Will AI replace Sawing Machine Setters, Operators, and Tenders, Wood?

Not as a job, but it is already doing parts of the work. Across the 22 official task statements scored for Sawing Machine Setters, Operators, and Tenders, Wood (United States, SOC 51-7041), 0% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 5 out of 100 (range 3–9, 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 “Sawing Machine Setters, Operators, and Tenders, Wood” do about AI?

Start from the ledger rather than the headline: 0% of this job's weighted core work is exposed, and roughly 97% 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 Sawing Machine Setters, Operators, and Tenders, Wood 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 22 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.

US dataswitch to UK

Sawing Machine Setters, Operators, and Tenders, Wood

inspecting and measuring workpieces to mark for cuts and to verify the accuracy of cuts, examining logs or lumber to plan the best cuts, counting, sorting or stacking finished workpieces and guiding workpieces against saws. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: inspecting and measuring workpieces to mark for cuts and to verify the accuracy of cuts 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: 0%
changing shape: 3%
staying human: 97%

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

Whole-job exposure score 5 out of 100 (3–9 allowing for uncertainty): minimal exposure, across 22 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 sawing machine setters, operators, and tenders, wood 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 examining blueprints, drawings, work orders or patterns to determine equipment set-up or selection details. This page scores what today's tools actually do, not headlines.

Your week, as this page understands it

Set up, operate, or tend wood sawing machines. May operate computer numerically controlled (CNC) equipment. Includes lead sawyers. The job title says “sawing machine setters”, “operators”, “tenders” or “wood”: officially one job, several names. The real job is the part underneath: inspecting and measuring workpieces to mark for cuts and to verify the accuracy of cuts. 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 sawing machine setters, operators, and tenders, wood is not one task. It is 22 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is inspecting and measuring workpieces to mark for cuts and to verify the accuracy of cuts, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 0%
changing shape: 3%
staying human: 97%

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

0 tasks

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.

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

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.

Examining blueprints, drawings, work orders or patterns to determine equipment set-up or selection details
The software now makes the first pass at blueprints, drawings, work orders or patterns, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Supplemental
Source: “Examine blueprints, drawings, work orders, or patterns to determine equipment set-up or selection details, procedures to be used, or dimensions of final products.” (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: Reading drawings and work orders to plan the setup is document work AI can do.
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

21 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.

Inspecting and measuring workpieces to mark for cuts and to verify the accuracy of cuts
This work happens in the physical world: workpieces, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Inspect and measure workpieces to mark for cuts and to verify the accuracy of cuts, using rulers, squares, or caliper rules.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–7 allowing for uncertainty): minimal 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: Measuring and marking workpieces means holding a rule or caliper against the wood.
The five ratings: output a model can produce 2/4 · 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.
Setting up, operate or tend saws or machines that cut or trim wood to specified dimensions
This work happens in the physical world: up, operate or tend saws or machines, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Set up, operate, or tend saws or machines that cut or trim wood to specified dimensions, such as circular saws, band saws, multiple-blade sawing machines, scroll saws, ripsaws, or crozer 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: Setting up and running saws means standing 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.
Adjusting saw blades
This work happens in the physical world: saw blades, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Adjust saw blades, using wrenches and rulers, or by turning handwheels or pressing pedals, levers, or panel buttons.” (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 saw blades is done with wrenches and handwheels 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.
Monitoring sawing machines, adjusting speed and tension and clearing jams to ensure proper operation
This work happens in the physical world: machines, adjusting speed and tension and clearing jams, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Monitor sawing machines, adjusting speed and tension and clearing jams to ensure proper operation.” (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: Watching machines and clearing jams happens at the saw.
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.
Sharpening blades or replacing defective or worn blades or bands, using hand tools
This work happens in the physical world: blades, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Sharpen blades, or replace defective or worn blades or bands, 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: Sharpening and changing blades is done by hand.
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.
Mounting and bolting sawing blades or attachments to machine shafts
This work happens in the physical world: blades, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Mount and bolt sawing blades or attachments to machine shafts.” (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: Mounting and bolting blades onto machine shafts 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.
Guiding workpieces against saws, saw over workpieces by hand or operating automatic feeding devices to guide cuts
This work happens in the physical world: workpieces against saws, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Guide workpieces against saws, saw over workpieces by hand, or operate automatic feeding devices to guide cuts.” (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 workpieces into a saw is 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.
Inspecting stock for imperfections or to estimate grades or qualities of stock or workpieces
This work happens in the physical world: stock, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Inspect stock for imperfections or to estimate grades or qualities of stock or workpieces.” (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: Grading stock is a visual judgment made with the boards in front of you, though scanners can help.
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.
Clearing machine jams, using hand tools
This work happens in the physical world: machine jams, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Clear machine jams, 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: Clearing a jam means reaching into the machine with tools.
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 12 tasks

Selecting 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: “Select saw blades, types or grades of stock, or cutting procedures to be used, according to work orders or supervisors' instructions.” (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: Blade and stock choice follows written work orders, though the final pick is made at the machine.
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.
Examining logs or lumber to plan the best cuts
staying human
This work happens in the physical world: logs, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Examine logs or lumber to plan the best cuts.” (O*NET task statement)
How this row was scored
Exposure score: 17 out of 100 (10–24 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: Working out the best cuts is a calculation software does well, but the log has to be looked at in the yard.
The five ratings: output a model can produce 3/4 · 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.
Operating panelboards of saw or conveyor systems to move stock through processes or to cut stock to specified dimensions
staying human
This work happens in the physical world: panelboards of saw, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Operate panelboards of saw or conveyor systems to move stock through processes or to cut stock to specified dimensions.” (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 the saw and conveyor panel means being at the controls.
The five ratings: output a model can produce 1/4 · 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 bolts, clamps, stops, guides or table angles or heights, using hand tools
staying human
This work happens in the physical world: bolts, clamps, stops, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Adjust bolts, clamps, stops, guides, or table angles or heights, 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: Adjusting clamps, stops, guides and table heights is done with hand tools.
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.
Counting, sorting or stacking finished workpieces
staying human
This work happens in the physical world: finished workpieces, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Count, sort, or stack finished 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: Counting, sorting and stacking finished pieces 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 1/4.
Lubricating or cleaning machines, using wrenches, grease guns or solvents
staying human
This work happens in the physical world: machines, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Lubricate or clean machines, using wrenches, grease guns, or solvents.” (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: Greasing and cleaning machines is physical maintenance.
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.
Disposing of waste material after completing work assignments
staying human
This work happens in the physical world: waste material after completing work assignments, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Dispose of waste material after completing work assignments.” (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: Clearing away waste material 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.
Measuring and marking stock for cuts
staying human
This work happens in the physical world: stock, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Measure and mark stock for cuts.” (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: Measuring and marking stock is done with the board in hand.
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.
Trimming lumber to straighten rough edges or remove defects
staying human
This work happens in the physical world: lumber, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Trim lumber to straighten rough edges or remove defects, using circular saws.” (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: Trimming rough edges and defects is done at the saw.
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 and clamping stock on tables
staying human
This work happens in the physical world: stock, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Position and clamp stock on tables, conveyors, or carriages, using hoists, guides, stops, dogs, wedges, or wrenches.” (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: Clamping stock onto tables and carriages 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.
Cutting grooves, bevels or miters
staying human
This work happens in the physical world: grooves, bevels or miters, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Cut grooves, bevels, or miters, saw curved or irregular designs, and sever or shape metals, according to specifications or work orders.” (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 grooves, bevels and shapes is done at the saw.
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.
Unclamping and removing finished workpieces from tables
staying human
This work happens in the physical world: finished workpieces, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Unclamp and remove finished workpieces from tables.” (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: Unclamping and removing finished pieces is 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.

What this job pays, and how many people do it

Median pay: $42,770a 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: 40,850in 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: blueprints, drawings, work orders or patterns in, a record out. The rows above are exactly that shape: examining blueprints, drawings, work orders or patterns to determine equipment set-up or selection details. What it cannot do is be there in the room, and that is still where workpieces 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: inspecting and measuring workpieces to mark for cuts and to verify the accuracy of cuts 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, 3% in rows that change shape rather than disappear, and 97% in rows it is nowhere near. That is the position, measured across 22 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. Examining blueprints, drawings, work orders or patterns to determine equipment set-up or selection details 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 blueprints, drawings, work orders or patterns, 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 up, operate or tend saws or machines 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 examining blueprints, drawings, work orders or patterns to determine equipment set-up or selection details. 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 sawing machine setters, operators, and tenders, wood (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was cutting and slicing machine setters, operators, and tenders: only about 8% of its durable work is work you already do. And on the numbers you do not need one. This job scores 5/100 here, with only 0% of the task list in the top band, and “inspect and measure workpieces to mark for cuts and to verify the…” 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.

Cutting and Slicing 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 adjust saw blades, using wrenches and rulers, or by turning handwheels or pressing…, and their equivalent is to press buttons, pull levers, or depress pedals to start and operate cutting and…. 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.
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 inspect and measure workpieces to mark for cuts and to verify the accuracy…, 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 7% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 7% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →
Milling and Planing 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 inspect and measure workpieces to mark for cuts and to verify the accuracy…, and their equivalent is to verify alignment of workpieces on machines, 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.
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: 0% of its task weight, across 22 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 inspecting and measuring workpieces to mark for cuts and to verify the accuracy of cuts 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.

If you run a team doing this job

If you run a team doing this job, the conversation you owe them is the one on this page, and sooner than feels comfortable. Show them the ledger rather than a reassurance: the rows moving toward the software are examining blueprints, drawings, work orders or patterns to determine equipment set-up or selection details, and the rows that are not are where you want your people visible. Ask each of them to do the this-week move and bring the list to your next one-to-one. It turns a rumour into a piece of work, and it tells you which parts of your team's week are actually at stake. And say the thing out loud that a team lead usually leaves unsaid: a shrinking team is your exposure too, so do the move yourself as well.

You are reading the United States figures

The United Kingdom splits this work across more than one official group, of which Paper and wood machine 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

In UK official statistics this job is counted as Paper and wood machine operatives. 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:
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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 sawing machine setters / operators / tenders / wood 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 sawing machine setters / operators / tenders / wood 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 sawing machine setters / operators / tenders / wood 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 sawing machine setters / operators / tenders / wood 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 Sawing Machine Setters, Operators, and Tenders, Wood?: Not as a job, but it is already doing parts of the work. Across the 22 official task statements scored for Sawing Machine Setters, Operators, and Tenders, Wood (United States, SOC 51-7041), 0% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 5 out of 100 (range 3–9, 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 “Sawing Machine Setters, Operators, and Tenders, Wood” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Examine blueprints, drawings, work orders, or patterns to determine equipment set-up or selection details, procedures to be used, or dimensions of final prod…” (56/100, partial); “Select saw blades, types or grades of stock, or cutting procedures to be used, according to work orders or supervisors' instructions” (38/100, low); “Examine logs or lumber to plan the best cuts” (17/100, minimal). 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 “Sawing Machine Setters, Operators, and Tenders, Wood” stay human?: About 97% 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: “Unclamp and remove finished workpieces from tables” (0/100, minimal); “Cut grooves, bevels, or miters, saw curved or irregular designs, and sever or shape metals, according to specifications or work orders” (0/100, minimal); “Position and clamp stock on tables, conveyors, or carriages, using hoists, guides, stops, dogs, wedges, or wrenches” (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 “Sawing Machine Setters, Operators, and Tenders, Wood” do about AI?: Start from the ledger rather than the headline: 0% of this job's weighted core work is exposed, and roughly 97% 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 Sawing Machine Setters, Operators, and Tenders, Wood 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 22 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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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.