Hayes contends that if demand for AI training and inference falters, the cash-flow projections underpinning data centers and semiconductor investments will collapse. This credit stress, in his view, would force Washington to act as a buyer of last resort for AI compute or bail out stressed insurers heavily exposed to private credit. Both outcomes would necessitate government borrowing or monetary expansion, providing a catalyst for Bitcoin prices.
While AI companies like OpenAI and Anthropic attribute recent development slowdowns to safety and cybersecurity concerns, Hayes dismisses these claims as cover for cooling demand. Independent data from Apollo indicates that AI-related debt issuance is significant, with projections suggesting the sector could support over $2 trillion in investment-grade debt through 2030. However, the Federal Reserve remains on a tightening path, having recently raised interest rates to a range of 3.75%–4.00%.
Beyond corporate debt, Hayes points to systemic risks within the insurance sector, specifically citing potential vulnerabilities in reinsurance structures tied to private credit. While regulators at the NAIC are monitoring private credit transparency, there is no evidence of widespread insolvency. Major financial institutions, including BlackRock and Goldman Sachs, continue to mobilize capital for AI compute platforms, suggesting that institutional commitment to the sector remains robust despite the speculative risks highlighted by Hayes.
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