US dataswitch to UK
Rolling Machine Setters, Operators, and Tenders, Metal and Plastic
monitoring machine cycles and mill operation to detect jamming and to ensure that products conform, reading rolling orders, calculating draft space and roll speed for each mill stand to plan rolling sequences and specified dimensions and tempers and installing equipment, guides, guards, gears, cooling equipment and rolls. If that's your week, this page is about your job.
The honest answer
AI changes the edges of this job, not the middle: adjusting and correcting machine set-ups to reduce thicknesses is work software can't reach.
What shifts is reading rolling orders, blueprints and mill schedules to determine setup specifications, work sequences, product dimensions and installation procedures: the overhead at the edges, not the middle you trained for.
Your week, as this page understands it
Set up, operate, or tend machines to roll steel or plastic forming bends, beads, knurls, rolls, or plate, or to flatten, temper, or reduce gauge of material. The job title says “rolling machine setters”, “operators”, “tenders”, “metal” or “plastic”: officially one job, several names. The real job is the part underneath: adjusting and correcting machine set-ups to reduce thicknesses. That is the thing someone has to be right about.
The exposed part of this job is specific, and we won’t pretend it is coming back. But rolling machine setters, operators, and tenders, metal and plastic is not one task. It is 19 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is adjusting and correcting machine set-ups to reduce thicknesses, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 0%
- changing shape
- 16%
- staying human
- 84%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 11 out of 100 (9–16 allowing for uncertainty): minimal exposure, across 19 scored tasks. The number is the support for the sentence above it, not a headline about anyone’s future.
How we know this
What is measured: Every published task statement for rolling machine setters, operators, and tenders, metal and plastic is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.
How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.
Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.
Your job, task by task
These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.
- 1 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
Shifting to AI
0 tasksTasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.
Nothing in this job’s scored task list landed in this group. That is the measurement, not an editorial choice, and it is worth knowing either way.
Changing shape
3 tasksTasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.
Reading rolling orders, blueprints and mill schedules to determine setup specifications, work sequences, product dimensions and installation procedures
The software now makes the first pass at orders, blueprints and mill schedules, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Read rolling orders, blueprints, and mill schedules to determine setup specifications, work sequences, product dimensions, and installation procedures.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Pulling setup details out of rolling orders, drawings and schedules is document reading software does well.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Calculating draft space and roll speed for each mill stand to plan rolling sequences and specified dimensions and tempers
The software now makes the first pass at draft space, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Calculate draft space and roll speed for each mill stand to plan rolling sequences and specified dimensions and tempers.” (O*NET task statement)
How this row was scored
Exposure score: 51 out of 100 (44–58 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; mistakes that are cheap to catch.
The rating behind it: Draft and roll-speed calculations follow known formulas, though the numbers depend on how a specific mill behaves.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Recording mill production on schedule sheets
The software now makes the first pass at mill production, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Record mill production on schedule sheets.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Writing production figures onto schedule sheets is routine record-keeping that software handles easily.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Staying human
16 tasksTasks that stay with a person, because they happen in the physical world, because the rules need someone accountable, or because the value is that a specific person does them.
Adjusting and correcting machine set-ups to reduce thicknesses
This work happens in the physical world: machine set-ups, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Adjust and correct machine set-ups to reduce thicknesses, reshape products, and eliminate product defects.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Correcting a machine setup means putting hands on the machine.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Monitoring machine cycles and mill operation to detect jamming and to ensure that products conform to specifications
This work happens in the physical world: machine cycles, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Monitor machine cycles and mill operation to detect jamming and to ensure that products conform to specifications.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (2–10 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Spotting jams and off-spec output means watching the running mill in person.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Examining, inspecting and measuring raw materials and finished products to verify conformance to specifications
This work happens in the physical world: raw materials, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Examine, inspect, and measure raw materials and finished products to verify conformance to specifications.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Inspecting and measuring metal stock and finished product is done by hand with gauges.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Manipulating controls and observing dial indicators
This work happens in the physical world: controls, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Manipulate controls and observe dial indicators to monitor, adjust, and regulate speeds of machine mechanisms.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Working the controls while watching the dials is hands-on machine operation.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Setting distance points between rolls
This work happens in the physical world: distance points, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Set distance points between rolls, guides, meters, and stops, according to specifications.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Setting distances between rolls and guides means physically adjusting them.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Positioning align and securing arbors, spindles, coils, mandrels, dies and slitting knives
This work happens in the physical world: align, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Position, align, and secure arbors, spindles, coils, mandrels, dies, and slitting knives.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Positioning and securing spindles, dies and knives is precise physical work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Directing and training other workers to change rolls
This work happens in the physical world: other workers, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Direct and train other workers to change rolls, operate mill equipment, remove coils and cobbles, and band and load material.” (O*NET task statement)
How this row was scored
Exposure score: 4 out of 100 (0–11 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Showing other workers how to change rolls and clear cobbles happens at the machine, hand over hand.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 1/4.
Show the other 9 tasks
Selecting rolls, dies, roll stands and chucks from data charts to form specified contours and to fabricate products
staying humanThis work happens in the physical world: rolls, dies, roll stands and chucks, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Select rolls, dies, roll stands, and chucks from data charts to form specified contours and to fabricate products.” (O*NET task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Choosing rolls and dies from data charts is a lookup, but the tooling still has to be fetched and fitted.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Starting operation of rolling and milling machines
staying humanThis work happens in the physical world: operation, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Start operation of rolling and milling machines to flatten, temper, form, and reduce sheet metal sections and to produce steel strips.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Starting the rolling mill is a physical operation at the machine.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Threading or feeding sheets or rods through rolling mechanisms
staying humanThis work happens in the physical world: sheets, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Thread or feed sheets or rods through rolling mechanisms, or start and control mechanisms that automatically feed steel into rollers.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Threading sheets and rods into the rollers is physical handling of hot or heavy material.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Filling oil cups, adjust valves and observing gauges to control flow of metal coolants and lubricants onto workpieces
staying humanThis work happens in the physical world: oil cups, adjust valves and observing gauges, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Fill oil cups, adjust valves, and observe gauges to control flow of metal coolants and lubricants onto workpieces.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Filling oil cups and adjusting valves means being at the machine.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Installing equipment, guides, guards, gears, cooling equipment and rolls, using hand tools
staying humanThis work happens in the physical world: equipment, guides, guards, gears, cooling equipment and rolls, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Install equipment such as guides, guards, gears, cooling equipment, and rolls, using hand tools.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Fitting guides, guards and gears with hand tools is physical installation.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Signaling and assisting other workers to remove and position equipment
staying humanThis work happens in the physical world: other workers, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Signal and assist other workers to remove and position equipment, fill hoppers, and feed materials into machines.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Signalling and helping other workers move equipment and feed material is physical teamwork on the floor.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Activating shears and grinders to trim workpieces
staying humanThis work happens in the physical world: shears, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Activate shears and grinders to trim workpieces.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Running shears and grinders on the workpiece is physical operation.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Removing scratches and polish roll surfaces
staying humanThis work happens in the physical world: scratches, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Remove scratches and polish roll surfaces, using polishing stones and electric buffers.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Polishing scratches out of roll surfaces is hands-on work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Disassembling sizing mills removed from rolling lines
staying humanThis work happens in the physical world: mills, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Disassemble sizing mills removed from rolling lines, and sort and store parts.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Stripping down a mill and sorting its parts is physical work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
What this job pays, and how many people do it
- Median pay
- $50,140a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
- People doing this job
- 25,250in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)
What is deliberately not here: a forecast of how many of these jobs exist in ten years. Where an official projection exists for a market we publish it with its vintage; where it does not, we leave the space empty rather than borrow the other country’s number.
Why this is shifting
The reason is boringly specific. Most of what is shifting here is reading one thing and writing another: orders, blueprints and mill schedules in, a record out. The rows above are exactly that shape: reading rolling orders. What it cannot do is be there in the room, and that is still where machine set-ups get done. Which is why this page talks about your tasks changing, not your job ending.
Your move
Over a pint: what I’d tell you if you were my friend
Start with what does not change: adjusting and correcting machine set-ups to reduce thicknesses is the middle of this job, and the evidence on this page says it stays with a person.
So, given all that: 0% of this job's task weight sits in rows the software is already learning, 16% in rows that change shape rather than disappear, and 84% in rows it is nowhere near. That is the position, measured across 19 scored tasks. It is not a forecast about you.
So the thing worth your attention is not the job going away. It is the layer around it. Reading rolling orders, blueprints and mill schedules to determine setup specifications, work sequences, product dimensions and installation procedures is the part turning into software, and being the person who understands that layer is worth money.
This week: one thing
Ask the one question. Find whoever is bringing new software into your workplace (the manager, the office, whoever runs the system) and ask them what it is meant to do to orders, blueprints and mill schedules, and what it is not meant to touch. Ten minutes, this week, before anyone decides it for you.
- What you end up holding
- a straight answer about what is actually being rolled out, and when
- How long it takes
- ten minutes
If there’s nobody obvious to ask, or you’d rather not ask your manager: Put the same question to your union rep, your shift lead or the person who has been there longest, in person, over a break. Same ten minutes, same answer, and you will usually get a straighter one. Write down what they say. The note is the artifact, and it tells you whether machine set-ups are in scope or not. Nothing to log into, no license needed.
Over the next 90 days
Get inside the tool rollout rather than waiting for it. Over the next ninety days, ask to be in the group that tests, checks or signs off whatever new system arrives near reading rolling orders, blueprints and mill schedules to determine setup specifications, work sequences, product dimensions and installation procedures. It is usually an unglamorous seat that nobody fights for, and it is the one that decides how the software is used on your job rather than to it.
Over the next 12 months
On this evidence I would not retrain out of this job, and I will say that plainly rather than hedge it. The task list here is dominated by work that stays with a person. What I would do with a year is get formally recognised for the layer around it (the systems, the compliance, the planning), so you are the one who understands the software instead of the one it is done to. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, and it is listed below with the rest of the free routes.
The roads out of here, and why I am not sending you down them
I looked at the obvious moves out of this job, and here is what I found.
I checked the 12 nearest US occupations to rolling machine setters, operators, and tenders, metal and plastic (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was forging machine setters, operators, and tenders, metal and plastic: only about 8% of its durable work is work you already do. And on the numbers you do not need one. This job scores 11/100 here, with only 0% of the task list in the top band, and “adjust and correct machine set-ups to reduce thicknesses, reshape products, and eliminate…” is not work that hands over cleanly. None of them beats deepening what you already have.
How that was checked: this job was compared against all 830 US occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.
3 moves I checked and rejected
These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.
Forging Machine Setters, Operators, and Tenders, Metal and Plastic
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already examine, inspect, and measure raw materials and finished products to verify conformance to…, and their equivalent is to measure and inspect machined parts to ensure conformance to product specifications. Across both published task lists that is about 8% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 8% of the durable side of that job. That is a different job, not a next step.
Grinding, Lapping, Polishing, and Buffing Machine Tool Setters, Operators, and Tenders, Metal and Plastic
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already examine, inspect, and measure raw materials and finished products to verify conformance to…, and their equivalent is to inspect or measure finished workpieces to determine conformance to specifications, using measuring instruments. Across both published task lists that is about 6% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 6% of the durable side of that job. That is a different job, not a next step.
Inspectors, Testers, Sorters, Samplers, and Weighers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already examine, inspect, and measure raw materials and finished products to verify conformance to…, and their equivalent is to inspect, test, or measure materials, products, installations, or work for conformance to specifications. Across both published task lists that is about 6% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 6% of the durable side of that job. That is a different job, not a next step.
What I’d stop worrying about
A friend tells you what not to spend fear on. This is that list.
The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 0% of its task weight, across 19 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The headlines about your trade disappearing
They are usually about the technology, not the timetable. Changes to work like adjusting and correcting machine set-ups to reduce thicknesses arrive through rules, insurance and money, slowly and visibly. This page tracks the task evidence and will move when it moves.
Retraining out of a job that is holding up
On this evidence I would not spend money leaving. Spend it on the layer around the job instead: the tools, the paperwork, the planning. That is where the change actually is.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.
You are reading the United States figures
The United Kingdom splits this work across more than one official group, of which Plastics process operatives is the closest. The pay and employment figures are not directly comparable, and we do not average them together.
Switch to the United Kingdom page →partial match
The other groups this work is counted across:
In UK official statistics this job is counted as Plastics process operatives, Metal machining setters and setter-operators, Metal working machine operatives and Metal making and treating process operatives. Pay is shown separately for each of those groups (medians cannot be averaged together), while the task list and the scores on this page are for this group only.
Your route through this
Where to go next, and what it costs
Free, and complete
The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.
Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
Free
Why there is no community here
Collab365, who build this site, run paid Spaces for a small number of subjects, and none of them is built for this job. We are not going to point you at the nearest one and call it a fit.
So the free services listed on this page are the whole answer, and it is the same answer we would give a friend.
Noted, and thank you. We’ll email you if a Space for rolling machine setters / operators / tenders / metal / plastic launches. Nothing else.
That did not look like an email address, so nothing was saved. Have another go below.
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No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.
Questions people ask about this job
- Will AI replace Rolling Machine Setters, Operators, and Tenders, Metal and Plastic?
- Not as a job, but it is already doing parts of the work. Across the 19 official task statements scored for Rolling Machine Setters, Operators, and Tenders, Metal and Plastic (United States, SOC 51-4023), 0% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 11 out of 100 (range 9–16, band: minimal). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
- Which tasks in “Rolling Machine Setters, Operators, and Tenders, Metal and Plastic” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Read rolling orders, blueprints, and mill schedules to determine setup specifications, work sequences, product dimensions, and installation procedures” (56/100, partial); “Record mill production on schedule sheets” (56/100, partial); “Calculate draft space and roll speed for each mill stand to plan rolling sequences and specified dimensions and tempers” (51/100, partial). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
- Which tasks in “Rolling Machine Setters, Operators, and Tenders, Metal and Plastic” stay human?
- About 84% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Disassemble sizing mills removed from rolling lines, and sort and store parts” (0/100, minimal); “Remove scratches and polish roll surfaces, using polishing stones and electric buffers” (0/100, minimal); “Activate shears and grinders to trim workpieces” (0/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
- What should someone working in “Rolling Machine Setters, Operators, and Tenders, Metal and Plastic” do about AI?
- Start from the ledger rather than the headline: 0% of this job's weighted core work is exposed, and roughly 84% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.
- How is the AI exposure score for Rolling Machine Setters, Operators, and Tenders, Metal and Plastic calculated?
- Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 19 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.
Where these numbers come from
Worth knowing about these figures
- The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
- 1 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
- Task statements
- onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
- Task weights
- onet-db (im-rt)
- Scores
- Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
- Pay and employment
- bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))
Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.
The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.
The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.
Using these figures?
Cite this
Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.
Plain text
Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).
BibTeX
@misc{collab365futureproof2026q41,
title = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
author = {{Collab365}},
year = {2026},
url = {https://futureproof.collab365.com/data/2026-q4.1},
note = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}Data as of release 2026-q4.1, published . Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.