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Food Service Managers

monitoring employee and patron activities to ensure liquor regulations, monitoring budgets and payroll records and scheduling and receiving food and beverage deliveries. 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: establishing standards for personnel performance and customer service. That is a slice of tasks, not of you.

Your move: what you can actually do about this ↓

That slice is not coming back; the core of the job, performing some food preparation or service tasks, stays yours. New tools, same person answering for it.

Your week, as this page understands it

Plan, direct, or coordinate activities of an organization or department that serves food and beverages. The job title says “food service managers”. The real job is the part underneath: performing some food preparation or service tasks. 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 food service managers is not one task. It is 28 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is performing some food preparation or service tasks, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI
31%
changing shape
15%
staying human
54%

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

Whole-job exposure score 38 out of 100 (33–44 allowing for uncertainty): low exposure, across 28 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 food service managers 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.

Shifting to AI

9 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.

  • Establishing standards for personnel performance and customer service

    This is reading one thing and writing another: standards in, a record out. That is the shape today's tools are built for.

    importance 5 · Core
    Source: “Establish standards for personnel performance and customer service.” (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: Writing performance and service standards is document work AI drafts well, though managers still set the expectations.

    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.

  • Ordering and purchasing equipment and supplies

    This is reading one thing and writing another: equipment in, a record out. That is the shape today's tools are built for.

    importance 4 · Core
    Source: “Order and purchase equipment and supplies.” (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: Choosing and ordering supplies is a documented purchasing job that software can prepare and place.

    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.

  • Scheduling staff hours and assigning duties

    This is reading one thing and writing another: staff hours in, a record out. That is the shape today's tools are built for.

    importance 4 · Core
    Source: “Schedule staff hours and assign duties.” (O*NET task statement)
    How this row was scored

    Exposure score: 64 out of 100 (60–68 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: Building rotas and duty assignments from availability and demand is exactly what scheduling software already 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.

  • Estimating food, liquor, wine and other beverage consumption to anticipate amounts

    This is reading one thing and writing another: food, liquor, wine and other beverage consumption in, a record out. That is the shape today's tools are built for.

    importance 4 · Core
    Source: “Estimate food, liquor, wine, and other beverage consumption to anticipate amounts to be purchased or requisitioned.” (O*NET task statement)
    How this row was scored

    Exposure score: 75 out of 100 (71–79 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: Predicting how much food and drink will be used is forecasting that software does well from past sales.

    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.

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.

  • Reviewing work procedures and operational problems to determine ways to improve service

    The software now makes the first pass at work procedures, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.

    importance 4 · Core
    Source: “Review work procedures and operational problems to determine ways to improve service, performance, or safety.” (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: Reviewing procedures and problems to find improvements is analysis software supports 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.

  • Keeping records required by government agencies regarding sanitation or food subsidies

    The software now makes the first pass at records, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.

    importance 4 · Core
    Source: “Keep records required by government agencies regarding sanitation or food subsidies.” (O*NET task statement)
    How this row was scored

    Exposure score: 42 out of 100 (35–49 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; someone qualified has to answer for it.

    The rating behind it: The records are structured forms software can fill, but the business is legally responsible for them.

    The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.

  • Arranging for equipment maintenance and repairs

    The software now makes the first pass at equipment maintenance, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.

    importance 4 · Core
    Source: “Arrange for equipment maintenance and repairs, and coordinate a variety of services, such as waste removal and pest control.” (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: Arranging repairs and services is scheduling and phone work that can largely be handled automatically.

    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.

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.

  • Investigating and resolving complaints regarding food quality

    This work happens in the physical world: complaints regarding food quality, in a real place. Software cannot follow it there.

    importance 4 · Core
    Source: “Investigate and resolve complaints regarding food quality, service, or accommodations.” (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: Much of this happens face to face with an unhappy guest, though written replies and complaint logs can be drafted.

    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.

  • Performing some food preparation or service tasks

    This work happens in the physical world: some food preparation, in a real place. Software cannot follow it there.

    importance 4 · Core
    Source: “Perform some food preparation or service tasks, such as cooking, clearing tables, and serving food and drinks when necessary.” (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, clearing tables and serving food are hands-on jobs that need a person in the room.

    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.

  • Scheduling and receiving food and beverage deliveries

    This work happens in the physical world: food, in a real place. Software cannot follow it there.

    importance 4 · Core
    Source: “Schedule and receive food and beverage deliveries, checking delivery contents to verify product quality and quantity.” (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; mistakes that are cheap to catch; work that happens in the physical world.

    The rating behind it: Booking deliveries can be automated, but someone has to be on the loading bay checking what actually arrived.

    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 1/4 · how much data exists 3/4.

Show the other 18 tasks

  • Recording the number, type and cost of items sold to determine which items may be unpopular or less profitable

    shifting to AI

    This is reading one thing and writing another: the number, type and cost of items sold in, a record out. That is the shape today's tools are built for.

    importance 4 · Supplemental
    Source: “Record the number, type, and cost of items sold to determine which items may be unpopular or less profitable.” (O*NET task statement)
    How this row was scored

    Exposure score: 93 out of 100 (86–100 allowing for uncertainty): very high exposure, medium confidence.

    Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.

    The rating behind it: Sales data already sits in the till system, and working out which dishes lose money is routine number crunching.

    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.

  • Taking dining reservations

    shifting to AI

    This is reading one thing and writing another: reservations in, a record out. That is the shape today's tools are built for.

    importance 4 · Supplemental
    Source: “Take dining reservations.” (O*NET task statement)
    How this row was scored

    Exposure score: 79 out of 100 (75–83 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: Taking bookings is already handled by online systems and automated phone answering in most restaurants.

    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.

  • Monitoring budgets and payroll records

    shifting to AI

    This is reading one thing and writing another: budgets in, a record out. That is the shape today's tools are built for.

    importance 4 · Core
    Source: “Monitor budgets and payroll records, and review financial transactions to ensure that expenditures are authorized and budgeted.” (O*NET task statement)
    How this row was scored

    Exposure score: 75 out of 100 (71–79 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: Checking spending against budget and flagging unauthorised transactions is number work that software does quickly and accurately.

    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.

  • Reviewing menus and analyzing recipes to determine labor and overhead costs

    shifting to AI

    This is reading one thing and writing another: menus in, a record out. That is the shape today's tools are built for.

    importance 4 · Supplemental
    Source: “Review menus and analyze recipes to determine labor and overhead costs, and assign prices to menu items.” (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 prices is arithmetic on known ingredient and labour costs, though local pricing judgement still helps.

    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.

  • Planning menus and food utilization

    shifting to AI

    This is reading one thing and writing another: menus in, a record out. That is the shape today's tools are built for.

    importance 4 · Supplemental
    Source: “Plan menus and food utilization, based on anticipated number of guests, nutritional value, palatability, popularity, and 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: Menu planning against guest numbers, nutrition and cost is largely a paper exercise that software drafts 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.

  • Establishing and enforcing nutritional standards for dining establishments

    changing shape

    The software now makes the first pass at nutritional standards, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.

    importance 3 · Supplemental
    Source: “Establish and enforce nutritional standards for dining establishments, based on accepted industry standards.” (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: Nutritional standards are published and easy to write into policy, though enforcing them means checking the kitchen.

    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.

  • Organizing and directing worker training programs

    staying human

    The value here is that a specific person handles worker training programs and stands behind it. That is earned, not computed.

    importance 4 · Core
    Source: “Organize and direct worker training programs, resolve personnel problems, hire new staff, and evaluate employee performance in dining and lodging facilities.” (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: Training material writes itself easily, but hiring, discipline and appraisals rest on face-to-face judgement about people.

    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.

  • Assessing staffing needs and recruiting staff

    staying human

    The value here is that a specific person handles needs and stands behind it. That is earned, not computed.

    importance 4 · Core
    Source: “Assess staffing needs and recruit staff, using methods such as newspaper advertisements or attendance at job fairs.” (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: Working out staffing numbers is straightforward analysis, but recruiting still means meeting and judging candidates in person.

    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.

  • Scheduling use of facilities or catering services

    staying human

    The value here is that a specific person handles use of facilities and stands behind it. That is earned, not computed.

    importance 3 · Supplemental
    Source: “Schedule use of facilities or catering services for events such as banquets or receptions, and negotiate details of arrangements with clients.” (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: Diary management is easy to automate, but agreeing event details with a client rests on conversation 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 2/4 · how much data exists 3/4.

  • Maintaining food and equipment inventories

    staying human

    This work happens in the physical world: food, in a real place. Software cannot follow it there.

    importance 4 · Core
    Source: “Maintain food and equipment inventories, and keep inventory records.” (O*NET task statement)
    How this row was scored

    Exposure score: 29 out of 100 (22–36 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: Counting stock means walking the store room, though the record keeping and reorder maths are easily automated.

    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 3/4.

  • Creating specialty dishes and developing recipes to be used in dining facilities

    staying human

    This work happens in the physical world: specialty dishes, in a real place. Software cannot follow it there.

    importance 4 · Supplemental
    Source: “Create specialty dishes and develop recipes to be used in dining facilities.” (O*NET task statement)
    How this row was scored

    Exposure score: 29 out of 100 (22–36 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: AI can suggest recipes, but a dish only exists once someone cooks and tastes it in a real kitchen.

    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 3/4.

  • Coordinating assignments of cooking personnel to ensure economical use of food and timely preparation

    staying human

    This work happens in the physical world: assignments of cooking personnel, in a real place. Software cannot follow it there.

    importance 4 · Core
    Source: “Coordinate assignments of cooking personnel to ensure economical use of food and timely preparation.” (O*NET task statement)
    How this row was scored

    Exposure score: 21 out of 100 (14–28 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: Kitchen coordination happens live on the line, though the planning behind it can be worked out in advance.

    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 1/4 · how much data exists 2/4.

  • Monitoring compliance with health and fire regulations regarding food preparation and serving

    staying human

    This work happens in the physical world: compliance, in a real place. Software cannot follow it there.

    importance 4 · Core
    Source: “Monitor compliance with health and fire regulations regarding food preparation and serving, and building maintenance in lodging and dining facilities.” (O*NET task statement)
    How this row was scored

    Exposure score: 10 out of 100 (6–14 allowing for uncertainty): minimal exposure, high confidence.

    Why it sits in this group: the same decision, made over and over; work that happens in the physical world.

    The rating behind it: The rules are written down, but checking that a kitchen actually follows them means walking round the building.

    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 0/4 · how much data exists 3/4.

  • Monitoring food preparation methods, portion sizes and garnishing and presentation of food to ensure that food is prepared and presented in an acceptable manner

    staying human

    This work happens in the physical world: food preparation methods, in a real place. Software cannot follow it there.

    importance 4 · Core
    Source: “Monitor food preparation methods, portion sizes, and garnishing and presentation of food to ensure that food is prepared and presented in an acceptable manner.” (O*NET task statement)
    How this row was scored

    Exposure score: 7 out of 100 (3–11 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 portion size, garnish and presentation means standing in the kitchen looking at real plates.

    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 1/4 · how much data exists 2/4.

  • Monitoring employee and patron activities to ensure liquor regulations

    staying human

    This work happens in the physical world: employee, in a real place. Software cannot follow it there.

    importance 5 · Supplemental
    Source: “Monitor employee and patron activities to ensure liquor regulations are obeyed.” (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 rating behind it: Spotting over-serving or under-age drinking means being on the floor watching people, and the licence holder carries responsibility.

    The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.

  • Testing cooked food by tasting and smelling it to ensure palatability and flavor conformity

    staying human

    This work happens in the physical world: cooked food, in a real place. Software cannot follow it there.

    importance 4 · Core
    Source: “Test cooked food by tasting and smelling it to ensure palatability and flavor conformity.” (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: Tasting and smelling food needs a mouth and a nose in the room.

    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 0/4.

  • Greeting guests, escort them to their seats and presenting them with menus and wine lists

    staying human

    This work happens in the physical world: guests, escort them, in a real place. Software cannot follow it there.

    importance 5 · Supplemental
    Source: “Greet guests, escort them to their seats, and present them with 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 something a person does in the room.

    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 2/4 · how much data exists 2/4.

  • Counting money and making bank deposits

    staying human

    This work happens in the physical world: money, in a real place. Software cannot follow it there.

    importance 5 · Core
    Source: “Count money and make bank deposits.” (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: the same decision, made over and over; work that happens in the physical world.

    The rating behind it: Handling cash and taking it to the bank is physical work that software cannot do for you.

    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 3/4.

What this job pays, and how many people do it

Median pay
$69,390a 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
238,430in 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: work procedures in, a record out. The rows above are exactly that shape: establishing standards for personnel performance and customer service and ordering and purchasing equipment and supplies. What it cannot do is be there in the room, and that is still where some food preparation 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. Establishing standards for personnel performance and customer service is going; performing some food preparation or service tasks is not.

So, given all that: 31% of this job's task weight sits in rows the software is already learning, 15% in rows that change shape rather than disappear, and 54% in rows it is nowhere near. That is the position, measured across 28 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 (performing some food preparation or service tasks) 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 performing some food preparation or service tasks, 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 food service managers (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 food preparation and serving workers: only about 9% of its durable work is work you already do and it pays 36.5% less. And on the numbers you do not need one. This job scores 38/100 here, with only 31% of the task list in the top band, and “investigate and resolve complaints regarding food quality, service, or accommodations” 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 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 investigate and resolve complaints regarding food quality, service, or accommodations, and their equivalent is to resolve customer complaints regarding food service. 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: $44,080 against your $69,390, 36.5% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.

    Look at that job’s page anyway →

  • Chefs and Head Cooks

    Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already schedule and receive food and beverage deliveries, checking delivery contents to verify product…, and their equivalent is to check the quantity and quality of received products. Across both published task lists that is about 8% of the durable work in that job.

    Why I am not recommending it: Almost none of it is work you already do: about 8% of the durable side of that job. That is a different job, not a next step.

    Look at that job’s page anyway →

  • Cooks, Fast Food

    Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already schedule and receive food and beverage deliveries, checking delivery contents to verify product…, and their equivalent is to verify that prepared food meets requirements for quality and quantity. Across both published task lists that is about 6% of the durable work in that job.

    Why I am not recommending it: Almost none of it is work you already do: about 6% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $30,890 against your $69,390, 55.5% 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: 31% of its task weight, across 28 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 establishing standards for personnel performance and customer service, 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 Restaurant and catering establishment managers and proprietors 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 Restaurant and catering establishment managers and proprietors. 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.

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

Nothing Collab365 runs is built for food service managers, 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 31% 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 food service managers. 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 food service managers launches. Nothing else.

That did not look like an email address, so nothing was saved. Have another go below.

We could not save that. The fault is ours, not yours, and your address was not stored. Please try again later.

No Space for food service managers 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 food service managers existed, with researched problems, courses and people in the same boat, would you want in?

We use your email address for one thing: to tell you if a Space for food service managers 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 Food Service Managers?
Not as a job, but it is already doing parts of the work. Across the 28 official task statements scored for Food Service Managers (United States, SOC 11-9051), 31% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 38 out of 100 (range 33–44, 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 “Food Service Managers” can AI already do?
The highest-scoring tasks in release 2026-q4.1 are: “Record the number, type, and cost of items sold to determine which items may be unpopular or less profitable” (93/100, very high); “Take dining reservations” (79/100, high); “Monitor budgets and payroll records, and review financial transactions to ensure that expenditures are authorized and budgeted” (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 “Food Service Managers” stay human?
About 54% 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: “Count money and make bank deposits” (0/100, minimal); “Greet guests, escort them to their seats, and present them with menus and wine lists” (0/100, minimal); “Perform some food preparation or service tasks, such as cooking, clearing tables, and serving food and drinks when necessary” (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 “Food Service Managers” do about AI?
Start from the ledger rather than the headline: 31% of this job's weighted core work is exposed, and roughly 54% 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 Food Service Managers 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 28 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.

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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 . 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.