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Do you agree with the AI automation risk score calculated for this occupation?
AI Automation Index
Will AI Replace Painters, Construction and Maintenance?
Task-level automation exposure for Painters, Construction and Maintenance: 17 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
18%
weighted task index
17 of 17 tasks scored
Median Salary
$49,400 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
High
225,190 people hold this job — size, not growth
Projected 2025–35
+3.0%
employment change
24,900 openings a year · BLS line item
Pay by state
BLS OEWS publishes 54 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$24,070 – $68,220
Highest medians
Hawaii $68,220
Illinois $61,260
Alaska $60,980
Washington $59,650
New York $59,570
Lowest medians
Puerto Rico $24,070
Guam $32,960
Arkansas $40,090
South Carolina $40,840
Rhode Island $41,590
State figures come from the 47-2141 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 18%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 82%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 11%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 0%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 0/100
Low
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
17 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 13%
2 tasks
Medium exposure (≥ 35%) 5%
1 tasks
Low exposure (below 35%) 82%
14 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Emerging & rewritten tasks
Tasks O*NET added or rewrote for this occupation in its recent updates (05/2025 – 08/2026), with who proposed them. Additions are not in the scored task inventory — they are new work O*NET is still measuring, so they appear here and nowhere in the index. A Revision replaces a task that is scored, which is why only those move the "Rewritten by O*NET" share.
- New 07/2014 · Incumbent
Clean tools and equipment, such as brushes and rollers.
- New 07/2014 · Incumbent
Hang wallpaper.
Constituent Tasks
#11511 · Core · 4% automatable
Cover surfaces with dropcloths or masking tape and paper to protect surfaces during painting.
physical manipulation — Hands-on placement of protective coverings
Protect structures or surfaces near work areas to avoid damage.
#11516 · Core · 70% automatable
Read work orders or receive instructions from supervisors or homeowners to determine work requirements.
visual inspection — Specs reading aided, human validates requirements
Review blueprints or specifications to determine work requirements.
#11514 · Core · 10% automatable
Apply paint, stain, varnish, enamel, or other finishes to equipment, buildings, bridges, or other structures, using brushes, spray guns, or rollers.
physical manipulation — Applying paint requires physical brush or spray work
Apply paint to surfaces.
#11512 · Core · 5% automatable
Fill cracks, holes, or joints with caulk, putty, plaster, or other fillers, using caulking guns or putty knives.
physical manipulation — Applying filler to surfaces is hands-on
Apply material to fill gaps in surfaces.
#11523 · Core · 8% automatable
Smooth surfaces, using sandpaper, scrapers, brushes, steel wool, or sanding machines.
physical manipulation — Abrasive hand work on physical surfaces
Smooth surfaces with abrasive materials or tools.
#11517 · Core · 10% automatable
Erect scaffolding or swing gates, or set up ladders, to work above ground level.
physical manipulation — Erecting temporary structures requires physical assembly
Assemble temporary equipment or structures.
#11519 · Core · 7% automatable
Wash and treat surfaces with oil, turpentine, mildew remover, or other preparations, and sand rough spots to ensure that finishes will adhere properly.
physical manipulation — Surface preparation is hands-on physical work
Clean surfaces in preparation for work activities. Prepare surfaces for finishing.
#11513 · Core · 4% automatable
Apply primers or sealers to prepare new surfaces, such as bare wood or metal, for finish coats.
physical manipulation — Hands-on surface preparation before finishing
Prepare surfaces for finishing.
#11515 · Core · 66% automatable
Calculate amounts of required materials and estimate costs, based on surface measurements or work orders.
data analysis — Material takeoffs from plans; human verifies quantities
Estimate construction project costs. Estimate materials requirements for projects.
#11521 · Core · 10% automatable
Remove old finishes by stripping, sanding, wire brushing, burning, or using water or abrasive blasting.
physical manipulation — Surface preparation is hands-on physical work
Clean surfaces in preparation for work activities.
#11518 · Core · 4% automatable
Remove fixtures such as pictures, door knobs, lamps, or electric switch covers prior to painting.
physical manipulation — Hands-on placement of protective coverings
Protect structures or surfaces near work areas to avoid damage.
#11525 · Core · 4% automatable
Use special finishing techniques such as sponging, ragging, layering, or faux finishing.
physical manipulation — Hands-on textured finish application
Apply decorative or textured finishes or coverings.
#11526 · Core · 10% automatable
Waterproof buildings, using waterproofers or caulking.
physical manipulation — Applying sealants requires hands-on coating
Apply sealants or other protective coatings.
#11522 · Core · 53% automatable
Select and purchase tools or finishes for surfaces to be covered, considering durability, ease of handling, methods of application, and customers' wishes.
decision support — Construction procurement needs human supplier judgment
Select construction equipment. Order construction or extraction materials or equipment.
#11520 · Core · 12% automatable
Mix and match colors of paint, stain, or varnish with oil or thinning and drying additives to obtain desired colors and consistencies.
physical manipulation — Physical handling of substances in workspace
Mix substances or compounds needed for work activities.
#11524 · Supplemental · 8% automatable
Polish final coats to specified finishes.
physical manipulation — Abrasive hand work on physical surfaces
Smooth surfaces with abrasive materials or tools.
#11527 · Supplemental · 5% automatable
Cut stencils and brush or spray lettering or decorations on surfaces.
physical manipulation — Hand cutting of flexible flooring materials
Cut carpet, vinyl or other flexible materials. Apply decorative or textured finishes or coverings.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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