India's Data Centre Capacity Set to Surge Fivefold by 2030, Fueled by Tech Investments

Macquarie Equity Research projects a significant boom in India's data centre infrastructure. The current operational capacity of 1.4 GW is expected to double to 2.8 GW by 2027 with under-construction projects. If planned pipeline capacity is realized, this could expand fivefold to 7 GW by 2030.

Key drivers for this growth include India's data localisation laws, a favorable regulatory environment, government incentives, and the accelerating adoption of cloud computing across various industries.

The report estimates cumulative capital expenditure, excluding servers, to range between $30 billion and $45 billion, based on project cost estimates of $4 million to $7 million per Megawatt (MW).

This expansion is being bolstered by substantial investments. Notably, Google announced plans to invest $15 billion for an AI infrastructure hub in Andhra Pradesh, in partnership with Adani Group, including a gigawatt-scale data centre powered by clean energy. This investment will be spread over 2026-2030.

Other significant announcements mentioned include Tata Consultancy Services' $6.5 billion investment, Reliance Jio's green AI data centre plans in Jamnagar with Meta and Google as partners, and Amazon Web Services' commitment of $13 billion to expand its cloud infrastructure in India by 2030.

Impact This news is highly significant for the Indian stock market, indicating massive investment inflows into digital infrastructure and technology, potentially boosting related companies and the broader economy. Rating: 9/10.

Definitions: GW (Gigawatt): A unit of power equal to one billion watts. It is used here to measure the total capacity of data centers. MW (Megawatt): A unit of power equal to one million watts. It is used to measure the capacity of individual data center projects. Data Localisation Laws: Regulations that require companies to store data collected from a country's citizens or businesses within that country's borders. Cloud Adoption: The process of businesses and individuals using cloud computing services (such as data storage, software, and processing power delivered over the internet) instead of on-premises hardware and software. Pipeline Capacity: Refers to data center capacity that is currently in the planning stages and has not yet begun construction. Cumulative Capital Expenditure: The total amount of money invested over time in building and equipping infrastructure, in this case, data centers, not including the cost of the computing hardware itself (servers). AI Infrastructure Hub: A specialized facility designed to support artificial intelligence development and operations, featuring high-performance computing, large-scale data storage, and advanced networking.