Coating, Painting, and Spraying Machine Setters, Operators, and Tenders
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.
Set up, operate, or tend spraying or rolling machines to coat or paint any of a wide variety of products, including glassware, cloth, ceramics, metal, plastic, paper, or wood, with lacquer, silver, copper, rubber, varnish, glaze, enamel, oil, or rust-proofing materials. Includes painters of transportation vehicles such as painters in auto body repair facilities.
158,740 people do this job in the US. $48,250 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
Coating, Painting, and Spraying Machine Setters, Operators, and Tenders, 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: Record operational data (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%
- 0%
- 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
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 29 tasks showed up. Within each of Anthropic's methods, never across a change: 0.0021% to none (released February and March 2025).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.0021% | 691 of 708 | 1 of 29 |
| Released March 2025 | none | n/a | 0 of 29 |
| The week of Aug 4, 2025 (released September 2025) | none | n/a | 0 of 29 |
| The week of Nov 13, 2025 (released January 2026) | none | n/a | 0 of 29 |
| The week of Feb 5, 2026 (released March 2026) | none | n/a | 0 of 29 |
| April 2026 (released June 2026) | none | n/a | 0 of 29 |
| May 2026 (released June 2026) | none | n/a | 0 of 29 |
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 98% of this job's working time as physical work. For 89% of the working time, a robot has been shown doing most of the task somewhere: 75% in a purpose-built cell, 14% in a structured facility. 1.02 of 3, the 107th highest of the 923 jobs.
- Not physical 3%
- No robot shown 9%
- In a purpose-built cell 75%
- In a structured facility 14%
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.
- Spray primers and finish coats, the hands-on work, 8%
- Clean and reassemble sprayers, the hands-on work, 8%
- Clean equipment and work areas, the hands-on work, 7%
- Position spray guns, the hands-on work, 7%
- Apply undercoats and seal seams, the hands-on work, 7%
- Find and correct painting flaws, the hands-on work, 7%
What becomes checking the machine
No desk work within reach by then in tasks where a mistake costs something. Another 1% is desk work that is small if wrong, which can be handed over with lighter checks.
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 . 29 tasks from .
| Task | ||||
|---|---|---|---|---|
| Spray prepared surfaces with specified amounts of primers and decorative or finish coatings.Spraying the coats by hand.Done daily by most who do it. Robots: in a purpose-built cell, Dürr EcoRP / EcoBell4 painting robots (deployed). Anthropic's rating. | 8% | 38 min13 min to 1.7 h | Hands-on 100% | Stays with people |
| Disassemble, clean, and reassemble sprayers or power equipment, using solvents, wire brushes, and cloths.Sprayers taken apart, cleaned with solvent and rebuilt.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 8% | 38 min17 min to 1.7 h | Hands-on 100% | Stays with people |
| Clean equipment and work areas.Cleaning by hand.Done daily by most who do it. Robots: in a purpose-built cell, Herkules G205 / G375 automatic paint gun washer (sold). Anthropic's rating. | 7% | 25 min13 min to 1.1 h | Hands-on 100% | Stays with people |
| Hold or position spray guns to direct spray onto articles.Directing the spray by hand.Done hourly or more by most who do it. Robots: in a structured facility, FANUC CRX-10iA/L Paint cobot (sold). Anthropic's rating. | 7% | 17 min8 min to 50 min | Hands-on 100% | Stays with people |
| Apply rust-resistant undercoats and caulk and seal seams.Undercoating and caulking by hand.Done hourly or more by most who do it. Robots: in a purpose-built cell, GrayMatter Robotics Scan&Spray / GMR-AI autonomous cells (deployed). Anthropic's rating. | 7% | 33 min13 min to 1.3 h | Hands-on 100% | Stays with people |
| Monitor painting operations to identify flaws, such as blisters or streaks, and correct their causes.Watching the finish for blisters and streaks and fixing the cause.Done daily by most who do it. Robots: in a purpose-built cell, 3M Finesse-it Robotic Paint Repair System + Inovision SMARTInspect + FANUC M-710iC/70 (deployed). Anthropic's rating. | 7% | 25 min8 min to 50 min | Hands-on 100% | Stays with people |
| Remove grease, dirt, paint, or rust from surfaces in preparation for paint application, using abrasives, solvents, brushes, blowtorches, washing tanks, or sandblasters.Removing grease, paint and rust with abrasives, solvents, torches or sandblasters.Robots: in a purpose-built cell, Scan&Sand (GMR-AI) (GrayMatter Robotics) (deployed). Anthropic's rating. | 6% | 50 min17 min to 1.7 h | Hands-on 100% | Stays with people |
| Sand and apply sealer to properly dried finish.Sanding and sealer by hand.Robots: in a purpose-built cell, GrayMatter Robotics Scan&Sand (FANUC robot) (deployed). Anthropic's rating. | 4% | 38 min17 min to 1.3 h | Hands-on 100% | Stays with people |
| Dispose of hazardous waste in an appropriate manner.Handling and disposing of waste by the rules.Done daily by most who do it. Robots: in a purpose-built cell, Feige FILLING INTEGRA 84 automatic drum filling line (sold). Anthropic's rating. | 4% | 21 min8 min to 50 min | Hands-on 100% | Stays with people |
| Fill small dents or scratches with body fillers and smooth surfaces to prepare for painting.Body filler applied and sanded.Robots: no robot shown. Anthropic's rating. | 4% | 33 min17 min to 1.1 h | Hands-on 100% | Stays with people |
| Set up portable equipment, such as ventilators, exhaust units, ladders, or scaffolding.Portable equipment set up by hand.Done daily by most who do it.Robots: no robot shown. Anthropic's rating. | 3% | 29 min13 min to 1.1 h | Hands-on 100% | Stays with people |
| Operate auxiliary machines or equipment used in coating or painting processes.Running the auxiliary machines.Done daily by most who do it.Robots: in a purpose-built cell, Moldow automated powder coating line (BT Products AB / Toyota Material Handling plant) (deployed). Anthropic's rating. | 3% | 25 min8 min to 50 min | 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.
- Painting, Coating, and Decorating Workers0% now, 0% by 2028
- Plating Machine Setters, Operators, and Tenders, Metal and Plastic6% now, 6% by 2028
- Molders, Shapers, and Casters, Except Metal and Plastic0% now, 0% by 2028
- Furniture Finishers4% now, 4% by 2028
- Grinding and Polishing Workers, Hand11% now, 11% by 2028
- Adhesive Bonding Machine Operators and Tenders9% now, 9% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
- Automotive Repair and Maintenance27,290 people
- Coating, Engraving, Heat Treating, and Allied Activities16,500 people
- Fabricated Metal Product Manufacturing (3323 and 3324 only)11,470 people
- Machinery Manufacturing (3331, 3332, 3334, and 3339 only)11,340 people
- Aerospace Product and Parts Manufacturing6,680 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 Coating, Painting, and Spraying Machine Setters, Operators, and Tenders 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 Coating, Painting, and Spraying Machine Setters, Operators, and Tenders 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: Record operational data (100% of the task's time now).
- Which tasks of Coating, Painting, and Spraying Machine Setters, Operators, and Tenders stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Spray primers and finish coats; Clean and reassemble sprayers; and Clean equipment and work areas. Together such tasks are about 99% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Coating, Painting, and Spraying Machine Setters, Operators, and Tenders 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 Coating, Painting, and Spraying Machine Setters, Operators, and Tenders?
- 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 Coating, Painting, and Spraying Machine Setters, Operators, and Tenders?
- Anthropic's robot exposure rating (September 2026) finds 98% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 89% of the working time, 14% in a structured facility. Its index is 1.02 of 3. One example: FANUC CRX-10iA/L Paint cobot for "position spray guns". 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 29 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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