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Microsoft to invest US$3 billion in AI and cloud computing in India

Microsoft to invest US$3 billion in AI and cloud computing in India

Aims to train 10 million people on AI.

By Abbinaya Kuzhanthaivel on Jan 8, 2025 8:03PM

Microsoft will invest US$3 billion in India over the next two years, focusing on cloud and AI infrastructure, including the establishment of new data centres. 

The tech giant already has three cloud regions in India - Pune, Chennai, and Mumbai, with the fourth ready to go live in 2026. The company said this investment aims to develop a scalable AI computing ecosystem to meet the growing demands of India’s rapidly expanding AI start-ups and research community.

In 2024, Microsoft acquired a 16-acre plot of land in Pune for a new data centre. The company is also expanding in Hyderabad, with the development of a new cloud region.

The company aims to invest US$ 80billion in building AI data centres during the 2025 financial year, marking a substantial increase from last year. Over half of this investment will be directed towards the United States.

Microsoft chairman and CEO Satya Nadella also announced partnerships with private and public sector firms including RailTel, Apollo Hospitals, Bajaj Finserv, Mahindra Group, upGrad and India AI, a division of Digital India Corporation, to advance AI adoption.

The partnership with RailTel involves a five-year agreement to transform Indian Railways and the public sector through AI integration. 

Apollo Hospitals will work with Microsoft on healthcare solutions, including the creation of four specialised AI copilots for clinicians, patients, nurses, and hospital operations.

Microsoft further aims to train 10 million people in AI by 2030, as part of its ADVANTA(I)GE INDIA initiative. Their research lab established an AI Innovation Network to build new collaborations, especially with digital natives, to accelerate the transition from research to real, usable business solutions.

The lab has partnered with Physics Wallah on math reasoning and is in ongoing discussions with other natives on topics such as causal inference, optimising Indic LLMs, prompt optimisation, and reinforcement learning.

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