Economists
Life, Physical & Social SciencesAI exposure
- Data source: BLSPublished: '26.08
Very high· relative
LowFour relative bandsVery highGroup-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
- Data source: AnthropicPublished: '26.03
0.242
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: '25
0.55
0.09Range of values carried here0.70Group-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.
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
Show 28 hidden tasks| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Monitor or analyze market and environmental trends.19-3011 | 0.110055.0 | 0.240066.7 |
Review documents written by others.19-3011 | 0.050025.0 | 0.080022.2 |
Provide advice and consultation on economic relationships to businesses, public and private agencies, and other employers.19-3011 | 0.030015.0 | 0.00000.0 |
Explain economic impact of policies to the public.19-3011 | 0.01005.0 | 0.00000.0 |
Compile, analyze, and report data to explain economic phenomena and forecast market trends, applying mathematical models and statistical techniques.19-3011 | 0.00000.0 | 0.03008.3 |
Interpret indicators to ascertain the overall health of an environment.19-3011 | 0.00000.0 | 0.01002.8 |
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.
| Task | βE1 + 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®, Anthropic Economic Index, 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]