Occupational Therapists
HealthcareAI exposure
- Data source: BLSPublished: 2026-08
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
0.008
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.20
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, 86% 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 32 hidden tasks| Task | Claude.aiRaw / share % |
|---|---|
Provide consultation, support, or education to groups such as parents and teachers.29-1122 | 0.024052.9 |
Select activities that will help individuals learn work and life-management skills within limits of their mental or physical capabilities.29-1122 | 0.007917.5 |
Write reports or complete forms to document assessments, training, progress, or follow-up outcomes.29-1122 | 0.005311.8 |
Test and evaluate patients' physical and mental abilities and analyze medical data to determine realistic rehabilitation goals for patients.29-1122 | 0.005111.2 |
Provide training and supervision in therapy techniques and objectives for students or nurses and other medical staff.29-1122 | 0.00306.6 |
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 |
|---|---|
Complete and maintain necessary records.O*NET Task ID 347 | 1.0 |
Evaluate patients' progress and prepare reports that detail progress.O*NET Task ID 348 | 1.0 |
Test and evaluate patients' physical and mental abilities and analyze medical data to determine realistic rehabilitation goals for patients.O*NET Task ID 349 | 0.5 |
Recommend changes in patients' work or living environments, consistent with their needs and capabilities.O*NET Task ID 352 | 0.5 |
Help clients improve decision making, abstract reasoning, memory, sequencing, coordination, and perceptual skills, using computer programs.O*NET Task ID 354 | 0.5 |
Design and create, or requisition, special supplies and equipment, such as splints, braces, and computer-aided adaptive equipment.O*NET Task ID 357 | 0.5 |
Advise on health risks in the workplace or on health-related transition to retirement.O*NET Task ID 360 | 0.5 |
Conduct research in occupational therapy.O*NET Task ID 361 | 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