Athletic Trainers
Education & TrainingAI exposure
- Data source: BLSPublished: 2026-08
Moderate· 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
0.053
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.25
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, 77% 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 17 hidden tasks| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Develop training programs or routines designed to improve athletic performance.29-9091 | 0.020148.1 | 0.002322.7 |
Perform general administrative tasks, such as keeping records or writing reports.29-9091 | 0.011928.5 | 0.006160.8 |
Recommend special diets to improve athletes' health, increase their stamina, or alter their weight.29-9091 | 0.005412.9 | 0.001616.5 |
Advise athletes on the proper use of equipment.29-9091 | 0.00235.5 | —0 |
Conduct research or provide instruction on subject matter related to athletic training or sports medicine.29-9091 | 0.00215.0 | —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 |
|---|---|
Perform general administrative tasks, such as keeping records or writing reports.O*NET Task ID 18691 | 1.0 |
File athlete insurance claims and communicate with insurance providers.O*NET Task ID 18692 | 1.0 |
Teach sports medicine courses to athletic training students.O*NET Task ID 18693 | 1.0 |
Conduct an initial assessment of an athlete's injury or illness to provide emergency or continued care and to determine whether they should be referred to physicians for definitive diagnosis and treatment.O*NET Task ID 4221 | 0.5 |
Assess and report the progress of recovering athletes to coaches or physicians.O*NET Task ID 4225 | 0.5 |
Collaborate with physicians to develop and implement comprehensive rehabilitation programs for athletic injuries.O*NET Task ID 4226 | 0.5 |
Plan or implement comprehensive athletic injury or illness prevention programs.O*NET Task ID 4228 | 0.5 |
Develop training programs or routines designed to improve athletic performance.O*NET Task ID 4229 | 0.5 |
Inspect playing fields to locate any items that could injure players.O*NET Task ID 4232 | 0.5 |
Conduct research or provide instruction on subject matter related to athletic training or sports medicine.O*NET Task ID 4233 | 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