US dataswitch to UK
Butchers and Meat Cutters
preparing and placing meat cuts and products in display counter to appear attractive and catch the shopper's eye, preparing special cuts of meat ordered by customers and receiving, inspecting. If that's your week, this page is about your job.
The honest answer
AI changes the edges of this job, not the middle: preparing and placing meat cuts and products in display counter to appear attractive and catch the shopper's eye is work software can't reach.
What shifts is recording quantity of meat received and issued to cooks or keeping records of meat sales. This page scores what today's tools actually do, not headlines.
Your week, as this page understands it
Cut, trim, or prepare consumer-sized portions of meat for use or sale in retail establishments. The job title says “butchers” or “meat cutters”: officially one job, two names. The real job is the part underneath: preparing and placing meat cuts and products in display counter to appear attractive and catch the shopper's eye. 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 butchers and meat cutters is not one task. It is 11 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is preparing and placing meat cuts and products in display counter to appear attractive and catch the shopper's eye, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 6%
- changing shape
- 9%
- staying human
- 85%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 11 out of 100 (9–16 allowing for uncertainty): minimal exposure, across 11 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 butchers and meat cutters 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 2026-08-04. 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
1 taskTasks 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.
Recording quantity of meat received and issued to cooks or keeping records of meat sales
This is reading one thing and writing another: quantity of meat in, a record out. That is the shape today's tools are built for.
importance 4 · SupplementalSource: “Record quantity of meat received and issued to cooks or keep records of meat sales.” (O*NET task statement)
How this row was scored
Exposure score: 69 out of 100 (65–73 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Keeping records of meat received, issued and sold is ordinary record-keeping that software handles 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 taskTasks 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.
Estimating requirements and ordering or requisition meat supplies to maintain inventories
The software now makes the first pass at requirements, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Estimate requirements and order or requisition meat supplies to maintain inventories.” (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: Working out what to reorder from sales and stock levels is a forecasting task software does well.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Staying human
9 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.
Preparing and placing meat cuts and products in display counter to appear attractive and catch the shopper's eye
This work happens in the physical world: meat cuts, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Prepare and place meat cuts and products in display counter to appear attractive and catch the shopper's eye.” (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: Arranging cuts attractively in a display counter 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 1/4.
Cutting, trimming, bone, tie and grinding meats, such as beef, pork, poultry and fish
This work happens in the physical world: bone, tie and grinding meats, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Cut, trim, bone, tie, and grind meats, such as beef, pork, poultry, and fish, to prepare in cooking form.” (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, boning and grinding meat is skilled knife 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.
Wrapping, weighing, labelling and price cuts of meat
This work happens in the physical world: price cuts of meat, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Wrap, weigh, label, and price cuts of meat.” (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: Wrapping, weighing, labeling and pricing meat is physical counter work, even though scales print the labels.
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.
Preparing special cuts of meat ordered by customers
This work happens in the physical world: special cuts of meat, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Prepare special cuts of meat ordered by customers.” (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 a special order for a customer is hands-on knife 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 1/4 · how much data exists 1/4.
Receiving, inspecting and storing meat upon delivery to ensure meat quality
This work happens in the physical world: meat upon delivery, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Receive, inspect, and store meat upon delivery to ensure meat quality.” (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: Checking meat quality on delivery and putting it into storage 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 2/4.
Shaping lace and tie roasts, using boning knife, skewer and twine
This work happens in the physical world: lace, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Shape, lace, and tie roasts, using boning knife, skewer, and twine.” (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: Shaping, lacing and tying roasts is done by hand with knife and twine.
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.
Supervising other butchers or meat cutters
This work happens in the physical world: other butchers, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Supervise other butchers or meat cutters.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (0–13 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Supervising other cutters happens on the shop floor alongside them.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Curing smoke, tenderize and preserving meat
This work happens in the physical world: smoke, tenderize and preserving meat, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Cure, smoke, tenderize, and preserve meat.” (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: Curing, smoking and tenderizing meat is physical processing 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 1 task
Negotiating with representatives from supply companies to determine order details
staying humanThe value here is that a specific person handles representatives and stands behind it. That is earned, not computed.
importance 4 · SupplementalSource: “Negotiate with representatives from supply companies to determine order details.” (O*NET task statement)
How this row was scored
Exposure score: 26 out of 100 (19–33 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Negotiating order details with suppliers is a commercial conversation, though the price comparisons behind it can be prepared automatically.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
What this job pays, and how many people do it
- Median pay
- $40,140a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
- People doing this job
- 136,430in 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: quantity of meat in, a record out. The rows above are exactly that shape: recording quantity of meat received and issued to cooks or keeping records of meat sales and estimating requirements and ordering or requisition meat supplies to maintain inventories. What it cannot do is be there in the room, and that is still where meat cuts 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: preparing and placing meat cuts and products in display counter to appear attractive and catch the shopper's eye is the middle of this job, and the evidence on this page says it stays with a person.
So, given all that: 6% of this job's task weight sits in rows the software is already learning, 9% in rows that change shape rather than disappear, and 85% in rows it is nowhere near. That is the position, measured across 11 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. Recording quantity of meat received and issued to cooks or keeping records of meat sales 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 quantity of meat, 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 meat cuts 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 estimating requirements and ordering or requisition meat supplies to maintain inventories. 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 butchers and meat cutters (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was meat, poultry, and fish cutters and trimmers: only about 17% of its durable work is work you already do. And on the numbers you do not need one. This job scores 11/100 here, with only 6% of the task list in the top band, and “prepare and place meat cuts and products in display counter to appear…” 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.
Meat, Poultry, and Fish Cutters and Trimmers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already prepare special cuts of meat ordered by customers, and their equivalent is to cut and trim meat to prepare for packing. Across both published task lists that is about 17% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 17% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Slaughterers and Meat Packers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already prepare special cuts of meat ordered by customers, and their equivalent is to remove bones, and cut meat into standard cuts in preparation for marketing. Across both published task lists that is about 10% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 10% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Cooks, Institution and Cafeteria
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already cut, trim, bone, tie, and grind meats, and their equivalent is to clean, cut, and cook meat, fish, or poultry. Across both published task lists that is about 9% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 9% of the durable side of that job. That is a different job, not a next step.
What I’d stop worrying about
A friend tells you what not to spend fear on. This is that list.
The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 6% of its task weight, across 11 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 preparing and placing meat cuts and products in display counter to appear attractive and catch the shopper's eye 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 Butchers 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 Butchers and Fishmongers and poultry dressers. 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 butchers / meat cutters, 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 6% 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 butchers / meat cutters. 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 butchers / meat cutters launches. Nothing else.
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No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.
Questions people ask about this job
- Will AI replace Butchers and Meat Cutters?
- Not as a job, but it is already doing parts of the work. Across the 11 official task statements scored for Butchers and Meat Cutters (United States, SOC 51-3021), 6% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 11 out of 100 (range 9–16, band: minimal). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
- Which tasks in “Butchers and Meat Cutters” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Record quantity of meat received and issued to cooks or keep records of meat sales” (69/100, high); “Estimate requirements and order or requisition meat supplies to maintain inventories” (56/100, partial); “Negotiate with representatives from supply companies to determine order details” (26/100, 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 “Butchers and Meat Cutters” stay human?
- About 85% 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: “Cure, smoke, tenderize, and preserve meat” (0/100, minimal); “Shape, lace, and tie roasts, using boning knife, skewer, and twine” (0/100, minimal); “Receive, inspect, and store meat upon delivery to ensure meat quality” (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 “Butchers and Meat Cutters” do about AI?
- Start from the ledger rather than the headline: 6% of this job's weighted core work is exposed, and roughly 85% 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 Butchers and Meat Cutters 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 11 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 2026-08-04.
- 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.