US dataswitch to UK
Computer Numerically Controlled Tool Programmers
determining the sequence of machine operations, entering computer commands to store or retrieve parts patterns and revising programs or tapes to eliminate errors. If that's your week, this page is about your job.
The honest answer
Most tasks in this job are the kind AI has learned to do: entering computer commands to store or retrieve parts patterns. The tasks, though, are not you.
It would be a lie to soften that, and another lie to promise a rebuilt version of this job inside this job.
So the hope here is what you already carry: the judgment you bring to preventative maintenance is real, and the moves below are built from it. The first step is down this page.
Your week, as this page understands it
Develop programs to control machining or processing of materials by automatic machine tools, equipment, or systems. May also set up, operate, or maintain equipment. The job title says “computer numerically controlled tool programmers”. The real job is the part underneath: performing preventative maintenance or minor repairs on 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 computer numerically controlled tool programmers is not one task. It is 16 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is performing preventative maintenance or minor repairs on machines, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 87%
- changing shape
- 0%
- staying human
- 13%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 71 out of 100 (65–77 allowing for uncertainty): high exposure, across 16 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 computer numerically controlled tool programmers 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.
- 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
13 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.
Observing machines on trial runs or conducting computer simulations to ensure that programs and machinery will function properly and produce items that meet specifications
This is reading one thing and writing another: machines in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Observe machines on trial runs or conduct computer simulations to ensure that programs and machinery will function properly and produce items that meet specifications.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high 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: Simulations run on a computer, but a trial cut has to be watched at the machine.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Analyzing job orders, drawings, blueprints, specifications
This is reading one thing and writing another: job orders, drawings, blueprints, specifications in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Analyze job orders, drawings, blueprints, specifications, printed circuit board pattern films, and design data to calculate dimensions, tool selection, machine speeds, and feed rates.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high 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 specifications to work out dimensions, speeds and feeds is calculation software handles well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Determining the sequence of machine operations
This is reading one thing and writing another: the sequence of machine operations in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Determine the sequence of machine operations, and select the proper cutting tools needed to machine workpieces into the desired shapes.” (O*NET task statement)
How this row was scored
Exposure score: 68 out of 100 (61–75 allowing for uncertainty): high 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: Software can propose a sequence and tooling, but the choice depends on the tools and machines that shop actually has.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Entering computer commands to store or retrieve parts patterns
This is reading one thing and writing another: computer commands in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Enter computer commands to store or retrieve parts patterns, graphic displays, or programs that transfer data to other media.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very 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: Storing and retrieving programs and patterns is straightforward computer file work.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Revising programs or tapes to eliminate errors
This is reading one thing and writing another: programs in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Revise programs or tapes to eliminate errors, and retest programs to check that problems have been solved.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high 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: Finding and fixing program errors is well within software's reach, though the retest happens on the machine.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Modifying existing programs to enhance efficiency
This is reading one thing and writing another: programs in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Modify existing programs to enhance efficiency.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high 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: Reworking an existing program for speed is code optimization software does well, with a programmer checking the result.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Writing programs in the language of a machine's controller and storing programs on media
This is reading one thing and writing another: programs in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Write programs in the language of a machine's controller and store programs on media, such as punch tapes, magnetic tapes, or disks.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (76–90 allowing for uncertainty): very high 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: Machine code is a documented language software writes well, though the program still needs proving on the specific machine.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Changing shape
0 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.
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.
Staying human
3 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.
Performing preventative maintenance or minor repairs on machines
This work happens in the physical world: preventative maintenance, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Perform preventative maintenance or minor repairs on 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: Maintenance and repairs need 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 2/4.
Entering coordinates of hole locations into program memories by depressing pedals or buttons of programmers
This work happens in the physical world: coordinates of hole locations, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Enter coordinates of hole locations into program memories by depressing pedals or buttons of programmers.” (O*NET task statement)
How this row was scored
Exposure score: 23 out of 100 (16–30 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: The coordinates are simple data, but they are keyed in at the machine's own panel.
The five ratings: output a model can produce 4/4 · 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 3/4.
Aligning and securing pattern film on reference tables of optical programmers
This work happens in the physical world: pattern film, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Align and secure pattern film on reference tables of optical programmers, and observe enlarger scope views of printed circuit boards.” (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: Aligning film on a reference table and looking through a scope 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.
Show the other 6 tasks
Determining reference points
shifting to AIThis is reading one thing and writing another: reference points in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Determine reference points, machine cutting paths, or hole locations, and compute angular and linear dimensions, radii, and curvatures.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very 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: Working out coordinates, paths, angles and radii is geometry and arithmetic that computers do faster and more accurately.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Comparing encoded tapes or computer printouts with original part specifications and blueprints to verify accuracy of instructions
shifting to AIThis is reading one thing and writing another: encoded tapes in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Compare encoded tapes or computer printouts with original part specifications and blueprints to verify accuracy of instructions.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very 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: Comparing a program against the original drawing for errors is exactly the kind of checking software does best.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Ordering tooling for jobs
shifting to AIThis is reading one thing and writing another: jobs in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Order tooling for jobs.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (76–90 allowing for uncertainty): very high 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: Ordering tooling from catalogs against a job's requirements is routine purchasing that software handles well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Preparing geometric layouts from graphic displays
shifting to AIThis is reading one thing and writing another: geometric layouts in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Prepare geometric layouts from graphic displays, using computer-assisted drafting software or drafting instruments and graph paper.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high 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: Producing geometric layouts is drafting work that software already does inside CAD packages.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Writing instruction sheets and cutter lists for a machine's controller to guide setup and encode numerical control tapes
shifting to AIThis is reading one thing and writing another: instruction sheets in, a record out. That is the shape today's tools are built for.
importance 4 · SupplementalSource: “Write instruction sheets and cutter lists for a machine's controller to guide setup and encode numerical control tapes.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high 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: Setup sheets and cutter lists are generated straight from the program, so software drafts them well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Sorting shop orders into groups to maximize materials utilization and minimize machine setup time
shifting to AIThis is reading one thing and writing another: shop orders in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Sort shop orders into groups to maximize materials utilization and minimize machine setup time.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high 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: Grouping shop orders to save material and setup time is a scheduling problem software solves well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
What this job pays, and how many people do it
- Median pay
- $68,120a 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
- 28,500in 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: computer commands in, a record out. The rows above are exactly that shape: entering computer commands to store or retrieve parts patterns and observing machines on trial runs or conducting computer simulations to ensure that programs and machinery will function properly and produce items that meet specifications. What it cannot do is be there in the room, and that is still where preventative maintenance gets 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
The exposed part of your job is the biggest part, and I am not going to dress that up: entering computer commands to store or retrieve parts patterns is work today's tools do quickly and cheaply, and that is not coming back.
So, given all that: 87% of this job's task weight sits in rows the software is already learning, 0% in rows that change shape rather than disappear, and 13% in rows it is nowhere near. That is the position, measured across 16 scored tasks. It is not a forecast about you.
What you have that the software does not is performing preventative maintenance or minor repairs on machines, plus the years of knowing when something looks wrong before you can say why. That is the raw material for everything below.
This week: one thing
Sit on the machine's side of the desk. Pick one real piece of computer commands you would normally do yourself, let whatever software you already have take the first pass at it, and then go through what it produced and write down every single thing it got wrong. One evening this week. Do not fix anything yet. Just catch it.
- What you end up holding
- a written list of the machine’s mistakes, in your handwriting
- How long it takes
- an evening, or an hour if you pick one job rather than one client
If you can’t run software on your employer’s or your clients’ data: Do the same hunt on paper. Take one printed piece of computer commands, work through it the way you always do, and mark every point where you made a call rather than followed a rule. Same evening, same list, nothing to log into and nobody to ask permission from. That list is the same artifact: it is the judgment written down.
Over the next 90 days
Change one sentence about what you do. Not on a CV. Out loud, to whoever pays you. From “my job is entering computer commands to store or retrieve parts patterns” to “I check what the software does and tell you what it means.” Your error list from this week is what makes that sentence true instead of a claim, so use it: show it once, to one person, inside the next ninety days. Same skills, priced as judgment rather than as typing.
Over the next 12 months
Walk toward the end of this job that answers for things, and get it recognised. Pick the one part of performing preventative maintenance or minor repairs on machines you are already best at, and spend the year making it formal: a qualification, a named responsibility, a specialism people ask for by name. Price it honestly: that is evenings, it is months rather than weeks, and the seats are competitive because everyone in your position is looking at the same door. 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 computer numerically controlled tool programmers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was computer numerically controlled tool operators: only about 5% of its durable work is work you already do and it pays 25.6% less. I am not going to pretend that is comfortable news: 87% of your own task list is already in the top exposure band. But the answer on this evidence is not a sideways jump into a job with the same problem. It is to walk toward the end of this one that answers for things. “perform preventative maintenance or minor repairs on machines” is the part that stays with a person, and spending a year getting formally recognised for it beats a standing start somewhere else.
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.
Computer Numerically Controlled Tool Operators
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already determine the sequence of machine operations, and select the proper cutting tools needed…, and their equivalent is to check to ensure that workpieces are properly lubricated and cooled during machine operation. Across both published task lists that is about 5% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 5% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $50,690 against your $68,120, 25.6% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Machinists
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already determine the sequence of machine operations, and select the proper cutting tools needed…, and their equivalent is to maintain machine tools in proper operational condition. Across both published task lists that is about 3% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 3% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $58,750 against your $68,120, 13.8% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
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 determine the sequence of machine operations, and select the proper cutting tools needed…, and their equivalent is to select machine tooling to be used, using knowledge of machine and production requirements. Across both published task lists that is about 2% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 2% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $46,550 against your $68,120, 31.7% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
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: 87% of its task weight, across 16 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
“It’s too late for me to become something else”
You are not starting from zero, and the page shows why: performing preventative maintenance or minor repairs on machines is work the software cannot do and you already do it. The move above is a repricing of what you know, not a new career. Nobody who has just left college has that.
“I should learn to code”
Almost certainly not. The value in your job is moving toward checking, deciding and answering for the output, not toward writing the software. A weekend of Python will not change your position; the error list from this week will.
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 Tool makers, tool fitters and markers-out 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 Tool makers, tool fitters and markers-out, Elementary process plant occupations n.e.c., Planning, process and production technicians and Industrial cleaning process occupations. 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
No Space for this job, but one for what is happening to it
Nothing Collab365 runs is built for computer numerically controlled tool programmers, and we are not going to point you at the nearest one and call it a fit.
There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 87% of the work on this page is already inside what they can do.
7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.
The AI Authority is a general community about working with AI, not a course for computer numerically controlled tool programmers. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.
Noted, and thank you. We’ll email you if a Space for computer numerically controlled tool programmers launches. Nothing else.
That did not look like an email address, so nothing was saved. Have another go below.
We could not save that. The fault is ours, not yours, and your address was not stored. Please try again later.
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 Computer Numerically Controlled Tool Programmers?
- Not as a job, but it is already doing parts of the work. Across the 16 official task statements scored for Computer Numerically Controlled Tool Programmers (United States, SOC 51-9162), 87% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 71 out of 100 (range 65–77, band: high). 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 “Computer Numerically Controlled Tool Programmers” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Determine reference points, machine cutting paths, or hole locations, and compute angular and linear dimensions, radii, and curvatures” (93/100, very high); “Compare encoded tapes or computer printouts with original part specifications and blueprints to verify accuracy of instructions” (93/100, very high); “Enter computer commands to store or retrieve parts patterns, graphic displays, or programs that transfer data to other media” (93/100, very high). 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 “Computer Numerically Controlled Tool Programmers” stay human?
- About 13% 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: “Perform preventative maintenance or minor repairs on machines” (0/100, minimal); “Align and secure pattern film on reference tables of optical programmers, and observe enlarger scope views of printed circuit boards” (0/100, minimal); “Enter coordinates of hole locations into program memories by depressing pedals or buttons of programmers” (23/100, low). 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 “Computer Numerically Controlled Tool Programmers” do about AI?
- Start from the ledger rather than the headline: 87% of this job's weighted core work is exposed, and roughly 13% 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 Computer Numerically Controlled Tool Programmers 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 16 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.
- 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.