63
/100

SOC 51-4081

Multiple Machine Tool Setters, Operators, and Tenders, Metal and Plastic

High RiskFrey/Osborne: 91.0%

Risk Score

โš ๏ธ

63/100

High Risk

US Employment

๐Ÿ‘ฅ

129,850

Total workers

Median Wage

๐Ÿ’ฐ

$46K

$34K โ€“ $73K

Projected Growth

๐Ÿ“ˆ

-0.5%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

45/100

Moderate exposure

How we calculate these numbers โ†’

๐Ÿ’ก Multiple Machine Tool Setters, Operators, and Tenders, Metal and Plastic face a risk score of 63/100 โ€” 19 points above the national average of 44. With only 45/100 GenAI exposure, most core tasks remain resistant to current AI capabilities. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $46K. 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 63/100, Multiple Machine Tool Setters, Operators, and Tenders, Metal and Plastic 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 129,850 workers in this occupation should focus on strengthening skills in troubleshooting complex equipment malfunctions and quality judgment requiring tactile and visual inspection to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Multiple Machine Tool Setters, Operators, and Tenders, Metal and Plastic?

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

AI quality inspection via computer vision systems

3

Cobots handling repetitive material handling tasks

4

Automated CNC programming and machine operation

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Troubleshooting complex equipment malfunctions

โœ“

Quality judgment requiring tactile and visual inspection

โœ“

Setup and calibration of custom production runs

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

Inspect workpieces for defects, and measure workpieces to determine accuracy of machine operation, using rules, templates, or other measuring instruments.

โ€ข

Position, adjust, and secure stock material or workpieces against stops, on arbors, or in chucks, fixtures, or automatic feeding mechanisms, manually or using hoists.

โ€ข

Read blueprints or job orders to determine product specifications and tooling instructions and to plan operational sequences.

โ€ข

Select, install, and adjust alignment of drills, cutters, dies, guides, and holding devices, using templates, measuring instruments, and hand tools.

โ€ข

Observe machine operation to detect workpiece defects or machine malfunctions, adjusting machines as necessary.

๐Ÿ’ป Technology Skills

โ€ข

Computer aided design CAD software

โ€ข

Electronic mail software

โ€ข

Enterprise resource planning ERP software

โ€ข

Spreadsheet software

โ€ข

Office suite software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Production and Processing

โ€ข

Mechanical

โ€ข

Mathematics

โ€ข

English Language

โ€ข

Design

๐Ÿ“Š vs National Average

Median Wage$46K
$-250

National avg: $46K

Risk Score63/100
+19

National avg: 44/100

GenAI Exposure45/100
+7

National avg: 38/100

Projected Growth-0.5%
-4.2%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
Engineers20$106K51%
First-Line Supervisors of Transportation and Material Moving Workers, Except Aircraft Cargo Handling Supervisors25$62K61%
Fabric and Apparel Patternmakers33$68K75%