Google Cloud Unveils $15B AI Data Center Campus in India, Aims for 5GW Capacity

April 25, 2026
Google Cloud Unveils $15B AI Data Center Campus in India, Aims for 5GW Capacity
  • Google Cloud plans a $15 billion AI-ready data center campus in Visakhapatnam (Vizag), India, with capacity up to 5 gigawatts and multiple data centers across the campus.

  • The Visakhapatnam campus will join Google's AI data centers across 12 countries, enabling rapid transfer of AI workflows between centers in crisis situations.

  • The Visakhapatnam project is planned over five years from 2026 to 2030 and represents Google’s largest-ever investment in India and its largest project outside the United States.

  • The plan’s 5 GW capacity is significantly larger than India's existing 2025 total data center capacity of about 1.5 GW, underscoring the scale of Google's initiative.

  • Company leadership noted that data localization mandates can be waived during crises, implying flexibility in data movement between regions in emergencies.

  • Thomas Kurian disclosed these plans during a media roundtable at Google Cloud Next 2026 in Las Vegas.

  • The investment aligns with India's Digital Personal Data Protection Act, 2023, which permits cross-border data flows while allowing government restrictions on transfers to certain jurisdictions.

  • Google Cloud CEO noted the ability to shift workloads across Google's global network during disruptions and to replicate data between Mumbai and Delhi within India if needed.

  • Google acknowledged capacity allocation constraints amid rising global demand and said it measures demand locations to better meet them.

  • Overall, the announcement marks Google's most substantial commitment in India and its biggest project outside the United States as it scales infrastructure to support AI adoption.

  • Once operational, the Visakhapatnam campus will expand Google's AI data center network and is expected to far exceed India's existing total data center capacity of about 1.5 GW as of end-2025.

  • Kurian pointed to rising demand for AI computing, highlighting API throughput increasing from 10 billion to 16 billion tokens per minute between December and March (a 50% rise in 3 months).

Summary based on 2 sources


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