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Among the five factors eroding AI's positive fiscal impact, a projected 35% rise in interest rates is mathematically the most significant. With US debt already at 100% of GDP, even small changes in borrowing costs have an enormous effect on the deficit, overwhelming other factors like defense spending or labor force changes.
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.
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.
Contrary to the idea that AI justifies rate cuts, the boom is likely increasing the neutral rate of interest (R-star). By stimulating corporate investment and household consumption, AI creates upward pressure on rates, which limits the Federal Reserve's ability to ease monetary policy.
AI data center investments are viable because long-term leases cover initial costs, leaving developers with a valuable future asset. Rising rates increase lease costs and decrease the present value of that future asset, threatening the financial viability of the entire AI infrastructure buildout.
Contrary to the belief that AI is purely deflationary, its initial impact is inflationary. The massive, immediate demand for investment in data centers, chips, and energy far outweighs any short-term productivity benefits. This capital-intensive build-out puts upward pressure on interest rates and prices across the economy.
The macro trend of rising bond yields creates a specific, acute risk for the AI sector. Many AI startups are funded by floating-rate private credit, and their debt service costs will explode as rates rise. This is compounded by high CapEx and an inability to scale revenues proportionally, creating a potential crash.
The biggest risk to capital-intensive AI ventures isn't a lack of demand but losing access to cheap financing. The current boom is built on borrowing long-dated money at low rates (e.g., 6%). A shift to a higher yield environment (8-10%) would make funding massive, negative cash-flow projects untenable.
While an AI productivity boom could significantly reduce the US primary deficit, economist Ben Harris argues this optimism must be tempered. His model shows that five factors—longer life spans, lower labor participation, a shift to lower-taxed capital income, an AI arms race, and higher interest rates—will erase roughly half the fiscal gains from growth.