US dataswitch to UK
Chefs and Head Cooks
monitoring sanitation practices to ensure that employees follow standards and regulations, estimating amounts and costs of required supplies and coordinating planning. If that's your week, this page is about your job.
The honest answer
This job is splitting in two: ordering or requisitioning food or other supplies needed to ensure efficient operation is work AI now does quickly and cheaply, and monitoring sanitation practices to ensure that employees follow standards and regulations is work it can't touch.
Which half fills your week decides your exposure. Moving toward the second half is a real, doable plan.
Your week, as this page understands it
Direct and may participate in the preparation, seasoning, and cooking of salads, soups, fish, meats, vegetables, desserts, or other foods. May plan and price menu items, order supplies, and keep records and accounts. The job title says “chefs” or “head cooks”: officially one job, two names. The real job is the part underneath: monitoring sanitation practices to ensure that employees follow standards and regulations. 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 chefs and head cooks is not one task. It is 21 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is monitoring sanitation practices to ensure that employees follow standards and regulations, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 37%
- changing shape
- 0%
- staying human
- 63%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 35 out of 100 (30–41 allowing for uncertainty): low exposure, across 21 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 chefs and head cooks 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.
- 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
8 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.
Ordering or requisitioning food or other supplies needed to ensure efficient operation
This is reading one thing and writing another: food in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Order or requisition food or other supplies needed to ensure efficient operation.” (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: Ordering stock against par levels and expected covers is exactly what inventory software does.
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.
Estimating amounts and costs of required supplies
This is reading one thing and writing another: amounts in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Estimate amounts and costs of required supplies, such as food and ingredients.” (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: Estimating how much food is needed and what it costs is calculation from recipes and sales figures.
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 recipes to assign prices to menu items
This is reading one thing and writing another: recipes in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Analyze recipes to assign prices to menu items, based on food, labor, and overhead costs.” (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: Costing recipes and setting menu prices follows arithmetic on ingredient, labor and overhead figures.
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 production schedules and staff requirements necessary to ensure timely delivery of services
This is reading one thing and writing another: production schedules in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Determine production schedules and staff requirements necessary to ensure timely delivery of services.” (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: Production schedules and staffing levels follow from expected covers and recorded prep times.
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.
Coordinating planning, budgeting or purchasing for all the food operations within establishments, clubs, hotels or restaurant chains
This is reading one thing and writing another: all the food operations within establishments, clubs in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Coordinate planning, budgeting, or purchasing for all the food operations within establishments such as clubs, hotels, or restaurant chains.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 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: Planning, budgeting and purchasing across several kitchens is largely number and document work.
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 1/4 · how much data exists 3/4.
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
13 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.
Monitoring sanitation practices to ensure that employees follow standards and regulations
This work happens in the physical world: sanitation practices, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Monitor sanitation practices to ensure that employees follow standards and regulations.” (O*NET task statement)
How this row was scored
Exposure score: 9 out of 100 (2–16 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; someone qualified has to answer for it.
The rating behind it: Watching whether staff follow hygiene rules means being in the kitchen, and a certified manager is legally required.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 2/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Instructing cooks or other workers in the preparation
This work happens in the physical world: cooks, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Instruct cooks or other workers in the preparation, cooking, garnishing, or presentation of food.” (O*NET task statement)
How this row was scored
Exposure score: 10 out of 100 (3–17 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Recipes and method notes are easy to produce, but teaching cooks happens at the stove alongside them.
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 2/4 · how much data exists 3/4.
Supervising or coordinating activities of cooks or workers engaged in food preparation
This work happens in the physical world: activities of cooks, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Supervise or coordinate activities of cooks or workers engaged in food preparation.” (O*NET task statement)
How this row was scored
Exposure score: 10 out of 100 (3–17 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Some coordination runs through prep lists, but supervising a kitchen during service means being in it.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Inspecting supplies, equipment or work areas to ensure conformance to established standards
This work happens in the physical world: supplies, equipment or work areas, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Inspect supplies, equipment, or work areas to ensure conformance to established standards.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Checking supplies, equipment and work areas means walking the kitchen and looking at them.
The five ratings: output a model can produce 1/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Checking the quantity and quality of received products
This work happens in the physical world: the quantity, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Check the quantity and quality of received products.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Counting and checking a delivery means handling the boxes as they arrive.
The five ratings: output a model can produce 1/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Show the other 11 tasks
Recording production or operational data on specified forms
shifting to AIThis is reading one thing and writing another: production in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Record production or operational data on specified forms.” (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: Recording production and operations data on set forms is routine paperwork software handles.
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.
Collaborating with other personnel to plan and develop recipes or menus
shifting to AIThis is reading one thing and writing another: other personnel in, a record out. That is the shape today's tools are built for.
importance 3 · CoreSource: “Collaborate with other personnel to plan and develop recipes or menus, taking into account such factors as seasonal availability of ingredients or the likely number of customers.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 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: Recipe and menu development draws on well documented cooking knowledge, seasonality and sales data.
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 1/4 · how much data exists 3/4.
Arranging for equipment purchases or repairs
shifting to AIThis is reading one thing and writing another: equipment purchases in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Arrange for equipment purchases or repairs.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 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: Arranging purchases and repairs is largely quotes, scheduling and paperwork.
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 1/4 · how much data exists 3/4.
Recruiting and hiring staff, such as cooks and other kitchen workers
staying humanThe value here is that a specific person handles staff and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Recruit and hire staff, such as cooks and other kitchen workers.” (O*NET task statement)
How this row was scored
Exposure score: 30 out of 100 (23–37 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Adverts and screening are easy to automate, but kitchen hiring usually turns on a trial shift.
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 3/4.
Meeting with sales representatives to negotiate prices or order supplies
staying humanThe value here is that a specific person handles sales representatives and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Meet with sales representatives to negotiate prices or order supplies.” (O*NET task statement)
How this row was scored
Exposure score: 30 out of 100 (23–37 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Prices and order lists prepare easily, but negotiating with a supplier rep is a conversation.
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 3/4.
Determining how food should be presented and creating decorative food displays
staying humanThis work happens in the physical world: how food, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Determine how food should be presented and create decorative food displays.” (O*NET task statement)
How this row was scored
Exposure score: 25 out of 100 (18–32 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Presentation ideas can be generated, but building the actual display is hands-on work with the food.
The five ratings: output a model can produce 2/4 · 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 2/4.
Meeting with customers to discuss menus for special occasions
staying humanThe value here is that a specific person handles customers and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Meet with customers to discuss menus for special occasions, such as weddings, parties, or banquets.” (O*NET task statement)
How this row was scored
Exposure score: 24 out of 100 (17–31 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Menu options draft easily, but couples planning a wedding want a chef they have met and trust.
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 3/4 · how much data exists 3/4.
Planning, directing
staying humanThis work happens in the physical world: food preparation, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Plan, direct, or supervise food preparation or cooking activities of multiple kitchens or restaurants in an establishment such as a restaurant chain, hospital, or hotel.” (O*NET task statement)
How this row was scored
Exposure score: 20 out of 100 (13–27 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Multi-site planning is desk work, but directing cooking across kitchens still means showing up in them.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Demonstrating new cooking techniques or equipment to staff
staying humanThis work happens in the physical world: new cooking techniques, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Demonstrate new cooking techniques or equipment to staff.” (O*NET task statement)
How this row was scored
Exposure score: 10 out of 100 (3–17 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Showing staff a new technique or a new machine happens hands-on in the kitchen.
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 2/4 · how much data exists 3/4.
Checking the quality of raw or cooked food products to ensure that standards are met
staying humanThis work happens in the physical world: the quality of raw, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Check the quality of raw or cooked food products to ensure that standards are met.” (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: Judging food quality means tasting, smelling and looking 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.
Preparing and cooking foods of all types
staying humanThis work happens in the physical world: foods of all types, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Prepare and cook foods of all types, either on a regular basis or for special guests or functions.” (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: Cooking the food is physical work at the stove.
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
- $62,470a 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
- 200,040in 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: food in, a record out. The rows above are exactly that shape: ordering or requisitioning food or other supplies needed to ensure efficient operation and estimating amounts and costs of required supplies. What it cannot do is be answerable: sanitation practices need a named person the rules will accept, and software cannot be that person. 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
Your week is splitting in two, and which half fills it is the whole question. Ordering or requisitioning food or other supplies needed to ensure efficient operation is going; monitoring sanitation practices to ensure that employees follow standards and regulations is not.
So, given all that: 37% of this job's task weight sits in rows the software is already learning, 0% in rows that change shape rather than disappear, and 63% in rows it is nowhere near. That is the position, measured across 21 scored tasks. It is not a forecast about you.
The occupation is an average and you are not, so the first job below is finding out where your own week actually sits.
This week: one thing
Print the task ledger above and put your own hours next to each row. Roughly, in pen, in one sitting. Then look at which group your hours actually pile up in. Twenty minutes, this week.
- What you end up holding
- your own week, on one page, sorted into what is shifting and what is not
- How long it takes
- about twenty minutes
If printing it isn’t practical: Read the rows off this page and write the same list on the back of an envelope. Same twenty minutes, same page, and it works just as well said out loud to someone who knows the job. The point is your hours next to the rows, not the paper it is on.
Over the next 90 days
Volunteer toward the durable end, visibly. Over the next ninety days put your hand up for the work in the bottom group (monitoring sanitation practices to ensure that employees follow standards and regulations) and let people see you doing it. Not a new project: the same job, with your mix deliberately tilted. The point is that when the rota or the reorganisation comes, the version of you people picture is the one doing the part that stays.
Over the next 12 months
Claim a specialism at the durable end and let the other end go. Over a year, deliberately become the person who handles monitoring sanitation practices to ensure that employees follow standards and regulations, and deliberately stop being the first choice for the rows in the top group. That trade costs something, because the exposed work is often the comfortable work. Decide it on purpose rather than by drift. 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 chefs and head cooks (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was cooks, fast food: only about 16% of its durable work is work you already do and it pays 50.6% less. And on the numbers you do not need one. This job scores 35/100 here, with only 37% of the task list in the top band, and “monitor sanitation practices to ensure that employees follow standards and regulations” 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.
Cooks, Fast Food
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already instruct cooks or other workers in the preparation, cooking, garnishing, or presentation of…, and their equivalent is to clean food preparation areas, cooking surfaces, and utensils. Across both published task lists that is about 16% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 16% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on. It is a pay cut, in those words: $30,890 against your $62,470, 50.6% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Food Service Managers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already instruct cooks or other workers in the preparation, cooking, garnishing, or presentation of…, and their equivalent is to perform some food preparation or service tasks. 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.
First-Line Supervisors of Food Preparation and Serving Workers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already inspect supplies, equipment, or work areas to ensure conformance to established standards, and their equivalent is to inspect supplies, equipment, and work areas to ensure efficient service and conformance to…. 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. It is a pay cut, in those words: $44,080 against your $62,470, 29.4% 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: 37% of its task weight, across 21 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The whole-job doom story
Nothing on this page says this job ends. It says the mix inside it moves. Half the rows above are unchanged or changing shape, and the plan is about which half your week sits in. That is a very different problem, and a solvable one.
Panic-buying a course
Do the twenty-minute sorting exercise first. Most people who buy a course before they have done it buy the wrong one, and the free services listed below will tell you the same thing without charging for it.
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 Chefs 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 Chefs. 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:
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 chefs / head cooks, 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 37% 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 chefs / head cooks. 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 chefs / head cooks launches. Nothing else.
That did not look like an email address, so nothing was saved. Have another go below.
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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 Chefs and Head Cooks?
- Not as a job, but it is already doing parts of the work. Across the 21 official task statements scored for Chefs and Head Cooks (United States, SOC 35-1011), 37% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 35 out of 100 (range 30–41, band: low). 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 “Chefs and Head Cooks” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Order or requisition food or other supplies needed to ensure efficient operation” (93/100, very high); “Record production or operational data on specified forms” (93/100, very high); “Estimate amounts and costs of required supplies, such as food and ingredients” (75/100, 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 “Chefs and Head Cooks” stay human?
- About 63% 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: “Prepare and cook foods of all types, either on a regular basis or for special guests or functions” (0/100, minimal); “Inspect supplies, equipment, or work areas to ensure conformance to established standards” (0/100, minimal); “Check the quantity and quality of received products” (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 “Chefs and Head Cooks” do about AI?
- Start from the ledger rather than the headline: 37% of this job's weighted core work is exposed, and roughly 63% 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 Chefs and Head Cooks 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 21 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.
- 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 2026-08-04.
- 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.