Automotive Service Technicians and Mechanics
In short: today's best AI models could do about 3% 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 the same by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 97% of the time, stays with people.
Diagnose, adjust, repair, or overhaul automotive vehicles.
704,640 people do this job in the US. $50,620 a year.
Reviewed on September 30, 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 work1 h
- Desk work AI can't do yet0 h
- Stays with people39 h
Automotive Service Technicians and Mechanics, now: of a 40-hour week, AI could take on 0 hours, 1 hours become checking its work, 0 hours are desk work it can't do yet, and 39 hours stay with people.
The largest pieces: Estimate repair costs (under an hour, a person checks); Plan work from manuals and experience (under an hour, a person checks); Review work orders with supervisors (under an hour).
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.
- 2%
- 1%
- 0%
- 2%
- 95%
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 3% 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, 3%. Today's estimate: 3%.
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, 0.032% went to this job's tasks in May 2026, the 258th largest of the 447 jobs that showed up at all; 1 of its 30 tasks showed up. Within each of Anthropic's methods, never across a change: 0.011% to 0.01% (released February and March 2025); 0.0017% to 0.019% (August 2025 to February 2026); 0.034% to 0.032% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.011% | 516 of 708 | 3 of 30 |
| Released March 2025 | 0.01% | 500 of 703 | 2 of 30 |
| The week of Aug 4, 2025 (released September 2025) | 0.0017% | 645 of 655 | 1 of 30 |
| The week of Nov 13, 2025 (released January 2026) | 0.019% | 397 of 672 | 4 of 30 |
| The week of Feb 5, 2026 (released March 2026) | 0.019% | 407 of 677 | 3 of 30 |
| April 2026 (released June 2026) | 0.034% | 251 of 434 | 1 of 30 |
| May 2026 (released June 2026) | 0.032% | 258 of 447 | 1 of 30 |
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 85% 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 408th highest of the 923 jobs.
- Not physical 15%
- No robot shown 61%
- 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
97% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Replace pistons, gears and bearings, the hands-on work, 12%
- Repair or rebuild transmissions, the hands-on work, 11%
- Rebuild crankshafts and cylinder blocks, the hands-on work, 9%
- Rebuild power and steering assemblies, the hands-on work, 5%
- Service air conditioning and electrical systems, the hands-on work, 5%
- Perform scheduled maintenance, the hands-on work, 4%
What becomes checking the machine
2% 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.
- Estimate repair costs, costly if wrong, 0.8%
- Plan work from manuals and experience, costly if wrong, 0.8%
- Inspect vehicles and record findings, costly if wrong, 0.5%
What to learn
- The hands-on craft. About 95% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- Judgment where errors are severe. Some tasks are severe if wrong. Knowing when not to trust an output matters more there than speed.
- 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.
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 . 30 tasks from .
| Task | ||||
|---|---|---|---|---|
| Repair or replace parts such as pistons, rods, gears, valves, and bearings.Hands-on engine work.Done more than monthly by most who do it. Robots: no robot shown. Anthropic's rating. | 12% | 1 work day3.3 h to 2.1 work days | Hands-on 100% | Stays with people |
| Repair or rebuild transmissions.Hands-on repair.Done more than monthly by most who do it.Robots: no robot shown. Anthropic's rating. | 11% | 1 work day5 h to 2.1 work days | Hands-on 100% | Stays with people |
| Rebuild parts, such as crankshafts and cylinder blocks.Hands-on machine work.Done more than monthly by most who do it.Robots: no robot shown. Anthropic's rating. | 9% | 1 work day3.3 h to 2.5 work days | Hands-on 100% | Stays with people |
| Tear down, repair, and rebuild faulty assemblies, such as power systems, steering systems, and linkages.Hands-on repair of safety systems.Done more than weekly by most who do it. Robots: no robot shown. Anthropic's rating. | 5% | 3.3 h1.7 h to 6.7 h | Hands-on 100% | Stays with people |
| Repair and service air conditioning, heating, engine cooling, and electrical systems.Hands-on repair; refrigerant work takes a certified technician.Done more than weekly by most who do it. Robots: no robot shown. Anthropic's rating. | 5% | 2.1 h50 min to 5 h | Hands-on 100% | Stays with people |
| Perform routine and scheduled maintenance services, such as oil changes, lubrications, and tune-ups.Oil changes and tune-ups by hand.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 4% | 50 min25 min to 1.7 h | Hands-on 100% | Stays with people |
| Retrofit vehicle fuel systems with aftermarket products, such as vapor transfer devices, evaporation control devices, swirlers, lean burn devices, and friction reduction devices, to enhance combustion and fuel efficiency.Hands-on installation.Done more than monthly by most who do it.Robots: no robot shown. Anthropic's rating. | 4% | 3.3 h1.7 h to 6.7 h | Hands-on 100% | Stays with people |
| Overhaul or replace carburetors, blowers, generators, distributors, starters, and pumps.Hands-on repair.Done more than monthly by most who do it. Robots: no robot shown. Anthropic's rating. | 4% | 2.1 h1.3 h to 3.3 h | Hands-on 100% | Stays with people |
| Rewire ignition systems, lights, and instrument panels.Hands-on repair.Done more than monthly by most who do it. Robots: no robot shown. Anthropic's rating. | 3% | 2.1 h50 min to 5 h | Hands-on 100% | Stays with people |
| Tune automobile engines to ensure proper and efficient functioning.Hands-on work.Done more than weekly by most who do it. Robots: no robot shown. Anthropic's rating. | 3% | 1.3 h38 min to 2.5 h | Hands-on 100% | Stays with people |
| Diagnose and replace or repair engine management systems or related sensors for flexible fuel vehicles (FFVs) with ignition timing, fuel rate, alcohol concentration, or air-to-fuel ratio malfunctions.Tracing faults and replacing sensors.Done more than weekly by most who do it. Robots: no robot shown. Anthropic's rating. | 3% | 1.3 h38 min to 3.3 h | Hands-on 100% | Stays with people |
| Repair, reline, replace, and adjust brakes.Hands-on repair of a safety system.Done more than weekly by most who do it. Robots: no robot shown. Anthropic's rating. | 3% | 1.3 h38 min to 2.5 h | 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.
- Rail Car Repairers3% now, 3% by 2028
- Bus and Truck Mechanics and Diesel Engine Specialists2% now, 2% by 2028
- Electric Motor, Power Tool, and Related Repairers3% now, 3% by 2028
- Motorcycle Mechanics0% now, 0% by 2028
- Engine and Other Machine Assemblers9% now, 9% by 2028
- Motorboat Mechanics and Service Technicians3% now, 3% by 2028
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 Automotive Service Technicians and Mechanics is within reach of AI now?
- An estimated 3% of the working time is within reach of AI models now and 3% 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 Automotive Service Technicians and Mechanics 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: Estimate repair costs (70% of the task's time now); Plan work from manuals and experience (50% of the task's time now); and Review work orders with supervisors (50% of the task's time now).
- Which tasks of Automotive Service Technicians and Mechanics stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Replace pistons, gears and bearings; Repair or rebuild transmissions; and Rebuild crankshafts and cylinder blocks. Together such tasks are about 93% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Automotive Service Technicians and Mechanics learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are the hands-on craft; judgment where errors are severe; and reviewing work you did not do yourself. By the end of 2028 on the long-run pace at four in five, about 97% of the working time stays with people, 2% becomes checking a model's work and 1% 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 Automotive Service Technicians and Mechanics?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.032% went to this job's tasks, the 258th largest share of the 447 jobs that showed up; 1 of its 30 tasks appeared. 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 Automotive Service Technicians and Mechanics?
- Anthropic's robot exposure rating (September 2026) finds 85% 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: Fori Automation Toe Tool Systems / robotic toe tools (end-of-line wheel alignment) for "align wheels, axles and steering". 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 30 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 September 30, 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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