Tech companies are issuing more debt now than before the dot-com crash as a rapid infrastructure buildout unfolds in the AI boom, Moody’s Analytics Chief Economist Mark Zandi said in a LinkedInpost on Sunday.
Even after adjusting for inflation, big tech companies are issuing more bonds than during the late 1990s. And the companies aren’t just refinancing existing debt—they’re taking on additional debt.
“While the increasingly aggressive (and creative) borrowing by AI companies won’t be their downfall, if they do fall short of investors’ expectations and their stock prices suffer, their debts could quickly become a problem,” Zandi wrote. “Borrowing by AI companies should be on the radar screen as a mounting potential threat to the financial system and broader economy.”
The 10 largest AI companies, including Meta, Amazon, Nvidia and Alphabet, will issue more than $120 billion this year, Zandi said in a LinkedIn analysis last week.
And this time is different from dot-com era debt issuance, as internet companies back then didn’t have a lot of debt, he pointed out. Instead, they were funded by stocks and venture capital.
“That’s not the case with the AI boom,” Zandi added.
Even though hyperscalers like Amazon, Google, Meta and Microsoft could pay for the AI buildout with their profits, bond issuance is the “cheapest and cleanest” way to finance an infrastructure buildout of this scale, which will likely last more than a decade and be worth trillions of dollars, Shay Boloor, chief market strategist at Futurum Equities, told Fortune.
“These companies are a lot more comfortable issuing 10- to 40-year papers, for example, at very low spreads, because the market now views them as quasi-utility names—because they’re building all this infrastructure—not just a pure tech company anymore,” Boloor said.
He added that in the previous six months, tech companies have shown “proof in the pudding” that future demand for AI is booming.
Despite AI bubble concerns, Nvidia delivered a strong earnings report for its third quarter last month, saying its AI data center revenue increased by 66% from last year.
Still, critics warn that the buildout may not keep up with how rapidly AI is developing.
Computer hardware, which makes up most AI data centers’ cost, may be more susceptible to becoming obsolete and replaced by more advanced technology during the AI boom as opposed to wireless and internet buildouts, much of which still runs today, George Calhoun, professor and director of the Hanlon Financial Systems Center at Stevens Institute of Technology, told Fortune.
“The cycle of innovation in the chip industry is much faster than for wireless technology or fiber optics,” he explained. “There is a real risk that much of that hardware may become competitively disadvantaged by newer technologies in a much shorter timeframe,” before being fully paid off.
At the same time, big players in the AI boom—namely OpenAI—do not have the profits currently to cushion their massive investments, increasing their risk, Calhoun said.
“If OpenAI fails, the snowball effect of that is going to be substantial,” Futuruum Equities’ Boloor said. Though larger tech companies won’t likely be impacted much by a potential OpenAI bust, companies that largely rely on its business like Oracle could, he added.
Still, Boloor is optimistic about the AI buildout, saying the main bottleneck for its success is U.S. energy capacity.
“I think that the risk is that trillions of dollars of AI capacity gets built faster than the North American grid can support it, which could slow realization,” he warned.
