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# Will crushing and grinding machine operators be replaced by AI?

Updated October 2026

Crushing and grinding machine operators score 26 out of 100 for AI exposure. 62% of their task time needs a person. AI can do 11% and helps with 27%.

-   **11%** AI can do it
-   **27%** AI helps
-   **62%** Needs a person

Low exposure

Lower than 69% of the 923 jobs we scored.

## Task by task

We graded 21 tasks, most exposed first. AI can do 2 of them, helps with 5 and leaves 14 to people.

| Task | AI exposure |
| --- | --- |
| Record data from operations, testing, and production on specified forms. Recording readings into forms is simple digital data entry. | 75% AI can do it |
| Read work orders to determine production specifications and information. Reading work orders and pulling specs is strong document work. | 70% AI can do it |
| Notify supervisors of needed repairs. AI can draft repair notices; supervisor still acts on them. | 55% AI helps |
| Examine materials, ingredients, or products, visually or with hands, to ensure conformance to established standards. AI vision flags visible defects; touch checks stay with people. | 40% AI helps |
| Observe operation of equipment to ensure continuity of flow, safety, and efficient operation, and to detect malfunctions. Sensors and dashboards flag faults; floor presence still needed. | 35% AI helps |

## How crushing and grinding machine operators compare

All jobs (923)

Production (107)

The dark line is **crushing and grinding machine operators, at 26**. Each dot is a score, and darker dots mean more jobs share it. The short marks are the averages, 37 for all jobs and 22 for production.

## Pay and outlook in the US

Median pay

$48,540 a year, May 2025

People employed

26,000 in the US, May 2025

Projected change in jobs

\-1.7% from 2024 to 2034

## Skills to build

-   Enter and check production readings in Microsoft Excel
-   Pull and verify work orders in SAP software
-   Clear jams and maintain equipment with hand tools
-   Inspect chains and belts for wear at the machine
-   Write repair notices in Microsoft Word and Email software

## Safer roles nearby

5 related jobs with lower scores.

-   [Grinding machine operators21 out of 100](https://www.aigentcy.com/ai-exposure/grinding-machine-operators/)
-   [Hand polishers17 out of 100](https://www.aigentcy.com/ai-exposure/hand-polishers/)
-   [Machine feeders20 out of 100](https://www.aigentcy.com/ai-exposure/machine-feeders/)
-   [Cutting machine operators22 out of 100](https://www.aigentcy.com/ai-exposure/cutting-machine-operators/)
-   [Tool grinders17 out of 100](https://www.aigentcy.com/ai-exposure/tool-grinders/)

## Questions about crushing and grinding machine operators and AI

Will AI replace crushing and grinding machine operators?

Partly. About 2 in 10 working hours go to tasks AI can already do, mostly recording operating data on forms and reading work orders for production specs. Clearing jams, cleaning, moving materials and pulling samples from process lines stay with people because they need hands on heavy machinery.

Which tasks is AI taking over for crushing and grinding machine operators?

Recording readings on forms is taking over first, with an AI exposure score of 75, since it is simple digital data entry that software can fill from sensor feeds. Reading work orders for specs, scored 70, is document work AI extracts quickly. Drafting repair notices, scored 55, is also automatable, though a supervisor still acts on them.

Which tasks stay human for crushing and grinding machine operators?

Clearing jams manually, cleaning work areas, and maintaining equipment with hand tools each score 5 on AI exposure, the lowest in this job. Physical work near heavy machinery needs a person on the floor, which is why 62% of this job's task weight stays human.

How do crushing and grinding machine operators stay valuable?

Check the Microsoft Excel and SAP production logs yourself, so you catch bad readings before the report does. Read work orders in SAP and match specs to sample results. Keep hand maintenance, jam clearing and belt inspection skills sharp, since those tasks stay with you. Write clear repair notices in Email software so supervisors act on them fast.

## Related jobs

-   [Forming press operators26 out of 100](https://www.aigentcy.com/ai-exposure/forming-press-operators/)
-   [Woodworking machine operators16 out of 100](https://www.aigentcy.com/ai-exposure/woodworking-machine-operators/)
-   [Mixing machine operators24 out of 100](https://www.aigentcy.com/ai-exposure/mixing-machine-operators/)
-   [Rolling mill operators25 out of 100](https://www.aigentcy.com/ai-exposure/rolling-mill-operators/)

## Next steps for crushing and grinding machine operators

-   ### Check your job
    
    Your job title is a rough guide. Your tasks decide your score. Paste your job description or CV to see which tasks AI can do.
    
    [Check your job](https://www.aigentcy.com/tools/ai-exposure-checker/) [Check your CV](https://www.aigentcy.com/tools/cv-checker/)
    
-   ### Estimate team savings
    
    The score is per person. Add headcount and salary to see the hours AI can take on in a team of crushing and grinding machine operators, and what they cost.
    
    [Estimate what AI saves a team of crushing and grinding machine operators](https://www.aigentcy.com/tools/team-ai-audit/?role=crushing-and-grinding-machine-operators) [Work out the return on automation](https://www.aigentcy.com/tools/ai-savings-calculator/)
    

### Check which roles in your team AI can take on

We map your team's tasks, show what AI can do today and build the automations that pay back first.

[Book an AI audit](https://www.aigentcy.com/audit/)

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-   [**How we score AI exposure**The grading, the weights and every source.](https://www.aigentcy.com/ai-exposure/methodology/)

Sources and licences

Occupation data from the O\*NET 30.3 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), used under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) and modified by Aigentcy. O\*NET® is a trademark of USDOL/ETA. Wage, employment and projection data from the U.S. Bureau of Labor Statistics. EU occupation names from ESCO, European Commission. AI usage signals from the Anthropic Economic Index (CC BY) and Microsoft Research (CC BY 4.0). [Methodology and sources](https://www.aigentcy.com/ai-exposure/methodology/). Scores © Aigentcy. Quote them with a link to the page.
