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The AI Resilience Report helps you understand how AI is likely to impact your current or future career. Drawing on data from over 1,500 occupations, it provides a clear snapshot to support informed career decisions.
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Vulnerable
Last Update: 5/19/2026
Your role’s AI Resilience Score is
19.6%
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Med
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Low
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
Low
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
There are a reasonable number of sources for this result, but there is some disagreement between them.
Contributing sources
AI Resilience Report forPatternmakers, Metal and Plastic
Patternmakers, Metal and Plastic are much less resilient to AI impacts than most occupations, according to our analysis of 5 sources.
Patternmaking is labeled "Vulnerable" because some of its most time-intensive core tasks — like CNC programming and design optimization — are being taken over or dramatically sped up by AI tools, which means fewer hours of human work are needed to get the same job done. On top of that, the Bureau of Labor Statistics projects a 7% decline in employment for metal and plastic machine workers through 2034, and economic pressure is pushing shops to adopt these AI tools faster than ever.
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Patternmaking is labeled "Vulnerable" because some of its most time-intensive core tasks — like CNC programming and design optimization — are being taken over or dramatically sped up by AI tools, which means fewer hours of human work are needed to get the same job done. On top of that, the Bureau of Labor Statistics projects a 7% decline in employment for metal and plastic machine workers through 2034, and economic pressure is pushing shops to adopt these AI tools faster than ever.
Read full analysisAnalysis of Current AI Resilience
Metal/Plastic Patternmaker
Updated Quarterly • Last Update: 5/14/2026
How is AI changing Metal/Plastic Patternmaker jobs?
If you're worried about robots taking over patternmaking, here's the honest picture: AI is showing up in your future shop, but it's mostly working alongside humans rather than replacing them. The biggest changes are happening in CNC programming — one of the core tasks for patternmakers. Modern Machine Shop reports that AI-powered CAM tools like CloudNC's "CAM Assist" use generative algorithms to automate toolpath strategy selection, while Lambda Function's software fine-tunes cutting parameters in real time using live machine data [1].
According to coverage of IMTS 2026, these AI-driven CNC tools can cut programming time "from days to hours" while improving tool life and shop efficiency [2]. Design work is also being augmented: AI software from companies like Vixiv now helps engineers find optimal lightweight part designs in minutes, cutting a sample part's weight by 68% while speeding up manufacturing [3]. However, hands-on tasks — assembling pattern sections, building jigs and fixtures, and scribing layouts — are barely touched by AI because they require human dexterity and judgment.
Sources
How fast is AI adoption growing for Metal/Plastic Patternmaker?
Adoption is accelerating, but unevenly. A 2026 PwC survey of 443 industrial executives found manufacturers expect technology adoption to jump from 26% to 68% by 2030, with product design/development among the heaviest-use areas [4]. Economic pressure is real — the Bureau of Labor Statistics projects metal and plastic machine worker employment to decline 7% from 2024 to 2034, though about 87,900 openings are expected each year due to retirements and worker turnover [5].
That labor shortage is actually pushing shops to adopt AI faster. Still, adoption faces real friction: Modern Machine Shop notes that AI's "non-deterministic behavior" can feel like "jumping into the void" for shops trained on predictable CNC code [1], and the World Economic Forum's Future of Jobs Report 2025 found that skills gaps remain the biggest barrier to business transformation through 2030 [6]. The takeaway for young people: learning CAD/CAM software, additive manufacturing, and how to supervise AI tools will matter more than ever — but the human craft of building, fitting, and troubleshooting physical patterns isn't going anywhere soon.
Sources
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More Career Info
Career: Patternmakers, Metal and Plastic
They create designs and models for metal and plastic parts, which are used to guide machines in making the final products.
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Employment & Wage Data
Median Wage
$54,540
Jobs (2024)
1,600
Growth (2024-34)
-24.4%
Annual Openings
100
Education
High school diploma or equivalent
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Paint or lacquer patterns.
2
Construct platforms, fixtures, and jigs for holding and placing patterns.
3
Lay out and draw or scribe patterns onto material, using compasses, protractors, rulers, scribes, or other instruments.
4
Assemble pattern sections, using hand tools, bolts, screws, rivets, glue, or welding equipment.
5
Repair and rework templates and patterns.
6
Set up and operate machine tools, such as milling machines, lathes, drill presses, and grinders, to machine castings or patterns.
7
Clean and finish patterns or templates, using emery cloths, files, scrapers, and power grinders.
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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