AI capex projected at 3.6% of US GDP: Why the AI boom is bigger than the dotcom bubble, explains SBI MF
The surge in artificial intelligence investments has fueled strong economic growth in different parts of the world, particularly in the United States. However, the massive borrowing by hyperscalers and tech companies to fund their spending has also put upward pressure on long-term bond yields.
The scale of expenditure marks one of the largest capital spending cycles in history. Average annual AI capital expenditure (capex) is estimated at around 3.6% of US GDP during 2025–32, much higher than the 1.1% recorded during the 2000 dotcom cycle and 2.2% during the 19th-century railroad boom, NDTV Profit reported, citing a report by SBI Funds Management.
However, a key concern is whether the massive investments in AI will eventually generate enough revenue for companies to justify the spending. Technology giants such as Amazon, Microsoft, Alphabet and Meta, are spending billions of dollars on data centres, chips and other infrastructure. Worldwide spending on AI is forecast to total $2.67 trillion in 2026, marking a nearly 50% increase year-over-year, according to data from Gartner.
If AI boom fails to sustain, the impact could extend, not only to the technology sector, but also to US equities, economic growth and the allocation of capital across asset classes. With US equity valuations already looking stretched, investors could shift away from the market altogether.
SBI Funds Management noted that concerns over the sustainability of the AI boom have already triggered a repricing of US Treasury yields and prompted some foreign portfolio investors (FPIs) to redirect flows towards India.
The asset management company's remarks come following a global AI stock rout witnessed in early November across Wall Street and Asian technology hubs. This trend was driven by Democratic Party's sweep of both chambers of Congress, raising investor fears of tighter regulations, potential moratoriums and greater scrutiny of data-centre expansion, according to the news report.
Amid the AI-linked selloff, Indian indices inched higher, while large caps performed better than mid and small caps. The Nifty and the Sensex gained about 1.9% and 2.7% respectively for the month, making India one of the few major markets to advance. MSCI EM fell 6.6%, while the AI-linked markets of Korea and Taiwan, which had led gains earlier in the year, dropped 16.2% and 5.7%.
The widening sell-off reflects growing investor caution, with hedge funds reducing exposure to crowded trades, momentum strategies suffering sharp losses and large investors reluctant to step in and buy stocks during the decline, Livemint reported earlier.
In July, Aswath Damodaran, professor at New York University's Stern School of Business and a valuation expert, argued on the Excess Returns podcast that the dotcom boom was largely driven by software businesses and equity investments, the news report stated.
During the dotcom era, companies rushed to launch websites, online services and digital platforms, often without requiring massive investments in physical infrastructure. When the bubble burst, technology stocks collapsed, leaving investors with steep losses. However, the financial damage was largely limited to shareholders who had invested in these companies.
The AI boom, however, is built on a very different foundation. Training and deploying advanced AI models requires large investments in graphics processors, data centres, energy infrastructure and cloud computing networks. He called it the biggest “infrastructure buildout” witnessed in business history, comparing it to the rise of the automobile industry a century ago.
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