Will AI replace Cutting and Slicing Machine Setters, Operators, and Tenders?

Not as a job, but it is already doing parts of the work. Across the 25 official task statements scored for Cutting and Slicing Machine Setters, Operators, and Tenders (United States, SOC 51-9032), 5% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 8 out of 100 (range 7–12, 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.

What should someone working in “Cutting and Slicing Machine Setters, Operators, and Tenders” do about AI?

Start from the ledger rather than the headline: 5% of this job's weighted core work is exposed, and roughly 90% 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.

US dataswitch to UK

Cutting and Slicing Machine Setters, Operators, and Tenders

setting up, operate or tend machines that cut or slice materials, marking cutting lines or identifying information on stock, removing defective or substandard materials from machines and positioning stock along cutting lines. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: pressing buttons, pull levers or depress pedals to start and operate cutting and slicing machines is work software can't reach.

Your move: what you can actually do about this ↓

Where the work sits, by task weight

shifting to AI: 5%
changing shape: 5%
staying human: 90%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

Whole-job exposure score 8 out of 100 (7–12 allowing for uncertainty): minimal exposure, across 25 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 cutting and slicing machine setters, operators, and tenders 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.

What shifts is maintaining production records, such as quantities, types and dimensions of materials. This page scores what today's tools actually do, not headlines.

Your week, as this page understands it

Set up, operate, or tend machines that cut or slice materials, such as glass, stone, cork, rubber, tobacco, food, paper, or insulating material. The job title says “cutting”, “slicing machine setters”, “operators” or “tenders”: officially one job, several names. The real job is the part underneath: pressing buttons, pull levers or depress pedals to start and operate cutting and slicing machines. 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 cutting and slicing machine setters, operators, and tenders is not one task. It is 25 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is pressing buttons, pull levers or depress pedals to start and operate cutting and slicing machines, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 5%
changing shape: 5%
staying human: 90%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

How we know this

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

1 task

Tasks 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.

Maintaining production records, such as quantities, types and dimensions of materials
This is reading one thing and writing another: production records in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Maintain production records, such as quantities, types, and dimensions of materials produced.” (O*NET task statement)
How this row was scored
Exposure score: 69 out of 100 (65–73 allowing for uncertainty): high exposure, high 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: Production quantities, types and dimensions are structured records that shop-floor systems already capture.
The five ratings: output a model can produce 4/4 · 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.

Changing shape

1 task

Tasks 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.

Reviewing work orders, blueprints, specifications or job samples to determine components, settings and adjustments for cutting and slicing machines
The software now makes the first pass at work orders, blueprints, specifications or job samples, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Review work orders, blueprints, specifications, or job samples to determine components, settings, and adjustments for cutting and slicing machines.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (52–60 allowing for uncertainty): partial exposure, high 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: Reading a work order or drawing to work out machine settings is document work, though job samples are physical.
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

23 tasks

Tasks 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.

Pressing buttons, pull levers or depress pedals to start and operate cutting and slicing machines
This work happens in the physical world: buttons, pull levers or depress pedals, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Press buttons, pull levers, or depress pedals to start and operate cutting and slicing 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: Pressing the buttons and levers that run the machine is direct 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 2/4.
Starting machines to verify setups
This work happens in the physical world: machines, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Start machines to verify setups, and make any necessary adjustments.” (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 machines and adjusting them means standing at the controls.
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.
Monitoring operation of cutting or slicing machines to detect malfunctions or to determine whether supplies need replenishment
This work happens in the physical world: operation, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Monitor operation of cutting or slicing machines to detect malfunctions or to determine whether supplies need replenishment.” (O*NET task statement)
How this row was scored
Exposure score: 13 out of 100 (6–20 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Sensors can flag some faults, but noticing a machine going wrong is mostly watching and listening beside it.
The five ratings: output a model can produce 2/4 · 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 2/4.
Examining, measuring and weighing materials or products to verify conformance
This work happens in the physical world: materials, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Examine, measure, and weigh materials or products to verify conformance to specifications, using measuring devices, such as rulers, micrometers, or scales.” (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: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Measuring and weighing product with rulers, micrometers and scales means handling the 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 3/4.
Removing completed materials or products from cutting or slicing machines
This work happens in the physical world: completed materials, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Remove completed materials or products from cutting or slicing machines, and stack or store them for additional processing.” (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: Taking finished product off the machine and stacking it is manual handling.
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.
Moving stock or scrap to and from machines manually
This work happens in the physical world: stock, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Move stock or scrap to and from machines manually, or by using carts, handtrucks, or lift trucks.” (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: Moving stock and scrap by hand, cart or truck is manual material handling.
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 defective or substandard materials from machines
This work happens in the physical world: defective, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Remove defective or substandard materials from machines, and readjust machine components so that products meet standards.” (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: Pulling out bad material and resetting machine parts 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 2/4.
Feeding stock into cutting machines
This work happens in the physical world: stock, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Feed stock into cutting machines, onto conveyors, or under cutting blades, by threading, guiding, pushing, or turning handwheels.” (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: Feeding stock into the blades by hand is physical work that has to happen 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.

Show the other 15 tasks

Typing instructions on computer keyboards
staying human
This work happens in the physical world: instructions, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Type instructions on computer keyboards, push buttons to activate computer programs, or manually set cutting guides, clamps, and knives.” (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: Typing in a cutting program is easy to automate, but setting guides, clamps and knives by hand is not.
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.
Directing workers on cutting teams
staying human
This work happens in the physical world: workers, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Direct workers on cutting teams.” (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 value is that a specific person does it.
The rating behind it: Directing a cutting team means being on the floor with them while the work runs.
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 2/4.
Setting up, operate or tend machines that cut or slice materials
staying human
This work happens in the physical world: up, operate or tend machines, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Set up, operate, or tend machines that cut or slice materials, such as glass, stone, cork, rubber, tobacco, food, paper, or insulating material.” (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 up and running a cutting machine is hands-on work at the machine itself.
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.
Stacking and sorting cut material
staying human
This work happens in the physical world: cut material, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Stack and sort cut material for packaging, further processing, or shipping, according to types and sizes of material.” (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: Stacking and sorting cut material means lifting and moving it.
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.
Adjusting machine controls to alter position
staying human
This work happens in the physical world: machine controls, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Adjust machine controls to alter position, alignment, speed, or pressure.” (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: Adjusting position, speed and pressure is done by hand at the machine controls.
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.
Selecting and installing machine components
staying human
This work happens in the physical world: machine components, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Select and install machine components, such as cutting blades, rollers, and templates, according to specifications, 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 blades, rollers and templates with hand tools is direct 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 2/4.
Cleaning and lubricating cutting machines
staying human
This work happens in the physical world: machines, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Clean and lubricate cutting machines, conveyors, blades, saws, or knives, using steam hoses, scrapers, brushes, or oil cans.” (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: Cleaning and lubricating machines and blades has to be done 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 2/4.
Positioning stock along cutting lines
staying human
This work happens in the physical world: stock along cutting lines, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Position stock along cutting lines, or against stops on beds of scoring or cutting 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: Positioning stock against cutting lines and stops is a physical placement job.
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.
Changing or replacing saw blades
staying human
This work happens in the physical world: saw blades, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Change or replace saw blades, cables, cutter heads, and grinding wheels, 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: Changing blades, cables and grinding wheels is tool work 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 2/4.
Marking cutting lines or identifying information on stock
staying human
This work happens in the physical world: lines, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Mark cutting lines or identifying information on stock, using marking pencils, rulers, or scribes.” (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: Marking cutting lines on stock with a pencil or scribe is done by hand on the 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 2/4.
Turning cranks or press buttons to activate winches that move cars under sawing cables or saw frames
staying human
This work happens in the physical world: cranks, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Turn cranks or press buttons to activate winches that move cars under sawing cables or saw frames.” (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: Operating winches and cranks to move cars under saw frames is physical 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.
Positioning width gauge blocks between blades
staying human
This work happens in the physical world: width gauge blocks, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Position width gauge blocks between blades, and level blades and insert wedges into frames to secure blades to frames.” (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 gauge blocks and wedging blades into frames is precise manual 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.
Tightening pulleys or add abrasives to maintain cutting speeds
staying human
This work happens in the physical world: pulleys, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Tighten pulleys or add abrasives to maintain cutting speeds.” (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: Tightening pulleys and adding abrasives is maintenance done by hand on running equipment.
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.
Cutting stock manually to prepare for machine cutting
staying human
This work happens in the physical world: stock, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Cut stock manually to prepare for machine cutting, using tools such as knives, cleavers, handsaws, or hammers and chisels.” (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: Cutting stock by hand with knives, saws or chisels is manual work on the 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.
Sharpening cutting blades, knives or saws, using files, bench grinders or honing stones
staying human
This work happens in the physical world: blades, knives or saws, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Sharpen cutting blades, knives, or saws, using files, bench grinders, or honing stones.” (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: Sharpening blades on a grinder or stone is skilled work with the hands.
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: $46,570a 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: 44,980in 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: production records in, a record out. The rows above are exactly that shape: maintaining production records, such as quantities, types and dimensions of materials and reviewing work orders, blueprints. What it cannot do is be there in the room, and that is still where buttons, pull levers or depress pedals 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: pressing buttons, pull levers or depress pedals to start and operate cutting and slicing machines is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 5% of this job's task weight sits in rows the software is already learning, 5% in rows that change shape rather than disappear, and 90% in rows it is nowhere near. That is the position, measured across 25 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. Maintaining production records, such as quantities, types and dimensions of materials 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 production records, 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 buttons, pull levers or depress pedals 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 reviewing work orders, blueprints, specifications or job samples to determine components, settings and adjustments for cutting and slicing machines. 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 cutting and slicing machine setters, operators, and tenders (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was extruding, forming, pressing, and compacting machine setters, operators, and tenders: only about 14% of its durable work is work you already do. And on the numbers you do not need one. This job scores 8/100 here, with only 5% of the task list in the top band, and “press buttons, pull levers, or depress pedals to start and operate cutting…” 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.

Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already examine, measure, and weigh materials or products to verify conformance to specifications, using…, and their equivalent is to examine, measure, and weigh materials or products to verify conformance to standards, using…. Across both published task lists that is about 14% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 14% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Look at that job’s page anyway →
Adhesive Bonding Machine Operators and Tenders
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already examine, measure, and weigh materials or products to verify conformance to specifications, using…, and their equivalent is to examine and measure completed materials or products to verify conformance to specifications, using…. Across both published task lists that is about 11% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 11% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Look at that job’s page anyway →
Cutting, Punching, and Press 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, measure, and weigh materials or products to verify conformance to specifications, using…, and their equivalent is to measure completed workpieces to verify conformance to specifications, using micrometers, gauges, calipers, templates…. Across both published task lists that is about 10% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 10% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Look at that job’s page anyway →

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: 5% of its task weight, across 25 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 pressing buttons, pull levers or depress pedals to start and operate cutting and slicing machines 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 Process operatives n.e.c. 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

In UK official statistics this job is counted as Process operatives n.e.c.. Pay and employment stay on this page’s own group; the task list and the scores do not cross over.

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:
American Job Center locator
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
- CareerOneStop local help hub
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
CareerOneStop
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 cutting / slicing machine setters / operators / tenders launches. Nothing else.

That did not look like an email address, so nothing was saved. Have another go below.

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No Space for cutting / slicing machine setters / operators / tenders yet. Should there be one?

Collab365 Spaces is built by the same people as this site. We find the problems that AI and automation are creating inside one kind of work, then solve them as short courses, briefings and Blueprints. Each Space is the community too, so the research and the people doing your job are in the same place.

What a Space actually is, in full

Collab365 launches new communities where the need is real. If one for cutting / slicing machine setters / operators / tenders existed, with researched problems, courses and people in the same boat, would you want in?

Your email

We use your email address for one thing: to tell you if a Space for cutting / slicing machine setters / operators / tenders launches. We never sell it, never use it for unrelated marketing, and every email has a one-click unsubscribe. Our privacy policy has the full version.

This unlocks nothing. Every figure, every row and every step on this page is already yours, whether you fill this in or not.

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 Cutting and Slicing Machine Setters, Operators, and Tenders?: Not as a job, but it is already doing parts of the work. Across the 25 official task statements scored for Cutting and Slicing Machine Setters, Operators, and Tenders (United States, SOC 51-9032), 5% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 8 out of 100 (range 7–12, 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 “Cutting and Slicing Machine Setters, Operators, and Tenders” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Maintain production records, such as quantities, types, and dimensions of materials produced” (69/100, high); “Review work orders, blueprints, specifications, or job samples to determine components, settings, and adjustments for cutting and slicing machines” (56/100, partial); “Type instructions on computer keyboards, push buttons to activate computer programs, or manually set cutting guides, clamps, and knives” (38/100, low). 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 “Cutting and Slicing Machine Setters, Operators, and Tenders” stay human?: About 90% 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: “Sharpen cutting blades, knives, or saws, using files, bench grinders, or honing stones” (0/100, minimal); “Cut stock manually to prepare for machine cutting, using tools such as knives, cleavers, handsaws, or hammers and chisels” (0/100, minimal); “Tighten pulleys or add abrasives to maintain cutting speeds” (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 “Cutting and Slicing Machine Setters, Operators, and Tenders” do about AI?: Start from the ledger rather than the headline: 5% of this job's weighted core work is exposed, and roughly 90% 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 Cutting and Slicing Machine Setters, Operators, and Tenders 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 25 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.

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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}
}

Permalink

https://futureproof.collab365.com/data/2026-q4.1

Data as of release 2026-q4.1, published 2026-08-05. 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.