Indian conglomerate commits record investment to build renewable-powered AI data centers by 2035, positioning the nation as a strategic alternative to traditional computing hubs as global tech giants seek energy-efficient, regulation-friendly infrastructure beyond U.S. borders.

India's Adani Group has unveiled a transformative $100 billion investment plan to develop AI-ready data centers across the country over the next decade, marking one of the largest infrastructure commitments in the nation's history. The initiative, announced at India's AI Impact Summit in New Delhi, aims to establish 5 gigawatts of hyperscale data center capacity powered entirely by renewable energy by 2035. Building on AdaniConneX's existing 2-gigawatt platform a joint venture with U.S.-based EdgeConneX—the expansion represents a vertically integrated model coupling large-scale renewable generation with high-density AI computing infrastructure. The investment is projected to catalyze an additional $150 billion across related industries including server manufacturing, advanced electrical equipment, and sovereign cloud platforms, creating a cumulative $250 billion AI infrastructure ecosystem in India.

The announcement coincides with surging global demand for AI computing power and mounting pressure on tech companies to decarbonize operations. Adani's strategy leverages the group's 30-gigawatt Khavda renewable energy project in Gujarat already over 10 gigawatts operational supplemented by a separate $55 billion commitment to expand renewable generation and battery energy storage systems. Strategic facilities are planned across Visakhapatnam, Noida, Hyderabad, and Pune, with cable landing stations at Adani-operated ports designed to support low-latency global connectivity. Existing partnerships with Google and Microsoft will anchor initial campuses, while an expanded collaboration with Walmart-backed Flipkart focuses on digital commerce workloads. The facilities will incorporate liquid cooling systems and high-efficiency power architectures optimized for dense GPU clusters, with dedicated capacity reserved for Indian large language models, startups, and research institutions.

"India will not be a mere consumer in the AI age," declared Adani Group Chairman Gautam Adani, framing the investment as a long-term convergence play between energy and computing. "For decades, we imported technology. Now we are building the backbone. India will not follow the AI century India will shape it." The statement reflects broader national ambitions to transition from the periphery of the AI boom to becoming a central player, particularly as chip manufacturing capacity remains limited domestically.

According to TechSci Research, the Adani Group's $100 billion commitment represents a strategic inflection point in the global redistribution of AI infrastructure, signaling India's emergence as a viable alternative to concentrated capacity in the United States and Western Europe. This investment aligns with three converging macro trends: escalating energy demands from AI workloads that challenge grid stability in developed markets, tightening data sovereignty regulations requiring localized storage, and corporate net-zero mandates driving preference for renewable-powered facilities. India's combination of expanding digital economy, skilled technical workforce, favorable regulatory environment, and aggressive renewable energy buildout creates a unique value proposition for hyperscalers seeking geographic diversification. The parallel USD55 billion renewable energy investment addresses the sector's most critical bottleneck reliable, carbon-neutral power at scale while the emphasis on domestic component manufacturing (transformers, power electronics, thermal management systems) reflects lessons from recent supply chain disruptions. TechSci Research anticipates this will trigger a competitive response from rival conglomerates including Reliance Industries, which has announced plans for the world's largest AI data center, potentially accelerating India's timeline to capture 10-15% of global hyperscale capacity by 2035. However, execution risks remain substantial: land acquisition complexities, water resource constraints for cooling systems, and the need to synchronize renewable generation with 24/7 computing demands present operational challenges that will test the integrated model's viability at unprecedented scale.