Medical Transcriptionists
HealthcareAI exposure
- Data source: BLSPublished: '26.08
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: '26.03
0.636
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: '25
0.53
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, 14% 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 |
|---|---|
Transcribe dictation for a variety of medical reports, such as patient histories, physical examinations, emergency room visits, operations, chart reviews, consultation, or discharge summaries.O*NET Task ID 9413 | 1.0 |
Review and edit transcribed reports or dictated material for spelling, grammar, clarity, consistency, and proper medical terminology.O*NET Task ID 9414 | 1.0 |
Distinguish between homonyms and recognize inconsistencies and mistakes in medical terms, referring to dictionaries, drug references, and other sources on anatomy, physiology, and medicine.O*NET Task ID 9415 | 1.0 |
Return dictated reports in printed or electronic form for physician's review, signature, and corrections and for inclusion in patients' medical records.O*NET Task ID 9416 | 1.0 |
Translate medical jargon and abbreviations into their expanded forms to ensure the accuracy of patient and health care facility records.O*NET Task ID 9417 | 1.0 |
Identify mistakes in reports and check with doctors to obtain the correct information.O*NET Task ID 9419 | 1.0 |
Perform data entry and data retrieval services, providing data for inclusion in medical records and for transmission to physicians.O*NET Task ID 9420 | 1.0 |
Produce medical reports, correspondence, records, patient-care information, statistics, medical research, and administrative material.O*NET Task ID 9421 | 1.0 |
Answer inquiries concerning the progress of medical cases, within the limits of confidentiality laws.O*NET Task ID 9422 | 1.0 |
Perform a variety of clerical and office tasks, such as handling incoming and outgoing mail, completing and submitting insurance claims, typing, filing, or operating office machines.O*NET Task ID 9424 | 1.0 |
Receive and screen telephone calls and visitors.O*NET Task ID 9427 | 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
Occupation information
Recent Changes Affecting This Occupation
Mar 2026: Karpathy rates medical transcriptionists 10/10 — the only perfect AI exposure score — as virtually all core tasks are LLM-automatable.
[Source: Karpathy AI Exposure Score (Fortune)]