Why India’s AI Boom Is Running On A Waiting List

by · Inc42

SUMMARY

  • Despite easing shortages, demand for advanced AI GPUs continues to outpace supply, pushing delivery timelines from weeks to months
  • Geopolitical tensions, export controls and component bottlenecks are forcing AI infrastructure providers to secure capacity years in advance
  • As India scales its AI ambitions through private investment and the IndiaAI Mission, access to compute is emerging as a critical competitive advantage
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The way India buys AI compute is being rewritten. The acute GPU shortage that dominated the early GenAI boom has eased from its most extreme levels, but the market is still far from relaxed. 

Industry insiders say the scramble has now shifted from older-generation GPUs to acquiring the latest-generation AI chips, which remain difficult to source. To remedy this, cloud providers are now moving to reserve capacity months in advance and leaning on mixed fleets of old and new hardware to keep workloads moving. 

At the same time, geopolitics, export controls and the concentration of semiconductor production in a handful of regions have created a system in which large strategic buyers are prioritised, while smaller enterprises are waiting in a queue. 

As if this were not enough, the supply chain bottleneck has spread into the less visible layers of the chip manufacturing stack, meaning that all parts of the AI system may not be available at the same time.

The pressure is also altering behaviour on the demand side. AI companies are responding to chip scarcity by buying more GPUs and using them more efficiently and effectively. Training is becoming more scheduled, inference is becoming the dominant workload, and software optimisation is emerging as a competitive advantage. 

This has turned compute into a strategic resource rather than a simple purchase. The effect is especially sharp in India, where almost all high-end chips are imported. As demand continues to outrun supply, how is this gap for new chips reshaping the way cloud providers and startups source, allocate and consume compute? Let’s find out…

Sourcing Problem: Waiting Time Stretches For New Chips

At the top of the chain, the core problem is that the GPU supply is not keeping pace with demand. As per a Jefferies report, 8.9 GW of global data centre capacity became operational in 2025 against demand of nearly 21.1 GW, a shortfall of about 12 GW. 

With hyperscalers expected to infuse $770 Bn (up 74% YoY) in this sector in 2026, the crunch is only expected to deepen.

However, according to India Electronics and Semiconductor Association (IESA) president Ashok Chandak, delivery timelines for AI chips have improved since the peak of the shortage, but global data centre demand continues to massively outpace supply. He frames it as a structural imbalance rather than a passing squeeze.