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July 07, 2026
Partner, Chief Economist
Everyone talks about AI exposure in the labor market, but the reality is that there is no consensus about what this means.
This is illustrated by the five measures currently used in studies quantifying the impact of AI on the labor market:
"What could AI do to this job?" and "What are workers actually using AI for?" are not the same question, and the theoretical measures (3, 4 and 5) run systematically higher than the usage-based ones (1 and 2) because they ignore whether adoption is even happening or worth the cost.
As a result, many occupations look highly exposed under one measure and barely touched under another.
What is most striking is that the five measures disagree most exactly where the stakes are highest, among the very jobs everyone wants to flag as at-risk, such as telemarketers, tax preparers and writers.
The bottom line is that when someone says a job is "highly exposed to AI," the honest first question is: Exposed by which measure, and measuring what? Until that is pinned down, the label "AI exposure" carries far less meaning than it appears to.
My colleague Sania Edlich and I will dig further into this in upcoming Sparks.
Sources: Massenkoff & McCrory (2026); Tomlinson et al. (2025); Felten et al. (2021); Eisfeldt et al. (2023); Eloundou et al. (2024); Kharazian, Simon & Stevens (2026); Apollo Chief Economist
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