What should someone working in “First-Line Supervisors of Food Preparation and Serving Workers” do about AI?

Start from the ledger rather than the headline: 21% of this job's weighted core work is exposed, and roughly 61% 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.

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First-Line Supervisors of Food Preparation and Serving Workers

compiling and balancing cash receipts at the end of the day or shift, assigning duties and presenting bills and accept payments. If that's your week, this page is about your job.

The honest answer

AI is already taking a real slice of the routine work here: estimating ingredients and supplies required to prepare a recipe. That is a slice of tasks, not of you.

Your move: what you can actually do about this ↓

Where the work sits, by task weight

shifting to AI: 21%
changing shape: 18%
staying human: 61%

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

Whole-job exposure score 35 out of 100 (29–41 allowing for uncertainty): low exposure, across 26 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 first-line supervisors of food preparation and serving workers 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.

That slice is not coming back; the core of the job, supervising and participating in kitchen and dining area cleaning activities, stays yours. The tools change, the responsibility doesn't.

Your week, as this page understands it

Directly supervise and coordinate activities of workers engaged in preparing and serving food. The job title says “first-line supervisors of food preparation” or “serving workers”: officially one job, two names. The real job is the part underneath: supervising and participating in kitchen and dining area cleaning activities. 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 first-line supervisors of food preparation and serving workers is not one task. It is 26 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is supervising and participating in kitchen and dining area cleaning activities, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 21%
changing shape: 18%
staying human: 61%

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 2026-08-04. 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.

1 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Shifting to AI

7 tasks

Tasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.

Estimating ingredients and supplies required to prepare a recipe
This is reading one thing and writing another: ingredients in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Estimate ingredients and supplies required to prepare a recipe.” (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: Scaling a recipe to work out ingredient quantities is straightforward arithmetic for software.
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.
Forecasting staff, equipment and supplying requirements, based on a master menu
This is reading one thing and writing another: staff, equipment and supplying requirements in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Forecast staff, equipment, and supply requirements, based on a master menu.” (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: Predicting staff and supply needs from the menu and past sales is forecasting software handles well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Purchasing or requisitioning supplies and equipment needed to ensure quality and timely delivery of services
This is reading one thing and writing another: supplies in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Purchase or requisition supplies and equipment needed to ensure quality and timely delivery of services.” (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: Placing orders against supplier catalogues and delivery windows is routine purchasing work software does well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Developing equipment maintenance schedules and arranging for repairs
This is reading one thing and writing another: equipment maintenance schedules in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Develop equipment maintenance schedules and arrange for 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: Building a maintenance calendar and booking repairs is scheduling and admin that software handles well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.

Changing shape

4 tasks

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.

Assigning duties, responsibilities and work stations to employees in accordance with work requirements
The software now makes the first pass at duties, responsibilities and work stations, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Assign duties, responsibilities, and work stations to employees in accordance with work requirements.” (O*NET task statement)
How this row was scored
Exposure score: 48 out of 100 (41–55 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: Matching staff to stations against the shift plan is scheduling work that 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 1/4 · how much data exists 3/4.
Specifying food portions and courses
The software now makes the first pass at food portions, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Specify food portions and courses, production and time sequences, and workstation and equipment arrangements.” (O*NET task statement)
How this row was scored
Exposure score: 51 out of 100 (44–58 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; mistakes that are cheap to catch.
The rating behind it: Setting portions, timings and station layouts is planning work that can be worked out on paper.
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 2/4.
Analyzing operational problems, such as theft and wastage and establishing procedures to alleviate these problems
The software now makes the first pass at operational problems, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Analyze operational problems, such as theft and wastage, and establish procedures to alleviate these problems.” (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: Finding where stock and money go missing is pattern spotting in till and inventory data, which 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

15 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.

Resolving customer complaints regarding food service
This work happens in the physical world: customer complaints regarding food service, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Resolve customer complaints regarding food service.” (O*NET task statement)
How this row was scored
Exposure score: 7 out of 100 (0–14 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: Fixing a complaint usually means going to the table and putting the guest at ease face to face.
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 3/4 · how much data exists 2/4.
Training workers in food preparation
This work happens in the physical world: workers, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Train workers in food preparation, and in service, sanitation, and safety procedures.” (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: Course notes can be written by software, but showing someone how to hold a knife happens 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.
Supervising and participating in kitchen and dining area cleaning activities
This work happens in the physical world: kitchen, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Supervise and participate in kitchen and dining area cleaning activities.” (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 a kitchen and dining room is physical work done on the spot.
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.

Show the other 16 tasks

Scheduling parties and taking reservations
shifting to AI
This is reading one thing and writing another: parties in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Schedule parties and take reservations.” (O*NET task statement)
How this row was scored
Exposure score: 79 out of 100 (72–86 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: Taking bookings and slotting parties into a diary is exactly what reservation software already 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 1/4 · how much data exists 3/4.
Recording production, operational and personnel data on specified forms
shifting to AI
This is reading one thing and writing another: production, operational and personnel data in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Record production, operational, and personnel data on specified forms.” (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: Filling in production and staffing forms from system data is routine record-keeping software does accurately.
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.
Developing departmental objectives, budgets, policies, procedures and strategies
shifting to AI
This is reading one thing and writing another: departmental objectives, budgets, policies, procedures and strategies in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Develop departmental objectives, budgets, policies, procedures, and strategies.” (O*NET task statement)
How this row was scored
Exposure score: 68 out of 100 (61–75 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; mistakes that are cheap to catch.
The rating behind it: Drafting departmental goals, budgets and procedures is document work software produces to a usable standard.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Recommending measures for improving work procedures and worker performance to increase service quality and enhance job safety
changing shape
The software now makes the first pass at measures, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Recommend measures for improving work procedures and worker performance to increase service quality and enhance job safety.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; mistakes that are cheap to catch.
The rating behind it: Spotting where a process wastes time and suggesting fixes is analysis software can do from the shift data.
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 1/4 · how much data exists 2/4.
Compiling and balancing cash receipts at the end of the day or shift
staying human
This work happens in the physical world: cash receipts, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Compile and balance cash receipts at the end of the day or shift.” (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: Balancing the takings is arithmetic software does instantly, but counting the drawer is done by hand.
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.
Controlling inventories of food, equipment, smallware and liquor and reporting shortages to designated personnel
staying human
This work happens in the physical world: inventories of food, equipment, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Control inventories of food, equipment, smallware, and liquor, and report shortages to designated personnel.” (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: Stock levels and shortage alerts are tracked in software, but counting the walk-in still means walking in.
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.
Performing various financial activities, such as cash handling, deposit preparation and payroll
staying human
This work happens in the physical world: various financial activities, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Perform various financial activities, such as cash handling, deposit preparation, and payroll.” (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: Payroll and deposit paperwork suit software, but counting and moving cash is hands-on.
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.
Conducting meetings and collaborate with other personnel for menu planning
staying human
The value here is that a specific person handles meetings and stands behind it. That is earned, not computed.
importance 4 · Supplemental
Source: “Conduct meetings and collaborate with other personnel for menu planning, serving arrangements, and related 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: Agendas and notes can be produced by software, but the discussion itself depends on people in the room.
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.
Evaluating new products for usefulness and suitability
staying human
This work happens in the physical world: new products, in a real place. Software cannot follow it there.
importance 3 · Core
Source: “Evaluate new products for usefulness and suitability.” (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: Specifications can be compared on paper, but judging whether a product works usually means tasting or trying it.
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.
Performing personnel actions, such as hiring and firing staff
staying human
The value here is that a specific person handles personnel actions and stands behind it. That is earned, not computed.
importance 4 · Supplemental
Source: “Perform personnel actions, such as hiring and firing staff, providing employee orientation and training, and conducting supervisory activities, such as creating work schedules or organizing employee time sheets.” (O*NET task statement)
How this row was scored
Exposure score: 21 out of 100 (17–25 allowing for uncertainty): low exposure, high confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Rotas can be generated automatically, but hiring and firing are conversations that hinge on 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 2/4.
Observing and evaluating workers and work procedures to ensure quality standards and service
staying human
This work happens in the physical world: workers, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Observe and evaluate workers and work procedures to ensure quality standards and service, and complete disciplinary write-ups.” (O*NET task statement)
How this row was scored
Exposure score: 18 out of 100 (11–25 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: Write-ups can be drafted by software, but judging how a server actually handles a room means watching 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 2/4.
Assessing nutritional needs of patients
staying human
This work happens in the physical world: nutritional needs of patients, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Assess nutritional needs of patients, plan special menus, supervise the assembly of regular and special diet trays, and oversee the delivery of food trolleys to hospital patients.” (O*NET task statement)
How this row was scored
Exposure score: 16 out of 100 (9–23 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; someone qualified has to answer for it.
The rating behind it: Menus can be planned by software, but patient diets need a qualified dietitian and trays are assembled by hand.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 2/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Inspecting supplies, equipment and work areas to ensure efficient service and conformance to standards
staying human
This work happens in the physical world: supplies, equipment and work areas, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Inspect supplies, equipment, and work areas to ensure efficient service and conformance to standards.” (O*NET task statement)
How this row was scored
Exposure score: 13 out of 100 (6–20 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Checking supplies, equipment and work areas against standards means walking round and looking at 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 0/4 · how much data exists 2/4.
Presenting bills and accept payments
staying human
This work happens in the physical world: bills, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Present bills and accept payments.” (O*NET task statement)
How this row was scored
Exposure score: 12 out of 100 (5–19 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: Card readers and pay-at-table apps handle the money, but the bill is still carried over by hand.
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 1/4 · how much data exists 3/4.
Greeting and seating guests and presenting menus and wine lists
staying human
This work happens in the physical world: guests, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Greet and seat guests, and present menus and wine lists.” (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 value is that a specific person does it.
The rating behind it: Greeting and seating guests is the moment a person is physically there to welcome 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 2/4 · how much data exists 2/4.
Performing food preparation and serving duties
staying human
This work happens in the physical world: food preparation, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Perform food preparation and serving duties, such as carving meat, preparing flambe dishes, or serving wine and liquor.” (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: Carving meat and pouring wine are done with hands, in front of the guest.
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 2/4.

What this job pays, and how many people do it

Median pay: $44,080a 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: 1,223,240in 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: staff, equipment and supplying requirements in, a record out. The rows above are exactly that shape: estimating ingredients and supplies required to prepare a recipe and forecasting staff, equipment and supplying requirements. What it cannot do is be there in the room, and that is still where kitchen gets done. Which is why this page talks about your tasks changing, not your job ending.

Your move

Over a pint: what I’d tell you if you were my friend

Your week is splitting in two, and which half fills it is the whole question. Estimating ingredients and supplies required to prepare a recipe is going; supervising and participating in kitchen and dining area cleaning activities is not.

So, given all that: 21% of this job's task weight sits in rows the software is already learning, 18% in rows that change shape rather than disappear, and 61% in rows it is nowhere near. That is the position, measured across 26 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 (supervising and participating in kitchen and dining area cleaning activities) 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 supervising and participating in kitchen and dining area cleaning activities, 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 first-line supervisors of food preparation and serving workers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was first-line supervisors of transportation and material moving workers, except aircraft cargo handling supervisors: only about 10% of its durable work is work you already do. And on the numbers you do not need one. This job scores 35/100 here, with only 21% of the task list in the top band, and “resolve customer complaints regarding food service” 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.

First-Line Supervisors of Transportation and Material Moving Workers, Except Aircraft Cargo Handling Supervisors
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already inspect supplies, equipment, and work areas to ensure efficient service and conformance to…, and their equivalent is to inspect work areas or operating equipment to ensure conformance to established standards in…. 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.
Look at that job’s page anyway →
First-Line Supervisors of Personal Service Workers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already inspect supplies, equipment, and work areas to ensure efficient service and conformance to…, and their equivalent is to inspect work areas or operating equipment to ensure conformance to established standards in…. 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. And it is a narrow door: about 114,110 of those jobs against 1,223,240 of yours (OEWS May 2025), 9% as many seats.
Look at that job’s page anyway →
Hosts and Hostesses, Restaurant, Lounge, and Coffee Shop
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already greet and seat guests, and present menus and wine lists, and their equivalent is to provide guests with menus. 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. It is a pay cut, in those words: $31,200 against your $44,080, 29.2% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
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: 21% of its task weight, across 26 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.

If you run a team doing this job

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

You are reading the United States figures

The United Kingdom splits this work across more than one official group, of which 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

The other groups this work is counted across:

Cooks

In UK official statistics this job is counted as Chefs and Cooks. 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:
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No Space for this job, but one for what is happening to it

Nothing Collab365 runs is built for first-line supervisors of food preparation / serving workers, 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 21% 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 first-line supervisors of food preparation / serving workers. 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 first-line supervisors of food preparation / serving workers launches. Nothing else.

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No Space for first-line supervisors of food preparation / serving workers yet. Should there be one?

Collab365 Spaces is built by the same people as this site. We find the problems that AI and automation are creating inside one kind of work, then solve them as short courses, briefings and Blueprints. Each Space is the community too, so the research and the people doing your job are in the same place.

What a Space actually is, in full

Collab365 launches new communities where the need is real. If one for first-line supervisors of food preparation / serving workers existed, with researched problems, courses and people in the same boat, would you want in?

Your email

We use your email address for one thing: to tell you if a Space for first-line supervisors of food preparation / serving workers launches. We never sell it, never use it for unrelated marketing, and every email has a one-click unsubscribe. Our privacy policy has the full version.

This unlocks nothing. Every figure, every row and every step on this page is already yours, whether you fill this in or not.

No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.

Questions people ask about this job

Will AI replace First-Line Supervisors of Food Preparation and Serving Workers?: Not as a job, but it is already doing parts of the work. Across the 26 official task statements scored for First-Line Supervisors of Food Preparation and Serving Workers (United States, SOC 35-1012), 21% 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 29–41, 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 “First-Line Supervisors of Food Preparation and Serving Workers” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Estimate ingredients and supplies required to prepare a recipe” (93/100, very high); “Schedule parties and take reservations” (79/100, high); “Forecast staff, equipment, and supply requirements, based on a master menu” (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 “First-Line Supervisors of Food Preparation and Serving Workers” stay human?: About 61% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Perform food preparation and serving duties, such as carving meat, preparing flambe dishes, or serving wine and liquor” (0/100, minimal); “Supervise and participate in kitchen and dining area cleaning activities” (0/100, minimal); “Greet and seat guests, and present menus and wine lists” (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 “First-Line Supervisors of Food Preparation and Serving Workers” do about AI?: Start from the ledger rather than the headline: 21% of this job's weighted core work is exposed, and roughly 61% 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 First-Line Supervisors of Food Preparation and Serving Workers 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 26 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

Where these numbers come from

Worth knowing about these figures

The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
1 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Task statements: onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
Task weights: onet-db (im-rt)
Scores: Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-04.
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.

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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}
}

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.