Mobile Heavy Equipment Mechanics, Except Engines
In short: today's best AI models could do about 6% 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 94% of the time, stays with people.
Diagnose, adjust, repair, or overhaul mobile mechanical, hydraulic, and pneumatic equipment, such as cranes, bulldozers, graders, and conveyors, used in construction, logging, and mining.
176,600 people do this job in the US. $65,510 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 work0 h
- Desk work AI can't do yet0 h
- Stays with people38 h
Mobile Heavy Equipment Mechanics, Except Engines, now: of a 40-hour week, AI could take on 2 hours, 0 hours become checking its work, 0 hours are desk work it can't do yet, and 38 hours stay with people.
The largest pieces: Research and order parts (under an hour); Schedule maintenance and keep service records (under an hour); Diagnose faults (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.
- 3%
- 3%
- 0%
- 2%
- 92%
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 6% 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, 4%. Today's estimate: 6%.
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: 0.0068% to 0.006% (released February and March 2025); 0.0063% to 0.0066% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.0068% | 573 of 708 | 1 of 20 |
| Released March 2025 | 0.006% | 561 of 703 | 2 of 20 |
| The week of Aug 4, 2025 (released September 2025) | 0.0063% | 507 of 655 | 1 of 20 |
| The week of Nov 13, 2025 (released January 2026) | 0.0062% | 546 of 672 | 1 of 20 |
| The week of Feb 5, 2026 (released March 2026) | 0.0066% | 544 of 677 | 1 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 86% of this job's working time as physical work. For 20% of the working time, a robot has been shown doing most of the task somewhere: 20% in a purpose-built cell. 0.20 of 3, the 438th highest of the 923 jobs.
- Not physical 14%
- No robot shown 65%
- In a purpose-built cell 20%
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
94% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Repair transmissions and crawler heads, the hands-on work, 15%
- Overhaul and test machines, the hands-on work, 15%
- Repair and replace parts, the hands-on work, 14%
- Dismantle and reassemble heavy equipment, the hands-on work, 11%
- Test equipment after repair, the hands-on work, 7%
- Operate equipment to diagnose defects, the hands-on work, 5%
What becomes checking the machine
1% 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 faults, costly if wrong, 1%
What to learn
- The hands-on craft. About 92% 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 . 20 tasks from .
| Task | ||||
|---|---|---|---|---|
| Adjust, maintain, and repair or replace subassemblies, such as transmissions and crawler heads, using hand tools, jacks, and cranes.Hands-on work on the subassemblies with jacks and cranes.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 15% | 6.7 h1.7 h to 2.1 work days | Hands-on 100% | Stays with people |
| Overhaul and test machines or equipment to ensure operating efficiency.A full overhaul and test by hand.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 15% | 1.7 work days3.3 h to 1 work week | Hands-on 100% | Stays with people |
| Repair and replace damaged or worn parts.Hands-on repair and replacement of worn parts.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 14% | 2.5 h50 min to 6.7 h | Hands-on 100% | Stays with people |
| Dismantle and reassemble heavy equipment using hoists and hand tools.Taking the machine apart and back together with hoists and hand tools.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 11% | 6.7 h1.7 h to 2.5 work days | Hands-on 100% | Stays with people |
| Test mechanical products and equipment after repair or assembly to ensure proper performance and compliance with manufacturers' specifications.Running the repaired machine against the specifications.Done daily by most who do it. Robots: in a purpose-built cell, Duerr x-road InLine roll, brake and ABS test stand (sold). Anthropic's rating. | 7% | 1.7 h25 min to 3.3 h | Hands-on 100% | Stays with people |
| Operate and inspect machines or heavy equipment to diagnose defects.Running the machine and looking it over to find the fault.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 5% | 1.3 h25 min to 2.5 h | Hands-on 100% | Stays with people |
| Repair, rewire, and troubleshoot electrical systems.Tracing and rewiring the machine's electrical systems.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 4% | 2.5 h50 min to 5 h | Hands-on 100% | Stays with people |
| Fabricate needed parts or items from sheet metal.Making parts from sheet metal by hand.Done more than monthly by most who do it. Robots: in a purpose-built cell, Salvagnini L3/L5 fiber laser with ADLU/ADLL automation (sold). Anthropic's rating. | 4% | 2.5 h50 min to 5 h | Hands-on 100% | Stays with people |
| Diagnose faults or malfunctions to determine required repairs, using engine diagnostic equipment such as computerized test equipment and calibration devices.Hands on the machine and its test equipment, with manuals read alongside.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 3% | 1.7 h38 min to 3.3 h | Hands-on 60%, documents 40% | 40%Desk part half by now |
| Assemble gear systems, and align frames and gears.Assembling gears and aligning frames by hand.Done more than monthly by most who do it. Robots: in a purpose-built cell, Schaeffler planetary gearbox assembly cell with AICA 'Smart Assembly' cobot (deployed). Anthropic's rating. | 3% | 3.3 h1.3 h to 1 work day | Hands-on 100% | Stays with people |
| Fit bearings to adjust, repair, or overhaul mobile mechanical, hydraulic, and pneumatic equipment.Hands-on fitting of bearings on hydraulic and pneumatic equipment.Done daily by most who do it. Robots: in a purpose-built cell, Ahaus robot-integrated knuckle assembly cell (six-axis robot + bushing/sleeve press) (deployed). Anthropic's rating. | 3% | 2.5 h50 min to 5 h | Hands-on 100% | Stays with people |
| Research, order, and maintain parts inventory for services and repairs.Finding the right parts, then ordering them and keeping the stock record.Done daily by most who do it. | 2% | 1.3 h25 min to 2.5 h | Systems 60%, documents 40% | 100%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.
- Industrial Machinery Mechanics13% now, 13% by 2028
- Bus and Truck Mechanics and Diesel Engine Specialists2% now, 2% by 2028
- Maintenance Workers, Machinery4% now, 4% by 2028
- Rail Car Repairers3% now, 3% by 2028
- Electric Motor, Power Tool, and Related Repairers3% now, 3% by 2028
- Engine and Other Machine Assemblers9% now, 9% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
- Machinery, Equipment, and Supplies Merchant Wholesalers46,810 people
- Rental and Leasing Services (5322, 5323, and 5324 only)20,620 people
- Other Specialty Trade Contractors14,780 people
- Highway, Street, and Bridge Construction9,730 people
- Commercial and Industrial Machinery and Equipment (except Automotive and Electronic) Repair and Maintenance8,750 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 Mobile Heavy Equipment Mechanics, Except Engines is within reach of AI now?
- An estimated 6% of the working time is within reach of AI models now and 6% 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 Mobile Heavy Equipment Mechanics, Except Engines 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: Research and order parts (100% of the task's time now); Schedule maintenance and keep service records (100% of the task's time now); and Diagnose faults (40% of the task's time now).
- Which tasks of Mobile Heavy Equipment Mechanics, Except Engines stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Repair transmissions and crawler heads; Overhaul and test machines; and Repair and replace parts. Together such tasks are about 92% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Mobile Heavy Equipment Mechanics, Except Engines 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 94% of the working time stays with people, 1% 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 Mobile Heavy Equipment Mechanics, Except Engines?
- 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 Mobile Heavy Equipment Mechanics, Except Engines?
- Anthropic's robot exposure rating (September 2026) finds 86% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 20% of the working time. Its index is 0.20 of 3. One example: Duerr x-road InLine roll, brake and ABS test stand for "test equipment after repair". 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 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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