International experience highlights this emerging link between nuclear energy and AI infrastructure. In the USA, major technology companies like Microsoft and Google are exploring nuclear power as a means to meet the energy needs of their data centres. China has also been rapidly expanding nuclear capacity and developing Small Modular Reactors (SMRs) to support energy-intensive data centres.
These developments offer a broader context to look at India’s Sustainable Harnessing and Advancement of Nuclear Energy for Transforming India (SHANTI) Bill, 2025. As India focuses on data localisation and digital public infrastructure, meeting energy demand will require round-the-clock and low-carbon energy sources, which also remains central to India’s climate commitments.
Energy policy and governance structure
India’s energy governance framework is largely fragmented and designed for traditional industrial and household consumption rather than the continuous, high-load electricity demand generated by large data centres and AI infrastructure. Electricity planning is divided across multiple institutions, with generation, transmission, and distribution regulated separately.
Ministries of power at the central and state levels frame policies. The Central Electricity Regulatory Commission and the State Electricity Regulatory Commission frame regulations for the generation, transmission and distribution of electricity. The private sector is also involved in electricity generation, while transmission is carried out by a mix of public and private players. Power Grid Corporation of India Limited (PGCIL) serves as the central transmission utility along with the state transmission utilities.
Data centres fall primarily under the Ministry of Electronics and Information Technology, while land use, water allocation, and environmental approvals are handled by different authorities with little coordination. As a result, decisions regarding the location of data centres are often not well aligned with the assessment of grid capacity, water availability and long-term energy sustainability.
As electricity in India is largely generated and transmitted with a focus on the huge population, it still prioritises aggregate capacity addition rather than load quality and reliability. Data centres require uninterrupted, high-quality power with zero downtime. Also, the governance framework does not adequately incentivise low-carbon power such as nuclear, hydro or storage-backed renewables. This gap results in continued dependence on coal-based generation to provide baseload power.
Infrastructure and environment issues
In contrast to traditional computing that relies on explicitly programmed instructions, AI, particularly machine learning, learns patterns from large volumes of data. The scale of data used to train AI models has increased exponentially since 2008. It increased the demand for new data centres and posed new challenges for companies.
One of the foremost challenges is grid stress. Data centres consume electricity continuously and at a high load, which places disproportionate strain on local energy distribution. With India’s installed data capacity expected to reach 2.5 GW by 2027, grid strain is expected to intensify, which calls for an increased focus on renewable energy.
Another challenge is a continued reliance of data centres on coal-based energy to provide electricity. Although non-fossil fuel sources now contribute 235.7 GW of total capacity, coal still remains the prominent stabiliser for grid-supporting data centre clusters. This contributes to higher carbon emissions and complicates India’s climate commitments.
AI infrastructure, particularly for training and deploying large generative AI models, requires a massive amount of water for cooling hardware. Estimates suggest that AI-related infrastructure worldwide may soon consume up to 6 times the annual water use of Denmark, a country with a population of around six million. This is a serious concern in a world where nearly a quarter of the global population still lacks access to clean water and adequate sanitation.
Even a relatively small data centre of 100 megawatts consumes approximately two million litres of water per day. In India, major data centre hubs, such as Mumbai, Chennai and Hyderabad, are already experiencing acute water stress. Proliferating data centres are likely to compete directly with households, agriculture, and industry for limited water resources, potentially exacerbating existing inequalities and resource conflicts.
Policy and institutional gaps
Despite the rapid expansion of data centres, India lacks a comprehensive national data centre policy. The Draft Centre Policy 2020 was announced by the Ministry of Electronics and Information Technology, but it was not formally adopted or implemented. Presently, data centres are largely operated under state-level policies, which remain fragmented and are largely focused on investment incentives rather than systematic sustainability.
Additionally, in the context of land use, water governance, and environmental safeguards, ministries and different tiers of government often lack coordination, working in silos. Again, India still appears to have a major regulatory gap for data centres. There are no compulsory energy efficiency rules, and most sustainability standards are voluntary, followed mainly by large companies. There is also no clear policy or financial support for green data centres making clean power storage and sustainable cooling costly.
Institutional capacity is another concern. State utilities and regulators often lack the technical expertise to assess the long-term implications of large digital loads, especially when combined with smart grids and algorithmic management systems. Data governance and energy governance are treated separately, even though digital infrastructure increasingly depends on algorithmic control of electricity flows.
Need for an integrated AI-energy policy framework
India’s focus on data localisations and digital indigenisation has placed it at a critical crossroads, where its digital aspirations must be matched with equally robust and forward-looking energy governance. It requires comprehensive reforms in energy governance along with strengthening environmental safeguards.
To move forward, India would need an integrated AI-energy policy framework that recognises data centres as strategic energy consumers and not merely commercial consumers. Their requirements need to be incorporated into long-term power planning, grid design, and demand management strategies. For this, strong coordination between different ministries, along with the alignment of policies, would be crucial.
Equally important is the clean energy transition. While solar and wind energy remain essential, their intermittency limits their ability to support round-the-clock digital infrastructure. Nuclear power, including SMRs, can provide stable, low-carbon baseload electricity for data centres and AI systems. At the same time, greater use of treated wastewater for cooling can help reduce pressure on freshwater resources.
This can be complemented with policy support for green standards and financing. Mandatory energy-efficiency rules, water use limits, and emissions reporting can help manage resource use, while incentives for renewable power, storage, efficient cooling and low-carbon construction can help smaller players adopt sustainable practices.
If India aligns AI growth with clean energy and institutional reforms, it can build a digital economy that is competitive, resilient and environmentally sustainable.
Post read questions
What specific challenges do continuous, high-load AI data centres pose to electricity grids designed for variable industrial and household demand?
How does the focus on aggregate capacity addition in India’s power sector limit its ability to deliver high-quality, zero-downtime electricity for AI infrastructure?
How might integrating data centres into long-term grid planning alter investment priorities in transmission, storage, and firm power capacity?
How can mandatory energy-efficiency, water-use, and emissions-reporting standards reshape sustainability practices in the data centre sector?
How can India learn from international approaches to powering AI infrastructure while accounting for its unique development and climate constraints?
(Renuka is a Doctoral researcher at Himachal Pradesh National Law University, Shimla.)
Share your thoughts and ideas on UPSC Special articles with ashiya.parveen@indianexpress.com.
Click Here to read the UPSC Essentials magazine for November 2025. Subscribe to our UPSC newsletter and stay updated with the news cues from the past week.
Stay updated with the latest UPSC articles by joining our Telegram channel – IndianExpress UPSC Hub, and follow us on Instagram and X.
India’s energy governance framework is largely designed for traditional industrial and household consumption rather than the continuous, high-load electricity demand generated by large AI data centres. (File) 
Share
