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AI Automation Index
Will AI Replace Model Makers, Wood?
Task-level automation exposure for Model Makers, Wood: 14 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
22%
weighted task index
14 of 14 tasks scored
Median Salary
$56,550 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Low
280 people hold this job — size, not growth
Projected 2025–35
-3.3%
employment change
100 openings a year · BLS line item
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 22%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 55%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 8%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 7%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 12/100
Low
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
14 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 15%
2 tasks
Medium exposure (≥ 35%) 8%
1 tasks
Low exposure (below 35%) 77%
11 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Constituent Tasks
#14273 · Core · 61% automatable
Read blueprints, drawings, or written specifications, and consult with designers to determine sizes and shapes of patterns and required machine setups.
visual inspection — Blueprint setup reading partial, human confirms
Study blueprints or other instructions to determine equipment setup requirements. Exchange information with colleagues.
#14275 · Core · 5% automatable
Fit, fasten, and assemble wood parts together to form patterns, models, or sections, using glue, nails, dowels, bolts, screws, and other fasteners.
physical manipulation — Wood assembly requires hands-on fitting and fastening
Assemble wood products.
#14272 · Core · 28% automatable
Verify dimensions and contours of models during hand-forming processes, using templates and measuring devices.
physical manipulation — Hands-on dimensional measurement of workpieces
Measure dimensions of completed products or workpieces to verify conformance to specifications.
#14276 · Core · 6% automatable
Trim, smooth, and shape surfaces, and plane, shave, file, scrape, and sand models to attain specified shapes, using hand tools.
physical manipulation — Manual trimming of workpieces
Shape surfaces or edges of wood workpieces. Trim excess material from workpieces.
#14280 · Core · 8% automatable
Plan, lay out, and draw outlines of units, sectional patterns, or full-scale mock-ups of products.
physical manipulation — Drawing guide lines on materials is hands-on
Draw guide lines or markings on materials or workpieces using patterns or other references.
#14278 · Core · 5% automatable
Construct wooden models, patterns, templates, full scale mock-ups, and molds for parts of products and production tools.
physical manipulation — Mold building is hands-on craft work
Build production molds.
#14277 · Core · 40% automatable
Select wooden stock, determine layouts, and mark layouts of parts on stock, using precision equipment such as scribers, squares, and protractors.
decision support — Input material selection from specs; human approves
Measure materials to mark reference points, cutting lines, or other indicators. Select production input materials.
#14279 · Core · 12% automatable
Mark identifying information on patterns, parts, and templates to indicate assembly methods and details.
physical manipulation — Marking workpieces is hands-on physical task
Mark products, workpieces, or equipment with identifying information.
#14274 · Core · 14% automatable
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.
physical manipulation — Physical control setting for cutting
Set equipment controls to meet cutting specifications. Operate cutting equipment.
#14282 · Core · 82% automatable
Maintain pattern records for reference.
data analysis — Record production data into structured logs
Record operational or production data.
#14283 · Core · 4% automatable
Build jigs that can be used as guides for assembling oversized or special types of box shooks.
physical manipulation — Machine tool assembly is skilled manual work
Assemble machine tools, parts, or fixtures.
#14284 · Core · 20% automatable
Issue patterns to designated machine operators.
physical manipulation — Physically delivering supplies to workers
Distribute supplies to workers.
#14281 · Core · 7% automatable
Fabricate work aids such as scrapers or templates.
physical manipulation — Physical construction of templates and work aids
Construct patterns, templates, or other work aids.
#14285 · Supplemental · 10% automatable
Finish patterns or models with protective or decorative coatings such as shellac, lacquer, or wax.
physical manipulation — Applying finishes requires hands-on coating work
Apply protective or decorative finishes to workpieces or products.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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