Will AI replace Cutting and Slicing Machine Setters, Operators, and Tenders?
AI reaches little of this job’s work.
8/100
Low exposure
More exposed to AI than 15% of US workers.
- AI already used in
- 5% of the work
- As AI tools mature: up to
- 15% of the work
What the job involves
Set up, operate, or tend machines that cut or slice materials, such as glass, stone, cork, rubber, tobacco, food, paper, or insulating material.
Where AI reaches the work
The job’s main tasks, heaviest first, by how far AI reaches them.
Already happening(1)
- Review work orders, blueprints, specifications, or job samples to determine components, settings, and adjustments for cutting and slicing machines.
Within reach(2)
- Type instructions on computer keyboards, push buttons to activate computer programs, or manually set cutting guides, clamps, and knives.
- Maintain production records, such as quantities, types, and dimensions of materials produced.
Out of reach(25)
- Remove defective or substandard materials from machines, and readjust machine components so that products meet standards.
- Start machines to verify setups, and make any necessary adjustments.
- Adjust machine controls to alter position, alignment, speed, or pressure.
- Press buttons, pull levers, or depress pedals to start and operate cutting and slicing machines.
- Examine, measure, and weigh materials or products to verify conformance to specifications, using measuring devices, such as rulers, micrometers, or scales.
and 20 more
Also called
Cutter Operator · Cutter · Die Cutter · Saw Operator · Paper Cutter · Sheeter Operator · Band Cutter · Book Trimmer
Related jobs
- Grinding, Lapping, Polishing, and Buffing Machine Tool Setters, Operators, and Tenders, Metal and Plastic6/100
- Textile Cutting Machine Setters, Operators, and Tenders14/100
- Woodworking Machine Setters, Operators, and Tenders, Except Sawing3/100
- Cutting, Punching, and Press Machine Setters, Operators, and Tenders, Metal and Plastic2/100
- Sawing Machine Setters, Operators, and Tenders, Wood2/100
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