Orthodontists
HealthcareAI 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
0.000
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.15
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, 92% 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
| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Study diagnostic records, such as medical or dental histories, plaster models of the teeth, photos of a patient's face and teeth, and X-rays, to develop patient treatment plans.29-1023 | 0.00000.0 | 0.00000.0 |
| Not observed on any surface — 10 task(s) — These tasks have no row in the source for this release. The 0 in the share row is a display-stage composition ratio; absence is what the — in the raw row states. | ||
Fit dental appliances in patients' mouths to alter the position and relationship of teeth and jaws or to realign teeth. | —0 | —0 |
Diagnose teeth and jaw or other dental-facial abnormalities. | —0 | —0 |
Examine patients to assess abnormalities of jaw development, tooth position, and other dental-facial structures. | —0 | —0 |
Prepare diagnostic and treatment records. | —0 | —0 |
Adjust dental appliances to produce and maintain normal function. | —0 | —0 |
Provide patients with proposed treatment plans and cost estimates. | —0 | —0 |
Instruct dental officers and technical assistants in orthodontic procedures and techniques. | —0 | —0 |
Coordinate orthodontic services with other dental and medical services. | —0 | —0 |
Design and fabricate appliances, such as space maintainers, retainers, and labial and lingual arch wires. | —0 | —0 |
Advise patients to comply with treatment plans. | —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 |
|---|---|
Study diagnostic records, such as medical or dental histories, plaster models of the teeth, photos of a patient's face and teeth, and X-rays, to develop patient treatment plans.O*NET Task ID 7733 | 0.5 |
Diagnose teeth and jaw or other dental-facial abnormalities.O*NET Task ID 7734 | 0.5 |
Examine patients to assess abnormalities of jaw development, tooth position, and other dental-facial structures.O*NET Task ID 7735 | 0.5 |
Prepare diagnostic and treatment records.O*NET Task ID 7736 | 0.5 |
Provide patients with proposed treatment plans and cost estimates.O*NET Task ID 7738 | 0.5 |
Coordinate orthodontic services with other dental and medical services.O*NET Task ID 7740 | 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