The AI boom runs on chips, power, and data centers. Increasingly, it also runs on debt. New analyses from Goldman Sachs and Morgan Stanley show AI-related borrowing has hit levels that would have sounded fanciful a year ago. Both banks also flag a shift in mood. For some borrowers, the credit party for AI funding has already ended. The numbers behind the borrowing spree Goldman Sachs estimates that $489 billion in AI-related debt has been issued so far in 2026. That already sits above the $322 billion figure Goldman had forecast in 2025. Morgan Stanley takes the view out to year-end. The bank projects nearly $570 billion in global AI-related debt issuance for full-year 2026. The driver is no mystery. Hyperscalers, the giant tech firms that run cloud platforms and train frontier models, are pouring money into data centers, semiconductors, and power infrastructure. Morgan Stanley expects hyperscaler capital expenditure needs to likely exceed $1 trillion in 2027. The growth is even sharper in the riskier corners of credit. Goldman reported AI-linked leveraged finance issuance at $88 billion year-to-date in 2026. In the same period last year, that figure was $20 billion. High-yield AI ...
Goldman Sachs and Morgan Stanley dissect the AI debt binge as the credit party cools
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