A key component of the success model of U.S. technology giants in the past, which required relatively little capital to generate substantial profits, is increasingly under threat from the race to develop artificial intelligence.
According to Zhitong Finance, for two decades, the playbook for success among large technology companies has been rather straightforward yet immensely effective: create disruptive innovations, achieve remarkable growth rates, and maintain control over expenditures. A handful of tech giants, such as $Alphabet-A (GOOGL.US)$ 、 $Amazon (AMZN.US)$ 、$Meta Platforms (META.US)$ and$Microsoft (MSFT.US)$ , have leveraged this formula to capture market share from traditional enterprises and propel U.S. equities to repeated record highs. However, a critical component of this success model—generating substantial profits with relatively modest capital requirements—is increasingly under threat due to the race in artificial intelligence research and development.
Jim Morrow, CEO of Callodine Capital Management, which oversees $1.2 billion in assets, stated, “These companies possess some of the best business models the market has ever seen.” “But now, with a surge in capital intensity, they have become one of the most capital-intensive sectors in the market. This is nothing short of a fundamental shift.”
The four aforementioned companies are projected to collectively invest more than $380 billion in capital expenditures during the current fiscal year, with the majority allocated to chips, servers, and other data center-related expenses. This represents an increase of over 1,300% compared to a decade ago. Moreover, all these companies have committed to significantly boosting their spending in the next fiscal year.
Data shows that Microsoft’s capital expenditure now accounts for 25% of its revenue, more than triple what it was a decade ago. The software and cloud computing giant’s spending-to-sales ratio ranks among the top 20% of S&P 500 constituents, as do those of Alphabet and Amazon, far surpassing traditional capital-intensive industries like oil and gas exploration and telecommunications.
Despite uncertainties about future returns, investors have so far extended trust to these tech giants’ AI initiatives. Nearly all major spenders have seen their stock prices rise this year, accompanied by high valuations. For instance, Microsoft’s stock has climbed 15% in 2025, trading at a price-to-earnings (P/E) ratio exceeding 28 times based on expected earnings over the next 12 months. This is higher than its ten-year average of approximately 27 times and surpasses the S&P 500’s P/E ratio of 22 times.
However, signs of skepticism are quietly emerging. Meta, which owns Facebook and Instagram, faced market punishment following the release of its third-quarter earnings report, primarily because CEO Mark Zuckerberg failed to outline a clear path to achieving greater profitability from its escalating AI expenditures. On October 30, Meta experienced its worst trading day in three years, with shares plummeting 11% the day after the earnings announcement, followed by an additional 3.8% decline. After surging 25% in the first three quarters, the stock is up just 9.5% year-to-date, underperforming the S&P 500.
One contentious issue lies in the rising depreciation costs associated with AI chips and servers. Michael Burry, the hedge fund manager famous for “The Big Short,” has suggested that such equipment should be depreciated more quickly, which would severely undermine the profit growth of these companies.
These expenditures also exert pressure on free cash flow, potentially limiting the scale of capital returned to shareholders through stock buybacks and dividends. For example, Alphabet is projected to generate $63 billion in free cash flow this year, down from $73 billion last year and $69 billion in 2023. According to data, after accounting for shareholder returns, Meta and Microsoft are expected to post negative free cash flow, while Alphabet’s is anticipated to remain roughly flat.
At the same time, many companies are increasingly turning to debt and off-balance-sheet financing instruments to fund their expenditures, which also brings risks. For example, Meta recently issued $30 billion in bonds, marking the largest high-grade corporate bond deal of the year, in addition to arranging approximately $30 billion in private financing solutions.
Michael Bailey, director of research at Fulton Breakefield Broenniman, stated that the shift from a light-capital model to a capital-intensive business model could lead to lower valuations.
"A more capital-intensive business may experience more pronounced boom-and-bust cycles," he said. "Investors typically assign lower valuations for this."
Since the Mag 7 account for roughly one-third of the market-cap-weighted S&P 500 Index, a reduction in valuation multiples will almost certainly place significant pressure on the index. All of this underscores that investors are venturing into uncharted territory in terms of AI spending. The world's largest and most successful companies have never before decided to allocate so much cash toward a promising but unproven technology.
Callodine's Moro stated, "These companies historically did not really need to compete with each other. They each had their own territories within relatively oligopolistic or monopolistic market niches, generating enormous profits in low-capital-intensity businesses. Now, they are engaging in some form of competition with their respective high-capital-intensive AI business models." "At very high valuation multiples, facing uncertain outcomes, I believe this is a risk the market must contend with."
Editor/Liam
