Economists

Life, Physical & Social Sciences

AI exposure

  • Data source: BLSPublished: '26.08

    Very high· relative

    LowFour relative bandsVery high

    Group-level value

    Scale, basis and source

    Four relative bands (Low / Moderate / High / Very high)

    831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band

    Source dataset (XLSX download)

  • Data source: AnthropicPublished: '26.03

    0.242

    0.000Range of values carried here0.745
    Scale, basis and source

    Observed exposure index, 0–1 as published

    Mapped onto O*NET tasks

    Source dataset

  • Data source: ILOPublished: '25

    0.55

    0.09Range of values carried here0.70

    Group-level value

    Scale, basis and source

    Generative AI exposure index, 0–1 as published

    ISCO-08 unit group — every occupation sharing the code gets this value

    Computed by this site, not published by the ILO: of the 1,012 occupations this site links to the ILO dataset, 12% score at or above this value.

    Source dataset

What kind of figure this source publishes

The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.

Task-level exposure

Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.

TaskβE1 + 0.5 × E2
Study economic and statistical data in area of specialization, such as finance, labor, or agriculture.

O*NET Task ID 7536

0.5
Provide advice and consultation on economic relationships to businesses, public and private agencies, and other employers.

O*NET Task ID 7537

0.5
Compile, analyze, and report data to explain economic phenomena and forecast market trends, applying mathematical models and statistical techniques.

O*NET Task ID 7538

0.5
Formulate recommendations, policies, or plans to solve economic problems or to interpret markets.

O*NET Task ID 7539

0.5
Develop economic guidelines and standards, and prepare points of view used in forecasting trends and formulating economic policy.

O*NET Task ID 7540

0.5
Testify at regulatory or legislative hearings concerning the estimated effects of changes in legislation or public policy, and present recommendations based on cost-benefit analyses.

O*NET Task ID 7541

0.5
Supervise research projects and students' study projects.

O*NET Task ID 7542

0.5
Forecast production and consumption of renewable resources and supply, consumption, and depletion of non-renewable resources.

O*NET Task ID 7543

0.5
Teach theories, principles, and methods of economics.

O*NET Task ID 7544

0.5
Provide litigation support, such as writing reports for expert testimony or testifying as an expert witness.

O*NET Task ID 20051

0.5

β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.

Data sources & licenses — O*NET®, Eloundou et al. (2023): see full notices on the Credits page

Occupation information

Recent Changes Affecting This Occupation

Mar 2026: New blog post: economists face 60% exposure, 36% risk.

[Source: ACW Blog]