The race to build AI infrastructure is accelerating at breakneck speed — but behind the optimism lies a growing financial risk few people outside Wall Street are talking about. At the WSJ Tech Live conference in Laguna Beach, OpenAI CFO Sarah Friar suggested that the U.S. government might eventually need to step in and support the massive wave of debt being used to fund AI expansion.
Her comment hinted at a potential future bailout — one that would shield corporations and investors while shifting part of the financial burden onto taxpayers. Friar later attempted to soften her remark, clarifying on LinkedIn that she meant partnership, not government guarantee. But the moment exposed a hard truth: while the bond market is large enough to absorb AI-related borrowing, its appetite for risk may not match the scale of the AI spending frenzy.
And the scale is staggering.
JPMorgan analysts estimate that AI-related investment-grade corporate bond issuance could hit $1.5 trillion by 2030 — an enormous figure compared to the roughly $1.9 trillion in total U.S. corporate bonds issued annually since 2020.
Already this year, U.S. companies have issued over $200 billion in AI-linked bonds — about 10% of the entire corporate bond market.
Major tech giants are leading the charge:
- Amazon filed a $15 billion bond sale in November
- Alphabet raised $25 billion earlier in the month, with bonds maturing up to 50 years
- Meta brought in $30 billion in October
- Oracle issued $18 billion in September
These companies don’t need the cash — they’re sitting on enormous reserves. Meta has $44.5 billion in cash and equivalents; Alphabet and Amazon have nearly $100 billion each.
This is precisely why Friar’s remark rattled markets. If investor enthusiasm starts fading, even these blue-chip borrowers may need to pay higher yields or sweeten deal terms, driving borrowing costs up across the market.
Evidence of this is already emerging. Analysts at Janus Henderson say Alphabet and Meta had to pay 10–15 basis points more on recent bond deals compared to earlier issuances. After Meta’s sale, demand for Oracle’s new bonds dropped sharply — its 2055 bonds saw spreads widen by 11 basis points in just a week.
What looks like an AI financing boom could easily spill into a broader credit tightening.
The Risk of a Concentrated Debt Market
D.A. Davidson’s head of tech research, Gil Luria, says tens of billions in AI-related borrowing is manageable — but hundreds of billions could crowd out other companies needing to raise funds.
Investors typically rely on diversification to avoid major losses. But when countless companies depend on the same AI-driven spending model, diversification stops working. Analysts at S&P Global Ratings say that if demand for AI computing slows, tech, media, and telecom issuers could all face simultaneous stress.
Todd Czachor of Columbia Threadneedle draws a parallel to the shale boom, which funneled $600 billion into a single sector and reshaped global credit markets. He estimates AI infrastructure spending could reach $5.7 trillion, an expansion on a scale he says is “on a different planet.”
With so much debt hitting the market at once, even financially strong corporations could push up spreads across entire sectors, tightening credit conditions for everyone.
Portfolio rules magnify the problem. Bond funds, pensions, and insurers often have strict limits on how much exposure they can take to a single issuer or sector. These constraints protect investors — but they also block new entrants when one industry dominates issuance.
Index rules reflect this too:
- MSCI and Fidelity cap any single issuer at ~3%
- MarketAxess uses a 4% limit
- iShares corporate bond ETFs follow similar 3% issuer caps
Right now, these ceilings haven’t been breached — Oracle sits at 2% of the main iShares fund, and Meta is barely above 1%. But AI-related issuance is accelerating fast.
Why Private Credit Isn’t the Rescue Valve
Private credit was expected to absorb a chunk of the AI buildout, but early defaults in unrelated sectors have made lenders cautious. Private credit managers cite diversification limits as a major barrier — funds simply cannot dedicate too much capital to data center or AI infrastructure deals.
Wellington Management estimates that private markets may only absorb $200–300 billion of total AI funding — far below what’s needed. That shifts the load back to the public bond market, where spreads are already widening.
Portfolio guidelines often track issuer exposure, not thematic exposure, meaning funds can legally hold multiple 3% allocations across Alphabet, Meta, Microsoft, and Oracle — while unknowingly concentrating all their risk in a single theme: the AI megacycle.
“This is one huge bet,” Khurana warns.
Why This Could Spark a Credit Crunch
Khurana argues that the debt surge from big tech has already pushed spreads higher, and one more high-quality AI borrower offering an unusually attractive yield could reset the entire corporate bond market.
Investors would rush into safer AI issuers — and dump lower-quality names.
Who’s most exposed?
- AT&T (BBB) with $150 billion in outstanding debt
- Comcast (A-) with $100 billion
- Verizon (BBB+) with $120 billion
These telecom giants are among the biggest and most frequent issuers. If forced to compete with high-yielding AI bonds, they may face soaring borrowing costs — or lose access to funding altogether.
The risk doesn’t stop there. If AI borrowers continue dominating issuance, liquidity could drain from other sectors, yields could spike, and diversification screens could shut out entire industries.
What looks like a financing boom for the future of computing may end up being the catalyst for the next major credit crunch.
