Investment in the global artificial intelligence trade is shifting from semiconductors toward infrastructure assets, with India positioned as a primary opportunity [1, 2, 3].
This transition matters because it signals a move toward the physical requirements of AI—such as power and cooling—rather than just the chips that run the software. As the first wave of semiconductor investment matures, capital is flowing into the "picks-and-shovels" of the industry [1, 2].
Abhay Laijawala, CIO of Lighthouse Canton, said India's specific opportunity lies in AI infrastructure, including power and cooling systems [1]. Rahul Chadha, Managing Partner at Shikhara Investment, said the risk-reward balance is tilting in India's favor as macro-risk premiums are priced in and oil-supply diversification reduces geopolitical risk [2].
Supporting this shift is a significant government push. The Indian government has announced an investment of Rs 1.64 lakh crore [4] for AI and semiconductor manufacturing. This initiative coincides with the Digital India programme, which completed 11 years on July 1, 2026 [4].
There is some disagreement among analysts regarding the scale of this shift. While some experts highlight the growth of physical infrastructure, a June 18 report from CNBC suggested that physical infrastructure may actually take up a smaller share of capital expenditures compared to chips [3].
Despite these differing views, the trend suggests a diversification of the AI trade. Investors are increasingly looking at mid-cap Indian companies that provide the essential utility, and hardware support needed to sustain massive data centers [1].
“India's opportunity lies in AI infrastructure, power, cooling and other ‘picks‑and‑shovels’ plays.”
The movement of AI capital toward infrastructure indicates that the industry is entering a deployment phase where physical constraints—like electricity and heat management—become the primary bottlenecks. For India, leveraging its existing digital framework and new government subsidies could allow it to capture a significant portion of the global supply chain for AI support services, moving beyond software outsourcing into hard infrastructure.
