Will AI replace Office Machine Operators, Except Computer?

Not as a job, but it is already doing parts of the work. Across the 18 official task statements scored for Office Machine Operators, Except Computer (United States, SOC 43-9071), 5% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 14 out of 100 (range 11–19, 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 “Office Machine Operators, Except Computer” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Complete records of production, including work volumes and outputs, materials used, and any backlogs” (69/100, high); “Read job orders to determine the type of work to be done, the quantities to be produced, and the materials needed” (56/100, partial); “Maintain stock of supplies, and requisition any needed items” (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 “Office Machine Operators, Except Computer” stay human?

About 88% 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: “Move heat units and clamping frames over screen beds to form Braille impressions on pages, raising frames to release individual copies” (0/100, minimal); “Clean and file master copies or plates” (0/100, minimal); “Cut copies apart and write identifying information, such as page numbers or titles, on copies” (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 “Office Machine Operators, Except Computer” do about AI?

Start from the ledger rather than the headline: 5% of this job's weighted core work is exposed, and roughly 88% 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 Office Machine Operators, Except Computer 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 18 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

Office Machine Operators, Except Computer

reading job orders to determine the type of work to be done, computing prices for services and receiving payment and setting up and adjusting machines. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: operating office machines, high speed business photocopiers, readers, scanners, addressing machines, stencil-cutting 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: 7%
staying human: 88%

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

Whole-job exposure score 14 out of 100 (11–19 allowing for uncertainty): minimal exposure, across 18 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 office machine operators, except computer 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 completing records of production, including work volumes and outputs, materials used and any backlogs: the overhead at the edges, not the middle you trained for.

Your week, as this page understands it

Operate one or more of a variety of office machines, such as photocopying, photographic, and duplicating machines, or other office machines. The job title says “office machine operators” or “except computer”: officially one job, two names. The real job is the part underneath: operating office machines, high speed business photocopiers, readers, scanners, addressing machines, stencil-cutting 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 office machine operators, except computer is not one task. It is 18 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is operating office machines, high speed business photocopiers, readers, scanners, addressing machines, stencil-cutting machines, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 5%
changing shape: 7%
staying human: 88%

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.

One task scored differently between repeat runs, so its range on this page is wider. We would rather show the wobble than hide it.
3 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.

Completing records of production, including work volumes and outputs, materials used and any backlogs
This is reading one thing and writing another: records of production, including work volumes and outputs in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Complete records of production, including work volumes and outputs, materials used, and any backlogs.” (O*NET task statement)
How this row was scored
Exposure score: 69 out of 100 (62–76 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: Logging output volumes, materials used and backlogs is routine record-keeping that software does well.
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.

Reading job orders to determine the type of work to be done
The software now makes the first pass at job orders, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Read job orders to determine the type of work to be done, the quantities to be produced, and the materials needed.” (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 a job order for quantities and materials is straightforward document work.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.

Staying human

16 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.

Sorting, assembling and proof completed work
This work happens in the physical world: proof completed work, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Sort, assemble, and proof completed work.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (7–21 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: Proofing can be automated, but sorting and assembling the physical output cannot.
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 3/4.
Operating office machines, high speed business photocopiers, readers, scanners, addressing machines, stencil-cutting machines
This work happens in the physical world: office machines, high speed business photocopiers, readers, scanners, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Operate office machines such as high speed business photocopiers, readers, scanners, addressing machines, stencil-cutting machines, microfilm readers or printers, folding and inserting machines, bursters, and binder 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: Running copiers, scanners and binding machines means standing at them.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Setting up and adjusting machines
This work happens in the physical world: and adjusting machines, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Set up and adjust machines, regulating factors such as speed, ink flow, focus, and number of copies.” (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 speed, ink flow and focus on the machine means adjusting it 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.
Loading machines with materials, blank paper or film
This work happens in the physical world: machines, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Load machines with materials such as blank paper or film.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–7 allowing for uncertainty): minimal exposure, high confidence, and it moved between repeat runs, so the range is widened.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Loading paper or film into a machine 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.
Monitoring machine operation and making adjustments as necessary to ensure proper operation
This work happens in the physical world: machine operation, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Monitor machine operation, and make adjustments as necessary 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 a machine run and adjusting it is done standing at 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 1/4.
Operating auxiliary machines, collators, pad and tablet making machines, staplers and paper punching, folding, cutting and perforating machines
This work happens in the physical world: auxiliary machines, collators, pad and tablet making machines, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Operate auxiliary machines such as collators, pad and tablet making machines, staplers, and paper punching, folding, cutting, and perforating 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: Operating collators, staplers and folders is physical machine 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.
Maintaining stock of supplies and requisition any needed items
This work happens in the physical world: stock of supplies, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Maintain stock of supplies, and requisition any needed items.” (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: Reordering supplies is easy to automate, though checking what is on the shelf means looking.
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.
Cleaning machines, perform minor repairs and reporting major repair needs
This work happens in the physical world: machines, perform minor repairs and reporting major repair, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Clean machines, perform minor repairs, and report major repair needs.” (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 making minor repairs is hands-on 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 1/4.

Show the other 8 tasks

Computing prices for services and receiving payment
staying human
This work happens in the physical world: prices, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Compute prices for services and receive payment, or provide supervisors with billing information.” (O*NET task statement)
How this row was scored
Exposure score: 32 out of 100 (25–39 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: Price calculation is easy to automate, but taking payment over a counter still involves a person.
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 1/4 · how much data exists 3/4.
Filing and storing completed documents
staying human
This work happens in the physical world: completed documents, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “File and store completed documents.” (O*NET task statement)
How this row was scored
Exposure score: 19 out of 100 (12–26 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: Digital filing is easy to automate, but storing paper documents means physically putting them away.
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 3/4.
Placing original copies in feed trays
staying human
This work happens in the physical world: original copies, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Place original copies in feed trays, feed originals into feed rolls, or position originals on tables beneath camera lenses.” (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 originals into trays and rollers is physical handling of paper.
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.
Delivering completed work
staying human
This work happens in the physical world: completed work, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Deliver completed work.” (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: Delivering finished work means carrying it to someone.
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.
Preparing and processing papers for use in scanning
staying human
This work happens in the physical world: papers, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Prepare and process papers for use in scanning, microfilming, and microfiche.” (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: Preparing paper for scanning and microfilming means handling the documents.
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.
Cutting copies apart and writing identifying information
staying human
This work happens in the physical world: copies apart, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Cut copies apart and write identifying information, such as page numbers or titles, on copies.” (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 copies apart and writing on them 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.
Cleaning and filing master copies or plates
staying human
This work happens in the physical world: master copies, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Clean and file master copies or plates.” (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 filing master plates is physical 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.
Moving heat units and clamping frames over screen beds to form Braille impressions on pages
staying human
This work happens in the physical world: heat units, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Move heat units and clamping frames over screen beds to form Braille impressions on pages, raising frames to release individual copies.” (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 heat units and frames to form Braille pages is physical machine 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: $40,960a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
People doing this job: 25,130in 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: records of production, including work volumes and outputs in, a record out. The rows above are exactly that shape: completing records of production and reading job orders to determine the type of work to be done. What it cannot do is be there in the room, and that is still where office machines, high speed business photocopiers, readers, scanners 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: operating office machines, high speed business photocopiers, readers, scanners, addressing machines, stencil-cutting 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, 7% in rows that change shape rather than disappear, and 88% in rows it is nowhere near. That is the position, measured across 18 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. Completing records of production, including work volumes and outputs, materials used and any backlogs 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 records of production, including work volumes and outputs, 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 office machines, high speed business photocopiers, readers, scanners are in scope or not. Nothing to log into, no license needed.

Over the next 90 days

Get inside the tool rollout rather than waiting for it. Over the next ninety days, ask to be in the group that tests, checks or signs off whatever new system arrives near reading job orders to determine the type of work to be done. 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 office machine operators, except computer (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was data entry keyers: only about 7% of its durable work is work you already do and it is under the same pressure this job is. And on the numbers you do not need one. This job scores 14/100 here, with only 5% of the task list in the top band, and “sort, assemble, and proof completed work” 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.

Data Entry Keyers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already file and store completed documents, and their equivalent is to store completed documents in appropriate locations. 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. I will not move you off one melting floe onto another: 67% of its own task list already scores in the top exposure band (67/100 in this release), so the same software is eating it.
Look at that job’s page anyway →
Print Binding and Finishing Workers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already clean machines, perform minor repairs, and report major repair needs, and their equivalent is to lubricate, clean, or make minor repairs to machine parts to keep machines in…. 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 →
Woodworking Machine Setters, Operators, and Tenders, Except Sawing
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already monitor machine operation, and make adjustments as necessary to ensure proper operation, and their equivalent is to monitor operation of machines and make adjustments to correct problems and ensure conformance…. 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: 5% of its task weight, across 18 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 operating office machines, high speed business photocopiers, readers, scanners, addressing machines, stencil-cutting 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 Elementary administration occupations 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 Elementary administration occupations 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

No Space for this job, but one for what is happening to it

Nothing Collab365 runs is built for office machine operators / except computer, 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 5% of the work on this page is already inside what they can do.

Try The AI Authority free →

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 office machine operators / except computer. 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 office machine operators / except computer launches. Nothing else.

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Questions people ask about this job

Will AI replace Office Machine Operators, Except Computer?: Not as a job, but it is already doing parts of the work. Across the 18 official task statements scored for Office Machine Operators, Except Computer (United States, SOC 43-9071), 5% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 14 out of 100 (range 11–19, 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 “Office Machine Operators, Except Computer” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Complete records of production, including work volumes and outputs, materials used, and any backlogs” (69/100, high); “Read job orders to determine the type of work to be done, the quantities to be produced, and the materials needed” (56/100, partial); “Maintain stock of supplies, and requisition any needed items” (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 “Office Machine Operators, Except Computer” stay human?: About 88% 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: “Move heat units and clamping frames over screen beds to form Braille impressions on pages, raising frames to release individual copies” (0/100, minimal); “Clean and file master copies or plates” (0/100, minimal); “Cut copies apart and write identifying information, such as page numbers or titles, on copies” (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 “Office Machine Operators, Except Computer” do about AI?: Start from the ledger rather than the headline: 5% of this job's weighted core work is exposed, and roughly 88% 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 Office Machine Operators, Except Computer 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 18 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

About the data on this page

One task scored differently between repeat runs, so its range on this page is wider. We would rather show the wobble than hide it.
The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
3 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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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.