AI-related debt issuance hit $489 billion by mid-2026, according to Goldman Sachs, with hyperscalers Alphabet, Amazon, Meta, Microsoft, and Oracle responsible for roughly 40% of it. Bond investors are pricing in longer, riskier AI spending cycles, and the strain is starting to reach mega-cap tech valuations.
AI-related debt issuance reached $489 billion by mid-2026, according to Goldman Sachs. Hyperscalers — Alphabet, Amazon, Meta, Microsoft, and Oracle — accounted for roughly 40% of that total. Over the past five years, these firms added approximately $350 billion in debt specifically for AI data center expansion.
Borrowing accelerated through 2025 and 2026
Corporate bond issuance tied to AI infrastructure hit around $120 billion in 2025 alone. That marked growth of over 500% compared to 2024.
Meta issued roughly $30 billion in bonds earmarked for data centers. Alphabet and Oracle together sold nearly $60 billion in bonds in February 2026 alone.
Credit markets start pricing in risk
Bond investors are starting to question whether AI capital expenditure cycles are as short and safe as the original pitch suggested. Oracle's credit default swap spreads increased 44%, reaching 87 basis points within a month of its heavy borrowing activity.
Investors are also selling longer-dated AI-linked bonds, wary of holding 30-year paper from companies whose cash flow picture five or ten years out stays uncertain. Oracle and Amazon, most visibly, are showing rising leverage indicators alongside negative free cash flow projections.
Pressure reaches mega-cap valuations
For equity investors, a growing debt load paired with negative free cash flow pushes the market to discount future earnings more aggressively. That pressures valuations, particularly for the mega-cap tech names that have traded at premium multiples precisely because of their perceived financial strength. If investors keep demanding higher yields on AI-linked debt, the cost of capital rises across the sector — compressing margins, slowing infrastructure buildout, and potentially delaying the timeline for turning AI investment into AI revenue.
AI-adjacent crypto assets, including tokens tied to decentralized compute and AI inference infrastructure, have attracted investment partly on the premise that AI demand is structurally unstoppable. If that sentiment keeps cracking in traditional finance, the pressure could spill into crypto assets riding the same thematic wave.
Source: Crypto Briefing
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