Painters, Construction and Maintenance
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.
Paint walls, equipment, buildings, bridges, and other structural surfaces, using brushes, rollers, and spray guns. May remove old paint to prepare surface prior to painting. May mix colors or oils to obtain desired color or consistency.
225,190 people do this job in the US. $49,400 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
Painters, Construction and Maintenance, 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: Choose and buy finishes and tools (under an hour, a person checks); Estimate materials and costs (under an hour, a person checks); Read work orders and take instructions (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%
- 1%
- 97%
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, no reportable share went to this job's tasks in May 2026; 0 of its 17 tasks showed up. Within each of Anthropic's methods, never across a change: 0.0092% to 0.0043% (released February and March 2025); 0.0059% to 0.0056% (August 2025 to February 2026); 0.011% to none (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.0092% | 541 of 708 | 2 of 17 |
| Released March 2025 | 0.0043% | 598 of 703 | 2 of 17 |
| The week of Aug 4, 2025 (released September 2025) | 0.0059% | 514 of 655 | 1 of 17 |
| The week of Nov 13, 2025 (released January 2026) | 0.0044% | 586 of 672 | 2 of 17 |
| The week of Feb 5, 2026 (released March 2026) | 0.0056% | 563 of 677 | 2 of 17 |
| April 2026 (released June 2026) | 0.011% | 376 of 434 | 1 of 17 |
| May 2026 (released June 2026) | none | n/a | 0 of 17 |
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 90% of this job's working time as physical work. For 66% of the working time, a robot has been shown doing most of the task somewhere: 64% in a purpose-built cell, 1% in a structured facility. 0.67 of 3, the 266th highest of the 923 jobs.
- Not physical 10%
- No robot shown 24%
- In a purpose-built cell 64%
- In a structured facility 1%
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.
- Apply paint and finishes, the hands-on work, 38%
- Prime and seal surfaces, the hands-on work, 11%
- Fill cracks and holes, the hands-on work, 10%
- Sand and smooth surfaces, the hands-on work, 10%
- Mask and cover surfaces, the hands-on work, 7%
- Set up ladders and scaffolding, the hands-on work, 5%
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.
- Choose and buy finishes and tools, costly if wrong, 1%
- Estimate materials and costs, costly if wrong, 1.0%
What to learn
- The hands-on craft. About 97% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- 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.
- 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 . 17 tasks from .
| Task | ||||
|---|---|---|---|---|
| Apply paint, stain, varnish, enamel, or other finishes to equipment, buildings, bridges, or other structures, using brushes, spray guns, or rollers.Brush, roller and spray work.Done hourly or more by most who do it. Robots: in a purpose-built cell, Okibo EG7 (deployed). Anthropic's rating. | 38% | 2.5 h50 min to 6.7 h | Hands-on 100% | Stays with people |
| Apply primers or sealers to prepare new surfaces, such as bare wood or metal, for finish coats.By brush, roller or spray.Done daily by most who do it. Robots: in a purpose-built cell, Okibo EG7+ with BLASTER spray gun (deployed). Anthropic's rating. | 11% | 1.7 h25 min to 4.2 h | Hands-on 100% | Stays with people |
| Fill cracks, holes, or joints with caulk, putty, plaster, or other fillers, using caulking guns or putty knives.Caulk and putty by hand.Done daily by most who do it. Robots: in a purpose-built cell, Con-Vey + Argos Solutions automated panel repair (patch) line (deployed). Anthropic's rating. | 10% | 50 min13 min to 1.7 h | Hands-on 100% | Stays with people |
| Smooth surfaces, using sandpaper, scrapers, brushes, steel wool, or sanding machines.By hand and machine.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 10% | 1.3 h17 min to 2.5 h | Hands-on 100% | Stays with people |
| Cover surfaces with dropcloths or masking tape and paper to protect surfaces during painting.Taping and draping by hand.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 7% | 38 min13 min to 1.7 h | Hands-on 100% | Stays with people |
| Erect scaffolding or swing gates, or set up ladders, to work above ground level.Putting up scaffolds and ladders by hand.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 5% | 50 min17 min to 2.5 h | Hands-on 100% | Stays with people |
| Wash and treat surfaces with oil, turpentine, mildew remover, or other preparations, and sand rough spots to ensure that finishes will adhere properly.Cleaning and treating by hand.Done more than monthly by most who do it. Robots: no robot shown. Anthropic's rating. | 4% | 1.3 h25 min to 3.3 h | Hands-on 100% | Stays with people |
| Polish final coats to specified finishes.By hand.Done more than weekly by most who do it.Robots: in a purpose-built cell, Gottschild HBS 1600/1800/2200/2600 polishing and sanding machines (sold). Anthropic's rating. | 4% | 1.3 h25 min to 3.3 h | Hands-on 100% | Stays with people |
| Waterproof buildings, using waterproofers or caulking.Applying waterproofers and caulk.Done more than yearly by most who do it. Robots: in a purpose-built cell, Dürr sealing robots (EcoGun2 / EcoJet applicators, Ecopaint sealing line) (deployed). Anthropic's rating. | 3% | 2.5 h38 min to 6.7 h | Hands-on 100% | Stays with people |
| Select and purchase tools or finishes for surfaces to be covered, considering durability, ease of handling, methods of application, and customers' wishes.Choosing the products, buying them, and picking them up.Done more than weekly by most who do it. | 2% | 38 min17 min to 1.7 h | Documents 40%, systems 30%, hands-on 30% | 70%Desk part half by now |
| Use special finishing techniques such as sponging, ragging, layering, or faux finishing.Specialty brush and sponge work.Done yearly or less by most who do it. Robots: in a purpose-built cell, Okibo EG7+ (deployed). Anthropic's rating. | 2% | 2.5 h50 min to 6.7 h | Hands-on 100% | Stays with people |
| Remove old finishes by stripping, sanding, wire brushing, burning, or using water or abrasive blasting.Stripping and blasting by hand and machine.Done more than monthly by most who do it. Robots: in a purpose-built cell, Blastman B20C / B20S blast cleaning robots (sold). Anthropic's rating. | 2% | 2.5 h38 min to 6.7 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.
- Painting, Coating, and Decorating Workers0% now, 0% by 2028
- Helpers--Painters, Paperhangers, Plasterers, and Stucco Masons0% now, 0% by 2028
- Plasterers and Stucco Masons2% now, 2% by 2028
- Coating, Painting, and Spraying Machine Setters, Operators, and Tenders1% now, 1% by 2028
- Furniture Finishers4% now, 4% by 2028
- Roofers1% 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 Painters, Construction and Maintenance 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 Painters, Construction and Maintenance 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: Choose and buy finishes and tools (70% of the task's time now); Estimate materials and costs (100% of the task's time now); and Read work orders and take instructions (50% of the task's time now).
- Which tasks of Painters, Construction and Maintenance stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Apply paint and finishes; Prime and seal surfaces; and Fill cracks and holes. Together such tasks are about 96% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Painters, Construction and Maintenance 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; reviewing work you did not do yourself; and judgment where errors are severe. 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 Painters, Construction and Maintenance?
- 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 Painters, Construction and Maintenance?
- Anthropic's robot exposure rating (September 2026) finds 90% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 66% of the working time, 1% in a structured facility. Its index is 0.67 of 3. One example: RoadPrintz robotic pavement-marking truck for "paint lettering and decoration". 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 17 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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