Federal Revenue When AI Replaces Labor
An Examination of Economic Scenarios with Highly Capable Artificial Intelligence
ResearchPublished Aug 25, 2026
In this report, the authors analyze how artificial intelligence (AI) replacing human labor could affect U.S. federal revenue. If displaced workers do not find new jobs, and especially if AI is widely accessible at cost, federal revenue could fall sharply. Corporate profits from AI would not fully offset lost labor taxes. The authors stress the need for proactive fiscal policy to address these risks and maintain economic stability.
An Examination of Economic Scenarios with Highly Capable Artificial Intelligence
ResearchPublished Aug 25, 2026
In this report, the authors examine the fiscal implications for the U.S. federal government in scenarios in which artificial intelligence (AI) and automation technologies replace human labor. Using a framework that considers whether displaced workers find new jobs and how AI is priced (monopolistically or at cost), they analyze both a hypothetical case of full displacement of human labor and a transitional scenario in which AI displaces 10 percent of the workforce.
Simulation results indicate that federal revenue is highly vulnerable to labor-displacing AI. The loss of high-income jobs would disproportionately affect federal revenue, and increased corporate profits from AI would not fully offset declines in labor-derived taxes unless corporate tax rates are significantly raised. If AI is widely accessible at cost, deflation and reduced corporate profits could further erode tax receipts.
The authors highlight the need for proactive fiscal policy adjustments to mitigate risks from transformative AI, emphasizing the importance of monitoring economic indicators and preparing now for potential disruptions to federal revenue and economic stability.
This work was supported by the Diller-von Furstenberg Family Foundation and Pershing Square Philanthropies and conducted by the RAND von Furstenberg Family Budget Model Initiative within RAND Education, Employment, and Infrastructure.
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This publication supersedes a previous version published in 2025 (WR-A4443-1).