India accelerates AI data centre expansion
Global technology groups including Microsoft, Amazon and Google have pledged billions of dollars to expand cloud and AI infrastructure across the country, betting on strong digital adoption, a vast developer base and policy support from New Delhi. At the same time, domestic conglomerates such as Reliance Industries and the Adani Group have unveiled plans to scale up capacity, signalling an arms race to capture the next phase of AI growth.
The surge is centred on established data centre hubs such as Mumbai, Hyderabad, Chennai and the National Capital Region. Industry estimates place India’s operational data centre capacity at more than 900 megawatts, with projections that this could double within a few years as hyperscale facilities come online. Much of the new supply is being designed for AI workloads, which require more powerful processors and higher rack densities than traditional cloud computing.
Microsoft has committed to expanding its Azure footprint in multiple regions, while Amazon Web Services continues to invest in its Mumbai and Hyderabad zones. Google Cloud has also deepened its presence, citing demand from financial services, healthcare and government clients. Nvidia, whose graphics processing units underpin many AI systems, has strengthened partnerships with Indian firms to support sovereign AI initiatives and localised computing.
Officials argue that this wave of investment will support economic growth, digital inclusion and advanced research. India’s data protection framework and semiconductor incentives have been positioned as part of a broader strategy to create a resilient digital ecosystem. The government has also outlined ambitions to develop domestic AI models trained on local languages and datasets, increasing the need for high-performance computing infrastructure within national borders.
Yet environmental experts warn that the geography of expansion raises difficult trade-offs. Mumbai and Chennai, two of the country’s largest data centre clusters, face periodic water shortages and are vulnerable to climate-related risks, including extreme heat and flooding. Hyderabad, another key hub, has experienced mounting pressure on groundwater resources amid rapid urbanisation.
AI data centres are particularly resource-intensive. Training large language models can consume vast amounts of electricity, and the cooling systems required to maintain optimal temperatures often rely on significant volumes of water. While operators increasingly use advanced cooling technologies and pursue renewable energy procurement, critics question whether efficiency gains can keep pace with the scale of expansion.
According to industry analysts, AI-optimised facilities can draw substantially more power per rack than conventional data centres. India’s peak power demand has been rising steadily, touching record highs during heatwaves. Coal continues to account for a large share of electricity generation, although solar and wind capacity have expanded rapidly. The tension between decarbonisation goals and surging digital energy needs is becoming more pronounced.
Water usage is another flashpoint. Traditional evaporative cooling systems can require millions of litres annually for large facilities, though some operators are shifting to air-cooled or liquid immersion systems to reduce dependence on freshwater. Companies state that they are investing in water recycling, rainwater harvesting and wastewater treatment, particularly in regions classified as water-stressed.
Environmental groups argue that even with mitigation measures, cumulative impacts could strain local communities. Urban residents in Chennai and parts of Maharashtra have already experienced water rationing during drought periods. The prospect of energy-hungry AI campuses expanding in these same areas has prompted calls for stricter environmental assessments and greater transparency around resource use.
Corporate leaders counter that hyperscale operators often have stronger sustainability commitments than smaller, on-premise data centres. Many global firms have pledged to run on 100 per cent renewable energy and to become water positive within the decade. In India, power purchase agreements for solar and wind farms are increasingly tied to data centre projects, supporting the build-out of clean energy capacity.
Policy makers face a delicate balancing act. Digital infrastructure is viewed as critical to competitiveness, especially as countries race to develop generative AI capabilities. India’s large pool of engineers and its expanding start-up ecosystem make it an attractive base for AI research and deployment. Delaying capacity expansion could risk ceding ground to regional rivals in Southeast Asia or the Middle East, where governments are also courting hyperscale investment.
At the same time, climate resilience is rising on the national agenda. The country has set ambitious renewable energy targets and emphasised sustainable development in international forums. Integrating AI growth with environmental safeguards will test regulatory frameworks at both central and state levels.
