AI Data Centres in India: Growth and Future

Artificial intelligence is creating a new infrastructure race in India. Training massive AI models and executing millions of AI queries needs significantly more computational power compared to normal digital applications. This has led to the development of dedicated AI data centers in India, which are built around GPU density, enhanced networking capabilities, high-level cooling facilities, and a reliable power supply.

There is an existing booming data center industry in India. According to the government statistics, there was an increase in the data center capacity in India from 375 MW in 2020 to 1,575 MW in 2026. On the other hand, IndiaAI Mission aims at increasing AI compute access for startups, researchers and others.

The next phase is different, however. Instead of simply adding conventional server capacity, India is increasingly building infrastructure specifically designed for AI workloads.

What Are AI Data Centres?

AI Data Centre: An AI data center is a purpose-built facility for training and deploying AI-based models on a massive scale. Normal data centers can handle website servers, cloud computing applications, databases, and enterprise software. AI applications might be computationally much more demanding in terms of number of GPUs or other specialized processors required.

Hence, an AI-ready data center needs much more than just server racks.

It typically requires:

High-density GPU computing
High-speed networking between processors
Advanced power distribution
Liquid or other high-performance cooling technologies
Large and reliable electricity supplies
High-bandwidth fibre connectivity
Strong physical and cybersecurity
Efficient energy and water management

For example, TCS’s HyperVault project in Hyderabad is being designed with high-density GPU deployments and direct-to-chip liquid cooling for AI training and inference workloads.

Why Are AI Data Centres Growing in India?

The demand for AI infrastructure in India is being led by various forces rather than one specific force. Firstly, businesses in India have started using generative AI, machine learning and AI-driven automation in various sectors including banking, healthcare, manufacturing, retail and technology.

Second, global technology companies increasingly want computing infrastructure closer to their customers and data. India’s large digital economy, technology workforce and expanding cloud market make it an important location for this infrastructure.

Third, the Indian government is actively trying to increase domestic access to AI compute. The IndiaAI Mission, approved with an outlay of ₹10,371.92 crore, includes a compute pillar designed to establish a public-private AI computing ecosystem of 10,000 or more GPUs.

By 2026, the government said more than 38,000 GPUs had been empanelled through 14 AI service providers, with AI compute being made available through the IndiaAI Compute Portal. The government has also said additional GPU capacity is being added.

This matters because access to compute is one of the biggest barriers for AI startups and researchers.

India’s Data Centre Capacity Is Expanding

AI is accelerating an already growing data-centre market.

As per CBRE, India’s operational data centre capacity stood at roughly 1,530 MW by September 2025, having witnessed addition of roughly 260 MW of supply over the first nine months of that year.

According to JLL, the country’s data centre capacity can touch 1.8 GW by 2027, with AI and demand from cloud service providers being some of the key drivers.

Latest information by the government indicates an installation capacity of approximately 1,575 MW. These prominent locations include Mumbai, Navi Mumbai, Chennai, Hyderabad, Bangalore, Delhi-NCR, and Jamnagar; the locations where there are some fresh investment prospects include Andhra Pradesh, Madhya Pradesh, Chhattisgarh, and West Bengal.

Importantly, this overall data-centre capacity should not be confused with dedicated AI capacity. Much of India’s existing infrastructure supports conventional cloud and enterprise workloads as well as AI.

Major AI Data Centre Projects in India

Several large projects illustrate how quickly the market is changing.

Google and AdaniConneX in Visakhapatnam

Google announced an approximately $15 billion investment over five years from 2026 to 2030 to establish an AI hub in Visakhapatnam, Andhra Pradesh.

The project includes gigawatt-scale data-centre infrastructure, energy infrastructure and a new international subsea gateway. Google is working with AdaniConneX and other ecosystem partners on the project.

This is significant because the project combines computing, energy and international connectivity rather than treating the data centre as an isolated facility.

Meta and Reliance in Jamnagar

Meta has agreed on a pact with Reliance Industries to set up an AI-enabled data center at Jamnagar, Gujarat.

This initial phase will be of 168 MW and scalable, with Meta leasing the capacity and Reliance providing the infrastructure and associated facilities.

The facility is planned to use renewable energy and desalinated seawater for cooling.

This is an example of the emerging built-to-suit model, where infrastructure is designed around the requirements of a major AI customer.

TCS HyperVault in Hyderabad

In September 2026, TCS announced that its HyperVault subsidiary had secured 264 acres for a 1 GW AI data-centre campus in Hyderabad.

The project is expected to be developed in phases and designed for frontier AI companies and hyperscalers. TCS says the campus will use high-density, liquid-cooled infrastructure and green-energy and water-neutral design principles. The company and its partners expect to invest up to ₹70,000 crore in developing and managing the infrastructure.

The project demonstrates how Hyderabad is positioning itself as an important location for high-performance AI infrastructure.

Yotta’s GPU Infrastructure

Yotta has also become an integral part of India’s AI computing industry.

Yotta revealed its intention to install 20,736 NVIDIA Blackwell Ultra GPUs at its data centre in the Greater Noida area, which will cost more than two billion dollars. Yotta stated that the installation would be live from August 2026.

Yotta is also an empanelled service provider under the IndiaAI Mission and provides GPU infrastructure through its cloud platform.

These projects show that India’s AI infrastructure is developing through several models: hyperscale campuses, built-to-suit facilities, sovereign AI infrastructure and GPU-as-a-service platforms.

Where Are AI Data Centres Being Built in India?

The main data-center markets in India have been Mumbai, Chennai, Delhi-NCR, Bengaluru and Hyderabad.

As per CBRE, at the end of September 2025, Mumbai contributed nearly 53% of the data-center space in India, after which came Chennai, Delhi-NCR and Bengaluru, making up 90% of the nation’s capacity in aggregate.

However, AI is changing the geography of the map.

Newer cities such as Visakhapatnam and Jamnagar are becoming home to data centers because AI data centers need a lot of energy, land and connectivity. Sometimes the access to energy becomes more crucial than the commercial center.

Why Power and Cooling Matter So Much

AI data centres are fundamentally an energy and cooling challenge. High-performance GPUs produce substantial amounts of heat, especially when many processors are running simultaneously. Air cooling systems are not always efficient in case of extreme densities of racks, which is why liquid cooling systems are used more often.

Power is an even larger issue. In July 2026, the government told Parliament that AI data centres could add 26.3 GW of electricity load by 2031–32, with the additional demand expected to be integrated into the grid and primarily served by renewable-energy capacity.

The figure is a projection, not current consumption. It also shows why AI data-centre development cannot be separated from India’s electricity generation, transmission and renewable-energy expansion.

Water is another consideration. Cooling requirements depend heavily on the technology used. Government information notes that modern AI infrastructure is increasingly adopting direct-to-chip liquid cooling, adiabatic cooling, immersion cooling and closed-loop systems.

What Does India’s AI Data Centre Growth Mean?

The expansion could have effects beyond technology companies. AI data-centre construction creates demand for electricity infrastructure, renewable power, transformers, cooling equipment, networking hardware, construction, engineering and specialised operations.

It could also help Indian startups and researchers gain better access to computing resources. The IndiaAI Mission’s shared compute model is particularly important because smaller organisations may not be able to purchase or operate expensive GPU clusters themselves.

For businesses, locally available AI infrastructure can also improve latency, data-control options and the ability to deploy AI workloads within India.

However, growth is not automatically beneficial. Power availability, transmission infrastructure, water consumption, environmental impact, GPU availability and project economics will determine how quickly announced capacity becomes operational.

The Future of AI Data Centres in India

India’s AI data-centre story is still developing. The country is moving from a traditional cloud and colocation market toward infrastructure specifically designed for high-density AI computing. Government-backed compute programmes are developing alongside private-sector investments from companies such as Google, Meta, Reliance, TCS, Yotta and others.

The most important change may be that compute is becoming strategic infrastructure. It is clear that the success of artificial intelligence in India will be dependent not just on the algorithms and software but also on whether India is able to provide enough GPUs, power supply, bandwidth, and cooling for compute. If India is successful in doing that, AI data centers can become an integral part of the Indian digital infrastructure.

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FAQs

What is an AI data centre?

An AI data centre is a specialised computing facility designed to train and run artificial intelligence models using high-performance GPUs or other AI accelerators, advanced networking and high-density cooling systems.

Why does India need AI data centres?

India requires AI Data Centers in order to offer computational capabilities for Indian AI startups, enterprises, research purposes, governmental uses and foreign tech firms working with AI technologies from India.

Which companies are building AI data centres in India?

Major announced or developing projects involve companies and groups including Google, AdaniConneX, Reliance Industries, Meta, TCS through HyperVault and Yotta, among others. Projects vary according to their size, location, ownership, and purpose.

Which Indian cities are major data-centre hubs?

Data centres in Mumbai, Navi Mumbai, Chennai, Hyderabad, Bengaluru, and Delhi-NCR have been some prominent ones. There are new projects in other areas as well like Visakhapatnam and Jamnagar.

How much power will AI data centres need in India?

The Ministry of Power has projected an additional 26.3 GW of load from AI data centres by 2031–32. This is a future projection rather than current consumption.

What is IndiaAI Compute?

IndiaAI Compute is part of the IndiaAI Mission and is intended to provide shared access to high-performance computing resources. The government confirmed that over 38,000 GPUs were empanelled with 14 AI service providers up to 2026.

Are AI data centres different from normal data centres?

Yes. While both involve servers and networking infrastructure, AI centers are usually built to provide a far greater density of computing resources and may need specialized GPUs, faster connections, advanced cooling systems and increased power supply.

Conclusion

The growth of AI data centres in India represents a shift in the country’s digital infrastructure strategy. India is no longer simply adding server capacity for cloud and enterprise applications; it is increasingly building infrastructure specifically for large-scale AI computing.

Projects in Visakhapatnam, Jamnagar, Hyderabad, Greater Noida and other locations show the scale of investment being considered. At the same time, India’s biggest challenge will be ensuring that computing growth is matched by reliable power, connectivity, cooling, skilled infrastructure operations and sustainable resource use.

For India’s AI ambitions, the data centre is becoming much more than a building full of servers. It is becoming the physical foundation on which the country’s AI economy will operate.

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