India is preparing to host its most ambitious conversations on artificial intelligence. The India AI Impact Summit is expected to position the country as a global hub for innovation, digital infrastructure, and responsible AI deployment. As governments gather to discuss the future of intelligent systems, another equally urgent conversation must accompany it: the climate cost of powering AI at scale.
Climate policy, at its core, is about limits – how much energy we use, how much carbon we emit, and how carefully we manage scarce natural resources. Over the last decade, the climate imperative has reshaped decisions across power, transport, manufacturing, and urban development. Yet deeply resource-intensive artificial intelligence is advancing rapidly through infrastructure without being placed squarely within the same climate accounting framework.
This is not a contradiction born out of neglect. In fact, industry and governments globally have begun exploring renewable-powered data centres and more efficient AI models. But these efforts remain fragmented and are yet to be fully embedded within the climate governance agenda. India faces a quiet paradox: accelerating digital expansion while accounting for its adverse environmental impacts.
AI is frequently described as virtual and weightless. In reality, it relies on physical infrastructure – vast data centres packed with servers, cooling systems, and a continuous power supply. Data centres today account for roughly one to two per cent of global electricity consumption, and projections suggest this demand could double by the end of the decade.
Even everyday use illustrates the scale challenge. A single generative AI query can consume several times as much electricity as a traditional web search, depending on the model's complexity and computational intensity.
For India, these trends carry particular weight. The country is among the world’s most climate-vulnerable, grappling with extreme heat, water stress, and rising energy demand. Simultaneously, India’s data centre capacity is projected to grow several-fold as AI adoption expands across governance, industry, and services. This growth is central to digital ambition, but it is not climate-neutral.
During heatwaves, when households and healthcare facilities draw heavily on electricity to cope with rising temperatures, AI-driven data centres remain always-on. Their cooling requirements intensify precisely when grids are under maximum strain. This is not a flaw of AI; it is an infrastructure reality that must be incorporated into national planning. Water is another hidden dimension. Cooling systems in large data centres can consume millions of litres of water daily. India cannot afford to overlook trade-offs that accompany digital growth in a warming climate.
India has an opportunity to move beyond ad hoc sustainability measures and instead shape how AI infrastructure itself is designed, located, and regulated. Environmental governance frameworks are already evolving in parallel, along with emerging conversations on groundwater management, which will increasingly apply to large digital infrastructure projects.
Equally important is the role of green building standards. India already has well-established rating systems for sustainable construction, including the GRIHA framework. As digital infrastructure expands, the development of dedicated sustainability ratings for data centres, tailored to their unique energy, cooling, and water demands, can play a critical role in setting benchmarks for responsible growth.
Rather than retrofitting sustainability after large-scale expansion, India can encourage the development of demonstrator AI and data centre projects that define best practice from the outset. Such models can specify optimal capacity thresholds, land and lab size, renewable energy sourcing, water recycling and zero-liquid-discharge norms, waste management standards, and minimum sustainability ratings. Over time, these models can inform regulation, investment decisions, and state-level approvals, ensuring that AI infrastructure scales within clearly defined environmental guardrails.
To be clear, AI offers powerful tools for climate solutions. It enhances weather forecasting, optimises renewable energy, strengthens disaster preparedness, and supports sustainable agriculture. These benefits are real and vital. But the gains enabled by AI are rarely weighed against the emissions and resources required to power the AI ecosystem. In climate terms, we are counting savings without fully accounting for the costs.
The deeper gap is one of integration. Climate strategy and AI strategy are evolving in parallel rather than together. While India’s AI Summit rightly emphasises ethics, governance, and innovation, it also presents an opportunity to widen the lens. Unlike emissions from factories or vehicles, which are regulated, monitored, and disclosed, AI’s environmental footprint is often aggregated within broader IT reporting, making its specific impact difficult to isolate. Sustainability discussions exist, but they are not yet commensurate with the speed and scale of AI infrastructure expansion.
India’s AI Summit, therefore, arrives at a pivotal moment. It offers the country a chance to lead not just in responsible AI use but also in responsible AI infrastructure. A clear, achievable path forward is evident. Measurement through disclosure of energy and water use linked to AI systems and data centres. Alignment through renewable energy integration and location planning. Efficiency by design through leaner models and responsible deployment. And integration of AI infrastructure into India’s broader climate, urban, and resource planning frameworks.
The climate challenge is ultimately about choices. AI will undoubtedly shape India’s future economy and governance. The question before policymakers is whether this growth will be shaped early by environmental discipline, or whether sustainability will be forced to catch up later.
India has an opportunity to set a global example, demonstrating that leadership in AI and leadership in climate responsibility need not diverge. Innovation and sustainability can advance together, but only if we recognise, plan for, and regulate the physical footprint behind the digital promise.
AI will shape the future. The real test is whether climate discipline shapes AI in return.
Leena Nandan is former secretary, Ministry of Environment, Forests and Climate Change and distinguished fellow, Earth Science and Climate Change at TERI; and Suryaprabha Sadasivan is Senior Vice President, Chase Advisors.
The opinions expressed in this article are those of the author and do not purport to reflect the opinions or views of THE WEEK.
