Industrial Machinery Mechanics
In short: today's best AI models could do about 13% 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 87% of the time, stays with people.
Repair, install, adjust, or maintain industrial production and processing machinery or refinery and pipeline distribution systems. May also install, dismantle, or move machinery and heavy equipment according to plans.
439,640 people do this job in the US. $64,520 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 on2 h
- A person checks AI's work3 h
- Desk work AI can't do yet0 h
- Stays with people35 h
Industrial Machinery Mechanics, now: of a 40-hour week, AI could take on 2 hours, 3 hours become checking its work, 0 hours are desk work it can't do yet, and 35 hours stay with people.
The largest pieces: Diagnose equipment problems (about 2 h, a person checks); Record parts used and reorder (about 1 h); Program machine controls (under an hour, 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.
- 5%
- 8%
- 0%
- 5%
- 82%
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 13% 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: 13%.
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, 0.021% went to this job's tasks in May 2026, the 319th largest of the 447 jobs that showed up at all; 1 of its 16 tasks showed up. Within each of Anthropic's methods, never across a change: 0.029% to 0.021% (released February and March 2025); 0.03% to 0.04% (August 2025 to February 2026); 0.034% to 0.021% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.029% | 369 of 708 | 2 of 16 |
| Released March 2025 | 0.021% | 410 of 703 | 2 of 16 |
| The week of Aug 4, 2025 (released September 2025) | 0.03% | 311 of 655 | 1 of 16 |
| The week of Nov 13, 2025 (released January 2026) | 0.045% | 250 of 672 | 2 of 16 |
| The week of Feb 5, 2026 (released March 2026) | 0.04% | 277 of 677 | 2 of 16 |
| April 2026 (released June 2026) | 0.034% | 263 of 434 | 1 of 16 |
| May 2026 (released June 2026) | 0.021% | 319 of 447 | 1 of 16 |
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 79% of this job's working time as physical work. For 27% of the working time, a robot has been shown doing most of the task somewhere: 27% in a purpose-built cell. 0.27 of 3, the 395th highest of the 923 jobs.
- Not physical 21%
- No robot shown 52%
- In a purpose-built cell 27%
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
87% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Maintain production machinery, the hands-on work, 29%
- Disassemble machinery for repair, the hands-on work, 10%
- Repair or replace components, the hands-on work, 10%
- Clean, oil and adjust machinery, the hands-on work, 8%
- Test machinery to find faults, the hands-on work, 7%
- Reassemble equipment, the hands-on work, 7%
What becomes checking the machine
8% 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.
- Diagnose equipment problems, severe if wrong, 6%
- Program machine controls, severe if wrong, 2%
- Study manuals and blueprints, costly if wrong, 0.9%
What to learn
- The hands-on craft. About 82% 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: 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 . 16 tasks from .
| Task | ||||
|---|---|---|---|---|
| Repair or maintain the operating condition of industrial production or processing machinery or equipment.Hands-on repair and upkeep of the plant's machines.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 29% | 4.2 h1.7 h to 6.7 h | Hands-on 100% | Stays with people |
| Disassemble machinery or equipment to remove parts and make repairs.Stripping the machine down by hand.Done more than weekly by most who do it. Robots: no robot shown. Anthropic's rating. | 10% | 2.1 h38 min to 4.2 h | Hands-on 100% | Stays with people |
| Repair or replace broken or malfunctioning components of machinery or equipment.Hands-on repair and replacement of parts.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 10% | 2.5 h50 min to 5 h | Hands-on 100% | Stays with people |
| Analyze test results, machine error messages, or information obtained from operators to diagnose equipment problems.Reading the test results and error codes, asking the operators, and working out the cause.Done daily by most who do it. | 9% | 1.3 h25 min to 2.5 h | Documents 40%, systems 30%, in person 30% | 70%Desk part half by now |
| Clean, lubricate, or adjust parts, equipment, or machinery.Routine hands-on upkeep.Done daily by most who do it. Robots: in a purpose-built cell, ICS robotic dry-ice cleaning cell for rubber/tire molds (sold). Anthropic's rating. | 8% | 1.3 h25 min to 2.5 h | Hands-on 100% | Stays with people |
| Observe and test the operation of machinery or equipment to diagnose malfunctions, using voltmeters or other testing devices.Watching the machine run and testing it with meters.Done several times a day by most who do it. Robots: in a purpose-built cell, Flying probe test systems (automated in-circuit/flying probe testers) (multiple) (sold). Anthropic's rating. | 7% | 1.7 h38 min to 3.3 h | Hands-on 100% | Stays with people |
| Reassemble equipment after completion of inspections, testing, or repairs.Putting the machine back together by hand.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 7% | 1.7 h38 min to 3.3 h | Hands-on 100% | Stays with people |
| Cut and weld metal to repair broken metal parts, fabricate new parts, or assemble new equipment.Cutting and welding metal by hand.Done more than weekly by most who do it. Robots: in a purpose-built cell, Path Robotics AW-3 / AF-1 intelligent welding cells (Obsidian AI) (sold). Anthropic's rating. | 5% | 2.5 h50 min to 5 h | Hands-on 100% | Stays with people |
| Examine parts for defects, such as breakage or excessive wear.Looking parts over by hand and eye for cracks and wear.Done daily by most who do it. Robots: in a purpose-built cell, AutoInspect (Lufthansa Technik) (deployed). Anthropic's rating. | 4% | 50 min17 min to 2.1 h | Hands-on 100% | Stays with people |
| Record parts or materials used and order or requisition new parts or materials, as necessary.Entries of parts used and the requisitions for more.Done daily by most who do it. | 3% | 38 min13 min to 1.3 h | Systems 100% | 100%Half by now |
| Operate newly repaired machinery or equipment to verify the adequacy of repairs.Running the machine after the repair and watching how it behaves.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 3% | 50 min17 min to 2.5 h | Hands-on 100% | Stays with people |
| Enter codes and instructions to program computer-controlled machinery.Keying codes and settings into the machine controller.Done more than monthly by most who do it. AI observed on this task. | 2% | 50 min17 min to 2.5 h | Systems 70%, hands-on 30% | 70%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.
- Maintenance Workers, Machinery4% now, 4% by 2028
- Electric Motor, Power Tool, and Related Repairers3% now, 3% by 2028
- Multiple Machine Tool Setters, Operators, and Tenders, Metal and Plastic10% now, 10% by 2028
- Mobile Heavy Equipment Mechanics, Except Engines6% now, 6% by 2028
- Engine and Other Machine Assemblers9% now, 9% by 2028
- Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic18% now, 18% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
- Commercial and Industrial Machinery and Equipment (except Automotive and Electronic) Repair and Maintenance53,790 people
- Machinery, Equipment, and Supplies Merchant Wholesalers46,600 people
- Machinery Manufacturing (3331, 3332, 3334, and 3339 only)18,570 people
- Plastics Product Manufacturing14,570 people
- Motor Vehicle Parts Manufacturing13,210 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 Industrial Machinery Mechanics is within reach of AI now?
- An estimated 13% of the working time is within reach of AI models now and 13% 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 Industrial Machinery 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: Diagnose equipment problems (70% of the task's time now); Record parts used and reorder (100% of the task's time now); and Program machine controls (70% of the task's time now).
- Which tasks of Industrial Machinery Mechanics stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Maintain production machinery; Disassemble machinery for repair; and Repair or replace components. Together such tasks are about 83% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Industrial Machinery 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 87% of the working time stays with people, 8% 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 Industrial Machinery Mechanics?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.021% went to this job's tasks, the 319th largest share of the 447 jobs that showed up; 1 of its 16 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 2%. 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 Industrial Machinery Mechanics?
- Anthropic's robot exposure rating (September 2026) finds 79% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 27% of the working time. Its index is 0.27 of 3. One example: ICS robotic dry-ice cleaning cell for rubber/tire molds for "clean, oil and adjust machinery". 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 16 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.
This job in your state or metro area
Embed these figures on your site
A small card with the share of working time within reach now and at the end of 2027, 2028 and 2030, the date and a link back. Free under CC BY 4.0; the card carries the credit.
Your own version of this job
The page above is the occupation. Your job is your title and what you actually do: give both, and they are read against these tasks in your browser, nothing sent anywhere. The headline is free: how much of your working time is within reach now and by the end of 2028, and how many of the tasks your description names.
The full personal report is $19, to print or save as a PDF: every task with when it comes within reach, which ones your description names, the parts of your description the task list does not cover, what stays with you, what becomes checking the machine and what to learn.