India plans to expand its AI-ready data center capacity to 3GW by 2028, backed by $126 billion in investment commitments. As high-intensity GPU clusters drive massive power demand, the government is introducing tax incentives to secure long-term digital growth. Investors are tracking how this scaling affects power utilities, real estate developers, and infrastructure firms across major hubs.
India is rapidly building its digital infrastructure to support the artificial intelligence boom, aiming to hit 3 gigawatts of capacity by 2028. This follows a period of growth that saw the country surpass 1.7 gigawatts of capacity by late 2025. This expansion is necessary because modern AI computing requires significantly more power than traditional data processing, demanding specialized electrical systems and advanced liquid cooling designs for massive GPU clusters.
Strategic Investments and Policy Support
The scale of this shift is supported by $126 billion in cumulative investment commitments. To attract long-term capital, the government has introduced significant policy measures, including a tax holiday extending until 2047 for foreign entities providing services from Indian facilities. This regulatory move aims to provide the stability needed for large-scale, multi-year projects. Financial markets are watching how these tax incentives and power availability support the profitability of data center operators and their suppliers.
Power and Geographic Expansion
Energy policy has become a core component of this infrastructure strategy. India reached a milestone by generating over 50 percent of its electricity from non-fossil sources as of June 2025, and it successfully executed a 55.3 gigawatt power build-out in a single financial year. This energy foundation is crucial because AI infrastructure requires reliable, high-capacity electricity to operate efficiently.
Geographically, Mumbai remains the primary hub for this development, currently housing roughly half of the nation's capacity. However, there is a clear trend toward decentralization, with secondary markets like Ahmedabad, Jaipur, and Lucknow beginning to attract interest as the industry seeks out new locations for edge computing. This shift helps manage land availability and localized power needs.
Sustainability and Operational Risks
While growth is rapid, the industry faces real-world operational challenges. Scaling to this level requires more than just capital; it requires efficient water management and high-standard cooling systems to prevent massive utility costs. Companies are now focusing on mandates for site efficiency, which are designed to avoid the expensive, forced retrofits that have challenged more mature international markets. For investors, the risk remains whether projects can be executed on time without significant cost overruns, particularly in securing the specialized electrical hardware and grid connections needed for these high-density campuses.
Investors and market participants may track the commissioning timelines of these large-scale campuses to gauge how quickly supply can meet the projected demand. Monitoring management commentary on energy costs and water usage efficiency will also be important, as these factors will influence long-term operating margins and the ability to maintain a competitive advantage in the global AI race.