An Apollo analysis of 321 occupations found that wages in jobs highly exposed to AI grew 6.7% more slowly after 2023, with no statistically significant employment effect. The gap was 10.7% in the lowest-paid quartile and absent in the highest.
The first measurable mark AI has left on the labour market is not unemployment. Apollo’s chief economist Torsten Slok says the employment effect so far is insignificant, and that the visible damage is to pay.
His analysis with Sania Edlich found that wages in occupations highly exposed to AI grew 6.7% more slowly after 2023 than in low-exposure work. Employment in those occupations showed no statistically significant change.
The distribution is the part worth sitting with. The gap was 10.7% in the bottom wage quartile, 5.4% in the second and 4.0% in the third, and there was no significant effect at all in the top quartile.
The method is unusual and worth stating. The authors matched 321 occupations to labour statistics data from 2015 to 2025, using the Anthropic Economic Index, which measures observed AI usage from actual model interactions rather than theoretical exposure.
They are candid about the limits. Exposure is measured from one company’s usage data, only 321 of roughly 800 occupations were matched, and their most dramatic figure, a 24.3% gap for service workers, is flagged as a small subsample to be treated with caution.
Other evidence points the other way. US statisticians found a 0.2% fall in jobs across 18 exposed occupations while payrolls overall grew 0.8%, and Goldman Sachs reported faster declines in openings in fields exposed to AI substitution, in a market where new entrants are already being squeezed.
Diane Gherson, formerly IBM’s chief human resources officer, offers a reason the job losses may be hard to see. Companies are quietly hiring fewer people into high-attrition, lower-wage roles rather than announcing layoffs.
She also names an accounting distortion that pushes the same way. Severance can be booked as a one-off restructuring charge that investors discount, while retraining lands in operating expenses every quarter, which makes cutting look better on paper than reskilling.
The counterexample she reaches for is European. Ikea retrained call centre staff as remote interior design advisers after automating much of their previous work, and the resulting service has been widely reported as a business worth around €1.3bn.
Slok’s wider claim is that the economy is getting more dynamic rather than smaller, with business formation at the highest rate on record. He also concedes the productivity payoff is unproven, since margins outside the largest technology companies have not yet risen.
Europe has no equivalent study, which is the gap worth noticing. The wage channel Apollo describes would be invisible in most European labour data, and TNW has already reported what AI is actually doing to jobs here without anyone measuring pay this way.
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