Not Very Resilient

Last Update: 10/7/2026

AI Resilience Score for Patternmakers, Wood:

27.6%

Median Score

Meaningful human contribution

Med

Long-term employer demand

Low

Sustained economic opportunity

Low

Our confidence in this score:
Medium-high

Methodology and Scoring Rationale

To score how resilient wood patternmaking is to AI, we ask one question in three parts:

First, how much of the job still needs a human, read from five AI-exposure sources: our own AI Resilience Model, Anthropic's Observed Exposure, Microsoft's AI Applicability, Will Robots Take My Job, and OpenAI Signals. We call this dimension Meaningful Human Contribution (MHC) and weight it at 40%.

Next, whether employers will keep hiring for this job over the long term. This dimension, which we call Long-term Employer Demand (LTE), is calculated from BLS data and weighted at 30%.

Last, whether pay and mobility will hold up. We use wage bill and adaptive capacity data from independent researchers (Althoff & Reichardt, 2026; Manning & Aguirre, 2026). We call this dimension Sustained Economic Opportunity (SEO) and weight it at 30%.

For wood patternmakers, all eight sources had data, but AI exposure was split: Anthropic and OpenAI Signals saw hands-on craft staying human, while AI Resilience Model and Will Robots Take My Job flagged high automation risk. That disagreement holds confidence at medium-high. Weak hiring and low pay mobility pulled the score down, landing this career at "Not Very Resilient."

AI Resilience Report forPatternmakers, Wood

$49,630 median salary•100 annual openings•SOC Code: 51-7032.00

Patternmakers, Wood are less resilient to AI impacts than most occupations, according to our analysis of 8 sources.

Wood patternmaking is labeled "Not Very Resilient" mainly because the biggest threats to this career actually arrived before modern AI, with CNC machining and 3D printing already cutting employment by 87.5 percent between 2007 and 2020. Now, AI is adding another layer of pressure by handling the computer-based tasks that remain, like calculating volumes, managing records, and organizing inventory, which are exactly the kinds of work that software handles easily.

Learn more about how you can thrive in this position

This role is not very resilient

Wood patternmaking is labeled "Not Very Resilient" mainly because the biggest threats to this career actually arrived before modern AI, with CNC machining and 3D printing already cutting employment by 87.5 percent between 2007 and 2020. Now, AI is adding another layer of pressure by handling the computer-based tasks that remain, like calculating volumes, managing records, and organizing inventory, which are exactly the kinds of work that software handles easily.

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Analysis of current AI resilience

Patternmakers, Wood

Updated quarterly

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Latest AI news for Patternmakers, Wood

The recommended articles provide valuable insights for students pursuing careers as wood patternmakers. They highlight that while AI may automate certain tasks, the tactile skills of adjusting cuts and ensuring joint fits remain irreplaceable. For instance, one article notes that future patternmakers will evolve into "digital pattern and mold specialists," integrating AI with traditional techniques. As AI enhances design precision, students can prepare by embracing new technologies while honing their craftsmanship, ensuring they remain resilient in a transforming industry.

More Career Info

Career: Patternmakers, Wood

They create detailed wooden models or patterns that are used to make molds for casting metal or other materials in manufacturing.

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Employment & Wage Data

Median Wage

$49,630

Jobs (2025)

600

Growth (2025-35)

-2.0%

Annual Openings

100

Education

High school diploma or equivalent

Experience

None

Source: Bureau of Labor Statistics, Employment Projections 2025-2035

Task-Level AI Resilience Scores

AI-generated estimates of task resilience over the next 3 years

1

95% ResilienceCore Task

Glue fillets along interior angles of patterns.

2

94% ResilienceCore Task

Finish completed products or models with shellac, lacquer, wax, or paint.

3

93% ResilienceCore Task

Fit, fasten, and assemble wood parts together to form patterns, models, or sections, using glue, nails, dowels, bolts, and screws.

4

93% ResilienceCore Task

Repair broken or damaged patterns.

5

92% ResilienceCore Task

Trim, smooth, and shape surfaces, and plane, shave, file, scrape, and sand models to attain specified shapes, using hand tools.

6

90% ResilienceCore Task

Construct wooden models, templates, full scale mock-ups, jigs, or molds for shaping parts of products.

7

88% ResilienceCore Task

Set up, operate, and adjust a variety of woodworking machines such as bandsaws and lathes to cut and shape sections, parts, and patterns, according to specifications.

Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.

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