Somewhat Resilient
Last Update: 8/30/2026
AI Resilience Score for Extruding, Forming, etc.:
41.7%
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%).
Med
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.
Limited data sources are available, or existing sources show notable disagreement on the outlook for this occupation.
Contributing sources
AI Resilience Report forExtruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders
$45,760 median salary•5,200 annual openings•SOC Code: 51-9041.00
Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders are somewhat less resilient to AI impacts than most occupations, according to our analysis of 6 sources.
This career sits in the "Somewhat Resilient" category because AI is genuinely changing parts of the job, especially the routine monitoring and data-recording tasks that operators used to handle manually. Smart sensors, quality cameras, and predictive maintenance software are taking over those repetitive duties, which means the role is shifting rather than disappearing.
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More career infoAnalysisChatNewsMoreThis role is somewhat resilient
This career sits in the "Somewhat Resilient" category because AI is genuinely changing parts of the job, especially the routine monitoring and data-recording tasks that operators used to handle manually. Smart sensors, quality cameras, and predictive maintenance software are taking over those repetitive duties, which means the role is shifting rather than disappearing.
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Extruding, Forming, etc.
Updated Quarterly
How is AI changing Extruding, Forming, etc. jobs?
If you're thinking about becoming a machine setter or operator, here's the honest picture: AI is showing up on shop floors, but it's mostly working alongside people rather than replacing them. In plastics and metal-forming plants, the fastest-moving tools are AI-guided quality cameras, "smart" sensors that read gauges automatically, and predictive-maintenance software — the same tasks O*NET flags as most automatable (recording production data, monitoring gauges). A recent Plastics Industry Association article notes that smart sorting equipment guided by deep learning identifies and categorizes plastic types at high speeds, while robotic arms driven by AI separate materials, and predictive maintenance driven by machine learning reduces downtime by forecasting equipment needs.
Industry analysts at IIoT World report [1] that facilities fully using AI-driven maintenance see 30–50% less unplanned downtime — a big shift in what monitoring means for operators. But real change is slow: Plastics Today reports [2] that the industry does not have an awareness problem or an investment problem — it has an execution problem, and only 22% of firms plan to use physical AI within two years, and just 10% have scaled generative AI across their networks. Hands-on tasks — clearing jams, cleaning dies, moving materials with hoists — remain firmly human work.
Sources
How fast is AI adoption growing for Extruding, Forming, etc.?
Adoption is being pulled by a worker shortage and pushed back by cost and trust. The U.S. Bureau of Labor Statistics projects [3] that overall employment of metal and plastic machine workers will decline 7% from 2025 to 2035, yet about 78,100 openings are projected each year to replace workers who retire or move on. That labor gap is huge motivation for factories to automate routine monitoring.
Manufacturing Dive's 2026 outlook [4] also highlights heavy investment in AI, automation, and workforce development. On the other hand, Plastics Today notes [2] executives have three times more trust in advanced technology than plant workers do, so scaling AI involves building trust with the workforce and using technology to support rather than replace frontline workers. Costs, older equipment, and safety rules also slow adoption in smaller shops.
The good news for you? The World Economic Forum's June 2026 framework [5] finds that three in four industrial jobs are expected to evolve, with around 40% of future industrial skills classified as new or emerging — meaning workers who learn to supervise AI, troubleshoot, and interpret data will be more valuable, not less.
Sources
Will AI replace Extruding, Forming, etc.?
Not entirely. We think AI will take over some tasks, but not the whole job.
Our 41.7% AI Resilience Score reflects real pressure on this role. AI-guided quality cameras, smart sensors, and predictive maintenance software are already handling the most automatable parts of the work, like reading gauges and logging production data. Facilities using AI-driven maintenance report 30 to 50% less unplanned downtime [1], and that shift changes what operators spend their time on.
But hands-on work stays human. Clearing jams, cleaning dies, moving materials, and responding to unexpected problems on the floor are not things software can do. And adoption is slower than headlines suggest: only 22% of firms plan to use physical AI within two years, and just 10% have scaled generative AI across their networks [2]. Cost, older equipment, and worker trust are all real brakes on change.
The job market picture is mixed. The BLS projects a 7% employment decline through 2035, yet about 78,100 openings are expected each year just to replace workers who retire or leave [3]. The World Economic Forum finds that around 40% of future industrial skills will be new or emerging [5]. Workers who learn to supervise AI tools and interpret data will be harder to replace, not easier.
Sources
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Latest AI news for Extruding, Forming, etc.
These articles provide valuable insights for students considering careers as Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders. Notably, the first article highlights job opportunities in Sioux City, emphasizing the demand in this field. However, the second article raises concerns about the high risk of AI replacement, scoring 88/100, which suggests that students should focus on developing skills that enhance their resilience against automation. Understanding both job prospects and AI risks can help students prepare effectively for their future careers.
Will AI Replace Extruding, Forming, Pressing, and Compacting ...
www.replacedbai.com • 8/20/2026
No, Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders roles face significant AI replacement risk. With a risk score of 88/100 ...
Job Details - IowaWORKS for Veterans Portal
iowaworksforveterans.gov • 8/20/2026
Jul 22, 2026 — Occupation: Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders Location: Sioux City, IA - 51101 Job Type: ... Read more
Will AI Replace Extruding and Forming Machine Setters, Operators ...
www.aiexposure.org • 8/20/2026
Extruding and Forming Machine Setters, Operators, and Tenders, Synthetic and Glass Fibers scored 64/100 for AI automation risk. 14900 Americans hold this ...
Job Details
www.worksourcegaportal.com • 8/20/2026
May 21, 2026 — Occupation: Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders Location: Madison, GA - 30650 Job Type: ... Read more
More Career Info
Career: Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders
They operate machines that shape materials into products by pressing, forming, or compacting them, ensuring everything runs smoothly and meets quality standards.
Parent Careers
Employment & Wage Data
Median Wage
$45,760
Jobs (2025)
58,300
Growth (2025-35)
+1.5%
Annual Openings
5,200
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
Disassemble equipment to repair it or to replace parts, such as nozzles, punches, and filters.
2
Couple air and gas lines to machines to maintain plasticity of material and to regulate solidification of final products.
3
Clean dies, arbors, compression chambers, and molds, using swabs, sponges, or air hoses.
4
Install, align, and adjust neck rings, press plungers, and feeder tubes.
5
Select and install machine components, such as dies, molds, and cutters, according to specifications, using hand tools and measuring devices.
6
Measure, mix, cut, shape, soften, and join materials and ingredients, such as powder, cornmeal, or rubber to prepare them for machine processing.
7
Move materials, supplies, components, and finished products between storage and work areas, using work aids such as racks, hoists, and handtrucks.
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.
