Artificial Intelligence Investments, Revenue. Spending, Expenses and Profitability: Showing Cracks

How has AI’s financial side been doing?

As of October 24^th, “Nvidia Is Now Worth $5 Trillion as It Consolidates Power in A.I. Boom” (Tripp Mickle, The New York Times, October 30^th).  One of the most dominant firms in recent times in a major field, providing “more than 90 percent of the market” for AI chips, it drew notice that its “stunning growth also comes with a warning to investors… that the stock market is becoming more and more dependent on a group of technology companies that are churning out billions in profits and splurging to develop an unproven technology that needs to deliver enormous returns.”  As of Wednesday morning, its market capitalization had dropped – to $4.52 trillion.

More money is going out, as “Big Tech’s A.I. Spending Is Accelerating (Again)” (Karen Weise, The New York Times, October 31^st).  Alphabet, parent of Google, expects to spend $91 billion this year on the technology, and Meta $70 billion.  Microsoft must handle the “$400 billion in future sales under contract,” and Amazon “had doubled its cloud infrastructure capacity since 2022, and expects to double it again by 2027.”  In response, “the Bank of England wrote that while the building of data centers, which provide computing power for A.I., had so far largely come from the cash produced by the biggest companies, it would increasingly involve more debt,” so “if A.I. underwhelms – or the systems ultimately require far less computing – there  could be growing risk.”  Indeed, “Debt Has Entered the A.I. Boom” (Ian Frisch, same source, November 8^th).  Cases include $3.46 billion in debt at “QTS, the biggest player in the artificial intelligence infrastructure market,” which will be refinanced using attachments to “10 data centers in six markets,” and the four companies just mentioned, which have “more recently… turned to loans,” adding $13.3 billion to the current inventory of “asset-backed securities (A.B.S.).” 

Soon thereafter, long-time commentator Cade Metz asked “The A.I. Boom Has Found Another Gear.  Why Can’t People Shake Their Worries?” (also in the Times, November 20^th).  “Some industry insiders say there is something ominous lurking behind all this bubbly news… a house of cards.”  Their concerns come from the thus-far unprofitability of AI producers, including Anthropic (“in the red”) and OpenAI which “is not profitable and doesn’t expect to be until 2030.”  Will these weaknesses matter, and if so, how much?

Fronting the Sunday, November 23^rd New York Times business section was “If A.I. Crashes, What Happens To the Economy?” (Ben Casselman and Sydney Ember).  If “the data center boom is overshadowing weakness in other industries,” as “everything tied to artificial intelligence is booming” and “just about everything else is not,” that means real exposure, as AI “will need to fulfill its promise not just as a useful tool, but as a transformational technology that leads to huge increases in productivity.”  Otherwise, “a lot of the investment that has been put in place might turn out to be unjustified,” meaning AI might no longer be a growth area, let alone the gigantic economic engine it was last year.

In the same publication’s “DealBook:  Penetrating the A.I. bubble debate” (December 23^rd), Andrew Ross Sorkin first asked “are we in an artificial intelligence bubble”?  One market analyst said, “if we’re not, we’re going to be,” as “railroads, steam engines, radio, airplanes, the internet” and any other “truly transformative technology” during the past 300 years” caused “asset bubble(s),” when “capital flows into a technology because everyone realizes that it’s transformative.”  The article does not consider what is clearly becoming the largest question here:  Exactly what is, and is not, a bubble?

More concerns popped up with “As A.I. Companies Borrow Billions, Debt Investors Grow Wary” (Joe Rennison, The New York Times, December 26^th).  The author mentioned that “in one debt deal for Applied Digital, a data center builder, the company had to pay as much as 3.75 percentage points above similarly rated companies, equivalent to roughly 70 percent more in interest.”  These bonds and other instruments have sometimes “tumbled in price after being issued… and the cost of credit default swaps, which protect bond investors from losses, has surged in recent months on some A.I. companies’ debt.”  Although these problems will not apply to all firms, they are bad news for an industry that many have seen as offering guaranteed success, and may stop some companies from continued operation.

On the end-user side, the “AI investment surge continues as CEOs commit to spending more in 2026” (David Jagielski, USA Today, January 8^th).  However, although “68% of executives plan to spend even more on AI this year,” “most of the current AI projects aren’t even profitable,” which “reinforces the notion that executives would rather continue investing in AI than potentially stop and perhaps admit to their shareholders that they haven’t been able to figure out to make AI generate meaningful gains.”  If that is true, it cannot go on forever, and some high-profile concerns admitting that the technology hasn’t worked for them, in part or in whole, could precipitate a swell of others doing the same.  That, for AI, would be bad.

The latest word goes to Sebastian Mallaby, who told us in the January 13^th New York Times that “This Is What Convinced Me OpenAI Will Run Out of Money.”  Remember this company had admitted no expected profitability for four more years.  While AI producers may eventually get there, “how long will it take for these companies to reach the promised land, and can they survive in the meantime?”  Per Mallaby, investors will lose patience with them, and “while behemoths such as Google, Microsoft, and Meta earn so much from legacy businesses that they can afford to spend hundreds of billions collectively as they build A.I., free-standing developers such as OpenAI are in a different position.”  So, when they can no longer get enough funding to continue, “OpenAI will be absorbed by” one of the four major firms.  That could be perceived as a bubble bursting, but “an OpenAI failure wouldn’t be an indictment of A.I.  It would be merely the end of the most hype-driven builder of it.”

There will almost certainly be some large bankruptcies.  How we get through them will be critical.  We know by now that AI will not go away, but its scope may be truncated.  In the meantime, a good façade notwithstanding, 2026 may be a bracing monetary year.  There are no guarantees – that is especially true for the business side of artificial intelligence.