AI could solve America’s $39 trillion debt crisis—but only if Washington abandons displaced workers, Yale Budget Lab warns

The big bet on AI—the near-trillion dollars that hyperscalers are spending to build out the technology’s infrastructure—is predicated on the belief that productivity will skyrocket.

If that bet pays off, a new report from policy research center Yale Budget Lab finds AI could help tackle one of the country’s most urgent crises: the $39 trillion national debt. The report offers a scenario on how AI could trim down the country’s piling debt, but comes with a significant caveat: to have AI productivity completely reverse the upward trajectory of the national debt, the government would have to forgo supporting the workers the technology displaces.

The study finds that moderate AI adoption could drive annual labor productivity growth of 2.5%—the median expectation among surveyed economists for 2025 to 2030—enough to slow, and eventually shrink, the debt-to-GDP ratio. However, increased federal spending to support displaced workers could hamper those plans. In a more-generous scenario, equivalent to the U.S.’s $42,400 retiree spending, and a less-generous one that matches the $5,500 spent per unemployed worker, productivity gains reduce the debt more than in a world where AI gains fail to materialize. But neither scenario is sufficient to keep the debt at its current level. That would require holding federal spending steady

“It seems unlikely tha...