As of August 2026,
Model Makers, Wood 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, Felten, Raj and Seamans AIOE index. BLS labor-market figures are separate context, not score inputs.
Model Makers, Wood
More exposed than 20% of the roles we track. Median pay ~US$56,550. About 100 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 Model Makers, Wood?
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.
How this role compares to similar Production roles
What this role usually involves
Construct full-size and scale wooden precision models of products. Includes wood jig builders and loft workers.
Broad guidance for this preparation level; exact requirements vary by role and employer.
Source: O*NET 29.1 exact occupation - Model Makers, Wood, SOC 51-7031.00. Context describes the role; the AI-exposure score remains a separate task-exposure estimate.
Model Makers, Wood tasks, by AI exposure
- Maintain pattern records for reference.
- Mark identifying information on patterns, parts, and templates to indicate assembly methods and details.
- Set up, operate, and adjust a variety of woodworking machines such as bandsaws and planers to cut and shape sections, parts, and patterns, according to specifications.
- Select wooden stock, determine layouts, and mark layouts of parts on stock, using precision equipment such as scribers, squares, and protractors.
- Issue patterns to designated machine operators.
No durable tasks identified for this role - its individually-assessed tasks split 64% automatable / 36% augmentable.
We analyzed all 14 Model Makers, Wood tasks - 9 automatable and 5 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
Every task scored with what to automate, augment, or protect.
Related roles with exposure deltas, salary, demand, and reachability. Lower-exposure options appear only when the data supports them.
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.
Maintain pattern records for reference.
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
Generation starts after checkout; reports are typically ready within a few minutes.