In a report published on September 11, 2026, S&P Global Ratings raised alarms over the rapid escalation of AI-related debt among major hyperscalers—including Amazon, Alphabet, Microsoft, Meta, Oracle, and SpaceX. The agency noted that while these firms remain investment-grade borrowers, their credit quality is gradually deteriorating due to mounting debt burdens tied to AI infrastructure expansion. Amazon alone has raised approximately $100 billion in bond financing this year to support its AI buildout.(axios.com)
S&P analysts highlighted that much of this borrowing is not only for internal use but also to back lending to riskier counterparties, leveraging their pristine credit ratings to facilitate broader AI ecosystem financing. This interconnected structure raises systemic concerns: if one of the lesser-known borrowers falters, it could ripple back to the hyperscalers.(axios.com)
The warning comes amid a broader trend: hyperscalers are projected to spend over $1.3 trillion on AI infrastructure by 2027, with negative free operating cash flow expected through 2026 and 2027. To fund this, they are increasingly relying on complex financing structures—debt issuance, leases, SPVs, and residual value guarantees—that obscure true leverage and complicate credit analysis.(press.spglobal.com)
Despite these concerns, S&P emphasized that the risks are not yet existential. Most hyperscalers maintain strong balance sheets and high credit ratings, though Oracle stands out as more vulnerable. Still, the agency warned that “Rumsfeldian” unknowns—unforeseen risks—are growing in this massive, debt-fueled sector.(axios.com)
This development underscores a critical inflection point: the AI boom is no longer just a technology story—it’s a capital markets story. As hyperscalers shift from cash-funded to debt-funded expansion, credit markets and regulators will need to monitor the sustainability of this model closely.