AI companies compete with the US Treasury for capital, driving up interest rates the government can't afford. Simultaneously, AI aims to eliminate white-collar jobs that form the core of the federal tax base. This creates a "snake-eating-its-own-tail" dynamic that pushes the US closer to a fiscal crisis.

Hoping AI will grow the economy out of its debt burden is flawed. The massive investment required to boost GDP growth (G) competes for capital, inadvertently raising interest rates (R). In the short term, this can increase the debt service cost (the R-G spread), potentially worsening the debt spiral before any productivity gains are realized.

Surging investment in AI infrastructure, often financed through debt, creates significant new competition for global savings. This increased demand for capital from the private sector clashes with massive government borrowing needs, contributing directly to the structural rise in global bond yields by altering the savings-investment balance.

Jeffrey Schmid suggests the massive capital investment required for the AI and data center build-out is creating significant new demand for credit. This demand competes directly with public sector borrowing and other commercial needs, which in turn puts upward pressure on bond yields as part of a classic supply-and-demand dynamic for money.

The AI build-out increases real interest rates by demanding vast amounts of capital, crowding out other investments. Simultaneously, it pushes up nominal rates by creating inflationary pressure on physical resources like labor, energy, and materials needed for data centers.

The AI industry and the US government both require trillions in funding. This creates a paradox: the more successful AI becomes, the more it erodes the white-collar tax base by automating jobs, forcing the Treasury to borrow even more and intensifying the competition for scarce capital.

While large tech companies ("hyperscalers") are issuing significant debt, their volume is trivial compared to the government's. The US Treasury's massive issuance is the primary factor forcing investors to demand higher yields across the board, effectively crowding out corporate borrowers rather than the other way around.

An anticipated $3 trillion in AI-related spending requires significant debt financing, creating a $1.5 trillion gap. This is expected to cause a 60% increase in net investment-grade bond issuance, creating a supply-side headwind that makes the asset class less attractive despite sound fundamentals.

Major tech companies are financing their AI build-outs so aggressively that they are undeterred by rising debt costs. This inelastic demand for capital could drive up borrowing costs across the entire corporate bond market, creating a 'crowding out' effect that impacts companies in unrelated sectors.