How exposed this work is to automation, shown as ranges with the reasoning and sources.
The short version: this role is moderately exposed to automation, and a near-term shift looks unlikely.
It is a sourced range, not a verdict, and the detail is below.
Built on O*NET tasks, BLS pay and projections, and peer-reviewed AI-exposure research. Sources shown.
Data snapshot SNAPSHOT-2026-11-06. How it works
AI / softwarerange 3.4 to 27.4
Physical / roboticsrange 41.4 to 65.4
When the change is likely
Largely unaffectedlocal demand growing
What to do about it
Use AI to outpace AI.
Strategies to protect your livelihood, most important first.
1
Stay sharp; urgency is low
This role looks durable. Keep your skills current and watch for shifts in your field.
2
Move up from the task to the system
Robotics targets the physical work. Shift toward supervising, maintaining, or programming the automation instead of competing with it.
3
Pivot toward Model Makers, Metal and Plastic
It is skill-adjacent and less exposed (50.2 vs 53). A lateral move now beats a forced one later.
4
Build a financial buffer
Keep 6 to 12 months of expenses and diversify your income, so a disruption is a setback rather than a catastrophe.
5
Add a recognised credential
A certification or license raises the bar against automation and signals value in a tightening market.
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Which of my tasks are exposed
Read blueprints, drawings, or written specifications, and consult with designers to determine sizes and shapes of patterns and required machine setups.
100.0
Fit, fasten, and assemble wood parts together to form patterns, models, or sections, using glue, nails, dowels, bolts, screws, and other fasteners.
53.4
Verify dimensions and contours of models during hand-forming processes, using templates and measuring devices.
53.4
Trim, smooth, and shape surfaces, and plane, shave, file, scrape, and sand models to attain specified shapes, using hand tools.
53.4
Plan, lay out, and draw outlines of units, sectional patterns, or full-scale mock-ups of products.
53.4
Construct wooden models, patterns, templates, full scale mock-ups, and molds for parts of products and production tools.
53.4
Select wooden stock, determine layouts, and mark layouts of parts on stock, using precision equipment such as scribers, squares, and protractors.
53.4
Mark identifying information on patterns, parts, and templates to indicate assembly methods and details.
53.4
Longer, orange bars are more automatable; short green bars are resistant.
What is driving my result
lowers risk
raises risk
Task: Read blueprints, drawings, or written specifications, and consult with designers to determine sizes and shapes of patterns and required machine setups.
Task: Fit, fasten, and assemble wood parts together to form patterns, models, or sections, using glue, nails, dowels, bolts, screws, and other fasteners.
Local demand is growing
Lower-risk adjacent roles
Model Makers, Metal and Plastic
50.2
A full, ranked mitigation plan is part of the paid tiers.
How this score is calculated
Map Model Makers, Wood to its standard O*NET task list (8 core tasks).
Score each task for AI/software exposure (Eloundou et al. 2023) and physical/robotics exposure (an O*NET work-context proxy), each 0 to 100.
The two axis scores are the task averages: AI 15.4, robotics 53.4.
The timeline comes from the higher axis (53.4), shifted for local demand (growing), and seniority. It is read against your remaining working years.
Ranges are about ±12 points. A backtest against real BLS employment change shows the risk ranking holds in aggregate, but individual outcomes are predicted weakly, so results are ranges, never a flat verdict.
Sources: O*NET, Eloundou et al. (2023), GPTs are GPTs, O*NET Work Context, BLS CPI-U, BLS OEWS.
Snapshot SNAPSHOT-2026-11-06. Full method and backtest on How it works.