Not Very Resilient
Last Update: 8/30/2026
AI Resilience Score for Rolling Machine Operator:
33.8%
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 forRolling Machine Setters, Operators, and Tenders, Metal and Plastic
$50,140 median salary•1,900 annual openings•SOC Code: 51-4023.00
Rolling Machine Setters, Operators, and Tenders, Metal and Plastic are less resilient to AI impacts than most occupations, according to our analysis of 6 sources.
This career is labeled "Not Very Resilient" because a significant chunk of the work, especially inspecting, measuring, and controlling rolling processes, is already being handled by AI and machine learning systems in real time. On top of that, the Bureau of Labor Statistics projects a 7% drop in jobs from 2025 to 2035, and robotic systems are expected to cut repetitive labor by around 40% across North American steel mills in just the next couple of years.
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This career is labeled "Not Very Resilient" because a significant chunk of the work, especially inspecting, measuring, and controlling rolling processes, is already being handled by AI and machine learning systems in real time. On top of that, the Bureau of Labor Statistics projects a 7% drop in jobs from 2025 to 2035, and robotic systems are expected to cut repetitive labor by around 40% across North American steel mills in just the next couple of years.
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View analysisChat with CoachLatest newsMore career infoAnalysisChatNewsMoreAnalysis of Current AI Resilience
Rolling Machine Operator
Updated Quarterly
How is AI changing Rolling Machine Operator jobs?
If you're worried about robots taking over rolling mills, here's a balanced picture: AI is definitely showing up in this field, but mostly as a helper rather than a total replacement. A 2026 review in Frontiers in Materials describes how machine learning is being used in hot rolling to predict and control crown, thickness, and width in real time [1], which handles the "inspect and measure" side of the job. In plastics, Conair recently showed off AI control technology that collects data, adapts in real time, and eliminates manual intervention for tasks like balancing conveying systems that used to take two workers [2].
The Society of Plastics Engineers is even training engineers on machine learning models for defect prediction in polymer extrusion [3]. Meanwhile, industry analysts project 5,000–8,000 robotic systems being deployed across North American steel mills in 2026–2027, cutting repetitive labor by about 40% while creating new jobs in AI engineering and process specialization [4]. Physical setup tasks — aligning arbors, threading coils, hand-tool installation — still need humans.
Sources
How fast is AI adoption growing for Rolling Machine Operator?
Adoption is speeding up but unevenly. The Bureau of Labor Statistics expects employment of metal and plastic machine workers to decline 7% from 2025 to 2035 as new facilities incorporate more automation and CNC tools [5], so the pressure is real. A Deloitte survey cited by Manufacturing Dive found about 58% of business leaders already use physical AI in operations, growing to 80% over the next two years [6], driven by labor shortages and competition.
But rollout is slowed by high capital costs, safety rules, and the fact that demos working 70% of the time aren't good enough — manufacturing needs 99%+ reliability [6]. The good news: skilled operators who learn to read data dashboards, troubleshoot AI-guided lines, and train coworkers will be more valuable, not less. Your hands-on judgment and mechanical intuition are exactly the skills these smart systems still can't copy.
Sources
Will AI replace Rolling Machine Operator?
In part. We think AI will eventually automate a real share of this work, but the full picture is more complicated than a simple takeover story.
Our 33.8% AI Resilience Score reflects genuine pressure on this role. The BLS projects employment of metal and plastic machine workers to decline 7% from 2025 to 2035 [5], and automation is accelerating: AI systems are already handling real-time thickness and crown control in hot rolling [1], and newer AI control technology in plastics can eliminate manual intervention for tasks that once required two workers [2]. That is real displacement, not hype.
Still, physical setup work, aligning components, threading coils, hands-on troubleshooting, stays human for now. The bigger point is what this means for your career journey. Operators who learn to read data dashboards and work alongside AI-guided lines will be more valuable than those who do not. The skills underneath this job, mechanical intuition, process problem-solving, quality judgment, transfer well into roles like CNC operation, process technician work, or AI system oversight in manufacturing. About 58% of business leaders already use physical AI in operations, with that figure expected to grow to 80% soon [6]. Getting ahead of that curve is the move.
Sources
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Latest AI news for Rolling Machine Operator
The recommended articles highlight the significant risk of AI replacing roles in the "Rolling Machine Setters, Operators, and Tenders, Metal and Plastic" field, with a high risk score of 87/100 noted in one article. However, understanding the specific tasks likely to be automated can help students build resilience in their careers. For example, the articles discuss how repetitive tasks may be automated first, suggesting that developing skills in troubleshooting and advanced machine operation can help future-proof their roles in an evolving industry. Embracing continuous learning will be key to thriving amidst these changes.
AI Impact on Metal & Plastic Workers: 74/100 Risk
www.aijobchecker.com • 8/20/2026
Metal Workers & Plastic Workers score 74/100 for AI replacement risk. See which tasks face automation first and how to future-proof your manufacturing c...
AI Job Risk in Production: All 100 Occupations Ranked
jobriskai.com • 8/20/2026
AI job risk in Production ; 23, Forging Machine Setters, Operators, and Tenders, Metal and Plastic, Low, 0.115, 39 ; 24, Miscellaneous Assemblers and Fabricators ... Read more
Will AI Replace Rolling Machine Setters, Operators, and ...
www.replacedbai.com • 8/20/2026
No, Rolling Machine Setters, Operators, and Tenders, Metal and Plastic roles face significant AI replacement risk. With a risk score of 87/100, this occupation ... Read more
Toward understanding the impact of artificial intelligence on ...
pmc.ncbi.nlm.nih.gov • 8/20/2026
by MR Frank · 2019 · Cited by 780 — Rapid advances in artificial intelligence (AI) and automation technologies have the potential to significantly disrupt labor markets.
The Impact of Job Exposure to Artificial Intelligence on ...
www.econometricsociety.org • 8/20/2026
by Y Lee · 2025 — This study suggests that technological progress through AI will impact the Korean labor market in a different way than previous technological. Read more
More Career Info
Career: Rolling Machine Setters, Operators, and Tenders, Metal and Plastic
They shape metal and plastic by setting up and operating machines, ensuring the materials are rolled into the correct thickness and size.
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Employment & Wage Data
Median Wage
$50,140
Jobs (2025)
25,300
Growth (2025-35)
-8.3%
Annual Openings
1,900
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
Direct and train other workers to change rolls, operate mill equipment, remove coils and cobbles, and band and load material.
2
Disassemble sizing mills removed from rolling lines, and sort and store parts.
3
Install equipment such as guides, guards, gears, cooling equipment, and rolls, using hand tools.
4
Position, align, and secure arbors, spindles, coils, mandrels, dies, and slitting knives.
5
Signal and assist other workers to remove and position equipment, fill hoppers, and feed materials into machines.
6
Adjust and correct machine set-ups to reduce thicknesses, reshape products, and eliminate product defects.
7
Remove scratches and polish roll surfaces, using polishing stones and electric buffers.
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.
