Skills it runs on
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Occupation · SOC 29-1216.00
Diagnose and provide nonsurgical treatment for a wide range of diseases and injuries of internal organ systems. Provide care mainly for adults and adolescents, and are based primarily in an outpatient care setting.
Also called: Internal Medicine Physician (IM Physician) · Internist · Medical Doctor (MD) · Physician · Doctor · Gastroenterologist · General Internal Medicine Physician · General Internist · Internal Medicine Doctor · Primary Care Physician · DO Physician (Doctor of Osteopathic Medicine Physician) · Endocrinologist
Job family: Healthcare Practitioners and Technical Occupations
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-29-1216-00/context.md directly.
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Independent published positions, read together — not a forecast.
68th-percentile task overlap — yet about 2,100 openings a year (+3.3% projected, BLS) . What exposure means →
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| LLM task exposure, γ (OpenAI / Eloundou) High | 81st | 0.9 | |
| AI assistant applicability (Microsoft) Moderate | 55th | 0.2 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.0), with simple added tooling (β 0.5), and including AI-powered software (γ 0.9). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.
| Analyze records, reports, test results, or examination information to diagnose medical condition of patient. | 2.5% | |
| Explain procedures and discuss test results or prescribed treatments with patients. | 1.6% | |
| Advise patients and community members concerning diet, activity, hygiene, and disease prevention. | 0.9% | |
| Prepare government or organizational reports on birth, death, and disease statistics, workforce evaluations, or the medical status of individuals. | 0.4% | |
| Monitor patients' conditions and progress and reevaluate treatments as necessary. | 0.3% | |
| Make diagnoses when different illnesses occur together or in situations where the diagnosis may be obscure. | 0.2% |
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | About average · +3.3% by 2034 |
| Projected annual openings | 2,100 |
| Employment 2024 → 2034 | 73,200 → 75,600 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
All 19 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
O*NET importance rating, from 1 (not important) to 5 (extremely important).
| Medicine and Dentistry | 4.9 | |
| Biology | 4.5 | |
| Therapy and Counseling | 4.4 | |
| Psychology | 4.3 | |
| Education and Training | 4.2 | |
| English Language | 4.2 | |
| Administration and Management | 3.9 | |
| Customer and Personal Service | 3.9 | |
| Computers and Electronics | 3.9 | |
| Mathematics | 3.5 | |
| Chemistry | 3.4 | |
| Personnel and Human Resources | 3.3 |
| Problem Sensitivity | 4.4 | |
| Oral Comprehension | 4.3 | |
| Oral Expression | 4.3 | |
| Inductive Reasoning | 4.3 | |
| Written Comprehension | 4.1 | |
| Deductive Reasoning | 4.1 | |
| Written Expression | 4.0 | |
| Information Ordering | 4.0 | |
| Category Flexibility | 4.0 | |
| Near Vision | 4.0 | |
| Speech Recognition | 3.9 | |
| Speech Clarity | 3.8 | |
| Flexibility of Closure | 3.4 | |
| Fluency of Ideas | 3.3 |
| Reading Comprehension | 4.1 | |
| Active Listening | 4.1 | |
| Writing | 4.0 | |
| Speaking | 4.0 | |
| Science | 4.0 | |
| Critical Thinking | 4.0 | |
| Active Learning | 3.9 | |
| Monitoring | 3.9 |
| Social Perceptiveness | 4.0 | |
| Complex Problem Solving | 4.0 | |
| Judgment and Decision Making | 4.0 | |
| Service Orientation | 3.8 | |
| Coordination | 3.3 | |
| Systems Analysis | 3.3 |
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
What to study: Health Professions and Related Programs , Medical Residency/Fellowship Programs . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Share of people in this occupation at each level of education.
| Post-Doctoral Training | 53.0% | |
| Doctoral Degree | 47.0% |
The interests and personal qualities O*NET associates with people who do this work.
| Intellectual Curiosity | 10.0 | |
| Cooperation | 9.0 | |
| Achievement Orientation | 8.0 | |
| Social Orientation | 7.0 | |
| Self-Control | 6.0 | |
| Stress Tolerance | 5.0 | |
| Empathy | 4.0 |
| Health Care Service | 6.8 | |
| Medical Science | 5.6 | |
| Life Science | 5.3 | |
| Social Service | 4.4 | |
| Professional Advising | 3.6 |
| Investigative | 6.8 | |
| Social | 6.1 | |
| Realistic | 4.4 | |
| Conventional | 3.6 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $70,100 |
| 25th percentile | $135,240 |
| Median (50th) | $236,350 |
| 75th percentile | — |
| 90th percentile | — |
| People employed | 66,640 |
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Health Care and Social Assistance · Sector | 59,110 | — |
| Management of Companies and Enterprises · Sector | 200 | — |
| Professional, Scientific, and Technical Services · Sector | 150 | $144,740 |
| Outpatient Mental Health and Substance Abuse Centers · National industry | 100 | $238,980 |
| Residential Mental Health and Substance Abuse Facilities · National industry | 50 | $235,240 |
| Other Services (except Public Administration) · Sector | 40 | $61,740 |
| Administrative and Support and Waste Management and Remediation Services · Sector | — | — |
| Educational Services · Sector | — | $183,670 |
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Health Care and Social Assistance · Sector | 5.92× | 59,110 |
| Outpatient Mental Health and Substance Abuse Centers · National industry | 0.75× | 100 |
| Management of Companies and Enterprises · Sector | 0.16× | 200 |
| Professional, Scientific, and Technical Services · Sector | 0.03× | 150 |
Part of the Healthcare & Human Services career cluster.
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
Options the data surfaces for General Internal Medicine Physicians — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Capabilities this work builds that are used across many other occupations.
Occupations O*NET rates as related — the nearby moves on the map.
How people typically prepare for this work.
See where this work sits in the bigger picture.
General Internal Medicine Physicians show 68th-percentile AI task overlap — and about 2,100 annual U.S. openings
General Internal Medicine Physicians show 68th-percentile AI task overlap — and about 2,100 annual U.S. openings • General Internal Medicine Physicians rank in the 68th percentile (High band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • The occupation is projected to see about 2,100 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be about average (+3.3%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $236,350, across about 66,640 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "General Internal Medicine Physicians". https://singulariki.com/roles/role-29-1216-00 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom
Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
Data compiled June 2, 2026. Figures are estimates, not advice.
Singulariki. "General Internal Medicine Physicians." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026. https://singulariki.com/roles/role-29-1216-00
Singulariki. (2026). General Internal Medicine Physicians. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-29-1216-00
@misc{singulariki-role-29-1216-00,
title = {General Internal Medicine Physicians},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-29-1216-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.