5 min readFeb 16, 2026 12:34 PM IST
First published on: Feb 16, 2026 at 12:34 PM IST
India’s trade deal with the United States marks a significant moment in its artificial intelligence ambitions. The agreement expands access to graphics processing units, deepens technology cooperation and encourages massive foreign investment in data centres. Alongside this, the Union Budget’s generous tax holidays for foreign hyperscalers signal that India is betting heavily on building the infrastructure backbone of its AI economy. Yet when examined through economic, environmental and democratic lenses, the emerging arrangement raises questions about how balanced and sustainable this bargain is for India.
The short-term gains are undeniable. India lacks domestic GPU manufacturing capacity and remains heavily dependent on imports dominated by American firms. The trade framework helps ease these constraints by expanding access to high-end chips and helping India escape earlier export control restrictions that had capped imports of advanced GPUs. This is critical because AI innovation today is shaped largely by computing power. Although the current GPU capacity under the IndiaAI Mission stands at about 40,000, far below the computing capacity of leading global technology companies, the government is betting that this number will rise to as much as 100,000 by the end of the year.
To complement this, India has rolled out sweeping fiscal incentives to attract global cloud providers. The Budget offers foreign companies a 21-year tax holiday extending until 2047 for operating cloud and data centre infrastructure from India. These incentives aim to resolve taxation disputes, reduce costs and trigger large-scale investments. Analysts estimate that such measures could catalyse tens of billions of dollars in data centre expansion while lowering compute costs for startups and enterprises. The policy also reflects explicit US demands during trade negotiations for tax breaks, resource access and infrastructure support.
However, these policies collectively deepen structural dependence on foreign technology providers. India is offering long-term fiscal concessions and market access without clear guarantees of technology transfer or domestic intellectual property creation. New Delhi has indicated that it intends to purchase around $500 billion worth of US goods over five years, including technology products and chips. At the same time, the allocation for the IndiaAI Mission has been reduced from Rs 2,000 crore to Rs 1,000 crore, raising concerns about whether India is underinvesting in its own AI backbone. Experts have already flagged the absence of sustained frontier research funding and long-term innovation incentives as a major vulnerability.
Beyond technological dependence, rapid data centre expansion raises environmental and democratic concerns that rarely gain traction in policy debates. Data centres are resource-intensive, especially in water and energy use. A hyperscale facility near Greater Noida is expected to consume about 160 megawatts of electricity, while global estimates suggest that even a one-megawatt data centre can use up to 25.5 million litres of water annually for cooling. In water-stressed regions, this creates competition between AI infrastructure and community needs. Villagers near one such Yotta Data Centre in Uttar Pradesh already report falling groundwater levels and deeper borewells after construction began.
These trends raise questions of distributive justice. Reports also suggest communities often learn about projects only after construction begins, highlighting gaps in consultation and local participation in decisions shaping India’s digital future.
To be fair, India’s strategy reflects pragmatic sequencing. Building domestic compute ecosystems requires enormous capital and technical expertise. Leveraging foreign investment and global supply chains may be necessary to build early capacity. This year’s budget takes a broader approach of treating AI as foundational infrastructure embedded across sectors, which could also strengthen productivity and global competitiveness.
Yet, infrastructure alone does not guarantee technological sovereignty or equitable development. If foreign hyperscalers dominate India’s data ecosystem while domestic research funding stagnates, India risks becoming a hosting ground rather than a technology leader. If environmental costs and community displacement remain externalised, AI infrastructure could replicate earlier development models where economic gains were national but ecological and social burdens remained local.
The India-US trade deal, therefore, reflects a strategic gamble. It delivers compute access and investment momentum in the short term. But without stronger domestic innovation investments, environmental safeguards and democratic participation, India may find that the infrastructure powering its AI ambitions is built on foundations that are economically productive yet socially and ecologically fragile.
The writer is a former fellow of Harvard Kennedy School and teaches at Jindal School of Government and Public Policy
