Tech companies are ramping up their debt issuance at a pace unseen since the dot-com crash, driven by a rapid infrastructure buildout amid the ongoing AI boom, according to Mark Zandi, Chief Economist at Moody’s Analytics. In a LinkedIn post on Sunday, Zandi noted that even when accounting for inflation, major tech firms are issuing more bonds than they did during the late 1990s, and they are increasingly opting for additional borrowing beyond merely refinancing existing debt.
Zandi cautioned that while the current borrowing spree is not likely to lead to immediate downfall for AI firms, any failure to meet investor expectations could quickly turn their debts into significant liabilities. “Borrowing by AI companies should be on the radar screen as a mounting potential threat to the financial system and broader economy,” he wrote.
The ten largest AI companies, including Meta, Amazon, Nvidia, and Alphabet, are projected to issue over $120 billion in bonds this year, according to Zandi’s analysis. This trend differs sharply from the dot-com era, when internet companies primarily relied on stocks and venture capital for funding, rather than accumulating substantial debt.
“That’s not the case with the AI boom,” Zandi emphasized. Major players such as Amazon, Google, Meta, and Microsoft have the financial capacity to fund AI infrastructure through their profits, but experts suggest that bond issuance represents the “cheapest and cleanest” method for financing such a large-scale buildout, which is expected to continue for over a decade and could be worth trillions of dollars. Shay Boloor, chief market strategist at Futurum Equities, expressed that the market now perceives these companies as quasi-utility entities due to their infrastructure investments.
Over the past six months, tech companies have demonstrated “proof in the pudding” that demand for AI is surging, Boloor said. Despite concerns surrounding a potential AI bubble, Nvidia recently reported a robust earnings performance for its third quarter, with its AI data center revenue soaring by 66% year-over-year.
However, analysts warn that the pace of AI development may outstrip the speed at which infrastructure can be built. George Calhoun, a professor and director at the Hanlon Financial Systems Center at Stevens Institute of Technology, pointed out that the hardware costs associated with AI data centers could quickly become obsolete as newer technologies emerge. “The cycle of innovation in the chip industry is much faster than for wireless technology or fiber optics,” he noted, adding that there is a real risk of hardware becoming less competitive before it is fully paid off.
Another concern arises from the current financial state of leading AI ventures such as OpenAI, which lacks sufficient profits to support its substantial investments. Calhoun warned that if OpenAI were to fail, the resulting repercussions could be significant. While larger tech firms may weather the storm, companies closely linked to OpenAI, such as Oracle, could face challenges.
Despite these challenges, Boloor remains optimistic about the AI buildout, highlighting that the primary bottleneck could be the energy capacity in the U.S. “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 remarked.
See also
Bloxley Raises $2.5M to Launch AI-Native Consumer Finance Platform in Q1 2026
CFOs Embrace Lean Financial Operations with AI to Enhance Agility and Cut Costs
Citi Report Reveals AI Agents Transforming $10B ‘Do It for Me’ Economy in Finance and E-commerce
Vision Fortune Finance Institute Launches Advanced Data Engine to Enhance Fortune Nexus AI’s Analytics
Oracle Reports Q2 Revenue of $16.06B, Stock Plummets 10% Amid AI Bubble Concerns
