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To monitor systemic risk in the AI ecosystem, watch single-name Credit Default Swaps (CDS) for hyperscalers. Cross-asset investors use these liquid contracts to hedge a wide range of less liquid exposures like private debt and equity books, making them a key forward-looking risk indicator.
The rapid accumulation of hundreds of billions in debt to finance AI data centers poses a systemic threat, not just a risk to individual companies. A drop in GPU rental prices could trigger mass defaults as assets fail to service their loans, risking a contagion effect similar to the 2008 financial crisis.
Private credit funds are exposed on two fronts: they are financing the massive debt rounds for AI infrastructure and also hold debt for traditional SaaS companies. As AI companies pitch a future where they render SaaS obsolete, it creates instability and default risk across these private credit portfolios.
To hedge against a potential financing bubble in AI, an investor could buy the old-line industrial companies building the physical data centers while shorting the private credit firms providing the financing. This strategy capitalizes on tangible spending while protecting against the downside of over-leveraged, high-risk financial arrangements.
Private credit has become a key enabler of the AI boom, with firms like Blue Owl financing tens of billions in data center construction for giants like Meta and Oracle. This structure allows hyperscalers to expand off-balance-sheet, effectively transferring the immense capital risk of the AI build-out from Silicon Valley tech companies to the broader Wall Street financial system.
While equity markets remain bullish on mega-cap tech, the bond market is flashing a warning. The credit spreads for hyperscalers are widening as they take on massive debt for AI capex. This signals that debt investors, who are often more risk-aware, see growing financial strain that equity investors are ignoring.
Unlike equities, credit markets face a growing risk from the AI boom. As companies increasingly use debt instead of cash to finance AI and data center expansion, the rising supply of corporate bonds could pressure credit spreads to widen, even in a strong economy, echoing dynamics from the late 1990s tech bubble.
The capital financing AI—from venture and credit to public markets—is so deeply interwoven that the system is fragile. Experts warn this creates systemic risk where a single negative event, like a major struggling AI IPO, could rapidly shift sentiment from the current "peak buoyancy" and trigger a broad market correction.
The systemic risk from a major AI company failing isn't the loss of its technology. It's the potential for its debt default to cascade through an opaque network of private credit and other lenders, triggering a financial crisis.
While MAG7 companies fund AI spending with cash flow, the real danger is other firms using debt, especially private credit. This transforms potential corporate failures from isolated events into systemic risks that can cause broader economic ripple effects.
Massive, strategically crucial AI capital expenditures by the world's wealthiest companies could create a new risk. These firms may be less sensitive to borrowing costs, potentially issuing debt even into a weakening market, which could drive credit spreads wider for all issuers.