Wealth from Oracle, the giant tech company founded by Larry Ellison, is enabling Larry and his son, David, to become media moguls. Thanks to backing from Larry’s Oracle billions, David has taken control of Paramount and is now engaged in a hotly contested $111 billion bid to take over Warner Bros. Discovery, too. They are trying build a media behemoth containing two big movie studios, multiple streaming services and the news networks CNN and CBS News, all under one enormous corporate roof.
The fight over the Oracle-financed empire has, understandably, captured plenty of headlines.
But what hasn’t received nearly as much attention is another important development, the downgrading of Oracle debt. It now stands just one notch above junk bond status. That happened on July 9, when S&P Global said that Oracle’s finances had been deteriorating. Oracle has also been hit hard in the stock market, reducing the value of Larry Ellison’s holdings since September by about $230 billion, according to my calculations based on FactSet data.
What has damaged Oracle’s debt rating and disturbed its finances is the elephant stomping throughout financial markets: colossal spending on artificial intelligence.
Data centers and the other infrastructure for A.I. involve staggering sums of money. These cascades of A.I.-driven cash have enriched diverse segments of the stock market, from semiconductor makers to engineering companies to utilities to energy producers. A.I. money is bolstering the entire U.S. economy, contributing perhaps 1.1 percent to the nation’s economic growth, JPMorgan Asset Management estimates.
But where’s that money coming from?
At this point, a major source is firms like Oracle, which has gone on an immense spending spree on A.I. data centers, increasingly selling bonds to raise the money. Oracle is not alone. Alphabet, Microsoft, Amazon and Meta are giant investors in data centers, too. (The industry jargon is “hyperscaler.) But their underlying finances are stronger than Oracle’s, and their expenditures have not landed them in the same level of trouble in the markets.
Microsoft, for example, has a Triple-A credit rating — better than the U.S. government’s. Whether Microsoft manages to retain that rating after its splurges on A.I. data centers remains to be seen. “Microsoft is starting from a much better place, financially, than Oracle is,” Mariya Entina, a portfolio manager for DoubleLine, the money management company, said in an interview. “It’s important to have enough information to be able to differentiate.”
These five companies combined are pouring more than $800 billion into A.I. investments this year, and plan to add more than $1.2 trillion in 2027, according to Morgan Stanley. To put that in context, as Robert Armstrong of The Financial Times noted, the U.S. military budget request for 2027 is less than that: $961 billion, according to the Congressional Budget Office.
Few people outside the markets have paid attention to what goes on behind the financial curtain for artificial intelligence. These big companies are able to categorize the money as an investment — a capital expenditure — and not as an expense. So under current accounting rules, the bulk of the spending has not yet counted against their gaudy earnings. That is helping to propel the stock market to new heights under rosy assumptions that A.I. will transform the world, and that the companies behind it will be making money.
With the notable exception of Oracle, which has borrowed aggressively for the last couple of years, most of these companies generated so much cash from their main businesses that, until recently, their spending on A.I. data centers barely weighed on the performance of their stock or on the solidity of their underlying finances.
But this year is turning out to be different.
A.I. data centers are increasingly running on borrowed money. The problem goes way beyond Oracle.
Hungry for Money
The gigantic A.I. infrastructure expenditures are outpacing growth in profits. According to Bank of America, total capital expenditures for Oracle, Alphabet, Microsoft, Amazon and Meta are exceeding their free cash flow. That’s the money their businesses generate beyond what they need to operate and invest in the future.
The hunger for cash is likely to mount. Bank of America noted that these big tech companies, which formerly operated on relatively little invested capital, are now as capital-intensive as old-line fossil fuel companies like Exxon Mobil and Chevron.
So the tech companies are going to the capital markets, mainly the bond market, which has begun to charge premiums for what it considers to be heightened risk. Oracle and Amazon bond prices have been hard hit. So have those issued by SpaceX, which is also building A.I. data centers. Its bonds are rated as investment grade but have been trading at fire-sale prices, like junk bonds.
One problem is that the expected revenue for the data centers isn’t rock solid. Much of it is linked to A.I. start-ups like OpenAI and Anthropic, which themselves rely on borrowed funds and speculative investments by venture capitalists and private equity funds. Oracle’s heavy dependence on OpenAI makes it especially vulnerable, S&P Global said.
In a presentation to reporters earlier this month, Savita Subramanian, Bank of America’s chief equity strategist, drew parallels with the dot-com era of the late 1990s and early 2000s. The big “hyperscalers” have far more solid business models than many of the old internet companies did, she said, but their immense need for borrowing “is a little nerve-racking.”
If their returns from A.I. investments don’t pan out, or if their borrowing costs become onerous because of rising rates on debt, these companies may not be in an enviable position. There will be questions about whether their share pricing is “appropriate,” she said, given their “leverage and capital intensity.”
A Great Winnowing
There are signs that the markets may have started to recoil from some of the more extravagant A.I. bets.
Four of the five big, long-established data-center companies have underperformed the S&P 500 this year. Oracle has been leading the pack downward, with a fall of more than 35 percent through Thursday.
Alphabet, on the other hand, has been ahead of the market, with a stock gain of more than 13 percent. Alphabet’s bonds are faring better, too. It may not just be that its Gemini A.I. model is highly rated. The company’s finances are more solid than Oracle’s. It has plans to raise more money through bonds — but also through additional equity sales, which would dilute the value of existing stock shares. The stock market has so far shrugged off that move.
SpaceX became a publicly traded company on June 8 — and is building big A.I. data centers with borrowed money. Its share price has been otherworldly, although the company has no earnings. The consensus estimate is that it will generate some next year — but only enough to give it a price-to-earnings ratio of 182, based on its current share price, according to FactSet. That number, which measures a stock price against a company’s earnings, is still off the charts: It’s 6.5 times the valuation of the average company in the S&P 500.
This week, SpaceX shares for the first time fell below their initial public offering price, a move that I’ve suggested is warranted.
One day earlier, IBM’s shares lost 25.2 percent. That was its steepest daily decline since the 1960s, and it was set off by an earnings shortfall that its chief executive attributed, in part, to the spending underway on A.I. data centers. “We did not anticipate the magnitude of the capex reprioritization,” Arvind Krishna, the company’s chief executive, wrote in a letter to investors. Other companies spent so much money to build A.I. foundations, he said, that there wasn’t as much left as expected for software service companies like IBM.
These are early days.
I have no doubt that artificial intelligence is an important technology. Great fortunes are already being made. But I’m also certain that there will be many losers, as there were in two other episodes of mammoth infrastructure investments in budding technologies: the railroads in the 19th century and the various early internet companies of the dot-com era.
Well-run, diversified and deep-pocketed companies have a better chance of survival in epochs like these than those that take on inordinate risk with their capital investments. Even so, the future champions may not be any of the early giants.
A great winnowing is coming, and prudent investors will accept that they cannot know in advance who the winners and losers will be.
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