General Internal Medicine Physicians
In short: today's best AI models could do about 42% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about 55% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 44% of the time, stays with people.
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.
67,150 people do this job in the US. $256,560 a year.
Reviewed on October 2, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on0 h
- A person checks AI's work16 h
- Desk work AI can't do yet6 h
- Stays with people18 h
General Internal Medicine Physicians, now: of a 40-hour week, AI could take on 0 hours, 16 hours become checking its work, 6 hours are desk work it can't do yet, and 18 hours stay with people.
The largest pieces: Diagnose from records and results (about 4 h, a person checks); Diagnose difficult cases (about 2 h, a person checks); Manage long-term patient care (about 2 h, a person checks).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 46%
- 9%
- 9%
- 32%
- 2%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
What handing it over would take, now
The 42% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
is conversation short enough by length. This site leaves conversation with people, so it is not in the total.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 1%. With Claude Mythos Preview (early), measured in April 2026, 35%. Today's estimate: 42%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, 0.016% went to this job's tasks in May 2026, the 339th largest of the 447 jobs that showed up at all; 2 of its 19 tasks showed up. Within each of Anthropic's methods, never across a change: 0.032% to 0.028% (released February and March 2025); 0.058% to 0.045% (August 2025 to February 2026); 0.013% to 0.016% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.032% | 355 of 708 | 6 of 19 |
| Released March 2025 | 0.028% | 372 of 703 | 7 of 19 |
| The week of Aug 4, 2025 (released September 2025) | 0.058% | 224 of 655 | 7 of 19 |
| The week of Nov 13, 2025 (released January 2026) | 0.042% | 264 of 672 | 5 of 19 |
| The week of Feb 5, 2026 (released March 2026) | 0.045% | 261 of 677 | 7 of 19 |
| April 2026 (released June 2026) | 0.013% | 332 of 434 | 2 of 19 |
| May 2026 (released June 2026) | 0.016% | 339 of 447 | 2 of 19 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates 16% of this job's working time as physical work. For 0% of the working time, a robot has been shown doing most of the task somewhere. 0.00 of 3.
- Not physical 84%
- No robot shown 16%
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
What changes for the people in this job
From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.
What stays with people
44% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Run health programs, the conversation, 8%
- Explain results and treatments, the in-person work, 5%
- Manage long-term patient care, the in-person work, 5%
- Manage common and complex illnesses, the in-person work, 4%
- Treat internal disorders, the in-person work, 4%
- Diagnose difficult cases, the in-person work, 3%
What becomes checking the machine
55% of the working time: desk work a model could do by then, in tasks where a mistake costs something or a licensed person signs. A person checks it.
- Run health programs, costly if wrong, 11%
- Diagnose from records and results, a licensed person signs, 9%
- Conduct clinical research, severe if wrong, 5%
- Diagnose difficult cases, a licensed person signs, 5%
- Manage long-term patient care, a licensed person signs, 5%
- Manage common and complex illnesses, a licensed person signs, 4%
What to learn
- Judgment where errors are severe. Some tasks are severe if wrong. Knowing when not to trust an output matters more there than speed.
- Signing off under your license. Some tasks need a licensed, certified or sworn person to do or sign them. The license, and the judgment it stands for, stays with the person.
- Reviewing work you did not do yourself. The tasks under What becomes checking the machine, where a mistake costs something, stay a person's to check or sign: spotting what a draft gets wrong is a skill of its own.
- Briefing a model and checking its drafts. About 46% of the time is documents and data, the part models reach first: writing a clear brief, giving the right material, and checking what comes back.
- The conversations. About 42% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).
The tasks
Sorted by . 19 tasks from .
| Task | ||||
|---|---|---|---|---|
| Plan, implement, or administer health programs in hospitals, businesses, or communities for prevention and treatment of injuries or illnesses.Planning the program and running it with the people involved.Done daily by most who do it. | 19% | 2.1 work days3.3 h to 1.7 work weeks | Documents 60%, conversation 40% | 9%Desk part half by Oct 2027 |
| Provide and manage long-term, comprehensive medical care, including diagnosis and nonsurgical treatment of diseases, for adult patients in an office or hospital.Seeing the patient over time, with the thinking and the orders behind each visit.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 9% | 50 min25 min to 2.1 h | In person 50%, documents 30%, systems 20% | 50%Desk part half by now |
| Analyze records, reports, test results, or examination information to diagnose medical condition of patient.Reading the record and results and reaching the diagnosis.Done hourly or more by most who do it. AI observed on this task. | 9% | 38 min17 min to 1.3 h | Documents 100% | 100%Half by now |
| Make diagnoses when different illnesses occur together or in situations where the diagnosis may be obscure.Examining the patient and working through the record and results.Done several times a day by most who do it. | 8% | 1.3 h25 min to 2.1 h | Documents 60%, in person 40% | 60%Desk part half by now |
| Manage and treat common health problems, such as infections, influenza or pneumonia, as well as serious, chronic, and complex illnesses, in adolescents, adults, and the elderly.Seeing the patient, working the problem through, and entering the orders.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 8% | 33 min17 min to 1.3 h | In person 50%, documents 30%, systems 20% | 50%Desk part half by now |
| Treat internal disorders, such as hypertension, heart disease, diabetes, or problems of the lung, brain, kidney, or gastrointestinal tract.Seeing the patient, working the problem through, and entering the orders.Done hourly or more by most who do it. | 7% | 33 min17 min to 1.3 h | In person 50%, documents 30%, systems 20% | 50%Desk part half by now |
| Conduct research to develop or test medications, treatments, or procedures to prevent or control disease or injury.Reading, analysis and writing, with some data gathered from patients.Done more than yearly by most who do it. | 7% | 2.5 work days6.7 h to 1 work week | Documents 80%, in person 20% | 18%Desk part half by Apr 2027 |
| Direct and coordinate activities of nurses, students, assistants, specialists, therapists, and other medical staff.Conversation on the unit, around the chart.Done hourly or more by most who do it. | 5% | 25 min8 min to 50 min | In person 60%, documents 40% | 40%Desk part half by now |
| Explain procedures and discuss test results or prescribed treatments with patients.Talking it through with the patient in the room.Done hourly or more by most who do it. AI observed on this task. | 5% | 21 min8 min to 38 min | In person 100% | Stays with people |
| Prescribe or administer medication, therapy, and other specialized medical care to treat or prevent illness, disease, or injury.Deciding the treatment with the patient in the room, entering the orders, and giving what is given by hand.Done hourly or more by most who do it. | 4% | 17 min8 min to 38 min | Systems 40%, in person 40%, hands-on 20% | 40%Desk part half by now |
| Monitor patients' conditions and progress and reevaluate treatments as necessary.Reading the record and results, and seeing the patient.Done hourly or more by most who do it. | 4% | 17 min8 min to 38 min | Documents 50%, in person 50% | 50%Desk part half by now |
| Collect, record, and maintain patient information, such as medical history, reports, or examination results.Taking the history from the patient and charting it.Done hourly or more by most who do it. AI observed on this task. | 3% | 13 min4 min to 25 min | Systems 60%, in person 40% | 60%Desk part half by now |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of General Internal Medicine Physicians is within reach of AI now?
- An estimated 42% of the working time is within reach of AI models now and 55% by the end of 2028, on METR's long-run pace at four in five (51% to 56% across the three paces the site shows). Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of General Internal Medicine Physicians come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Diagnose from records and results (100% of the task's time now); Diagnose difficult cases (60% of the task's time now); and Manage long-term patient care (50% of the task's time now).
- Which tasks of General Internal Medicine Physicians stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Explain results and treatments; Advise on diet and prevention; and Perform procedures on patients. Together such tasks are about 9% of the working time, and the people and body parts of the other tasks stay with people too.
- What should General Internal Medicine Physicians learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are judgment where errors are severe; signing off under your license; and reviewing work you did not do yourself. By the end of 2028 on the long-run pace at four in five, about 44% of the working time stays with people, 55% becomes checking a model's work and 0% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
- Do people already use AI for the work of General Internal Medicine Physicians?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.016% went to this job's tasks, the 339th largest share of the 447 jobs that showed up; 2 of its 19 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 8%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of General Internal Medicine Physicians?
- Anthropic's robot exposure rating (September 2026) finds 16% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 0% of the working time. Its index is 0.00 of 3. A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 19 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on October 2, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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