Medical Assistants
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
0.048
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.35
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, 61% 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
Exposed tasks onlyValues 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 |
|---|---|
Record patients' medical history, vital statistics, or information such as test results in medical records.O*NET Task ID 2026 | 1.0 |
Authorize drug refills and provide prescription information to pharmacies.O*NET Task ID 2031 | 1.0 |
Perform general office duties, such as answering telephones, taking dictation, or completing insurance forms.O*NET Task ID 2038 | 1.0 |
Keep financial records or perform other bookkeeping duties, such as handling credit or collections or mailing monthly statements to patients.O*NET Task ID 2042 | 1.0 |
Interview patients to obtain medical information and measure their vital signs, weight, and height.O*NET Task ID 2024 | 0.5 |
Explain treatment procedures, medications, diets, or physicians' instructions to patients.O*NET Task ID 2029 | 0.5 |
Schedule appointments for patients.O*NET Task ID 2034 | 0.5 |
Greet and log in patients arriving at office or clinic.O*NET Task ID 2036 | 0.5 |
Contact medical facilities or departments to schedule patients for tests or admission.O*NET Task ID 2037 | 0.5 |
Inventory and order medical, lab, or office supplies or equipment.O*NET Task ID 2039 | 0.5 |
Show patients to examination rooms and prepare them for the physician.O*NET Task ID 2025 | 0.0 |
Prepare and administer medications as directed by a physician.O*NET Task ID 2027 | 0.0 |
Collect blood, tissue, or other laboratory specimens, log the specimens, and prepare them for testing.O*NET Task ID 2028 | 0.0 |
Help physicians examine and treat patients, handing them instruments or materials or performing such tasks as giving injections or removing sutures.O*NET Task ID 2030 | 0.0 |
Prepare treatment rooms for patient examinations, keeping the rooms neat and clean.O*NET Task ID 2032 | 0.0 |
Clean and sterilize instruments and dispose of contaminated supplies.O*NET Task ID 2033 | 0.0 |
Change dressings on wounds.O*NET Task ID 2035 | 0.0 |
Perform routine laboratory tests and sample analyses.O*NET Task ID 2040 | 0.0 |
Set up medical laboratory equipment.O*NET Task ID 2041 | 0.0 |
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