The playbook for large tech companies over the past two decades has been simple yet remarkably successful: create disruptive innovations, achieve staggering growth rates, and keep spending under control. Giants like Alphabet Inc. (GOOGL.US), Amazon.com (AMZN.US), Meta Platforms, Inc. (META.US), and Microsoft (MSFT.US) leveraged this formula to seize market share from traditional industries and propel U.S. stocks to record highs. However, a critical component of this success—the relatively low capital required to generate massive profits—is now under threat due to the AI arms race.

Jim Morrow, CEO of Callodine Capital Management, which oversees $1.2 billion in assets, noted, "These companies have had some of the best business models in market history. But with capital intensity skyrocketing, they’ve become among the most capital-intensive sectors. This is a fundamental shift."

The four tech behemoths are projected to collectively spend over $380 billion in capital expenditures this fiscal year, largely allocated to chips, servers, and data center-related costs—a staggering 1,300% increase from a decade ago. Moreover, all have pledged to significantly ramp up spending next year.

Microsoft’s capital expenditures now account for 25% of its revenue, more than triple its level ten years ago. The software and cloud computing leader ranks in the top 20% of S&P 500 companies by capex-to-sales ratio, alongside Alphabet and Amazon, far surpassing traditionally capital-heavy industries like oil exploration and telecom.

Despite uncertainty over future returns, investors have so far placed faith in these tech giants’ AI ambitions. Nearly all major spenders have seen their stock prices rise this year, with valuations remaining lofty. For instance, Microsoft shares have gained 15% in 2025, trading at over 28 times forward earnings—above its 10-year average of 27x and the S&P 500’s 22x.

Yet cracks are emerging. Meta Platforms, Inc., owner of Facebook and Instagram, faced a market backlash after its Q3 earnings report, as CEO Mark Zuckerberg failed to outline a clear path to monetize ballooning AI investments. On October 30, Meta shares suffered their worst single-day drop in three years, plunging 11% post-earnings and sliding another 3.8% thereafter. After surging 25% in the first three quarters, the stock is up just 9.5% year-to-date, lagging the S&P 500.

A key concern is rising depreciation costs from AI chips and servers. Michael Burry, the hedge fund manager famed for "The Big Short," argued that such equipment should be depreciated faster, which would significantly dent profit growth. These expenditures also pressure free cash flow, potentially limiting shareholder returns via buybacks and dividends. Alphabet, for example, is projected to generate $63 billion in free cash flow this year, down from $73 billion in 2024 and $69 billion in 2023. Meta and Microsoft are expected to post negative free cash flow after shareholder payouts, while Alphabet may barely break even.

Meanwhile, many firms are increasingly turning to debt and off-balance-sheet financing to fund their spending, adding risk. Meta recently issued $30 billion in bonds—the year’s largest high-grade corporate offering—alongside ~$30 billion in private financing arrangements.

Michael Bailey, Research Director at Fulton Breakefield Broenniman, warned that shifting from light-capital to capital-intensive models could compress valuations. "More capital-intensive businesses tend to face sharper boom-bust cycles," he said. "Investors typically assign lower multiples to such models."

Given that the "Magnificent Seven" tech stocks account for roughly one-third of the S&P 500’s market-cap weight, any valuation contraction would inevitably pressure the broader index.

The situation underscores how investors are navigating uncharted territory with AI spending. Never before have the world’s largest and most successful companies committed such vast sums to a promising yet unproven technology.

Callodine’s Morrow concluded, "Historically, these firms didn’t need to compete fiercely. They operated in oligopolistic or monopolistic niches, minting profits with low capital intensity. Now, they’re locked in a high-stakes, capital-intensive AI battle with uncertain outcomes. At sky-high valuations, this is a risk the market must grapple with."