A new analysis from JPMorgan signals that Wall Street’s AI infrastructure boom may be entering a phase where funding demands push the limits of global credit markets, reviving fears of a setup reminiscent of the early-2000s telecom crash.
JPMorgan strategists led by Tarek Hamid say the hyperscaler-driven race to construct AI data centers will require tapping every corner of the capital stack, with investment-grade bond issuance alone expected to total roughly $1.5 trillion over the next five years, reports Bloomberg.
The bank estimates total AI data center spending could run at least $5 trillion, with a potential ceiling near $7 trillion, forcing capital to flow from investment-grade markets, high-yield credit, securitizations, private lenders and even governments. If fully realized, JPMorgan argues the buildout would “access every capital market.”
Even after anticipated borrowing across debt markets and roughly $150 billion in leveraged-finance capacity, JPMorgan still sees a $1.4 trillion funding gap. The firm says private credit and public-sector support would likely be needed to bridge the shortfall.
JPMorgan says the largest hyperscalers currently generate around $700 billion a year in net operating income and are diverting about $500 billion of it to capital expenditures, underscoring the extent to which Big Tech balance sheets are now intertwined with the AI cycle.
But the strategists warn that the scale of the buildout echoes the bubble witnessed in the late 1990s and early 2000s, when telecom and fiber-optic network overcapacity, along with stratospheric valuations, triggered a massive meltdown.
“Even if everything works, there will be spectacular winners, and probably some equally spectacular losers as well, given the amount of capital involved and winner-takes-all nature of portions of the AI ecosystem.”
Earlier this month, news emerged that US firms led by Meta, Oracle and Alphabet have issued $200 billion in bonds this year to fund the AI push.
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