Emergency Medicine Physicians
Healthcare Practitioners and Technical Occupations- O*NET-SOC code
- 29-1214.00
Make immediate medical decisions and act to prevent death or further disability. Provide immediate recognition, evaluation, care, stabilization, and disposition of patients. May direct emergency medical staff in an emergency department.
- 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: ILOPublished: 2025
0.27–0.29· 2 ISCO-08 groups
Scale, basis and source
Generative AI exposure index, 0–1 as published
Published per ISCO-08 unit group. Linked to this occupation, wholly or in part, by applying U.S. Bureau of Labor Statistics crosswalks (ISCO-08 to 2010 SOC, 2010 SOC to 2018 SOC) as published
- Data source: OpenAIPublished: 2023
0.353
0.000Range of values carried here0.844Scale, basis and source
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.
ILO value for each linked ISCO-08 group
- ISCO-08 2211Generalist Medical Practitioners0.29
- ISCO-08 2212Specialist Medical Practitioners0.27
Task-level exposure
Show 15 hidden tasks17 rated tasks · 14 tasks with β ≥ 0.5 (82.4%)
β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.
- Source unit: O*NET 27.2 tasks → O*NET 31.0 occupation code
- All rated tasks are in the O*NET 31.0 task list.
- Source
- OpenAI "GPTs are GPTs" exposure rubric
- Release
- gh-main-0471612
- License
- MIT License, Copyright (c) 2024 OpenAI
| Task (O*NET 30.2) | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Communicate likely outcomes of medical diseases or traumatic conditions to patients or their representatives.29-1214.00 | 0.080088.9 | 0.00000.0 |
Identify factors that may affect patient management, such as age, gender, barriers to communication, and underlying disease.29-1214.00 | 0.010011.1 | 0.0100100.0 |
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 (O*NET 27.2) | βE1 + 0.5 × E2 |
|---|---|
Collect and record patient information, such as medical history or examination results, in electronic or handwritten medical records.O*NET Task ID 22717 | 1.0 |
Analyze records, examination information, or test results to diagnose medical conditions.O*NET Task ID 22715 | 0.5 |
Assess patients' pain levels or sedation requirements.O*NET Task ID 22716 | 0.5 |
Communicate likely outcomes of medical diseases or traumatic conditions to patients or their representatives.O*NET Task ID 22718 | 0.5 |
Conduct primary patient assessments that include information from prior medical care.O*NET Task ID 22719 | 0.5 |
Consult with hospitalists and other professionals, such as social workers, regarding patients' hospital admission, continued observation, transition of care, or discharge.O*NET Task ID 22720 | 0.5 |
Direct and coordinate activities of nurses, assistants, specialists, residents, and other medical staff.O*NET Task ID 22721 | 0.5 |
Discuss patients' treatment plans with physicians and other medical professionals.O*NET Task ID 22722 | 0.5 |
Evaluate patients' vital signs or laboratory data to determine emergency intervention needs and priority of treatment.O*NET Task ID 22723 | 0.5 |
Identify factors that may affect patient management, such as age, gender, barriers to communication, and underlying disease.O*NET Task ID 22724 | 0.5 |
Monitor patients' conditions, and reevaluate treatments, as necessary.O*NET Task ID 22725 | 0.5 |
Refer patients to specialists or other practitioners.O*NET Task ID 22728 | 0.5 |
Select and prescribe medications to address patient needs.O*NET Task ID 22729 | 0.5 |
Select, request, perform, or interpret diagnostic procedures, such as laboratory tests, electrocardiograms, emergency ultrasounds, and radiographs.O*NET Task ID 22730 | 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
All O*NET 31.0 task statements (17)
All O*NET 31.0 task statements for this occupation (English, as published; task type core or supplemental). Exposure values are not listed here; they are in the table above, next to each task statement as worded in the O*NET version each source used.
| Task (O*NET 31.0) | Type |
|---|---|
| Analyze records, examination information, or test results to diagnose medical conditions. | Core |
| Assess patients' pain levels or sedation requirements. | Core |
| Collect and record patient information, such as medical history or examination results, in electronic or handwritten medical records. | Core |
| Communicate likely outcomes of medical diseases or traumatic conditions to patients or their representatives. | Core |
| Conduct primary patient assessments that include information from prior medical care. | Core |
| Consult with hospitalists and other professionals, such as social workers, regarding patients' hospital admission, continued observation, transition of care, or discharge. | Core |
| Direct and coordinate activities of nurses, assistants, specialists, residents, and other medical staff. | Core |
| Discuss patients' treatment plans with physicians and other medical professionals. | Core |
| Evaluate patients' vital signs or laboratory data to determine emergency intervention needs and priority of treatment. | Core |
| Identify factors that may affect patient management, such as age, gender, barriers to communication, and underlying disease. | Core |
| Monitor patients' conditions, and reevaluate treatments, as necessary. | Core |
| Perform emergency resuscitations on patients. | Core |
| Perform such medical procedures as emergent cricothyrotomy, endotracheal intubation, and emergency thoracotomy. | Core |
| Refer patients to specialists or other practitioners. | Core |
| Select and prescribe medications to address patient needs. | Core |
| Select, request, perform, or interpret diagnostic procedures, such as laboratory tests, electrocardiograms, emergency ultrasounds, and radiographs. | Core |
| Stabilize patients in critical condition. | Core |
0.00/ 3· Robot exposure index
Scale, basis and source
Each physical task is graded 0–3 by the setting in which robots that have been deployed, sold or demonstrated could do it (0 none · 1 purpose-built robot settings such as a fenced machine cell or a bottling line · 2 structured facilities such as a hospital pharmacy or a container port · 3 unstructured settings such as a private home or a construction site), and the grades are averaged by share of working time
Physical tasks among this occupation's O*NET 29.3 tasks
Anthropic estimated the grades and time shares with Claude Opus 5 using web search, as of 2026.
The robot exposure index is a different measure from the AI exposure figures on this site and cannot be added to or compared with them. It does not measure actual adoption or cost, and 0 also covers occupations with no physical tasks.
Tier of each physical task
Robot environment tiers (E0–E3)
E0 noneDetails
Rated not doable by robots that have been deployed, sold or demonstrated, even in a purpose-built setting
E1 purpose-built robot settingsDetails
Rated doable in a setting built around the machine, such as a fenced machine cell or a bottling line
E2 structured facilitiesDetails
Rated doable in a human work facility that an institution keeps to a working standard, such as a hospital pharmacy or a container port
E3 unstructured settingsDetails
Rated doable in a setting that no institution keeps to a working standard, such as a private home or a construction site
Only tasks classified as physical are listed; other tasks have no tier in the source.
| Task (O*NET 29.3) | Robot environment tier |
|---|---|
| Conduct primary patient assessments that include information from prior medical care. | E0 none |
| Monitor patients' conditions, and reevaluate treatments, as necessary. | E0 none |
| Perform emergency resuscitations on patients. | E0 none |
| Perform such medical procedures as emergent cricothyrotomy, endotracheal intubation, and emergency thoracotomy. | E0 none |
| Select, request, perform, or interpret diagnostic procedures, such as laboratory tests, electrocardiograms, emergency ultrasounds, and radiographs. | E0 none |
| Stabilize patients in critical condition. | E0 none |
Occupation information
Employment outlook (BLS)
- Employment, 2025
- 35K
- Projected employment, 2035
- 36K
- Change (2025–35)
- +3.2%
- Median annual wage, 2025
- $335,550
- Typical education needed for entry
- Doctoral or professional degree
Korea classification links (KSCO)
Links from the current release of the Korea Occupation Direct Crosswalk v1.1, made by AI Changing Work. Relation values are read from the O*NET-SOC occupation side.
| KSCO code | KSCO title | Relation | Status |
|---|---|---|---|
| 24119 | 그 외 전문 의사 | This occupation is narrower | confirmed |
Relation and status definitions(kr-direct v1.1)
ILO occupational description
AI Changing Work links the ISCO-08 unit groups below to this occupation by applying the U.S. Bureau of Labor Statistics crosswalks (2018 SOC to 2010 SOC, 2010 SOC to ISCO-08) as published, without case-by-case selection; each link may be whole or partial.
- ISCO-08 2211Generalist Medical Practitioners
- ISCO-08 2212Specialist Medical Practitioners
Sources: ILO ISCO-08 — details: Credits
ESCO occupational vocabulary
Each entry below is matched to this occupation in the published ESCO-O*NET Crosswalk (version 1, 2022). The match types are that crosswalk's; the wording is AI Changing Work's.
- specialised doctorESCO 2212.1This occupation is narrower
Specialised doctors prevent, diagnose and treat diseases depending on their medical or surgical specialty.
Source: European Commission, DG EMPL — ESCO API 2026-08-08 (bridge v1.2.1)
License: CC BY 4.0 (EU Reuse Notice)
ESCO reuse terms and the modification notice are in Credits.
France classification links (ROME)
AI Changing Work's links between this occupation and ROME 4.0 job profiles, judged with AI models. Relations are read from this occupation's side. Links marked “provisional” were adopted on the judgments of two judges from the same model family (Claude) alone, or by an operator rule applied to their judgments, so they rest on weaker evidence than confirmed links.
| ROME code | ROME title (French) | Relation |
|---|---|---|
| J1127 | Médecin urgentiste | Same scopeprovisional |
| J1108 | Médecin régulateur | Related, not a matchprovisional |
Source: France Travail — Répertoire Opérationnel des Métiers et des Emplois (ROME 4.0), version 61, last updated 15 June 2026 (https://www.data.gouv.fr/datasets/repertoire-operationnel-des-metiers-et-des-emplois-rome). Licence Ouverte 2.0.
ROME codes and titles are reproduced unchanged; the links to O*NET-SOC occupations are AI Changing Work's own judgment and are not a France Travail correspondence.
(AI Changing Work link release: fr-direct v1)
Spain classification links (CNO-11)
AI Changing Work's links between this occupation and CNO-11 occupations, judged with AI models. Relations are read from this occupation's side.
| CNO-11 code | CNO-11 title (Spanish) | Relation |
|---|---|---|
| 2112 | Otros médicos especialistas | This occupation is narrowerprovisional |
| 2111 | Médicos de familia | Related, not a matchprovisional |
Source: Instituto Nacional de Estadística (INE), National Classification of Occupations 2011 (CNO-11, Royal Decree 1591/2010) — www.ine.es · Licensed CC BY 4.0. CNO-11 codes and Spanish titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own judgment and are not an INE correspondence.
(AI Changing Work link release: es-direct v1)
Germany classification links (KldB)
AI Changing Work's links between this occupation and KldB occupations, judged with AI models. Relations are read from this occupation's side.
| KldB code | KldB title (German) | Relation |
|---|---|---|
| 81484 | Ärzte/Ärztinnen (sonstige spezifische Tätigkeitsangabe) - hoch komplexe Tätigkeiten | This occupation is narrower |
Source: © Statistik der Bundesagentur für Arbeit — Klassifikation der Berufe 2010 – überarbeitete Fassung 2020, https://statistik.arbeitsagentur.de. KldB codes and titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own mapping (eigene Zuordnung) and are not a Bundesagentur für Arbeit correspondence.
(AI Changing Work link release: de-direct v1)
Japan classification links (JSCO)
AI Changing Work's links between this occupation and JSCO occupations, judged with AI models. Relations are read from this occupation's side.
| JSCO code | JSCO title (Japanese) | Relation |
|---|---|---|
| 121 | 医師 | This occupation is narrowerprovisional |
Source: Ministry of Internal Affairs and Communications (MIC), Japan Standard Occupational Classification (Dec. 2009, MIC Notification No. 555). JSCO codes and Japanese titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own judgment and are not a MIC correspondence.
(AI Changing Work link release: jp-direct v1)
Sources, licenses and AI Changing Work's modification and translation notices for this page: Credits & sources