Context

• India has emerged as a global leader in Digital Public Infrastructure (DPI) by integrating Aadhaar, Unified Payments Interface (UPI), and DEPA/Account Aggregator into an interoperable ecosystem.
• Unlike countries that excel in individual digital systems, India has combined digital identity, payments, and data-sharing at an unprecedented scale.
• The next step is to extend this model to Artificial Intelligence (AI) by making intelligence a foundational public utility that is affordable, accessible, and interoperable.

India’s DPI Success Story

• India’s DPI has transformed governance and financial inclusion through Aadhaar, which has enrolled over 1.4 billion people and enabled low-cost digital identity verification.
• UPI has revolutionised payments by processing nearly 20 billion monthly transactions at minimal cost.
• Between 2016 and 2019, affordable mobile data connected nearly 500 million Indians, accelerating digital inclusion, Direct Benefit Transfers (DBTs), startups, e-commerce, and digital governance.
• India’s success lies in creating competitive digital markets supported by strong public infrastructure rather than direct subsidies.

AI as the Fourth Digital Public Infrastructure

• AI is becoming the next essential infrastructure after identity, payments, and data.
• Instead of competing with global technology giants in expensive AI model training, India should focus on making AI inference inexpensive and widely accessible.
• The objective is to reduce the cost of using AI through public infrastructure, enabling innovation across education, healthcare, agriculture, governance, and industry.

India’s Unequal Position in the Global AI Economy

• India contributes significantly to the global AI ecosystem through its engineering talent, researchers, multilingual data, and data annotation workforce.
• However, Indian start-ups depend heavily on costly foreign AI models and proprietary APIs, making them vulnerable to external pricing and policy decisions.
• This resembles the historical pattern of exporting raw materials while importing high-value finished products.
• India must move from being a supplier of AI inputs to becoming a producer of AI capabilities.

Building India’s National AI Token Economy

• Affordable Compute Infrastructure
  • The IndiaAI Mission, with an allocation of around ₹10,372 crores, seeks to build AI infrastructure through public-private partnerships.
  • More than 38,000 GPUs have been on boarded, with a target of 1,00,000 GPUs, providing subsidised compute access to startups and researchers.
  • AI infrastructure should also be integrated into the National Electricity Plan, supported by renewable and nuclear energy to ensure reliable, low-cost power for data centres.
• Open-Source Foundation Models
  • Affordable computing must be complemented by open-source Large Language Models (LLMs).
  • India should utilise anonymised public datasets such as legal judgments, agricultural information, and educational content in all 22 Scheduled Languages to develop indigenous AI models.
  • AI systems created using public funding should be released under open-weights licences, encouraging innovation while reducing dependence on proprietary foreign platforms.
• Unified Intelligence Interface (UII)
  • India should establish a UII based on the principles of UPI.
  • A common AI API gateway would provide interoperability, identity verification, consent management, billing, and safety standards.
  • Government agencies, educational institutions, start-ups, and businesses could access multiple AI services through a single platform, reducing costs and encouraging competition.

AI Token Entitlements for Inclusive Growth

• A national freemium AI model could provide free monthly AI tokens to verified students, researchers, and startups through Aadhaar authentication.
• Larger enterprises could pay commercial rates, creating a sustainable funding model.
• AI support for schools, research institutions, and public services would accelerate innovation and reduce barriers to technology adoption.

Socio-Economic Benefits of Near-Free Intelligence

• Affordable AI can significantly improve healthcare, education, agriculture, MSMEs, and governance.
• AI-assisted healthcare can expand medical access, personalised tutoring can benefit millions of students, multilingual AI can assist farmers in accessing government services, and small businesses can utilise AI for accounting, marketing, and compliance.
• AI-powered governance can further enhance efficient citizen service delivery.

Challenges

• Key challenges include high infrastructure costs, dependence on imported semiconductor technologies, data privacy, cybersecurity, algorithmic bias, responsible AI governance, and sustainable financing.
• Addressing these issues is essential for developing secure, inclusive, and trustworthy AI infrastructure.

Way Forward

• India should expand the IndiaAI Mission, promote open-source AI, invest in AI-specific energy infrastructure, develop Indic AI models.
• Also, India should establish the Unified Intelligence Interface, strengthen AI governance under the Digital Personal Data Protection Act, and encourage collaboration among government, academia, startups, and industry.

Conclusion

• India’s success with Digital Public Infrastructure demonstrates how public digital goods can reduce costs and expand participation.
• Extending this model to AI can democratise intelligence through affordable compute, open-source models, AI token entitlements, and a Unified Intelligence Interface.
• By making intelligence widely accessible, India can strengthen technological sovereignty, develop innovation, and ensure that AI becomes a powerful engine of inclusive economic and social development rather than a privilege available only to a few.