IT services majors are stepping into the asset-heavy data centre business, betting on artificial intelligence (AI)-driven demand and data localization rules. Tata Consultancy Services Ltd (TCS) and HCL Technologies Ltd (HCLTech) see AI infrastructure as the next frontier, positioning themselves as full-stack players in the digital economy. Mint explains.
How much are TCS and HCLTech planning to invest in data centres?
TCS plans to invest $6–7 billion over the next decade to build 1GW of data centre capacity through its AI-focused venture, HyperVault. HCLTech is committing ₹3,500 crore (around $360 million) to build up to 50MW of capacity and has invested $150 million in sovereign AI platform Sarvam AI.
The moves signal a strategic pivot: the top-tier IT firms want to anchor AI services in their own infrastructure, rather than rely solely on outsourcing contracts. India’s data centre capacity is projected to reach 8GW by 2030 from about 1.4GW as of the second quarter of 2025, according to the Economic Survey 2025-26.
Why enter an asset-heavy business when their core is software services?
Generative AI is disrupting the traditional asset-light software business model. As AI automates parts of coding and maintenance, IT services companies can no longer rely solely on adding headcount to drive growth. TCS, for instance, expects to have as many AI agents as human employees within the next three years.
Owning infrastructure could help IT companies capture more enterprise AI spending instead of merely renting capacity or running services on third-party data centres. Training large language models requires enormous computing power and specialized hardware, including advanced chips.
Data centres will provide the base for managing AI platforms and delivering services at scale. The bet is to remain relevant in the AI era.
What is driving demand?
AI workloads are processed in data centres. India generates 20% of the world's data but has less than 3% of its data centre capacity—around 150 of 11,000 worldwide, according to the Economic Survey.
Data localization requirements, including those under the Digital Personal Data Protection Act, are adding to the demand for local infrastructure. UPI (Unified Payments Interface) growth, BFSI (banking, financial services and insurance) digitization and AI-led transformation across sectors are further strengthening the case for low-latency, sovereign AI infrastructure.
Can Indian IT companies compete with global hyperscalers?
Amazon Web Services (AWS), Google and Microsoft have unmatched scale and R&D (research and development) capabilities, and are investing heavily in India. Indian IT firms cannot match that scale, but can carve out niches.
Sovereign data requirements favour domestic operators. Price-performance also matters: local providers may offer better performance per rupee or lower costs than global players. Indian IT firms are also bundling infrastructure with AI services, offering integrated solutions rather than raw computing capacity.
Hyperscalers will remain formidable. But Indian IT companies can align with government priorities, focus on regulated industries and position themselves as partners in data localization and AI adoption.
Will other Indian IT services companies enter the business?
The risks are significant. Data centres require huge amounts of power and cooling, while land in metros is expensive and regulations vary across states. The asset-heavy model also needs long-term capital and offers slower returns than software services. Yet, the strategic importance of AI infrastructure could push more large IT companies into the business.
Success will depend on balancing capital intensity with differentiated offerings. Early movers could build a competitive moat. But missteps could leave companies saddled with underutilized assets in a market where hyperscalers continue to dominate.