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Home / Business

Big Tech’s ‘spend little, earn lots’ formula is threatened by AI

Jeran Wittenstein
Bloomberg·
2 Dec, 2025 05:55 PM5 mins to read

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Big Tech's shift to AI is increasing capital expenditures, making it the most capital-intensive sector. Photo / Getty Images

Big Tech's shift to AI is increasing capital expenditures, making it the most capital-intensive sector. Photo / Getty Images

For two decades, the playbook for Big Tech was fairly simple and extremely successful: Create disruptive innovations, deliver blinding growth rates and keep a lid on spending.

A handful of behemoths like Alphabet Inc, Amazon.com Inc, Meta Platforms Inc and Microsoft Corp used this formula to seize market share from legacy businesses and power the US stock market to record after record. But a key part of the programme – the relatively small amount of capital required to generate those huge profits – is increasingly under threat from the race to develop artificial intelligence.

“They’re some of the best business models the market has ever seen,” said Jim Morrow, chief executive officer at Callodine Capital Management, which oversees US$1.2 billion ($2.09b) in assets. “Now you’ve seen this explosion in capital intensity to the point where it’s now the most capital intensive sector in the market. That’s just a radical change.”

Those four companies alone are expected to devote more than US$380b combined to capital expenditures in their current fiscal years, with most going to chips, servers and other data centre-related expenses. That’s a more than 1300% jump from a decade ago. And they’ve all pledged to spend significantly more in the year after that.

Microsoft’s capex is now 25% of its revenue, more than three times what it was 10 years ago, according to data compiled by Bloomberg. The software and cloud-computing giant’s spending-to-sales ratio is among the top 20% in the S&P 500, as are Alphabet’s and Amazon’s, well above companies in traditionally capital-intensive industries like oil and gas exploration and telecommunications.

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Despite the uncertainty of future payoffs, investors are giving the tech giants the benefit of the doubt on their AI plans, at least so far. Almost all of the big spenders have seen their stock prices rise this year, and their valuations are elevated. For example, Microsoft shares are up 16% in 2025, and the stock is priced at more than 28 times profits projected over the next 12 months, higher than its 10-year average of roughly 27 times and the S&P 500’s multiple of 22, according to data compiled by Bloomberg.

But there are creeping signs of doubt. Meta, which owns Facebook and Instagram, was punished after its third-quarter earnings report because chief executive officer Mark Zuckerberg failed to chart a convincing path to bigger profits from rising AI spending. The stock had its worst session in three years on October 30, plunging 11% the day after Meta reported earnings, and it has lost an additional 3.7% since then. After soaring 25% through the first three quarters, the shares are now up 9.6% for the year, underperforming the S&P 500.

One area of controversy is rising depreciation expenses from AI chips and servers. Michael Burry, the hedge fund manager made famous by the book The Big Short, suggested that such equipment should be written down on a faster schedule, which would seriously dent the companies’ profit growth.

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The spending is also weighing on free cash flow, which could limit the expansion of capital returns to shareholders via stock buybacks and dividends. Alphabet, for example, is projected to generate free cash flow of US$63b this year, down from US$73b last year and US$69b in 2023. Meta and Microsoft are expected to have negative free cash flow after accounting for shareholder returns, while Alphabet is seen roughly breaking even, according to data compiled by Bloomberg Intelligence.

At the same time, many companies are increasingly turning to debt and off-balance sheet vehicles to fund their spending, which raises its own risks. Meta, for instance, recently sold US$30b of bonds in the largest public high-grade corporate debt deal of the year and arranged a roughly US$30b private financing package.

Lower valuations could be the result of this shift from capital-light to capital-intensive business models, according to Michael Bailey, director of research at Fulton Breakefield Broenniman.

“A more capital-intensive business will probably have more of a boom-bust cycle,” he said. “Investors generally pay less for that.”

With seven technology companies accounting for about a third of the market capitalisation weighted S&P 500, lower multiples would almost certainly weigh heavily on the benchmark. All of which highlights the uncharted territory investors are in when it comes to AI spending. Never before have the world’s biggest and most successful companies all decided to throw so much cash at a promising, but unproven, technology.

“These are companies that historically have not really had to compete with each other. They’ve all had their own niche in a fairly oligopolistic or monopolistic sort of niche of the market, where they derived huge profits in low capital intensity businesses, and now they’re all kind of squaring off with different high capital intensity AI business models,” Morrow said. “An uncertain outcome at a really high multiple is the risk I think the market has to grapple with.”

With assistance from Subrat Patnaik, David Watkins and Stephen Kirkland.

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