As of August 2026, Layout Workers, Metal and Plastic has an AI-exposure score of 46/100 (Moderate exposure) on the AI-Safe Careers index. This is an estimate of task exposure, not a prediction of job loss.
Score inputs for this role: This role starts from O*NET 29.1 occupational descriptors and is empirically grounded by Penn/OpenAI GPTs are GPTs study, Anthropic Economic Index (June 26, 2026), Felten, Raj and Seamans AIOE index. BLS labor-market figures are separate context, not score inputs.

AI Exposure Score for

Layout Workers, Metal and Plastic

46/100
Moderate exposure
LowModerateElevatedHighVery High

More exposed than 20% of the roles we track. Median pay ~US$63,870. About 500 projected openings a year (BLS 2024–34 - growth plus replacement).

Pay & demand figures are US medians (BLS, in USD) - your local figures will differ. Your exposure score applies broadly.

Will AI replace Layout Workers, Metal and Plastic?

No exposure score can predict whether AI will replace this role. The 46/100 score means our current model estimates moderate task exposure from the sources listed on this page. It does not predict an employer decision, headcount, or an individual outcome. The task map below shows the work assessed and where human judgment remains important.

Early-career context (study ages 22-25)

This role is in our Moderate exposure band, not our highest-exposure bands. The study's 16% finding should not be applied directly to this role.

The November 2025 revision reports a 16% relative employment decline for workers ages 22-25 in the most AI-exposed U.S. occupations, after firm-level controls, relative to workers in less-exposed fields and more experienced workers in the same occupations.

Use the task map to identify durable work and the skills worth building early.

Stanford Digital Economy Lab, Canaries in the Coal Mine - November 2025 revision

This is group-level U.S. payroll evidence, not a personal forecast. The authors do not claim that AI alone caused the change, and this context does not alter the exposure score.

Data sources, not endorsements: O*NET and curated role data; empirical AI signals where matched; BLS employment, pay, and demand as separate context.Methodology Data sources
Role snapshot

What this role usually involves

O*NET 29.1 exact occupation

Lay out reference points and dimensions on metal or plastic stock or workpieces, such as sheets, plates, tubes, structural shapes, castings, or machine parts, for further processing. Includes shipfitters.

Common titles
Layout InspectorLayout ManLayout Technician (Layout Tech)Layout WorkerDevelopment MechanicLayout Fabricator
O*NET job-zone preparation
Job Zone 2 · Job Zone 1-2: Very Little to Some Preparation Needed Usually requires a high school diploma or GED, though some occupations may not. Some occupations may need little or no previous experience; others require several months to a year of experience.

Broad guidance for this preparation level; exact requirements vary by role and employer.

Skills and knowledge
MathematicsComplex Problem SolvingCritical ThinkingJudgment and Decision MakingMonitoringReading Comprehension
Work context
Frequent contact with othersDecision latitudeConsequence of error

Source: O*NET 29.1 exact occupation - Layout Workers, Metal and Plastic, SOC 51-4192.00. Context describes the role; the AI-exposure score remains a separate task-exposure estimate.

Know someone whose job is changing? Share your score.
Post Share Score card
Every share sends them to their own free scan.

Layout Workers, Metal and Plastic tasks, by AI exposure

Automatable
  • Locate center lines and verify template positions, using measuring instruments such as gauge blocks, height gauges, and dial indicators.
  • Plan locations and sequences of cutting, drilling, bending, rolling, punching, and welding operations, using compasses, protractors, dividers, and rules.
  • Add dimensional details to blueprints or drawings made by other workers.
2 more automatable tasks locked in the report.
Augmentable
  • Mark curves, lines, holes, dimensions, and welding symbols onto workpieces, using scribes, soapstones, punches, and hand drills.
  • Lay out and fabricate metal structural parts such as plates, bulkheads, and frames.
7 more augmentable tasks locked in the report.
Durable

No durable tasks identified for this role - its individually-assessed tasks split 64% augmentable / 36% automatable.

We analyzed all 14 Layout Workers, Metal and Plastic tasks - 5 automatable and 9 augmentable. The full task map - every task with exactly what to do about each - is in your Career Report.

Your report unlocks three concrete artifacts

Full task map

Every task scored with what to automate, augment, or protect.

Adjacent path comparison

Related roles with exposure deltas, salary, demand, and reachability. Lower-exposure options appear only when the data supports them.

30/60/90 plan + PDF

A keepable roadmap plus resume and LinkedIn repositioning.

Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate - not generic advice.

Adjacent career paths

This role is already among lower-exposure work. The adjacent paths below are shown for opportunity and skill transfer, not as lower-exposure alternatives.

Structural Metal Fabricators and Fitters
80% skills overlap; Same score - similar exposure within the 5-point model resolution; Moderate band; ~US$51,330
View path
46
7 more adjacent paths with exposure deltas, salary, demand, and reachability in your Career Report.
Agent Reality Check (on-site workflow preview)

Locate center lines and verify template positions, using measuring instruments such as gauge blocks, height gauges, and dial indicators.

Check what deployed AI agents can attempt on tasks like this using dated capability evidence. You review the real task before any analysis runs.
Unlock the report to check this task

Your AI-Safe Career Report

Every task scored with what to do about it; adjacent paths with honest exposure deltas, salary, demand, and reachability; a skill-gap map; a 30/60/90-day roadmap; Agent Reality Check; plus a résumé and LinkedIn rewrite and professional PDF.
Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate.

Workers with AI skills earn a roughly 62% wage premium - adapting pays. - PwC Global AI Jobs Barometer, 2026

Personalize it: paste your résumé & LinkedIn (optional) - your rewrite is included in the report
Used only to generate your report. You can delete it anytime via delete my data.
Optional preference: adds a clearly labeled tradeoff card. It never reorders or relabels the evidence-backed adjacent roles.
14-day money-back guarantee One-time · kept forever · no subscription

Generation starts after checkout; reports are typically ready within a few minutes.

Get ahead: a rising skill on this path is Critical Thinking. Explore courses →
Some course links are affiliate links - we may earn a small commission at no extra cost to you.
Unlock my report - $29
Important: This is an estimate of AI exposure, not a prediction that your job will disappear. It is designed to help you understand how your role may change and improve your career resilience.

Scan your own job

Layout Workers, Metal and Plastic - median pay by US state (BLS OEWS, USD)

California: US$74,490New York: US$62,700Florida: US$58,170Texas: US$48,220

Median annual wage, in USD. US national: US$63,870. More states are being added.

More Production roles

First-Line Supervisors of Production and Operating Workers Aircraft Structure, Surfaces, Rigging, and Systems Assemblers Coil Winders, Tapers, and Finishers Electrical and Electronic Equipment Assemblers Electromechanical Equipment Assemblers Engine and Other Machine Assemblers