Adani Commits USD 100 bn To Sovereign AI Infrastructure

20 Feb 2026 CW Team

It builds on AdaniConneX's existing two gigawatt (GW) national data centre platform and envisages expansion towards a five gigawatt (GW) target that the group says will position India at the epicentre of the global AI economy. The roadmap includes landmark partnerships with Google to establish a gigawatt-scale AI data centre campus in Visakhapatnam and collaborations with Microsoft across Hyderabad and Pune. The group is also advancing its data centre partnership with Flipkart to develop a second high-performance AI data centre to support next-generation digital commerce and large-scale AI workloads.

The five GW deployment is described as the world's largest integrated data centre platform, combining renewable power generation, transmission infrastructure and hyperscale compute within a single coordinated architecture. Facilities will be optimised for large high-density compute clusters with advanced liquid cooling and high-efficiency power architecture and will reserve dedicated capacity to support Indian large language models and national data initiatives to ensure long-term data sovereignty. Reliable transmission networks and advanced grid systems are planned to underpin stability, scalability and uptime at hyperscale.

The group will leverage Adani Green Energy's thirty gigawatt (GW) Khavda project, of which more than ten GW is already operational, and has committed to invest another USD 55 bn to expand its renewable energy portfolio including one of the world's largest battery energy storage systems. Strategic connectivity through cable landing stations and a network of ports is intended to ensure low-latency global integration with the Americas, Europe, Africa and Asia. This integrated approach is presented as competitively priced and carbon-neutral power essential for energy-intensive AI workloads.

The Adani Group announced a direct investment of USD 100 bn to develop renewable-energy-powered, hyperscale AI-ready data centres by 2035. The initiative is intended to catalyse an additional USD 150 bn across server manufacturing, advanced electrical infrastructure, sovereign cloud platforms and supporting industries, creating a USD 250 bn AI infrastructure ecosystem in India over the decade. The chairman said the plan forms a sovereign energy and compute platform aimed at positioning India as a global leader in the emerging intelligence economy. It builds on AdaniConneX's existing two gigawatt (GW) national data centre platform and envisages expansion towards a five gigawatt (GW) target that the group says will position India at the epicentre of the global AI economy. The roadmap includes landmark partnerships with Google to establish a gigawatt-scale AI data centre campus in Visakhapatnam and collaborations with Microsoft across Hyderabad and Pune. The group is also advancing its data centre partnership with Flipkart to develop a second high-performance AI data centre to support next-generation digital commerce and large-scale AI workloads. The five GW deployment is described as the world's largest integrated data centre platform, combining renewable power generation, transmission infrastructure and hyperscale compute within a single coordinated architecture. Facilities will be optimised for large high-density compute clusters with advanced liquid cooling and high-efficiency power architecture and will reserve dedicated capacity to support Indian large language models and national data initiatives to ensure long-term data sovereignty. Reliable transmission networks and advanced grid systems are planned to underpin stability, scalability and uptime at hyperscale. The group will leverage Adani Green Energy's thirty gigawatt (GW) Khavda project, of which more than ten GW is already operational, and has committed to invest another USD 55 bn to expand its renewable energy portfolio including one of the world's largest battery energy storage systems. Strategic connectivity through cable landing stations and a network of ports is intended to ensure low-latency global integration with the Americas, Europe, Africa and Asia. This integrated approach is presented as competitively priced and carbon-neutral power essential for energy-intensive AI workloads.

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