A study by Apollo Global Management compares real wages since 2023: companies would capture productivity gains through wage compression rather than job cuts.
Torsten Slok, Chief Economist of Apollo Global Management, and her co-author Sania Edlich compared the evolution of real wages according to the degree of exposure of trades to artificial intelligence. As a result, after 2023, high-risk occupations posted real wage growth of 6.7 percentage points lower than low-risk occupations, with no statistically significant effect on employment levels. The hypothesis put forward by the authors is that companies recover part of the productivity gains through moderation of wages rather than through layoffs.
The authors themselves present these figures as early indices: out of approximately 800 occupational categories in the Bureau of Labor Statistics, only 321 were exploitable and 11 crossed the high exposure threshold. Their methodological point is perhaps the most interesting: to measure the effect from the observed adoption, not from theoretical exposure estimated a priori.
Ben Zipperer, an economist at the Economic Policy Institute, considers the sample too thin to convince and recalls two biases. First of all, the money saved on an automated trade does not evaporate: it is redeployed elsewhere and mechanically makes appear the trades exposed worse off. Second, the slowing down of hiring in technology prolongs post-pandemic normalization and has little to do with AI.
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