The Government of India has recently released a whitepaper on AI infrastructure, laying the foundation for making it accessible to all citizens, especially those who predominantly use regional languages, and those who hail from non-metropolitan areas. The paper titled Democratising Access to AI Infrastructure aims to showcase ways to enable equitable participation in India’s digital transformation and economic growth.
The whitepaper prepared by Animesh Jain, Senior Policy Fellow (Adjunct), Office of the Principal Scientific Adviser to the Government of India, says, “Access to AI infrastructure, including compute power, data repositories, and model ecosystems, has become a critical determinant of innovation, competitiveness, and governance in the digital economy.” It finds, “Currently, these resources are concentrated in a handful of global firms and urban hubs, thereby limiting equitable participation. For India, democratizing access means treating these building blocks as shared resources so that innovators everywhere can participate in shaping the AI age.”
Wider and more equitable access
It says, “To democratize AI infrastructure, efforts need to focus on ensuring wider and more equitable access for all stakeholders. For that, it is critical to institutionalize governance frameworks that treat the building blocks of AI systems as Digital Public Goods (DPGs), alongside building and developing AI infrastructure.” It goes on to elaborate, saying, “This implies that the stakeholders are enabled to utilize the data, compute and the ecosystem of models and algorithms without needing to be in physical proximity and access to the infrastructure.”
Shedding light on ground realities, it says, “India hosts nearly 20 percent of the world’s data, but only 3 percent of global data center capacity,” adding, “In India, demand for data infrastructure is rapidly rising with the growth of AI workload and the current installed capacity of nearly 960 MW is expected to reach 9.2 GW by 2030.”
Laying the roadmap for development of AI infrastructure, it says, “Under the IndiaAI Mission, a secure GPU cluster is also being constructed to house 3,000 next-generation GPUs for sovereign and strategic applications,” adding that “the India Semiconductor Mission (ISM) is supporting the foundational layer of all processing units, the semiconductor chips. The mission is backed by an investment of Rs. 76,000 crore and has facilitated the approval of 10 advanced chip-making projects, including domestic fabrication and packaging facilities.”
With respect to ensuring access, it says, “In 2025, IndiaAIKosh was launched under the IndiaAI Mission. It aims to serve as a national repository of AI datasets, models and tools. The platform organises datasets in 20 sectors, covering a wide range of domains critical to India’s development. As of December 2025, it has onboarded 5722 datasets and 251 AI models from 54 entities across 20 sectors.” It explains that the platform provides “permission-based access, allowing contributors to retain control over data usage while facilitating AI development.” It further says, “Bhashini (National Language Translation Mission) is a government initiative to create language datasets (text and speech) and models for the diverse set of Indian languages.” This is crucial in a diverse country like India where there are over 20 official languages, and thousands of dialects.
When it comes to access to compute, it finds, “The national GPU pool being expanded by the IndiaAI Mission is accessible through a government-supported cloud infrastructure. The IndiaAI Compute Portal operates over 38,000 GPUs and 1,050 TPUs.” The IndiaAI mission has developed a unified compute portal, IndiaAI Compute Portal, where researchers, startups, and government bodies can request access. “This helped to increase the reach of AI infrastructure and enable customisation & localisation of AI services. For example, startups in smaller cities can train or fine-tune models for niche local markets at subsidised rates, while universities without on-premise HPC infrastructure can conduct advanced AI research,” finds the whitepaper.
Regulation and policy
On the subject of regulatory environment and policies pertaining to the growth and development of AI, it points to the MeitY-supported MeghRaj (GI Cloud) initiative, that creates a base for AI-oriented public storage by providing cloud storage services to government bodies. Many states such as Maharashtra, Tamil Nadu, Karnataka, and Telangana have their own data center policy with a national policy in the works.
Continuing with recommendations for creating a robust plan of action for enabling AI access for all, it says, “India’s priority to democratise access to AI infrastructure requires a scalable and transparent framework that lowers structural barriers while enabling innovation. This refers to making foundational AI resources, such as compute capacity, high-quality datasets, and enabling tools available beyond a limited set of large firms and major urban hubs, so that a wider range of actors can build, test, and deploy AI responsibly. “ It further explains, “In practice, this requires reducing costs, administrative friction and uneven institutional capacity while enabling predictable access pathways for startups, researchers, public institutions, and smaller organisations to use AI infrastructure without needing to own it. Crucially, such access must be governed in a manner that protects privacy, ensures accountability, and sustains public trust, particularly when AI systems rely on sensitive or public-interest datasets.”
It advocates for a Digital Public Infrastructure (DPI) approach to advance the democratization of access to AI infrastructure by establishing shared, standards-based layers that improve access, interoperability, accountability and trust. It further says, “DPI for AI should be understood not as a single platform or monolithic system, but as a set of modular public-good enablers that address specific coordination gaps in the AI ecosystem. Its value lies in creating predictable, transparent and interoperable access pathways, particularly for smaller firms, research institutions, and startups that face prohibitive entry barriers. By reducing costs, standardizing interfaces and establishing common governance norms, DPI can meaningfully expand the base of participants who can benefit from AI infrastructure.”
It goes on to encourage the private sector to play a greater role in India’s digital transformation by way of setting up edge infrastructure in non-metros. It also advocates resource efficiency, particularly with respect to power usage. It says that data centers currently account for roughly 0.5 percent of India’s total electricity consumption, a share that could rise to nearly 3 percent by 2030 as capacity and workloads expand. It also points out that while technology-mature sectors such as telecom, media, pharmaceuticals, and manufacturing are scaling AI rapidly, adoption remains uneven in agriculture, education, healthcare, and public services due to a lack of adequate infrastructure and access to resources.
