Somewhat Resilient

Last Update: 8/30/2026

AI Resilience Score for Machine Setters & Tenders:

39.3%

Median Score

Meaningful human contribution

Med

Long-term employer demand

Med

Sustained economic opportunity

Low

Our confidence in this score:
Medium

Contributing sources

Methodology and Scoring Rationale

To score how resilient cutting, punching, and press machine work 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 cutting, punching, and press machine setters and tenders, six of eight sources had data. The AI exposure picture was split: AI Resilience Model and Microsoft saw strong human involvement, while Will Robots Take My Job flagged higher risk, keeping confidence at medium. Weak pay and mobility signals pulled the economic score down, landing this role at "Somewhat Resilient."

AI Resilience Report forCutting, Punching, and Press Machine Setters, Operators, and Tenders, Metal and Plastic

$46,330 median salary13,200 annual openingsSOC Code: 51-4031.00

Cutting, Punching, and Press Machine Setters, Operators, and Tenders, Metal and Plastic 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 the day-to-day work, not just hovering on the horizon. Smart machines are already handling tasks like adjusting settings, monitoring quality, and predicting maintenance needs, which means the repetitive, routine parts of the job are shifting toward automation.

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This role is somewhat resilient

This career sits in the "Somewhat Resilient" category because AI is genuinely changing the day-to-day work, not just hovering on the horizon. Smart machines are already handling tasks like adjusting settings, monitoring quality, and predicting maintenance needs, which means the repetitive, routine parts of the job are shifting toward automation.

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Analysis of Current AI Resilience

Machine Setters & Tenders

Updated Quarterly

Analysis
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State of Automation

How is AI changing Machine Setters & Tenders jobs?

If you're worried about robots taking over the press machine, here's the honest news: AI is starting to change this field, but mostly it's making machines smarter, not making operators disappear. At the huge Automate 2026 show, robot makers demonstrated cobots that can be "trained" by simply pointing a camera at a part or typing "metal ring" in plain English — Standard Bots' AI features let users train a robot to recognize objects by clicking on them in the camera's live feed, and Text Find lets users type a natural language description of a part for the robot to find, thanks to foundation models pretrained on billions of images [1]. In plastics processing, the trade association explains that AI can help adjust machine settings to minimize downtime, and predictive algorithms can forecast when a machine part needs replacement [2].

On the metal side, forecasters expect robotic stamping systems and AI-driven quality control to reduce cycle times by up to 30% and minimize defects, with IoT-enabled presses enabling real-time monitoring and predictive maintenance [3]. Most of this is augmentation — AI reads work orders, sets speeds, and watches the cut, while humans still load material, verify tolerances, troubleshoot, and clean up.

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AI Adoption

How fast is AI adoption growing for Machine Setters & Tenders?

Adoption is moving fast in big shops but slowly in small ones. Deloitte reports that nearly one-quarter (22%) of manufacturers plan to use physical AI in just two years — a more than twofold increase from today (9%) [4], and a 2026 survey found that the overwhelming majority of manufacturers are either using AI today or plan to use it within the next two years [5]. What's driving it?

A serious worker shortage — the Plastics Industry Association notes AI is being used to address challenges like talent shortages, rising operational costs, and the need for greater efficiency [2], and Metal Stamping Atlas warns that 25% of the workforce is nearing retirement [3]. What's slowing it? Cost and complexity.

The same source estimates high initial investments in automation of USD 1-5 million per line remain a barrier for SMEs [3], and Modern Machine Shop points out that just 6% of American manufacturers have a robot [1] because they've been "too hard to use and not capable enough." The good news for you: the BLS still projects production occupations to account for nearly 550,000 openings each year, on average, over the 2024–2034 decade [6]. Human judgment, hands-on setup, and problem-solving skills — the parts of the job hardest to automate — will keep this a real career for people who stay curious and keep learning.

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Will AI replace Machine Setters & Tenders?

Will AI replace Machine Setters & Tenders?

Not entirely. We think AI will take over some tasks, but not the whole job.

Our 39.3% AI Resilience Score tells the honest story here: this career faces real pressure, but it is not going away. AI is already making machines smarter in meaningful ways. Cobots can now be trained to recognize parts from a camera feed using plain-language descriptions, and predictive algorithms can forecast when a machine component needs replacement (mmsonline.com, plasticsindustry.org). AI handles the watching and adjusting. Humans still handle the setup, the judgment calls, and the troubleshooting when something goes wrong.

Adoption is accelerating, especially in larger shops. Nearly a quarter of manufacturers plan to use physical AI within two years [4], and robotic stamping systems are expected to reduce cycle times and minimize defects [3]. But high upfront costs of 1 to 5 million dollars per line remain a real barrier for smaller employers, and only 6% of American manufacturers currently have a robot [1].

The economic picture is tighter than the day-to-day job picture. Wage growth and career flexibility scores are low, so staying adaptable matters more than ever. The workers who will do best here are the ones who learn to work alongside the new tools, not against them.

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Latest AI news for Machine Setters & Tenders

These articles provide valuable insights for students interested in cutting, punching, and press machine careers. The Indiana Career Connect listing highlights job opportunities in Mount Summit, IN, emphasizing the demand in this field. Meanwhile, the AI-exposure score of 46/100 indicates moderate risk of automation. Understanding these dynamics can help students prepare for a resilient career by focusing on skills that machines can't easily replicate, such as problem-solving and machine maintenance. Staying informed about industry trends will be crucial in adapting to technological advancements.

More Career Info

Career: Cutting, Punching, and Press Machine Setters, Operators, and Tenders, Metal and Plastic

They shape and cut metal and plastic parts using machines, making sure everything is the right size and shape for building products.

Employment & Wage Data

Median Wage

$46,330

Jobs (2025)

171,000

Growth (2025-35)

-10.5%

Annual Openings

13,200

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

78% ResilienceSupplemental

Hone cutters with oilstones to remove nicks.

2

75% ResilienceSupplemental

Remove housings, feed tubes, tool holders, or other accessories to replace worn or broken parts, such as springs or bushings.

3

73% ResilienceSupplemental

Select, clean, and install spacers, rubber sleeves, or cutters on arbors.

4

72% ResilienceSupplemental

Replace defective blades or wheels, using hand tools.

5

72% ResilienceSupplemental

Sharpen dulled blades, using bench grinders, abrasive wheels, or lathes.

6

70% ResilienceSupplemental

Install, align, and lock specified punches, dies, cutting blades, or other fixtures in rams or beds of machines, using gauges, templates, feelers, shims, and hand tools.

7

70% ResilienceSupplemental

Set blade tensions, heights, and angles to perform prescribed cuts, using wrenches.

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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