Unlike prior tech revolutions funded mainly by equity, the AI infrastructure build-out is increasingly reliant on debt. This blurs the line between speculative growth capital (equity) and financing for predictable cash flows (debt), magnifying potential losses and increasing systemic failure risk if the AI boom falters.

While default risk exists, the more pressing problem for credit investors is a severe supply-demand imbalance. A shortage of new M&A and corporate issuance, combined with massive sideline capital (e.g., $8T in money markets), keeps spreads historically tight and makes finding attractive opportunities the main challenge.

Traditional credit rotation strategies based on beta and starting spreads have become ineffective. Analysis now shows a sector's net supply—the volume of new debt issued versus what's maturing—is the most critical factor determining its relative performance, making technicals more important than fundamentals.

For the first time in years, leading-edge tech is incredibly expensive. This requires structured finance and massive capital, bringing Wall Street back to the table after being sidelined by cash-rich tech giants. The chaos and expense of AI create a new, lucrative playground for financiers.

Widespread credit is the common accelerant in major financial crashes, from 1929's margin loans to 2008's subprime mortgages. This same leverage that fuels rapid growth is also the "match that lights the fire" for catastrophic downturns, with today's AI ecosystem showing similar signs.

A new risk is entering the AI capital stack: leverage. Entities are being created with high-debt financing (80% debt, 20% equity), creating 'leverage upon leverage.' This structure, combined with circular investments between major players, echoes the telecom bust of the late 90s and requires close monitoring.

The expected wave of M&A and LBOs has not materialized, leaving the deal pipeline thin. This lack of new debt supply provides a strong supportive backdrop for credit spreads, allowing the market to absorb geopolitical volatility more easily than fundamentals would otherwise suggest.

The massive capital rush into AI infrastructure mirrors past tech cycles where excess capacity was built, leading to unprofitable projects. While large tech firms can absorb losses, the standalone projects and their supplier ecosystems (power, materials) are at risk if anticipated demand doesn't materialize.

Instead of an imminent collapse, the credit market is likely poised for a final surge in risk-taking. A combination of AI enthusiasm, Fed easing, and fiscal spending will probably drive markets higher and fuel more corporate debt issuance. This growth in leverage will sow the seeds for the eventual downturn.