Actuaries
Business & Financial OperationsAI exposure
- Data source: BLSPublished: 2026-08
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: 2026-03
0.054
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.56
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, 8% 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
Exposed tasks only| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Provide advice to clients on a contract basis, working as a consultant.15-2011 | 0.251595.4 | 0.0138100.0 |
Determine or help determine company policy, and explain complex technical matters to company executives, government officials, shareholders, policyholders, or the public.15-2011 | 0.00451.7 | —0 |
Determine policy contract provisions for each type of insurance.15-2011 | 0.00301.1 | —0 |
Provide expertise to help financial institutions manage risks and maximize returns associated with investment products or credit offerings.15-2011 | 0.00281.1 | —0 |
Design, review and help administer insurance, annuity and pension plans, determining financial soundness and calculating premiums.15-2011 | 0.00180.7 | —0 |
| Not observed on any surface — 9 task(s) — These tasks have no row in the source for this release. The 0 in the share row is a display-stage composition ratio; absence is what the — in the raw row states. | ||
Ascertain premium rates required and cash reserves and liabilities necessary to ensure payment of future benefits. | —0 | —0 |
Analyze statistical information to estimate mortality, accident, sickness, disability, and retirement rates. | —0 | —0 |
Collaborate with programmers, underwriters, accounts, claims experts, and senior management to help companies develop plans for new lines of business or improvements to existing business. | —0 | —0 |
Testify before public agencies on proposed legislation affecting businesses. | —0 | —0 |
Testify in court as expert witness or to provide legal evidence on matters such as the value of potential lifetime earnings of a person who is disabled or killed in an accident. | —0 | —0 |
Construct probability tables for events such as fires, natural disasters, and unemployment, based on analysis of statistical data and other pertinent information. | —0 | —0 |
Determine equitable basis for distributing surplus earnings under participating insurance and annuity contracts in mutual companies. | —0 | —0 |
Manage credit and help price corporate security offerings. | —0 | —0 |
Explain changes in contract provisions to customers. | —0 | —0 |
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 |
|---|---|
Ascertain premium rates required and cash reserves and liabilities necessary to ensure payment of future benefits.O*NET Task ID 3500 | 0.5 |
Analyze statistical information to estimate mortality, accident, sickness, disability, and retirement rates.O*NET Task ID 3501 | 0.5 |
Design, review, and help administer insurance, annuity and pension plans, determining financial soundness and calculating premiums.O*NET Task ID 3502 | 0.5 |
Collaborate with programmers, underwriters, accounts, claims experts, and senior management to help companies develop plans for new lines of business or improvements to existing business.O*NET Task ID 3503 | 0.5 |
Determine, or help determine, company policy, and explain complex technical matters to company executives, government officials, shareholders, policyholders, or the public.O*NET Task ID 3504 | 0.5 |
Testify before public agencies on proposed legislation affecting businesses.O*NET Task ID 3505 | 0.5 |
Provide advice to clients on a contract basis, working as a consultant.O*NET Task ID 3506 | 0.5 |
Testify in court as expert witness or to provide legal evidence on matters such as the value of potential lifetime earnings of a person disabled or killed in an accident.O*NET Task ID 3507 | 0.5 |
Construct probability tables for events such as fires, natural disasters, and unemployment, based on analysis of statistical data and other pertinent information.O*NET Task ID 3508 | 0.5 |
Determine policy contract provisions for each type of insurance.O*NET Task ID 3509 | 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