Rehabilitation Counselors

Healthcare

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

    0.000

    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

    0.28

    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, 73% 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
Prepare and maintain records and case files, including documentation, such as clients' personal and eligibility information, services provided, narratives of client contacts, or relevant correspondence.

O*NET Task ID 9202

1.0
Monitor and record clients' progress to ensure that goals and objectives are met.

O*NET Task ID 9200

0.5
Arrange for physical, mental, academic, vocational, and other evaluations to obtain information for assessing clients' needs and developing rehabilitation plans.

O*NET Task ID 9203

0.5
Analyze information from interviews, educational and medical records, consultation with other professionals, and diagnostic evaluations to assess clients' abilities, needs, and eligibility for services.

O*NET Task ID 9204

0.5
Develop rehabilitation plans that fit clients' aptitudes, education levels, physical abilities, and career goals.

O*NET Task ID 9205

0.5
Locate barriers to client employment, such as inaccessible work sites, inflexible schedules, or transportation problems, and work with clients to develop strategies for overcoming these barriers.

O*NET Task ID 9208

0.5
Confer with physicians, psychologists, occupational therapists, and other professionals to develop and implement client rehabilitation programs.

O*NET Task ID 9210

0.5
Develop diagnostic procedures to determine clients' needs.

O*NET Task ID 9211

0.5
Participate in job development and placement programs, contacting prospective employers, placing clients in jobs, and evaluating the success of placements.

O*NET Task ID 9212

0.5
Collaborate with community agencies to establish facilities and programs for persons with disabilities.

O*NET Task ID 9214

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