Medical Equipment Repairers
In short: today's best AI models could do about 28% 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 33% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 67% of the time, stays with people.
Test, adjust, or repair biomedical or electromedical equipment.
65,990 people do this job in the US. $61,660 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 on1 h
- A person checks AI's work10 h
- Desk work AI can't do yet2 h
- Stays with people27 h
Medical Equipment Repairers, now: of a 40-hour week, AI could take on 1 hours, 10 hours become checking its work, 2 hours are desk work it can't do yet, and 27 hours stay with people.
The largest pieces: Help write maintenance procedures (about 3 h, a person checks); Troubleshoot faulty equipment (about 2 h, a person checks); Study manuals and attend training (about 1 h).
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.
- 31%
- 2%
- 5%
- 5%
- 57%
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 28% 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, 0%. With Claude Mythos Preview (early), measured in April 2026, 10%. Today's estimate: 28%.
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, no reportable share went to this job's tasks in May 2026; 0 of its 20 tasks showed up. Within each of Anthropic's methods, never across a change: 0.025% to 0.014% (released February and March 2025); 0.0033% to 0.0034% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.025% | 406 of 708 | 2 of 20 |
| Released March 2025 | 0.014% | 470 of 703 | 2 of 20 |
| The week of Aug 4, 2025 (released September 2025) | 0.0033% | 578 of 655 | 1 of 20 |
| The week of Nov 13, 2025 (released January 2026) | none | n/a | 0 of 20 |
| The week of Feb 5, 2026 (released March 2026) | 0.0034% | 603 of 677 | 2 of 20 |
| April 2026 (released June 2026) | none | n/a | 0 of 20 |
| May 2026 (released June 2026) | none | n/a | 0 of 20 |
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 76% of this job's working time as physical work. For 24% of the working time, a robot has been shown doing most of the task somewhere: 24% in a purpose-built cell. 0.24 of 3, the 407th highest of the 923 jobs.
- Not physical 24%
- No robot shown 51%
- In a purpose-built cell 24%
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
67% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Troubleshoot faulty equipment, the hands-on work, 9%
- Test and calibrate equipment, the hands-on work, 8%
- Repair or replace defective parts, the hands-on work, 7%
- Fabricate parts to modify equipment, the hands-on work, 7%
- Repair shop and hospital equipment, the hands-on work, 6%
- Perform preventive maintenance, the hands-on work, 6%
What becomes checking the machine
29% 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. Another 4% is desk work that is small if wrong, which can be handed over with lighter checks.
- Help write maintenance procedures, costly if wrong, 11%
- Troubleshoot faulty equipment, severe if wrong, 4%
- Fabricate parts to modify equipment, severe if wrong, 3%
- Plan and do assigned work from drawings, severe if wrong, 2%
- Evaluate equipment for purchase, costly if wrong, 2%
- Test and calibrate equipment, severe if wrong, 2%
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.
- The hands-on craft. About 57% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- 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: spotting what a draft gets wrong is a skill of its own.
- Briefing a model and checking its drafts. About 31% 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.
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 . 20 tasks from .
| Task | ||||
|---|---|---|---|---|
| Contribute expertise to develop medical maintenance standard operating procedures.Writing and reviewing the maintenance procedures with the department.Done more than yearly by most who do it. | 16% | 6.7 h1.7 h to 2.1 work days | Documents 70%, conversation 30% | 43%Desk part half by now |
| Inspect, test, or troubleshoot malfunctioning medical or related equipment, following manufacturers' specifications and using test and analysis instruments.Testing the device with instruments to find the fault, the specifications alongside.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 13% | 2.5 h50 min to 5 h | Hands-on 70%, documents 30% | 30%Desk part half by now |
| Fabricate, dress down, or substitute parts or major new items to modify equipment to meet unique operational or research needs, working from job orders, sketches, modification orders, samples, or discussions with operating officials.Making or adapting parts at the bench from sketches and job orders.Done more than yearly by most who do it.Robots: no robot shown. Anthropic's rating. | 10% | 5 h1.7 h to 1.3 work days | Hands-on 70%, documents 30% | 27%Desk part half by now |
| Test or calibrate components or equipment, following manufacturers' manuals and troubleshooting techniques, using hand tools, power tools, or measuring devices.Testing and adjusting the device with the instruments, the manual alongside.Done daily by most who do it. Robots: in a purpose-built cell, Trescal DMM calibration robot (with Thinkbot Solutions / Linestar Automation) (deployed). Anthropic's rating. | 10% | 1.3 h25 min to 3.3 h | Hands-on 80%, documents 20% | 20%Desk part half by now |
| Disassemble malfunctioning equipment and remove, repair, or replace defective parts, such as motors, clutches, or transformers.Taking the unit apart and replacing what failed.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 7% | 2.5 h50 min to 6.7 h | Hands-on 100% | Stays with people |
| Repair shop equipment, metal furniture, or hospital equipment, including welding broken parts or replacing missing parts, or bring item into local shop for major repairs.Welding and replacing parts in the shop.Done more than monthly by most who do it. Robots: no robot shown. Anthropic's rating. | 6% | 3.3 h50 min to 6.7 h | Hands-on 100% | Stays with people |
| Study technical manuals or attend training sessions provided by equipment manufacturers to maintain current knowledge.Reading the manuals and sitting the manufacturers' courses; the knowing is the technician's own.Done more than yearly by most who do it. | 6% | 3.3 h50 min to 6.7 h | Documents 50%, in person 50% | 46%Desk part half by now |
| Plan and carry out work assignments, using blueprints, schematic drawings, technical manuals, wiring diagrams, or liquid or air flow sheets, following prescribed regulations, directives, or other instructions as required.Reading the drawings and manuals, then doing the job they describe.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 6% | 1.7 h25 min to 4.2 h | Hands-on 60%, documents 40% | 39%Desk part half by now |
| Perform preventive maintenance or service, such as cleaning, lubricating, or adjusting equipment.Cleaning, lubricating and adjusting the equipment by hand on its schedule.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 6% | 1.1 h25 min to 2.5 h | Hands-on 100% | Stays with people |
| Test, evaluate, and classify excess or in-use medical equipment and determine serviceability, condition, and disposition, in accordance with regulations.Testing each unit and deciding whether it stays in service, is repaired or goes.Done daily by most who do it. Robots: in a purpose-built cell, OMRON TM Series cobot PCB test cells (Absolute Robotics integration at Hanover Displays) (deployed). Anthropic's rating. | 5% | 1.7 h25 min to 3.3 h | Hands-on 60%, documents 40% | 39%Desk part half by now |
| Examine medical equipment or facility's structural environment and check for proper use of equipment to protect patients and staff from electrical or mechanical hazards and to ensure compliance with safety regulations.Walking the rooms and checking the devices and outlets for electrical and mechanical hazards, with the findings noted.Done more than monthly by most who do it. Robots: in a purpose-built cell, UR10 cobot + Robotiq 2F-85 gripper/FT sensor test cell (integrator KPI Engineering) at Diehl Aviation (Universal Robots / Robotiq / KPI Engineering) (deployed). Anthropic's rating. | 3% | 1.7 h25 min to 3.3 h | Hands-on 80%, documents 20% | 20%Desk part half by now |
| Install medical equipment.Setting the equipment up in place and connecting it.Done more than monthly by most who do it. Robots: in a purpose-built cell, Epson T3/LS6-B/LS3-B SCARA robot line (Tessy Automation) (deployed). Anthropic's rating. | 3% | 3.3 h1.7 h to 1.3 work days | Hands-on 100% | Stays with people |
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.
- Calibration Technologists and Technicians37% now, 55% by 2028
- Electrical and Electronics Repairers, Commercial and Industrial Equipment26% now, 32% by 2028
- Electrical and Electronic Engineering Technologists and Technicians39% now, 48% by 2028
- Aerospace Engineering and Operations Technologists and Technicians10% now, 21% by 2028
- Photonics Technicians15% now, 16% by 2028
- Robotics Technicians22% now, 26% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
- Professional and Commercial Equipment and Supplies Merchant Wholesalers23,790 people
- Electronic and Precision Equipment Repair and Maintenance9,580 people
- General Medical and Surgical Hospitals7,670 people
- Rental and Leasing Services (5322, 5323, and 5324 only)7,340 people
- Health and Personal Care Retailers3,760 people
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 Medical Equipment Repairers is within reach of AI now?
- An estimated 28% of the working time is within reach of AI models now and 33% by the end of 2028, on METR's long-run pace at four in five. 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 Medical Equipment Repairers 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: Help write maintenance procedures (43% of the task's time now, 70% by the end of 2028); Troubleshoot faulty equipment (30% of the task's time now); and Study manuals and attend training (46% of the task's time now).
- Which tasks of Medical Equipment Repairers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Repair or replace defective parts; Repair shop and hospital equipment; and Perform preventive maintenance. Together such tasks are about 24% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Medical Equipment Repairers 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; the hands-on craft; and reviewing work you did not do yourself. By the end of 2028 on the long-run pace at four in five, about 67% of the working time stays with people, 29% becomes checking a model's work and 4% 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 Medical Equipment Repairers?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 0%. 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 Medical Equipment Repairers?
- Anthropic's robot exposure rating (September 2026) finds 76% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 24% of the working time. Its index is 0.24 of 3. One example: Trescal DMM calibration robot (with Thinkbot Solutions / Linestar Automation) for "test and calibrate equipment". 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 20 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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