68
/100

SOC 51-9021

Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders

High RiskFrey/Osborne: 97.0%

Risk Score

โš ๏ธ

68/100

High Risk

US Employment

๐Ÿ‘ฅ

28,550

Total workers

Median Wage

๐Ÿ’ฐ

$47K

$35K โ€“ $66K

Projected Growth

๐Ÿ“ˆ

-2.5%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

53/100

Moderate exposure

How we calculate these numbers โ†’

๐Ÿ’ก Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders face a risk score of 68/100 โ€” 24 points above the national average of 44. With 53/100 GenAI exposure, this occupation faces significant pressure from AI tools despite weak projected growth. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $47K ($580 above the national median). The 3 recommended career transitions all maintain competitive wages while reducing automation exposure. Explore transition paths โ†’

๐Ÿ” AI Impact Analysis

With a risk score of 68/100, Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders faces moderate automation pressure. While tasks like industrial robotics replacing manual assembly tasks are increasingly handled by AI, the role retains significant human elements. The 28,550 workers in this occupation should focus on strengthening skills in coordinating workflow across diverse production teams and troubleshooting complex equipment malfunctions to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders?

Read our full analysis with verdict, risk factors, safe tasks, and career transition paths โ†’

โš ๏ธ Top Risk Factors

1

Industrial robotics replacing manual assembly tasks

2

Predictive maintenance reducing manual inspection roles

3

Cobots handling repetitive material handling tasks

4

Smart factory scheduling and production optimization

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Coordinating workflow across diverse production teams

โœ“

Troubleshooting complex equipment malfunctions

โœ“

Quality judgment requiring tactile and visual inspection

๐Ÿ“Š Task Automation Breakdown

Based on O*NET task analysis and GenAI exposure scoring. Shows the estimated proportion of this occupation's core tasks that are automatable by current AI, augmented by AI tools, or require essential human skills.

๐Ÿ“‹ O*NET Task Profile

โ€ข

Observe operation of equipment to ensure continuity of flow, safety, and efficient operation, and to detect malfunctions.

โ€ข

Clean, adjust, and maintain equipment, using hand tools.

โ€ข

Tend accessory equipment, such as pumps and conveyors, to move materials or ingredients through production processes.

โ€ข

Move controls to start, stop, or adjust machinery and equipment that crushes, grinds, polishes, or blends materials.

โ€ข

Notify supervisors of needed repairs.

๐Ÿ’ป Technology Skills

โ€ข

Electronic mail software

โ€ข

Spreadsheet software

โ€ข

Office suite software

โ€ข

Word processing software

โ€ข

Enterprise resource planning ERP software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Administration and Management

โ€ข

Production and Processing

โ€ข

English Language

โ€ข

Education and Training

โ€ข

Public Safety and Security

๐Ÿ“Š vs National Average

Median Wage$47K
+$580

National avg: $46K

Risk Score68/100
+24

National avg: 44/100

GenAI Exposure53/100
+15

National avg: 38/100

Projected Growth-2.5%
-6.2%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
Engineers20$106K61%
First-Line Supervisors of Transportation and Material Moving Workers, Except Aircraft Cargo Handling Supervisors25$62K51%
Fabric and Apparel Patternmakers33$68K70%