Model makers, metal and plastic
SOC Code: 51-4061
Model makers, metal and plastic carries a 42% AI exposure score (High automation risk), with a median annual wage of $62,700 and -18.2% projected employment growth from 2024 to 2034 (BLS), affecting approximately 3,200 workers. Full task breakdown, skills, and employer data are below.
Proportion of tasks susceptible to AI automation (O*NET analysis)
At 42% AI exposure, Model makers, metal and plastic sits 5 points above the 37.2% average across 832 U.S. occupations - more exposed than 75% of them. Most of its core tasks still require human judgment.
Career outlook score
28/100
Model makers, metal and plastic, weighted across 3 of 3 tracked dimensions
A weighted composite of median wage, projected growth, and AI-automation security (inverted exposure), each benchmarked against every other tracked occupation. It describes this occupation's standing across those three dimensions, not a guarantee of future outcomes.
- Median wage C $62,700
Annual median wage, percentile rank vs all tracked occupations
- Projected growth F -18.2%
Projected employment change, 2024-2034, BLS Employment Projections
- AI exposure (inverted) F 42% exposure
Lower O*NET task-automability scores lower risk; this dimension scores security, not exposure
Home health and personal care aides is #1 of 832 occupations by employment (4.3M, AI exposure rank #392 at 35%) vs. Bookkeeping, accounting, and auditing clerks #1 by AI task exposure (95%, employment rank #17 at 1.6M).
Automation-risk inventory
Exclusive cut of 832 occupations by PlainWorkforce automation-risk band. Orthogonal to the continuous AI-exposure distribution chart below and to this occupation's single risk badge, this is the corpus band mix, with Model makers, metal and plastic in the High band.
Credential × growth standing
Open entry on a declining BLS line
Typical entry is HS / some college (333/832) while growth is Declining (111/832). This is the crowded high-risk corner of the map - automation and headcount pressure compound without a degree moat.
Where Model makers, metal and plastic sits among all occupations
AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.
Where Model makers, metal and plastic sits by AI exposure
AI-exposure score distribution across U.S. occupations (O*NET task analysis)
42% Around the middle lower than 25% of 832 occupations
Occupations, banded by AI-exposure score
Each bar is a band; taller bars hold more occupations. The dashed line + filled bar mark this entry. Hover or tap any bar for its full count and share, and where it sits relative to this entry.
Source O*NET task data (U.S. Department of Labor) · BLS 2024–2034
Source: O*NET task data (U.S. Department of Labor); AI-exposure scores are PlainWorkforce's analysis. As of BLS 2024–2034.
Model makers, metal and plastic vs. its occupational neighbors
AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Model makers, metal and plastic is marked in rose; the top-left corner is the most future-proof.
Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).
Employment Projections
Where This Score Comes From
Model makers, metal and plastic's High automation-risk tier is computed from O*NET Database 30.0 task-level analysis, where each documented task the occupation performs is evaluated against current generative AI, robotic process automation, and machine-learning capabilities. A score in the 40–70% range indicates meaningful automation pressure on specific task categories, but the role as a whole still requires human judgment for coordination, exception handling, or client interaction.
The employment, wage, and education figures above come from a second, separate federal source: BLS Employment Projections 2024–2034, matched to the O*NET task data by Standard Occupational Classification (SOC 51-4061) code, with the wage figure cross-validated against the BLS Occupational Employment and Wage Statistics (OEWS) May 2024 survey. BLS figures are presented exactly as published, with no adjustment on our part; the SOC-code match is what lets Model makers, metal and plastic be compared directly against every other tracked occupation on the same basis, not just roles that happen to share a job title.
For career planners, this profile should be read alongside the task, skill, and knowledge breakdowns below and the list of employers whose workforce composition includes Model makers, metal and plastic. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure.
Education & Entry Requirements
Top Tasks (O*NET)
- 1. Study blueprints, drawings, and sketches to determine material dimensions, required equipment, and operations sequences.
- 2. Set up and operate machines, such as lathes, drill presses, punch presses, or bandsaws, to fabricate prototypes or models.
- 3. Program computer numerical control (CNC) machines to fabricate model parts.
- 4. Inspect and test products to verify conformance to specifications, using precision measuring instruments or circuit testers.
- 5. Cut, shape, and form metal parts, using lathes, power saws, snips, power brakes and shears, files, and mallets.
- 6. Rework or alter component model or parts as required to ensure that products meet standards.
- 7. Drill, countersink, and ream holes in parts and assemblies for bolts, screws, and other fasteners, using power tools.
- 8. Grind, file, and sand parts to finished dimensions.
- 9. Devise and construct tools, dies, molds, jigs, and fixtures, or modify existing tools and equipment.
- 10. Record specifications, production operations, and final dimensions of models for use in establishing operating standards and procedures.
Key Skills Required
- Operation and Control
- Operations Monitoring
- Critical Thinking
- Quality Control Analysis
- Monitoring
- Equipment Selection
- Troubleshooting
- Judgment and Decision Making
- Time Management
- Reading Comprehension
Knowledge Areas
- Mechanical
- Mathematics
- Production and Processing
- Design
- Engineering and Technology
- Computers and Electronics
- Sales and Marketing
- Customer and Personal Service
- English Language
- Education and Training
Frequently Asked Questions
Will AI replace Model makers, metal and plastic?
Model makers, metal and plastic has an AI exposure score of 42%, indicating a high level of automation risk. Some tasks in this role can be augmented or partially automated by AI, but core responsibilities require human judgment.
What is the job outlook for Model makers, metal and plastic?
According to BLS Employment Projections 2024-2034, Model makers, metal and plastic is projected to decline by 18.2% over the decade. Current employment stands at approximately 3,200 workers.
What skills are needed for Model makers, metal and plastic?
Key skills for Model makers, metal and plastic include Operation and Control, Operations Monitoring, Critical Thinking, and others. Typical entry-level education is High school diploma or equivalent.
How much do Model makers, metal and plastic earn?
The median annual wage for Model makers, metal and plastic is $62,700, according to BLS Occupational Employment and Wage Statistics (May 2024). Actual earnings vary by location, experience, industry, and employer. The BLS publishes detailed wage percentiles by region in its Occupational Employment and Wage Statistics program.
What education is required for Model makers, metal and plastic?
The typical entry-level education for Model makers, metal and plastic is High school diploma or equivalent. Employers generally expect None of related work experience. On-the-job training typically involves Moderate-term on-the-job training. Requirements can vary by employer and specialization.
Which companies employ Model makers, metal and plastic?
Model makers, metal and plastic roles exist across many industries and employers. Workforce composition is estimated from BLS industry-occupation employment distributions matched to SEC-registered public companies.
AI Exposure Rating
High automation risk based on 10 analyzed tasks. A moderate share of tasks may be augmented by AI tools.
Nationwide occupations with similar workforce profiles
Two data-derived peer sets for Model makers, metal and plastic: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).
Similar AI exposure score
Nearest O*NET task-automability scores nationwide (42% here).
- Career/technical education teachers, postsecondary · AI exposure 42%
- Dispatchers, except police, fire, and ambulance · AI exposure 42%
- Flight attendants · AI exposure 42%
- Hairdressers, hairstylists, and cosmetologists · AI exposure 42%
Similar projected growth (2024–2034)
Nearest BLS employment change rates nationwide (-18.2% here).
- Order clerks · growth -17.2%
- Payroll and timekeeping clerks · growth -16.7%
- Structural metal fabricators and fitters · growth -16.3%
- Print binding and finishing workers · growth -16.1%
Peers are nearest-neighbor matches on published BLS + O*NET metrics among occupations with ≥10,000 workers in 2024; corpus ranks above sort the full tracked set.
Related Occupations
Showing 6 of 19 occupations with a comparable automation-risk profile.
What to do with this
Use Model makers, metal and plastic's numbers above to compare, not just read in isolation.
- Compare Model makers, metal and plastic side by side against another occupation on wage, growth, and AI exposure. Workforce comparison tool
- Understand how the AI exposure score above is actually calculated before treating it as a verdict. Reading AI exposure scores
- See the full ranked list of occupations with the lowest automation exposure nationwide. Safest occupations from AI
AI exposure scores estimate task automatability from O*NET data; they are not a certainty of job loss, and BLS growth projections are estimates, not guarantees.
Data sources: Bureau of Labor Statistics Employment Projections 2024–2034 and O*NET Database 30.0. Employment figures are rounded. Wage data from BLS Occupational Employment Statistics (OES).