78
/100

SOC 51-4061

Model Makers, Metal and Plastic

High RiskFrey/Osborne: 93.0%

Risk Score

โš ๏ธ

78/100

High Risk

US Employment

๐Ÿ‘ฅ

3,230

Total workers

Median Wage

๐Ÿ’ฐ

$63K

$38K โ€“ $96K

Projected Growth

๐Ÿ“ˆ

-18.2%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

48/100

Moderate exposure

How we calculate these numbers โ†’

๐Ÿ’ก Model Makers, Metal and Plastic face a risk score of 78/100 โ€” 34 points above the national average of 44. With only 48/100 GenAI exposure, most core tasks remain resistant to current AI capabilities. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $63K ($16K 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 78/100, Model Makers, Metal and Plastic faces significant automation pressure. Key threats include smart factory scheduling and production optimization and cobots handling repetitive material handling tasks. The 3,230 Americans in this role should actively develop skills in setup and calibration of custom production runs and troubleshooting complex equipment malfunctions to remain competitive. Workers who proactively adapt will find new opportunities even as traditional tasks are automated.

Will AI Replace Model Makers, Metal and Plastic?

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

โš ๏ธ Top Risk Factors

1

Smart factory scheduling and production optimization

2

Cobots handling repetitive material handling tasks

3

Industrial robotics replacing manual assembly tasks

4

Predictive maintenance reducing manual inspection roles

5

AI quality inspection via computer vision systems

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Setup and calibration of custom production runs

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

Study blueprints, drawings, and sketches to determine material dimensions, required equipment, and operations sequences.

โ€ข

Inspect and test products to verify conformance to specifications, using precision measuring instruments or circuit testers.

โ€ข

Drill, countersink, and ream holes in parts and assemblies for bolts, screws, and other fasteners, using power tools.

โ€ข

Cut, shape, and form metal parts, using lathes, power saws, snips, power brakes and shears, files, and mallets.

โ€ข

Set up and operate machines, such as lathes, drill presses, punch presses, or bandsaws, to fabricate prototypes or models.

๐Ÿ’ป Technology Skills

โ€ข

Computer aided manufacturing CAM software

โ€ข

Spreadsheet software

โ€ข

Office suite software

โ€ข

Word processing software

โ€ข

Computer aided design CAD software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Design

โ€ข

Mathematics

โ€ข

Engineering and Technology

โ€ข

Mechanical

โ€ข

Production and Processing

๐Ÿ“Š vs National Average

Median Wage$63K
+$16K

National avg: $46K

Risk Score78/100
+34

National avg: 44/100

GenAI Exposure48/100
+10

National avg: 38/100

Projected Growth-18.2%
-21.9%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
Engineers20$106K61%
Fabric and Apparel Patternmakers33$68K75%
Supervisors of Production Workers34$71K73%