America’s largest IT company has enough money to do almost everything at once for years.
According to conventional wisdom, Microsoft (MSFT), Meta Platforms (META), Alphabet (GOOGL) and Amazon (AMZN) could build data centers and buy back billions of dollars in stock while still maintaining the strongest balance sheets of corporate America.
However, artificial intelligence is starting to test this paradigm.
Billionaire investor Chamath Palihapitiya said the spending boom poses a less obvious risk. He said on the All-In Podcast on October 30 that technology companies may need external capital to finance artificial intelligence infrastructure to compete with the U.S. government, another big borrower.
Palihapitiya estimates that the broader artificial intelligence industry already owes capital markets about $340 billion to $400 billion.
This is important even though demand for artificial intelligence remains high.
Big tech companies are returning less and less to shareholders while investing more and more in infrastructure. Investors may need to pay closer attention to borrowing costs and free cash flow.
The quest to develop state-of-the-art technology is no longer the primary focus of the AI race. Financing issues have come into focus.
Big Tech’s AI spending is eating into cash returns
According to Reuters, Microsoft, Alphabet, Amazon, Meta and Oracle generated a combined $542.9 billion in operating cash flow in the first nine months of 2026.
Their capital expenditures doubled to $556.9 billion, according to 2011 data, exceeding the cash flow generated by these five companies for the first time.
Shareholders are already feeling the pinch.
The group’s total share buybacks fell 83% to $13.6 billion. At that time, Microsoft accounted for the majority of the remaining buybacks, while Alphabet and Meta did not conduct any buybacks.
This eliminates long-term windfalls for investors. By reducing the number of shares outstanding, buybacks allow earnings per share to grow faster than overall profits.
“The entire U.S. economy is leveraged by the artificial intelligence complex,” Palihapitiya said.
Artificial intelligence is not necessarily a bad investment because of its hefty expenses. If the new infrastructure generates enough revenue and profits, shareholders may ultimately benefit.
However, the threshold is getting higher and higher.
Reuters found that the five companies’ free cash flow swung to a $14 billion deficit in the first nine months of 2026, up from $143.5 billion a year earlier.
Investors are giving up some cash returns today in exchange for potentially higher AI gains in the future.
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Metadata shows how the artificial intelligence equation is changing
Meta is an example of how investing in artificial intelligence can quickly put pressure on healthy balance sheets.
S&P Global Ratings changed Meta’s credit outlook to negative on Oct. 30, citing rapidly rising capital spending and uncertainty about future free operating cash flow.
Meta expects capital spending this year to be $135 billion to $145 billion. S&P expects free operating cash flow deficits to reach $39 billion in 2026 and $71 billion in 2027, and predicts that the company may eventually use more debt to finance expansion.
Meta disagreed with S&P’s assessment and highlighted the business prospects brought by artificial intelligence.
This sums up the main tension.
Whether Meta can afford its current expansion is not an issue. It is possible. The question is how long it will take for such investments to start generating enough income to cover expenses.
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What happens when more AI companies borrow money is Palihapitiya’s broader concern.
By the end of 2027, their funding needs could account for nearly 30% of new U.S. Treasury debt issuance expected in that period, according to his forecast.
The exact ratio should be interpreted with caution as it is Palihapitiya’s estimate and not an official government measurement.
However, the idea is simple.
Many investors provide capital to companies and the federal government. To attract capital, companies may need to offer higher returns as a result of increased corporate borrowing.
This increases the required return on investment in artificial intelligence.
Microsoft shows what artificial intelligence investors need to watch
Microsoft provided an example of why the bearish scenario remains unresolved.
Microsoft Azure grew 48% in the most recent quarter, indicating that large-scale infrastructure construction is supporting huge demand.
Investors in big tech companies must see AI-related revenue and profits growing fast enough to support the investment in processors, data centers and power.
Perhaps the most obvious test is free cash flow.
If Microsoft, Meta, Alphabet and Amazon end up making money from artificial intelligence faster than capital expenditures grow, pressure on balance sheets and shareholder returns may ease.
If spending continues to rise while debt rises and free cash flow declines, Palihapitiya’s reasoning will be harder to reject.
Repo also provides another helpful tip. A steady increase in buybacks coupled with continued AI investments will indicate that these businesses are once again making far more money than they need to fund their growth.
Palihapitiya’s reasoning therefore differs from previous warnings about an AI bubble.
The financial equation doesn’t need to break down for artificial intelligence to become more challenging.
It will only get more expensive.
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