Why in News?
· After successfully democratising identity (Aadhaar), digital payments (UPI) and consent-based data sharing (DEPA/Account Aggregator), India stands at the threshold of its next Digital Public Infrastructure (DPI) revolution - Artificial Intelligence (AI).
· The core objective is not merely to build advanced AI models but to make intelligence affordable, interoperable and universally accessible, just as India transformed digital identity, payments and internet access into public utilities.
· The G20 New Delhi Leaders' Declaration (2023) and the World Bank have recognised India's DPI as a global model of inclusive digital transformation.
India's DPI Model: Foundation for AI
India's digital transformation is based on interoperable public digital infrastructure rather than isolated digital services.
Digital Identity (Aadhaar): More than 1.4 billion Aadhaar numbers issued, making it the world's largest biometric identity programme and enabled paperless authentication, e-KYC, DBT and financial inclusion.
- According to the World Bank, Aadhaar has significantly improved efficiency in welfare delivery.
Digital Payments (UPI): Processes nearly 20 billion transactions every month, making it one of the world's largest real-time payment systems, reduced transaction costs to near zero and enabled digital inclusion of MSMEs, street vendors and rural households.
Affordable Internet: Between 2016 and 2019, mobile data prices declined from nearly US$4 per GB to below US$0.30, among the lowest globally.
- Nearly 500 million people came online, enabling rapid expansion of e-commerce, fintech, digital governance and startups.
Consent-Based Data Sharing (DEPA): The Data Empowerment and Protection Architecture (DEPA) and Account Aggregator framework provide secure, consent-based data sharing, empowering citizens while enabling innovation.
Why AI Should Become India's Fourth DPI
Artificial Intelligence is increasingly becoming a general-purpose technology, comparable to electricity or the internet. However, the present AI economy is highly concentrated.
India contributes: World-class AI engineers and researchers, large multilingual datasets, data annotation workforce and massive digital user base.
Yet Indian startups continue to purchase expensive AI services through proprietary foreign APIs.
India exports talent, data and innovation while importing high-value AI services, creating technological dependence. Democratising AI through DPI can reverse this imbalance.
India's AI Challenges
Dependence on Foreign AI Models: Most frontier AI models are owned by multinational companies, exposing Indian startups to pricing changes, licensing restrictions and geopolitical risks.
Compute Infrastructure Gap: According to the Stanford AI Index Report 2026, frontier AI increasingly depends on massive compute infrastructure concentrated among a few global technology companies.
- India remains dependent on imported GPUs and foreign cloud infrastructure.
Data Sovereignty: Indian public data, languages and user interactions contribute significantly to AI development, but much of the resulting economic value is captured outside India.
High AI Inference Cost: The real challenge is not only training AI models but reducing the cost of AI inference, which determines mass adoption by students, MSMEs, researchers and citizens.
AI as India's Next Digital Public Infrastructure
Affordable Compute Infrastructure: The IndiaAI Mission, with an allocation of ₹10,371.92 crore, aims to establish sovereign AI infrastructure through public-private partnerships.
- Its seven pillars include: IndiaAI Compute + IndiaAI Innovation Centre + IndiaAI Datasets Platform + Indigenous Foundation Models + Startup Financing + Future Skills + Safe and Trusted AI.
- More than 38,000 GPUs have already been onboarded with a target of 1 lakh GPUs, providing compute access at approximately ₹65 per GPU hour for eligible startups and researchers.
- Policy Measures: Recognise AI infrastructure under the National Electricity Plan, develop renewable and nuclear energy-powered AI data centres, strengthen indigenous semiconductor manufacturing through the India Semiconductor Mission and expand the National Supercomputing Mission for sovereign compute capacity.
- Just as inexpensive spectrum enabled digital connectivity, affordable electricity and compute can democratise AI.
Open Foundation Models: India should prioritise development of open-weight Indic Large Language Models (LLMs).
- Government-supported datasets should include court judgments, agricultural databases, educational content, health records (anonymised), scientific literature, governance documents and all Scheduled Languages.
- Models developed using public compute or government datasets should be released under open-weight licences, following the philosophy of open digital public goods.
- The World Bank's Digital Progress and Trends Report 2025 identifies four critical pillars for AI development connectivity, compute, context (local datasets) and competency (digital skills).
- Open-source AI can significantly reduce dependence on a few dominant AI providers.
Unified Intelligence Interface (UII): A Unified Intelligence Interface would function as a UPI for Artificial Intelligence.
- Key features include: Open APIs, model interoperability, digital identity integration, consent-based access, standard billing architecture and AI safety protocols.
- Like UPI abstracts banking complexity, UII would abstract AI infrastructure, enabling seamless access to multiple AI models.
National AI Token Economy: India can introduce a public AI token framework.
- Features: Free monthly AI tokens for students, teachers, startups and researchers, subsidised AI access for schools, universities and research institutions, commercial pricing for enterprises after scaling, government-supported AI credits for innovation and affordable AI access can become the equivalent of affordable internet in the AI era.
Sectoral Applications
Healthcare: AI can support early disease diagnosis, radiology, telemedicine, clinical decision support, drug discovery and complementing the Ayushman Bharat Digital Mission.
Education: Supports the objectives of NEP 2020 through personalised tutoring, adaptive assessments, teacher assistance and multilingual education using BHASHINI
Agriculture: Applications include precision agriculture, crop disease detection and weather forecasting
Soil monitoring: Voice-enabled crop insurance and supporting nearly 45% of India's workforce dependent on agriculture.
- MSMEs: India's 6.3 crore MSMEs, contributing nearly 30% of GDP and 45% of exports, can leverage AI for accounting, inventory, marketing, customer support and productivity enhancement.
Governance: AI can improve citizen grievance redressal, welfare targeting, policy formulation, judicial translation and public service delivery
Global Best Practices
United States: Global leader in frontier AI research driven by private innovation.
China: State-supported AI ecosystem with indigenous foundation models and semiconductor capabilities.
European Union: AI Act provides the world's first comprehensive risk-based AI regulatory framework.
Singapore: National AI Strategy 2.0 focuses on trusted AI and public sector adoption.
Brazil: Pix demonstrates successful digital payment infrastructure, though without India's integrated DPI architecture.
Estonia: Global leader in digital governance and digital identity but lacks India's comprehensive DPI ecosystem.
Way Forward
Expand sovereign compute infrastructure under the IndiaAI Mission.
Build open-weight Indic foundation models using high-quality multilingual datasets.
Establish a Unified Intelligence Interface as an interoperable AI protocol.
Integrate AI infrastructure into national energy and industrial planning.
Strengthen semiconductor manufacturing under the India Semiconductor Mission.
Promote ethical AI consistent with the UNESCO Recommendation on the Ethics of Artificial Intelligence (2021) and OECD AI Principles.
Expand AI skilling through FutureSkills, higher education institutions and research centres.
Encourage public-private partnerships while preserving openness, interoperability and competition.
Position India as the global leader in Digital Public Infrastructure for the Global South.
