Will AI replace Coating, Painting, and Spraying Machine Setters, Operators, and Tenders?
AI reaches little of this job’s work.
1/100
Low exposure
More exposed to AI than 4% of US workers.
- AI already used in
- 2% of the work
- As AI tools mature: up to
- 2% of the work
What the job involves
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.
Where AI reaches the work
The job’s main tasks, heaviest first, by how far AI reaches them.
Already happening(1)
- Record operational data on specified forms.
Out of reach(28)
- Dispose of hazardous waste in an appropriate manner.
- Clean equipment and work areas.
- Hold or position spray guns to direct spray onto articles.
- Monitor painting operations to identify flaws, such as blisters or streaks, and correct their causes.
- Spray prepared surfaces with specified amounts of primers and decorative or finish coatings.
and 23 more
Also called
Painter · Auto Refinisher (Automobile Refinisher) · Auto Refinisher · Paint Line Operator · Automotive Refinish Technician (Auto Refinish Tech) · Aircraft Painter · Auto Body Painter (Automotive Body Painter) · Auto Body Painter
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What these numbers mean
The score is the share of this job’s work, weighted by how important and frequent each task is, that AI could do in half the time: tasks an AI model could do alone count in full, tasks that need software built on AI count half.
“AI already used” is the share of the work in tasks where people are recorded using AI today. “As AI tools mature” counts every task AI could halve, with or without extra software.
The percentile compares the score with every job’s, weighted by how many people in the US do each one. Exposure means AI could change how the work is done, not that the job goes away. These are estimates for the typical job, not predictions.
Sources
- O*NET 31.0 Database, U.S. Department of Labor, Employment and Training Administration
- GPTs are GPTs: Labor market impact potential of LLMs (task labels), Eloundou, Manning, Mishkin & Rock (2023), OpenAI and University of Pennsylvania
- Anthropic Economic Index: labor market impacts (task penetration), Anthropic
- Occupational Employment and Wage Statistics, May 2025 (national and metropolitan areas), U.S. Bureau of Labor Statistics