Talent Agents

Business & Financial Operations

AI exposure

  • Data source: BLSPublished: 2026-08

    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: 2026-03

    0.118

    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: 2025

    0.44

    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, 28% 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

Exposed tasks only

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
Collect fees, commissions, or other payments, according to contract terms.

O*NET Task ID 12865

1.0
Send samples of clients' work and other promotional material to potential employers to obtain auditions, sponsorships, or endorsement deals.

O*NET Task ID 21163

1.0
Confer with clients to develop strategies for their careers, and to explain actions taken on their behalf.

O*NET Task ID 12866

0.5
Develop contacts with individuals and organizations, and apply effective strategies and techniques to ensure their clients' success.

O*NET Task ID 12867

0.5
Schedule promotional or performance engagements for clients.

O*NET Task ID 12868

0.5
Negotiate with managers, promoters, union officials, and other persons regarding clients' contractual rights and obligations.

O*NET Task ID 12869

0.5
Keep informed of industry trends and deals.

O*NET Task ID 12870

0.5
Manage business and financial affairs for clients, such as arranging travel and lodging, selling tickets, and directing marketing and advertising activities.

O*NET Task ID 12871

0.5
Arrange meetings concerning issues involving their clients.

O*NET Task ID 12873

0.5
Prepare periodic accounting statements for clients.

O*NET Task ID 12874

0.5
Conduct auditions or interviews to evaluate potential clients.

O*NET Task ID 12872

0.0

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