Will AI replace Textile Cutting Machine Setters, Operators, and Tenders?
AI reaches little of this job’s work.
14/100
Low exposure
More exposed to AI than 25% of US workers.
- AI already used in
- 4% of the work
- As AI tools mature: up to
- 28% of the work
What the job involves
Set up, operate, or tend machines that cut textiles.
Where AI reaches the work
The job’s main tasks, heaviest first, by how far AI reaches them.
Already happening(1)
- Program electronic equipment.
Within reach(4)
- Notify supervisors of mechanical malfunctions.
- Confer with coworkers to obtain information about orders, processes, or problems.
- Record information about work completed and machine settings.
- Study guides, samples, charts, and specification sheets or confer with supervisors or engineering staff to determine set-up requirements.
Out of reach(13)
- Inspect products to ensure that the quality standards and specifications are met.
- Start machines, monitor operations, and make adjustments as needed.
- Repair or replace worn or defective parts or components, using hand tools.
- Place patterns on top of layers of fabric and cut fabric following patterns, using electric or manual knives, cutters, or computer numerically controlled cutting devices.
- Clean, oil, and lubricate machines, using air hoses, cleaning solutions, rags, oilcans, and grease guns.
and 8 more
Also called
Cutter · Cuff Cutter · Felt Cutter · Glove Cutter · Label Pinker · Material Cutter · Pillowcase Cutter · Rug Cutter
Related jobs
- Woodworking Machine Setters, Operators, and Tenders, Except Sawing3/100
- Cutting, Punching, and Press Machine Setters, Operators, and Tenders, Metal and Plastic2/100
- Grinding, Lapping, Polishing, and Buffing Machine Tool Setters, Operators, and Tenders, Metal and Plastic6/100
- Paper Goods Machine Setters, Operators, and Tenders3/100
- Cutting and Slicing Machine Setters, Operators, and Tenders8/100
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