AI growth or bust: Wall Street debates if the newest warnings are one other head faux or the actual factor

For instance, whenever AI chip giant Nvidia saw its market cap cross the $2 trillion, $3 trillion, $4 trillion or $5 trillion milestones, bears sounded the alarm.

The borrowing binge by AI hyperscalers and their astronomical capital spending plans raised more red flags. The DeepSeek shock in early 2025 triggered another freakout as the Chinese AI model stirred doubts about the necessity of all that capex.

Also last year, OpenAI CEO Sam Altman’s admission that an AI bubble exists and Michael Burry’s bearish bets represented more red flags. This year, the Iran war, the South Korean stock market’s meltdown, and “circular” funding deals between AI companies added to the fears.

But earnings continued to soar, and stocks eventually rebounded to set record high after record high.

Of course, the persistence of traders to keep doubling down on AI could also be a sign of a bubble. Many on Wall Street also acknowledge that the good times will come to an end at some point. The only question is how long to ride the AI bets without leaving money on the table.

Now there’s a new reason to wonder if it’s time to cash out.

The current AI angst centers around whether the trillions of dollars in AI spending will pay off sufficiently, dragging down debt-laden companies like CoreWeave. The neoclound computing firm saw its stock tumble and credit default swaps surge recently.

For Dan Greenhaus, strategist at Solus Alternative Asset Management, CoreWeave isn’t a canary in the coal mine that signals the AI bust is imminent.

“How many canaries have we killed in the coal mine over the last three years as everybody has latched on to every new sign of weakness so to speak as evidence that the bull market was about to end only to see the broad market, both tech and otherwise, go on to make new highs?” he told CNBC on Friday. “So I don’t know that I would read any more into what’s happening now than I would have or did any of the other headlines.”

To be sure, borrowing costs have jumped as the Iran war and oil prices sent bond yields to the highest levels in more than 20 years. The Federal Reserve is also hiking rates again to rein in stubborn inflation.

That’s put more scrutiny on the riskier areas of the AI boom, which has grown increasingly reliant on issuing debt via the bond market.

But Greenhaus pointed out that CoreWeave’s unsecured debt has been especially targeted, calling it “the riskier of the riskier AI buildout play.” Meanwhile, earnings from AI chip suppliers like Taiwan Semiconductor indicate the broader demand environment remains robust.

At the same time, he also doesn’t expect companies across the AI ecosystem will be able to keep financing themselves indefinitely as rates go higher.

“I don’t know whether this is the breaking point or another 25 or 50 basis points higher is the breaking point,” Greenhaus explained. “But as rates move higher, the more speculative tails so to speak of the buildout are going to be called into question, and right now that’s CoreWeave.”

For its part, CoreWeave CEO Mike Intrator said markets can “misunderstand and act irrationally” and told employees in a memo that the company’s deal backlog is more than enough to sustain its debt obligations.

Nvidia CEO Jensen Huang also backed CoreWeave, which counts the chipmaker as a shareholder, saying it does not need a financial backstop.

“CoreWeave’s strength is improving every day,” he told Bloomberg. “I’m optimistic. Their cost of capital is actually decreasing.”

Others on Wall Street also see strong demand for AI and think the recent selloff is yet another buying opportunity.

Still, even eye-popping revenue estimates may not be enough to support sky-high spending. On Wednesday, Gartner warned AI data center owners need to generate a cumulative $8.5 trillion in revenue through 2030 to cover capital spending, financing costs, and a 12% return.

But total enterprise and consumer AI revenue that’s headed to data centers will only be $3.6 trillion at most, putting more than $4 trillion in asset value exposed to write-down risk through 2032.

On Friday, analysts at Bank of America said in a note that the AI investment boom is following a classic capital cycle, which usually end in disappointment “even though the underlying technology often lived up to expectations.”

Typically, early profit margins tend to be high, driving overinvestment and excess capacity while also attracting more competition.

In AI’s case, competition has already ramped up, especially from Chinese open-weight models. On top of that, business spending on AI has started to dip, as higher token volumes fail to offset lower prices for tokens.

“This monetization disappointment in the face of intense competition is precisely the failure mode seen in past capital cycles,” BofA added.