Cleaners of Vehicles and Equipment
In short: today's best AI models could do about 1% 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 99% of the time, stays with people.
Wash or otherwise clean vehicles, machinery, and other equipment. Use such materials as water, cleaning agents, brushes, cloths, and hoses.
380,430 people do this job in the US. $35,830 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 work0 h
- Desk work AI can't do yet0 h
- Stays with people40 h
Cleaners of Vehicles and Equipment, now: of a 40-hour week, AI could take on 0 hours, 0 hours become checking its work, 0 hours are desk work it can't do yet, and 40 hours stay with people.
The largest pieces: Keep supply inventories (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.
- 0%
- 1%
- 0%
- 1%
- 99%
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 1% 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, 1%. Today's estimate: 1%.
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
None of this job's 20 tasks showed up in the Claude.ai conversations Anthropic sampled in any of its 7 releases, from February 2025 to May 2026.
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 100% of this job's working time as physical work. For 85% of the working time, a robot has been shown doing most of the task somewhere: 70% in a purpose-built cell, 15% in a structured facility. 1.00 of 3, the 116th highest of the 923 jobs.
- No robot shown 15%
- In a purpose-built cell 70%
- In a structured facility 15%
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
99% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Polish and wax vehicles, the hands-on work, 22%
- Scrub and spray down equipment, the hands-on work, 15%
- Clean vehicle windows, the hands-on work, 9%
- Soak and rinse parts, the hands-on work, 8%
- Clean car interiors, the hands-on work, 7%
- Inspect cleaned vehicles, the hands-on work, 6%
What becomes checking the machine
No desk work within reach by then in tasks where a mistake costs something.
What to learn
- The hands-on craft. About 99% 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.
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 | ||||
|---|---|---|---|---|
| Apply paints, dyes, polishes, reconditioners, waxes, or masking materials to vehicles to preserve, protect, or restore color or condition.Applying polish, wax and touch ups by hand.Done daily by most who do it. Robots: in a purpose-built cell, Automated tire shiners (independent-roller applicators; MacNeil Gloss Boss, Motor City Super Shiner, Sonny's/Simoniz) (deployed). Anthropic's rating. | 22% | 1.3 h25 min to 2.5 h | Hands-on 100% | Stays with people |
| Scrub, scrape, or spray machine parts, equipment, or vehicles, using scrapers, brushes, clothes, cleaners, disinfectants, insecticides, acid, abrasives, vacuums, or hoses.Scrubbing and spraying with brushes, cleaners and hoses.Done daily by most who do it. Robots: in a purpose-built cell, PDQ LaserWash 360 Plus in-bay automatic (deployed). Anthropic's rating. | 15% | 38 min13 min to 1.7 h | Hands-on 100% | Stays with people |
| Clean and polish vehicle windows.Washing and polishing glass.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 9% | 17 min8 min to 33 min | Hands-on 100% | Stays with people |
| Pre-soak or rinse machine parts, equipment, or vehicles by immersing objects in cleaning solutions or water, manually or using hoists.Dipping and rinsing by hand or hoist.Done daily by most who do it. Robots: in a purpose-built cell, PDQ LaserWash 360 Plus (OPW Vehicle Wash Solutions) (deployed). Anthropic's rating. | 8% | 25 min8 min to 50 min | Hands-on 100% | Stays with people |
| Clean the plastic work inside cars, using paintbrushes.Detailing the interior plastics by hand.Done daily by most who do it.Robots: in a purpose-built cell, Confinity Robotics STAGS (stationary gantry system) (demonstrated). Anthropic's rating. | 7% | 25 min8 min to 50 min | Hands-on 100% | Stays with people |
| Inspect parts, equipment, or vehicles for cleanliness, damage, and compliance with standards or regulations.Looking the work over for spots and damage.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 6% | 17 min4 min to 33 min | Hands-on 100% | Stays with people |
| Drive vehicles to or from workshops or customers' workplaces or homes.Driving the customer's vehicle.Done daily by most who do it. Robots: in a structured facility, Hyundai WIA Parking Robot (with Smart Parking Control System) (sold). Anthropic's rating. | 6% | 25 min13 min to 50 min | Hands-on 100% | Stays with people |
| Rinse objects and place them on drying racks or use cloth, squeegees, or air compressors to dry surfaces.Rinsing and drying by hand.Done daily by most who do it. Robots: in a purpose-built cell, Conveyor tunnel car wash system (spot-free rinse arch + blowers/dryers) (deployed). Anthropic's rating. | 4% | 13 min4 min to 33 min | Hands-on 100% | Stays with people |
| Sweep, shovel, or vacuum loose debris or salvageable scrap into containers and remove containers from work areas.Sweeping and shoveling into bins and carrying them out.Done daily by most who do it. Robots: in a purpose-built cell, Confinity Robotics interior cleaning robot (stationary gantry system) (demonstrated). Anthropic's rating. | 4% | 17 min8 min to 38 min | Hands-on 100% | Stays with people |
| Fit boot spoilers, side skirts, or mud flaps to cars.Fitting accessories by hand.Done daily by most who do it.Robots: in a purpose-built cell, Universal Robots UR10 cobot screwdriving stations in automotive final assembly (examples cited at Stellantis plants) (deployed). Anthropic's rating. | 3% | 50 min25 min to 1.7 h | Hands-on 100% | Stays with people |
| Maintain inventories of supplies.Counting the stock and noting what is low.Done daily by most who do it. Robots: in a purpose-built cell, Stretch (Boston Dynamics) (deployed). Anthropic's rating. | 3% | 25 min13 min to 50 min | Hands-on 70%, systems 30% | 30%Desk part half by now |
| Monitor operation of cleaning machines and stop machines or notify supervisors when malfunctions occur.Keeping an eye on the machine and stopping it or fetching the supervisor.Done daily by most who do it. Robots: in a structured facility, NoPileups (DRB) (deployed). Anthropic's rating. | 3% | 17 min4 min to 50 min | Hands-on 80%, in person 20% | 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.
- Laundry and Dry-Cleaning Workers1% now, 1% by 2028
- Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders5% now, 5% by 2028
- Janitors and Cleaners, Except Maids and Housekeeping Cleaners3% now, 3% by 2028
- Septic Tank Servicers and Sewer Pipe Cleaners6% now, 6% by 2028
- Maintenance Workers, Machinery4% now, 4% by 2028
- Coating, Painting, and Spraying Machine Setters, Operators, and Tenders1% now, 1% 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 Cleaners of Vehicles and Equipment is within reach of AI now?
- An estimated 1% of the working time is within reach of AI models now and 1% 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 Cleaners of Vehicles and Equipment 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: Keep supply inventories (30% of the task's time now).
- Which tasks of Cleaners of Vehicles and Equipment stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Polish and wax vehicles; Scrub and spray down equipment; and Clean vehicle windows. Together such tasks are about 97% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Cleaners of Vehicles and Equipment 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; and judgment where errors are severe. By the end of 2028 on the long-run pace at four in five, about 99% of the working time stays with people, 0% 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 Cleaners of Vehicles and Equipment?
- 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 Cleaners of Vehicles and Equipment?
- Anthropic's robot exposure rating (September 2026) finds 100% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 85% of the working time, 15% in a structured facility. Its index is 1.00 of 3. One example: Hyundai WIA Parking Robot (with Smart Parking Control System) for "drive vehicles to and from customers". 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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