Will AI replace Cutters and Trimmers, Hand?
AI reaches little of this job’s work.
0/100
Low exposure
More exposed to AI than 2% of US workers.
- AI already used in
- 0% of the work
- As AI tools mature: up to
- 0% of the work
What the job involves
Use hand tools or hand-held power tools to cut and trim a variety of manufactured items, such as carpet, fabric, stone, glass, or rubber.
Where AI reaches the work
The job’s main tasks, heaviest first, by how far AI reaches them.
Out of reach(18)
- Mark or discard items with defects such as spots, stains, scars, snags, chips, scratches, or unacceptable shapes or finishes.
- Cut, shape, and trim materials, such as textiles, food, glass, stone, and metal, using knives, scissors, and other hand tools, portable power tools, or bench-mounted tools.
- Mark cutting lines around patterns or templates, or follow layout points, using squares, rules, and straightedges, and chalk, pencils, or scribes.
- Trim excess material or cut threads off finished products, such as cutting loose ends of plastic off a manufactured toy for a smoother finish.
- Position templates or measure materials to locate specified points of cuts or to obtain maximum yields, using rules, scales, or patterns.
and 13 more
Also called
Offline Cutter · Bright Cutter · Carpet Cutter · Diagrammer · Fur Trimmer · Gold Cutter · Hand Coper · Hand Hose Cutter
Related jobs
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