Arts Administrators

Management

AI exposure

  • Data source: BLSPublished: 2026-08

    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

    0.052

    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

    0.32

    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, 64% 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

Show 6 hidden tasks

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
Write articles, manuals, and other publications, and assist in the distribution of promotional literature about facilities and programs.

O*NET Task ID 5230

1.0
Review and approve new programs, or recommend modifications to existing programs, submitting program proposals for school board approval as necessary.

O*NET Task ID 5210

0.5
Prepare, maintain, or oversee the preparation and maintenance of attendance, activity, planning, or personnel reports and records.

O*NET Task ID 5211

0.5
Prepare and submit budget requests and recommendations, or grant proposals to solicit program funding.

O*NET Task ID 5213

0.5
Direct and coordinate school maintenance services and the use of school facilities.

O*NET Task ID 5214

0.5
Advocate for new schools to be built, or for existing facilities to be repaired or remodeled.

O*NET Task ID 5218

0.5
Plan and develop instructional methods and content for educational, vocational, or student activity programs.

O*NET Task ID 5219

0.5
Develop partnerships with businesses, communities, and other organizations to help meet identified educational needs and to provide school-to-work programs.

O*NET Task ID 5220

0.5
Direct and coordinate activities of teachers, administrators, and support staff at schools, public agencies, and institutions.

O*NET Task ID 5221

0.5
Evaluate curricula, teaching methods, and programs to determine their effectiveness, efficiency, and use, and to ensure compliance with federal, state, and local regulations.

O*NET Task ID 5222

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