AI could tackle America's $39 trillion debt crisis, but Yale report reveals a harsh trade-off

AI could solve America's $39 trillion debt crisis -- but only if Washington abandons displaced workers, Yale report warns | Fortune

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 that AI will be some kind of free, infinite money tree," Martha Gimbel, executive director and co-founder of the Yale Budget Lab, told Fortune. "One, it depends on how big the productivity shock is and, two, how much you need to spend in response." The national debt just hit a sobering milestone last month, reaching 100% of GDP. Now, the U.S. is spending $88 billion a month on interest payments alone, a chunk of change roughly equivalent to defense and education spending combined. Getting the country back on a sustainable fiscal path within 30 years requires painful changes: large tax hikes, deep spending cuts, or some combination of the two, totaling $827 billion, in line with past defense budget proposals. Business leaders like Elon Musk have lauded AI productivity as a savvy fix to the country's national debt. While AI productivity gains may offer a simpler solution to the issue, the spending required to support the workers the technology threatens to displace -- with spending proposals floated by everyone from Sen. Bernie Sanders (I-VT) to Sam Altman -- is an added cost which Gimbel said policymakers must take into consideration when discussing AI productivity. The report considers other revenue factors associated with an AI-induced productivity shock, mainly the consequences of shifting the burden of tax from labor to capital, as many business leaders and politicians have pointed out is a critical consideration given the threat of job displacement. Because capital is generally taxed more lightly than labor, the report warns AI productivity gains could inadvertently reduce federal revenues. What's more, another counterintuitive hurdle to debt reduction is the pressure on interest rates caused by rapid growth. Historically, faster productivity growth leads to higher rates, which will then increase the cost for the government to service its debt. The higher interest payments would partially offset the fiscal gains generated by AI. To be sure, it's not exactly clear to what extent AI will disrupt the labor market. While previously claiming AI will wipe out half of the entry-level white-collar workforce, Anthropic CEO Dario Amodei recently changed tune, saying the technology could actually transform and multiply roles rather than destroy them. And it's not at all a guarantee AI will have the productivity gains the study assumes. But the researchers emphasize that even if these productivity gains do materialize, they will not occur in a vacuum. "I think it's important to look at the industrial revolution -- that obviously was a major productivity shock, but in that case there were substantial costs that the government didn't manage," Gimbel said. "It's really important to keep in mind that productivity is not the only impact of AI."

AI Productivity Boom Could Ease $39 Trillion National Debt -- But Only If The Government Stops Doing This -

AI productivity might be a viable solution to America's $39 trillion national debt crisis, according to a Yale Budget Lab report. However, it also warned that achieving this would require specific action from the government. Government Worker Aid May Offset Gains The study, released on Wednesday, suggested that moderate AI adoption could lead to an annual labor productivity growth of 2.5% from 2025 to 2030. This could potentially slow and eventually reduce the debt-to-GDP ratio. However, increased federal spending to support displaced workers could undermine these plans. Higher Capital Tax, Interest Rate Could Be Burden The report warns that even if AI significantly boosts productivity, it may not reduce U.S. debt as much as expected. One reason is that AI-driven automation could shift income from workers to capital owners, and capital is typically taxed at lower rates than labor, potentially shrinking federal tax revenues. Faster economic growth from AI could also push interest rates higher, increasing government debt-servicing costs and offsetting some fiscal benefits. At the same time, the long-term impact of AI on jobs and productivity remains uncertain. Elon Musk Touts AI As A Debt Solution Dimon urged policymakers to address the issue, pointing to the unimplemented Obama-era Simpson-Bowles deficit reduction plan as a missed opportunity that could have helped resolve fiscal challenges. Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. Image via Shutterstock Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.