The plan treats AI infrastructure as Digital Public Goods, allowing researchers, startups, and public institutions to access data, compute, and model ecosystems remotely via shared platforms, rather than relying on hardware ownership.

India unveiled a white paper to democratize AI by expanding compute power, datasets, and AI models, enabling innovation beyond tech hubs and promoting responsible AI adoption through shared digital layers and Digital Public Goods.

Sustainability is a core consideration, with data centers projected to consume up to 3% of India’s electricity by 2030 and states mandating renewable energy for new facilities.

Democratizing access means making AI compute, datasets, and model ecosystems broadly affordable and available to individuals and institutions across the country.

Industry activity is expanding with investments in hyperscale and sovereign cloud storage from Yotta Data Services, NTT, CtrlS, and AdaniConneX, including Asia’s largest single-building data centre in Navi Mumbai (72 MW) and CtrlS’s 19 facilities totaling 250 MW.

The expansion is driven by growing AI workloads and is framed within a broader shift toward distributed AI infrastructure.

Efforts to improve energy efficiency include renewable-powered cooling, hybrid power sources, and state mandates in states like Maharashtra and Tamil Nadu to require renewables for data centers.

Startups and researchers already leverage commercial cloud datasets from AWS, Google Cloud, and Microsoft Azure, while platforms like Yotta, CtrlS, and AdaniConneX push hyperscale and sovereign cloud capacity.

To meet rising demand, projected data center capacity is set to grow from about 960 MW today to around 9.2 GW by 2030, requiring roughly 45–50 million square feet of real estate.

AI agents and conversational interfaces are aiding KYC, credit evaluation, and anomaly detection, contributing to reduced NPAs and greater financial inclusion.

Current hubs include Mumbai, Bengaluru, and Hyderabad, with Chennai and Delhi-NCR emerging as new centers for data center growth.

Adoption of AI is strongest in telecom, media, pharmaceuticals, and manufacturing, while sectors like agriculture, healthcare, education, and public services face data and infrastructure access gaps.