Google to build $15b data center hub in India

Google plans to break ground on a 1-GW data center hub in Andhra Pradesh on April 28.

The project carries a planned investment of US$15 billion, and the three campuses are expected to be commissioned by July 2028.

Google subsidiary Raiden Infotech India Private Limited is implementing the project and has partnered with Adani Infra (India) Limited, while APIIC has approved the allotment for the hub to Adani Infra.

Plans for the hub include submarine cable landings, cable landing stations, and metro fiber links.

🔗 Source: The Economic Times

🧠 Food for thought

Implications, context, and why it matters.

State incentives and clean energy are the real story behind the investment

Google’s US$15 billion plan gets a ₹22,002 crore (about US$2.45 billion) incentive package from the Andhra Pradesh government 1.
Terms include a 25% land discount, waived stamp duty and registration charges, a 10% capital subsidy on plant and machinery for 10 years, and power priced at 1 rupee (US$0.011) per unit for up to 15 years with an overall cap on the power-subsidy portion 1.
Energy sits at the center of the project. Google and Adani say they will co-invest in new transmission lines, clean energy generation, and energy storage systems in Andhra Pradesh to run the data center and strengthen grid resilience 2.
The approach matches Google’s global goal to run data centers on 24/7 carbon-free energy. An earlier Visakhapatnam plan set aside US$2 billion for renewable energy development 3.

This partnership signals India’s ambition to build domestic AI infrastructure

The Visakhapatnam hub fits Adani Group’s plan to invest US$100 billion by 2035 in renewable-energy-powered, AI-ready data centers 4.
Adani describes the push as a “sovereign energy and computing backbone” for India’s AI ecosystem 4.
The roadmap also covers India’s “five-layer AI stack” with applications, models, chips, energy, and data centers 5.
Adani says it will reserve part of its GPU capacity (graphics processing units, widely used to train and run AI systems) for Indian AI startups, research institutions, and deep-technology innovators 4.