Cutting, Punching, and Press Machine Setters, Operators, and Tenders, Metal and Plastic
Cutting, Punching, and Press Machine Setters, Operators, and Tenders, Metal and Plastic — AI exposure, safer roles, and a pivot plan.
Also known as: Adjuster · Bander Operator · Angle Shear Operator · Arbor Press Operator · Automatic Screwmaker · Bench Shear Operator
This score estimates how exposed the tasks in a role are to current and near-term AI capabilities. It does not predict whether a specific person will lose a job.
Most exposed tasks
Highest structured exposure values in this role’s task mix — the work AI systems can already do most of.
No strongly automatable task in the current data release.
Augmentable tasks
Work where AI assists rather than replaces — the productivity frontier of this role.
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Start machines, monitor their operations, and record operational data.58
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Examine completed workpieces for defects, such as chipped edges or marred surfaces and sort defective pieces according to types of flaws.57
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Read work orders or production schedules to determine specifications, such as materials to be used, locations of cutting lines, or dimensions and tolerances.56
Most durable tasks
Lowest exposure — typically judgment, relationships, physical presence, or accountability. This is the human moat.
The current data release does not distinguish durable tasks for this role.
Task exposure values and classifications come from the versioned data release — they are structured data, not model output. Bars show exposure contribution relative to this role’s task mix.
What this means
A score of 47 puts Cutting, Punching, and Press Machine Setters, Operators, and Tenders, Metal and Plastic in the second quartile of analyzed occupations. In practice, exposure this level is about the mix: 0 of 20 analyzed tasks lean automatable, 20 augmentable, and 0 durable. The useful question isn’t “will AI take this job” — it’s which tasks go first, which get faster, and where to reposition time. That’s what the personalized report maps against your actual week.
One next move: adopt AI deliberately on the augmentable tasks and build visible evidence of the durable ones.
Lower-exposure adjacent roles
No adjacent role in the current data release is at least 10 points lower with ≥50% skill overlap — we don’t label anything “safer” unless the data supports it.
Labor-market context
- $46,330median wage
- 171,200employed
- 14,400annual openings
- -12.1%projected growth
Context only — labor statistics are not inputs to the exposure score. See methodology.
Your week probably doesn’t match the average
This page scores the occupation. The $9 Personalized Risk & Action Report scores your task mix — paste what you actually do and get your own score, confidence level, task matrix, human moat, and a 7/30/90-day plan.
Personalize my result — $9Related roles
Adjacent by skills or family — no exposure claim implied.
FAQ — Cutting, Punching, and Press Machine Setters, Operators, and Tenders, Metal and Plastic
- What does a score of 47 mean for a Cutting, Punching, and Press Machine Setters, Operators, and Tenders, Metal and Plastic?
- It means that, weighted across the 20 tasks we analyzed for this role, the task mix sits at 47 on a 0–100 exposure scale — in the second quartile of analyzed occupations. It measures task exposure to current and near-term AI capabilities, not the probability of losing a job.
- Which tasks in this role are most exposed to AI?
- This role has no strongly automatable task in the current data release.
- Which parts of this job are most durable?
- The current data release does not distinguish durable tasks for this role.
- Is this score personalized to me?
- No — this page shows the occupation-level baseline. Two people with the same title often do different work. The $9 personalized report recalculates the score from the tasks you actually do and builds a concrete 7/30/90-day plan around them.
Score version jr-v1 · data release 2026.07.11-r1 · updated 2026-07-11 · baseline mapping: 20 of 20 tasks carry source-level provenance · methodology