Music 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
0.040
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 50 hidden tasks| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Analyze or synthesize client data to draw conclusions or make recommendations for therapy.29-1129 | 0.050071.4 | 0.0300100.0 |
Document evaluations, treatment plans, case summaries, or progress or other reports related to individual clients or client groups.29-1129 | 0.010014.3 | 0.00000.0 |
Write treatment plans, case summaries, or progress or other reports related to individual clients or client groups.29-1129 | 0.010014.3 | —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 |
|---|---|
Observe and document client reactions, progress, or other outcomes related to music therapy.O*NET Task ID 19176 | 1.0 |
Document evaluations, treatment plans, case summaries, or progress or other reports related to individual clients or client groups.O*NET Task ID 19182 | 1.0 |
Compose, arrange, or adapt music for music therapy treatments.O*NET Task ID 19184 | 1.0 |
Participate in continuing education.O*NET Task ID 20167 | 1.0 |
Adapt existing or develop new music therapy assessment instruments or procedures to meet an individual client's needs.O*NET Task ID 19164 | 0.5 |
Analyze data to determine the effectiveness of specific treatments or therapy approaches.O*NET Task ID 19165 | 0.5 |
Analyze or synthesize client data to draw conclusions or make recommendations for therapy.O*NET Task ID 19166 | 0.5 |
Communicate client assessment findings and recommendations in oral, written, audio, video, or other forms.O*NET Task ID 19168 | 0.5 |
Confer with professionals on client's treatment team to develop, coordinate, or integrate treatment plans.O*NET Task ID 19169 | 0.5 |
Customize treatment programs for specific areas of music therapy, such as intellectual or developmental disabilities, educational settings, geriatrics, medical settings, mental health, physical disabilities, or wellness.O*NET Task ID 19170 | 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