Even if tech companies post historic growth rates, excessive debt obligations can still bankrupt them. As seen in tech cycles, revenues might increase parabolically, but if the growth takes longer than projected to outpace fixed debt commitments, servicing that debt creates severe cash shortfalls. Running out of liquidity to service compounding obligations can eliminate a firm before it achieves required profitability.
Hardware suppliers like Nvidia and Broadcom use residual value guarantees, special purpose vehicles (SPVs), and circular financing to enable customers to borrow and purchase their chips. This closely mirrors the dot-com era where Nortel and Lucent financed customer purchases through bond markets. When end-customer revenues fall short, both the buyers and the backstopping suppliers are hit simultaneously, threatening systemic balance across the industry.
Leading AI frontier labs highlight extreme existential risks—such as ending humanity—not merely as SEC disclosures, but as an intentional strategy to secure regulatory moats. Pushing for governmental oversight under the banner of safety allows established incumbents to lock in regulatory capture, blocking future competitors from entering the market and choking off open-weight alternatives.
Debt deals in the AI sector rely on 'residual value support,' using chips and servers as loan collateral while suppliers guarantee their value. However, chips depreciate rapidly, making their true collateral value uncertain. If customers default and equipment floods the market, suppliers assuming they can effortlessly repurpose or resell servers may find the collateral cannot sustain the debt amounts.
AI infrastructure is demanding hundreds of billions in liquidity just as sovereign treasuries run multi-trillion-dollar deficits. Because AI builders are determined to invest regardless of price, this inelastic demand forces debt yields and rates higher. As the tech boom and government debt simultaneously compete for global capital, private credit and corporate borrowing become far more expensive, compounding macroeconomic stress.
Stricter banking regulations enacted after the 2008 financial crisis did not eliminate borrower appetite for extreme leverage; instead, the demand migrated directly into private credit and shadow banking. Unconstrained by conventional bank lending standards, asset managers package opaque debt structures into complex SPVs, distributing unseen systemic risk broadly throughout institutional portfolios.
If regulatory capture fails and open-weight models propagate globally, software intelligence becomes a commoditized race to the bottom. In that scenario, pricing power collapses for model builders, pushing value away from application and foundational model layers and concentrating durable, long-term returns inside basic physical infrastructure such as power, hardware, and compute facilities.