{"id":368684,"date":"2026-07-31T17:10:07","date_gmt":"2026-07-31T11:40:07","guid":{"rendered":"https:\/\/forumias.com\/blog\/?p=368684"},"modified":"2026-08-02T11:13:14","modified_gmt":"2026-08-02T05:43:14","slug":"ai-as-the-next-digital-public-infrastructure-dpi","status":"publish","type":"post","link":"https:\/\/forumias.com\/blog\/ai-as-the-next-digital-public-infrastructure-dpi\/","title":{"rendered":"AI as the Next Digital Public Infrastructure (DPI)"},"content":{"rendered":"

UPSC Syllabus<\/strong>– GS Paper II: Government policies, DPI & e-Governance. GS Paper III: AI, Digital Infrastructure, Science & Technology.<\/p>\n

Introduction<\/strong><\/h2>\n

India’s digital transformation over the last decade has been driven by the JAM trinity<\/strong> and its extensions-Aadhaar<\/strong> (identity), UPI<\/strong> (payments), and DEPA\/Account Aggregator (data)-which together form one of the world’s most advanced Digital Public Infrastructure (DPI) ecosystems<\/strong>. By making these services widely accessible at minimal cost, India turned digital infrastructure into a public utility that millions rely on every day. As artificial intelligence (AI) begins to reshape the global digital economy, an important question arises: can India replicate this model by making AI the next public utility through the same approach of building shared digital infrastructure and bringing down the cost of access? AI as the Next Digital Public Infrastructure (DPI).<\/strong><\/p>\n

\"AI<\/p>\n

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  1. India’s DPI Success: Lessons for AI<\/strong><\/li>\n<\/ol>\n

    India has repeatedly demonstrated that state-enabled competition<\/strong>, rather than subsidies alone, can make essential digital services affordable and accessible.<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Affordable data:<\/strong> Between 2016 and 2019, mobile data prices fell sharply due to infrastructure expansion and market competition, bringing nearly 500 million people online<\/strong> within a few years.<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Affordable identity:<\/strong> Aadhaar enrolled over a billion residents, replacing costly paper-based identity verification with a low-cost, API-driven digital system.<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Affordable payments:<\/strong> UPI transformed digital payments into a near-free public utility by enabling seamless interoperability across banks and payment applications.<\/p>\n

    In each case, the government created the digital infrastructure, standards, and regulatory framework, while competition among private players reduced costs and expanded access.<\/p>\n

    2. India’s Comparative Advantage in Digital Public Infrastructure<\/strong><\/p>\n

    Unlike many countries that have developed digital systems in isolated sectors, India has integrated identity, payments, and data-sharing<\/strong> into a single interoperable public digital ecosystem.<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Estonia<\/strong> has an advanced digital identity system but lacks an equivalent public payments infrastructure.<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Brazil’s Pix<\/strong> provides an efficient instant-payment platform but functions largely as a standalone system.<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Singapore’s Singpass and SGFinDex<\/strong>, along with Europe’s open banking framework<\/strong>, offer data portability but only in limited domains.<\/p>\n

    India’s strength lies not in any one platform, but in the seamless integration of Aadhaar, UPI, and the Account Aggregator framework<\/strong> as interoperable digital public goods. This unique ecosystem provides a strong foundation for extending the DPI approach to artificial intelligence.<\/p>\n

    3. Why India Needs an AI-DPI<\/strong><\/p>\n

    Despite its success in digital public infrastructure, India occupies a relatively weak position in the global AI value chain.<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Indian engineers develop and fine-tune frontier AI models that are largely created abroad.<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 India’s digitised public life-including languages, transactions, and documents\u2014serves as valuable training data for foreign AI models.<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Indian universities and the Indian diaspora contribute significantly to global AI research.<\/p>\n

    Yet, Indian startups often have to buy back AI capabilities through expensive, dollar-denominated API services controlled by foreign companies and hosted outside India’s jurisdiction.<\/p>\n

    This resembles India’s historical experience during the colonial textile trade, where raw cotton was exported cheaply while finished cloth was imported at a premium. Similarly, India today exports data, talent, and AI usage<\/strong>, while importing finished AI capabilities on terms set by others. This underscores the need for an AI ecosystem built on India’s own digital public infrastructure.<\/p>\n

    4. Building an Indian AI-DPI Ecosystem<\/strong><\/p>\n

    (a) Democratising Compute<\/strong><\/p>\n

    Through the IndiaAI Mission<\/strong>, backed by significant government investment, India has adopted a public-private partnership model<\/strong> for AI compute. Instead of creating a state-owned data-centre monopoly, the government has empanelled private cloud providers and aggregated national demand.<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Tens of thousands of GPUs have already been onboarded, with plans for further expansion.<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 This enables startups and researchers to access computing resources at a fraction of global market costs.<\/p>\n

    A complementary proposal is to integrate AI compute requirements into national electricity and grid planning<\/strong>, treating power supply for data centres as strategic infrastructure, much like coal linkages were once prioritised for steel production.<\/p>\n

    (b) Promoting Open-Weight Foundation Models<\/strong><\/p>\n

    Dependence on proprietary foreign AI models exposes Indian startups to pricing uncertainty and policy changes beyond their control.<\/p>\n

    The proposed approach includes:<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Aggregating anonymised public datasets-such as legal judgments, agricultural records, and educational content in India’s official languages-for developing open-source AI models.<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Requiring that AI models built using publicly subsidised compute or public datasets be released under an open-weights licence<\/strong>.<\/p>\n

    This reflects the philosophy behind UPI, where the government builds and standardises the underlying infrastructure while private firms compete by creating innovative applications and services.<\/p>\n

    (c) Unified Intelligence Interface (UII): “UPI for AI”<\/strong><\/p>\n

    Just as UPI’s greatest strength lies in interoperability rather than free payments alone, the proposed Unified Intelligence Interface (UII)<\/strong> aims to provide a standardised API gateway through which applications can seamlessly access multiple AI models\u2014both sovereign and private.<\/p>\n

    The UII would establish common standards for:<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Identity verification<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 User consent<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Billing<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Safety and governance<\/p>\n

    This would enable startups, government departments, and educational institutions to access translation, vision, and text-generation services at minimal cost.<\/p>\n

    5. Financing Inclusive AI Access<\/strong><\/p>\n

    To ensure broad and affordable access, proposals include introducing an Aadhaar-linked freemium token model<\/strong>, under which:<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Verified students, researchers, and startups would receive subsidised AI API tokens.<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Commercial enterprises would gradually shift to paid access, helping cross-subsidise free users.<\/p>\n

    Another proposal is to reallocate a portion of existing subsidy expenditure\u2014for example, from fertiliser subsidies\u2014to support AI access for schools, universities, and research institutions.<\/p>\n

    6. Transformative Potential of AI-DPI<\/strong><\/p>\n

    If AI becomes affordable and widely accessible, it could significantly improve service delivery across multiple sectors.<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Healthcare:<\/strong> India-trained AI models could strengthen healthcare delivery in underserved rural areas.<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Education:<\/strong> Personalised multilingual tutoring could become accessible to hundreds of millions of learners.<\/p>\n

    \u25cf\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Agriculture and governance:<\/strong> Voice-enabled services in Indian languages could simplify access to crop insurance, public services, and grievance redressal.<\/p>\n

    This would not only reduce the cost of accessing intelligence but also make AI a powerful tool for inclusive development across the country.<\/p>\n

    Challenges and Concerns<\/u><\/strong><\/h2>\n