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Adani pledges $100B for renewable AI data centers in India

Adani pledges $100B for renewable AI data centers in India Image: Primary
Adani Group said on Monday it would invest $100 billion over the next decade to build data centers specialized for artificial intelligence across India. The investment, which will run through 2035, targets renewable energy powered facilities for AI workloads. The company expects the plan to catalyze an additional $150 billion in related investments and create a $250 billion AI infrastructure ecosystem in India. Adani Group chairman Gautam Adani called the plan a long term bet on the convergence of energy and computing. India will not be a mere consumer in the AI age, he said. The group aims to help build a domestic AI infrastructure base. The announcement coincides with India's ongoing AI Impact Summit in New Delhi this week. Leaders from some of the world's top AI companies, including OpenAI, Nvidia, Anthropic, Microsoft and Google, are meeting policymakers and industry executives. The plan builds on Adani's existing data center platform and partnerships with Google and Microsoft. The conglomerate is developing campuses in Visakhapatnam and Noida, with plans for facilities in Hyderabad and Pune and an expanded partnership with Walmart owned Flipkart. Adani said the plan calls for up to 5 gigawatts of data center capacity developed as a unified system. The effort builds on AdaniConneX, a joint venture with US based EdgeConneX that has already developed about 2 gigawatts of capacity. Central to the strategy is Adani's renewable energy portfolio, which will supply carbon neutral power from its 30 gigawatt Khavda project in western India. The company plans an additional $55 billion investment to expand renewable generation and battery storage. Adani also plans to co invest in domestic manufacturing of components such as transformers, power electronics and thermal management systems to reduce exposure to global supply chain disruptions. The company did not respond to questions about committed capital, spending phases or timelines for operational AI workloads.
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