The American Enterprise Institute published a formal rebuttal to Senator Bernie Sanders' HELP Committee staff report on AI and employment, arguing the report "ignores the data on AI and inequality" and that current AI tools function as "skill equalisers" that raise performance among lower-skilled workers rather than eliminating their jobs outright 1. The rebuttal targets Sanders' central claim that AI could replace more than half of jobs in 15 of 20 major sectors, potentially affecting approximately 100 million US positions over a decade — the data foundation for his planned per-position "robot tax" on corporations that replace workers with automation.
The AEI argument draws on a body of research that does exist. The Federal Reserve Bank of Dallas found AI is "simultaneously aiding and replacing workers," with experienced workers gaining pay rises in AI-exposed sectors while entry-level workers face compressed opportunities. Anthropic's own usage-based research by Maxim Massenkoff and Peter McCrory found no systematic unemployment increase among heavily exposed occupations since late 2022. Oxford Economics concluded in January that AI's role in layoffs may be "overstated" and that firms do not appear to be replacing workers with AI on a significant scale . The NBER working paper by Anders Humlum and Emilie Vestergaard found LLM adoption linked to task restructuring but without net changes in hours or earnings .
But the equaliser framing has limits the AEI piece does not fully address. The same Dallas Fed research shows the equalisation effect benefits those already employed — it does nothing for the young workers whose job-finding rates have collapsed in AI-exposed industries. Harvard Business Review research by Thomas H. Davenport and Laks Srinivasan found only approximately 2% of organisations reported layoffs tied to actual AI implementation 2 — the other 98% are cutting in anticipation of capability that does not yet exist, which means the displacement is driven by executive expectations, not by the technology's current equalising properties. The Orgvue survey finding that 55% of leaders regret AI-driven layoffs 3 suggests the cuts are running ahead of any measurable productivity offset.
The policy stakes are concrete. A Brookings working paper by Anton Korinek and Benjamin Lockwood found approximately three-quarters of US federal tax revenue derives from labour taxation 4. Andrew Yang and Anthropic CEO Dario Amodei have both called for taxing AI-generated wealth to offset that fiscal exposure . AEI's counter-argument — that AI lifts rather than displaces — would make such taxes economically counterproductive. The Warner-Rounds Economy of the Future Commission Act is designed to resolve precisely this empirical question over the next 13 months, but Congress is unlikely to wait for the commission's findings before the robot tax debate forces a vote. The data war between AEI and the Sanders camp is, in practical terms, a fight over whether the US tax code treats AI as a complement to labour or a substitute for it.
