Will AI replace Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders?
AI reaches little of this job’s work.
8/100
Low exposure
More exposed to AI than 18% of US workers.
- AI already used in
- 5% of the work
- As AI tools mature: up to
- 16% of the work
What the job involves
Set up, operate, or tend machines to crush, grind, or polish materials, such as coal, glass, grain, stone, food, or rubber.
Where AI reaches the work
The job’s main tasks, heaviest first, by how far AI reaches them.
Already happening(1)
- Record data from operations, testing, and production on specified forms.
Within reach(2)
- Notify supervisors of needed repairs.
- Read work orders to determine production specifications and information.
Out of reach(18)
- Observe operation of equipment to ensure continuity of flow, safety, and efficient operation, and to detect malfunctions.
- Tend accessory equipment, such as pumps and conveyors, to move materials or ingredients through production processes.
- Clean work areas.
- Weigh or measure materials, ingredients, or products at specified intervals to ensure conformance to requirements.
- Move controls to start, stop, or adjust machinery and equipment that crushes, grinds, polishes, or blends materials.
and 13 more
Also called
Miller · Grinder · Grinder Operator · Polisher · Pulverizer · Crusher Operator · Mill Operator · Mold Polisher
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