
• Hybrid Strategy: India should combine indigenous models like Sarvam with open-source models such as Llama, Qwen, DeepSeek and Kimi.
• Strategic Capability: AI infrastructure should be treated as a national strategic asset similar to the space and nuclear programmes.
• Open-Source Benefits: Open models improve digital sovereignty, lower costs, enable Indic language customisation and enhance transparency.

Building National AI Capability

• Operational Competence: Hosting LLMs requires expertise in high availability, low latency, security, energy efficiency and data residency.
• National Infrastructure: India must develop expertise in running AI services at national scale rather than merely consuming foreign AI platforms.
• Data Sovereignty: Sovereign hosting strengthens national security, government applications and long-term technological independence.

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Diversified Compute Hardware

• Vendor Diversification: India should avoid excessive dependence on NVIDIA by adopting a multi-vendor hardware ecosystem.
• Balanced Architecture:
• • 40% using AWS Trainium and AMD
  • 30% using Google TPUs
  • 30% using NVIDIA GPUs
• Strategic Independence: Diversification reduces vendor lock-in, lowers costs and improves technology resilience.

National AI Token Policy

• Policy Framework: India should announce a National AI Token Policy with implementation over the next 24 months.
• Pilot Phase: Initial rollout should cover the top 20 IITs, IISc, selected universities and 500 AI startups.
• School Education: AI literacy should gradually expand to 5,000 schools across multiple States.
• Indic AI: India should develop sovereign Indic AI benchmarks and support AI deployment across all 22 Scheduled Languages.

Expected Outcomes

• Innovation Ecosystem: AI access can stimulate the growth of over 10,000 AI-native startups.
• Sectoral Transformation: Fine-tuned AI models can improve healthcare, agriculture, judiciary and education.
• Economic Growth: Large-scale AI adoption can significantly improve productivity, innovation and long-term GDP growth.
• Global Leadership: India can emerge as a global leader in AI applications by combining Digital Public Infrastructure with AI infrastructure.

Challenges

• Low R&D Investment: India continues to underinvest in research and development compared to major innovation economies.
• Infrastructure Cost: Building sovereign AI infrastructure requires significant investments in compute, data centres and energy.
• Vendor Dependence: Excessive reliance on foreign AI hardware and cloud providers may weaken technological sovereignty.
• Implementation Complexity: Coordinating government, industry, academia and technology companies requires effective institutional mechanisms.

Way Forward

• National AI Mission: Launch a comprehensive National AI Token Policy with clear implementation milestones.
• Increase R&D Spending: Significantly raise public and private investment in research, AI and innovation.
• Promote Open Models: Encourage open-source AI, sovereign hosting and Indic language AI ecosystems.
• Strengthen Public-Private Partnerships: Collaborate with hyperscalers, industry and academic institutions for AI infrastructure development.
• Develop Indigenous Capacity: Build domestic expertise in AI hardware, software, model deployment and AI governance.

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Conclusion

Reforms 3.0 should position Artificial Intelligence as the next pillar of India’s development by combining Digital Public Infrastructure, sovereign AI capability, open models, strategic investment and institutional reforms to achieve sustained high economic growth and technological leadership.

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