Adani Enterprises on February 17 announced an ambitious plan to invest $100 billion by 2035 to develop renewable energy-powered, AI-ready data centres across India, marking one of the largest private infrastructure commitments in the country’s digital economy. The conglomerate framed the initiative as a foundational step toward building a sovereign energy-and-compute platform capable of supporting the next wave of artificial intelligence adoption.

According to the company’s the programme is designed not merely as a capacity expansion but as a long-term strategic architecture combining green power generation, transmission networks, cloud infrastructure and hyperscale computing. Management estimates the project could catalyse an additional $150 billion of investment across adjacent industries such as server manufacturing, electrical systems, sovereign cloud platforms and related supply chains. Together, this ecosystem could reach a cumulative value of $250 billion over the next decade.

The initiative builds on the group’s existing data centre operations under Adani Connex, which currently operates a national capacity of about 2 GW and is targeting expansion to 5 GW. This would place India among the largest global hubs for AI compute infrastructure, a segment increasingly viewed as strategic as energy or defence assets.

Chairman Gautam Adani described the move as preparation for an “Intelligence Revolution,” arguing that countries capable of aligning energy supply with computational capacity will dominate the next phase of global economic competition. The emphasis on renewable energy is particularly significant, as AI data centres are among the most power-intensive industrial facilities, raising sustainability concerns worldwide.

The roadmap includes large-scale campuses in multiple cities. A flagship gigawatt-scale AI data centre campus is planned in Visakhapatnam in partnership with Google, while additional facilities are being developed in Noida, Hyderabad and Pune with involvement from Microsoft. The group also indicated ongoing discussions with other global technology players exploring hyperscale campuses in India.

In addition to cloud and enterprise workloads, the infrastructure will support domestic digital platforms. The company said it plans to deepen its partnership with Flipkart by building a second AI-focused data centre tailored for high-performance computing and next-generation e-commerce applications.

Unlike conventional data centre rollouts that rely on existing grid capacity, the Adani model integrates power generation, transmission resilience and compute infrastructure within a unified framework. By synchronising these layers, the group aims to mitigate one of the biggest constraints facing AI expansion globally — reliable, affordable electricity supply.

From a market perspective, the announcement reinforces Adani Enterprises’ positioning as a diversified infrastructure platform rather than a pure energy or logistics player. Shares of the company rose about 2.6 percent intraday following the news, reflecting investor optimism about long-term growth potential, though execution timelines remain extended.

For India, the strategic implications are substantial. AI infrastructure is increasingly treated as sovereign capability, similar to semiconductor manufacturing. Currently, much of the world’s AI computing power is concentrated in the United States and China. Large-scale domestic capacity could reduce dependence on foreign cloud providers, strengthen data localisation policies and support indigenous AI development.

Sectorally, the plan could trigger multiplier effects across renewable energy, power equipment, construction, real estate, electronics manufacturing and telecommunications. It also aligns with government priorities to expand digital infrastructure while transitioning to clean energy sources.

However, the scale of the commitment introduces significant uncertainties. Funding requirements are enormous, and execution will depend on regulatory approvals, land acquisition, power transmission build-out and sustained demand growth for AI services. Global technology cycles are volatile, and oversupply risks cannot be ruled out if capacity expansions worldwide outpace actual AI adoption.