Will AI replace Food Preparation Workers?

Not as a job, but it is already doing parts of the work. Across the 31 official task statements scored for Food Preparation Workers (United States, SOC 35-2021), 0% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 3 out of 100 (range 2–7, band: minimal). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.

Which tasks in “Food Preparation Workers” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Keep records of the quantities of food used” (56/100, partial); “Inform supervisors when equipment is not working properly and when food and supplies are getting low, and order needed items” (24/100, low); “Take and record temperature of food and food storage areas, such as refrigerators and freezers” (10/100, minimal). 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 Preparation Workers” stay human?

About 98% 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: “Assemble meal trays with foods in accordance with patients' diets” (0/100, minimal); “Vacuum dining area and sweep and mop kitchen floor” (0/100, minimal); “Operate cash register, handle money, and give correct change” (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 Preparation Workers” do about AI?

Start from the ledger rather than the headline: 0% of this job's weighted core work is exposed, and roughly 98% 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 Preparation 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 31 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

US dataswitch to UK

Food Preparation Workers

cleaning and sanitizing work areas, informing supervisors when equipment is not working properly and when food and supplies are getting low and preparing a variety of foods. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: cleaning and sanitizing work areas is work software can't reach.

Your move: what you can actually do about this ↓

Where the work sits, by task weight

shifting to AI: 0%
changing shape: 2%
staying human: 98%

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

Whole-job exposure score 3 out of 100 (2–7 allowing for uncertainty): minimal exposure, across 31 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 preparation 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.

What shifts is keeping records of the quantities of food: the overhead at the edges, not the middle you trained for.

Your week, as this page understands it

Perform a variety of food preparation duties other than cooking, such as preparing cold foods and shellfish, slicing meat, and brewing coffee or tea. The job title says “food preparation workers”. The real job is the part underneath: cleaning and sanitizing work areas. 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 preparation workers is not one task. It is 31 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is cleaning and sanitizing work areas, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 0%
changing shape: 2%
staying human: 98%

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.

2 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

0 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.

Nothing in this job’s scored task list landed in this group. That is the measurement, not an editorial choice, and it is worth knowing either way.

Changing shape

1 task

Tasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.

Keeping records of the quantities of food
The software now makes the first pass at records of the quantities of food, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Supplemental
Source: “Keep records of the quantities of food used.” (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: Usage records come from stock and till systems, so this counting and logging can largely be automated.
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

30 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.

Cleaning and sanitizing work areas
This work happens in the physical world: work areas, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Clean and sanitize work areas, equipment, utensils, dishes, or silverware.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Cleaning and sanitising surfaces, dishes and equipment is hands-on work in the kitchen.
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.
Carrying food supplies, equipment and utensils to and from storage and work areas
This work happens in the physical world: food supplies, equipment and utensils, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Carry food supplies, equipment, and utensils to and from storage and work areas.” (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: Carrying supplies and equipment between storage and the kitchen is physical work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Removing trash and cleaning kitchen garbage containers
This work happens in the physical world: trash, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Remove trash and clean kitchen garbage containers.” (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: Taking out rubbish and scrubbing bins is hands-on work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Storing food in designated containers and storage areas to prevent spoilage
This work happens in the physical world: food, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Store food in designated containers and storage areas to prevent spoilage.” (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: Putting food away correctly is physical handling in the store 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 3/4.
Assisting cooks and kitchen staff with various tasks
This work happens in the physical world: cooks, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Assist cooks and kitchen staff with various tasks as needed, and provide cooks with needed items.” (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: Helping cooks and fetching what they need means being in the kitchen alongside them.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 1/4.
Informing supervisors when equipment is not working properly and when food and supplies are getting low
This work happens in the physical world: supervisors, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Inform supervisors when equipment is not working properly and when food and supplies are getting low, and order needed items.” (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: Stock reordering can be automated from records, but noticing broken equipment comes from being in the 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 1/4 · how much data exists 3/4.
Weighing or measuring ingredients
This work happens in the physical world: ingredients, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Weigh or measure ingredients.” (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: Weighing and measuring ingredients means handling the actual food.
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.
Vacuuming dining area and sweep and mop kitchen floor
This work happens in the physical world: area, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Vacuum dining area and sweep and mop kitchen floor.” (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: Vacuuming, sweeping and mopping floors is physical cleaning work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Washing peel and cutting various foods, such as fruits and vegetables, to prepare for cooking or serving
This work happens in the physical world: peel, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Wash, peel, and cut various foods, such as fruits and vegetables, to prepare for cooking or serving.” (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: Washing, peeling and cutting food is done by hand at the counter.
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 21 tasks

Taking and recording temperature of food and food storage areas
staying human
This work happens in the physical world: temperature of food, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Take and record temperature of food and food storage areas, such as refrigerators and freezers.” (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: Logging the readings is simple, but someone has to physically check the food and fridges with a thermometer.
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.
Packaging take-out foods or serving food to customers
staying human
This work happens in the physical world: take-out foods, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Package take-out foods or serve food to customers.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Packing takeaway food and serving customers is done by hand at the counter.
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.
Portioning and wrapping food or placing it directly on plates for service to patrons
staying human
This work happens in the physical world: food, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Portion and wrap food, or place it directly on plates for service to patrons.” (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: Portioning, wrapping and plating food is done by hand.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Placing food trays over food warmers for immediate service
staying human
This work happens in the physical world: food trays over food warmers, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Place food trays over food warmers for immediate service, or store them in refrigerated storage cabinets.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Moving trays onto warmers or into fridges means lifting and carrying them.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Receiving and storing food supplies
staying human
This work happens in the physical world: food supplies, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Receive and store food supplies, equipment, and utensils in refrigerators, cupboards, and other storage areas.” (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: Taking in deliveries and putting them away is physical work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Stocking cupboards and refrigerators and tend salad bars and buffet meals
staying human
This work happens in the physical world: cupboards, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Stock cupboards and refrigerators, and tend salad bars and buffet meals.” (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: Stocking fridges and topping up salad bars and buffets is physical work on the floor.
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.
Preparing and serving a variety of beverages
staying human
This work happens in the physical world: a variety of beverages, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Prepare and serve a variety of beverages, such as coffee, tea, and soft drinks.” (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: Making and pouring drinks is hands-on work behind the counter.
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 3/4.
Making special dressings and sauces as condiments for sandwiches
staying human
This work happens in the physical world: special dressings, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Make special dressings and sauces as condiments for sandwiches.” (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: Making dressings and sauces means mixing real ingredients in the kitchen.
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.
Scraping leftovers from dishes into garbage containers
staying human
This work happens in the physical world: leftovers, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Scrape leftovers from dishes into garbage containers.” (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: Scraping plates into the bin is physical work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Using manual or electric appliances
staying human
This work happens in the physical world: manual, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Use manual or electric appliances to clean, peel, slice, and trim foods.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Running food through peelers, slicers and trimmers means handling the machines and the food.
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.
Stirring and straining soups and sauces
staying human
This work happens in the physical world: soups, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Stir and strain soups and sauces.” (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: Stirring and straining soups and sauces is done at the stove by hand.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Distributing food to waiters and waitresses to serve to customers
staying human
This work happens in the physical world: food, in a real place. Software cannot follow it there.
importance 5 · Supplemental
Source: “Distribute food to waiters and waitresses to serve to customers.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Passing plated food to serving staff happens at the kitchen pass in person.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 1/4.
Loading dishes, glasses and tableware into dishwashing machines
staying human
This work happens in the physical world: dishes, glasses and tableware, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Load dishes, glasses, and tableware into dishwashing machines.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Loading dishes and glasses into a dishwasher is physical work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Butchering and cleaning fowl, fish, poultry and shellfish to prepare for cooking or serving
staying human
This work happens in the physical world: fowl, fish, poultry and shellfish, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Butcher and clean fowl, fish, poultry, and shellfish to prepare for cooking or serving.” (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: Butchering and cleaning fish and poultry is physical preparation work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Cutting slice or grinding meat
staying human
This work happens in the physical world: slice, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Cut, slice or grind meat, poultry, and seafood to prepare for cooking.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Cutting and grinding meat and fish is hands-on work with knives and machines.
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.
Adding cutlery, napkins, food and other items to trays on assembly lines in hospitals, cafeterias, airline kitchens and similar establishments
staying human
This work happens in the physical world: cutlery, napkins, food and other items, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Add cutlery, napkins, food, and other items to trays on assembly lines in hospitals, cafeterias, airline kitchens, and similar establishments.” (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: Adding items to trays on a line is physical assembly work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Mixing ingredients for green salads
staying human
This work happens in the physical world: ingredients, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Mix ingredients for green salads, molded fruit salads, vegetable salads, and pasta salads.” (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: Mixing salads means handling the ingredients directly.
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.
Distributing menus to hospital patients
staying human
This work happens in the physical world: menus, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Distribute menus to hospital patients, collect diet sheets, and deliver food trays and snacks to nursing units or directly to patients.” (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: Handing out menus and carrying trays to wards is physical work moving around the building.
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.
Preparing a variety of foods
staying human
This work happens in the physical world: a variety of foods, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Prepare a variety of foods, such as meats, vegetables, or desserts, according to customers' orders or supervisors' instructions, following approved procedures.” (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: Cooking and preparing dishes means handling real ingredients and equipment.
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.
Operating cash register, handle money and give correct change
staying human
This work happens in the physical world: cash register, handle money and give correct change, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Operate cash register, handle money, and give correct change.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–7 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 rating behind it: Handling cash and giving change happens at the counter with the customer in front of you.
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 1/4 · how much data exists 3/4.
Assembling meal trays with foods in accordance with patients' diets
staying human
This work happens in the physical world: meal trays, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Assemble meal trays with foods in accordance with patients' diets.” (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: Putting the right food on each patient tray is hands-on assembly work in the kitchen.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 1/4 · 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: $35,320a 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: 893,600in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)

What is deliberately not here: a forecast of how many of these jobs exist in ten years. Where an official projection exists for a market we publish it with its vintage; where it does not, we leave the space empty rather than borrow the other country’s number.

Why this is shifting

The reason is boringly specific. Most of what is shifting here is reading one thing and writing another: records of the quantities of food in, a record out. The rows above are exactly that shape: keeping records of the quantities of food. What it cannot do is be there in the room, and that is still where work areas get done. Which is why this page talks about your tasks changing, not your job ending.

Your move

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

Start with what does not change: cleaning and sanitizing work areas is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 0% of this job's task weight sits in rows the software is already learning, 2% in rows that change shape rather than disappear, and 98% in rows it is nowhere near. That is the position, measured across 31 scored tasks. It is not a forecast about you.

So the thing worth your attention is not the job going away. It is the layer around it. Keeping records of the quantities of food is the part turning into software, and being the person who understands that layer is worth money.

This week: one thing

Ask the one question. Find whoever is bringing new software into your workplace (the manager, the office, whoever runs the system) and ask them what it is meant to do to records of the quantities of food, and what it is not meant to touch. Ten minutes, this week, before anyone decides it for you.

What you end up holding: a straight answer about what is actually being rolled out, and when
How long it takes: ten minutes

If there’s nobody obvious to ask, or you’d rather not ask your manager: Put the same question to your union rep, your shift lead or the person who has been there longest, in person, over a break. Same ten minutes, same answer, and you will usually get a straighter one. Write down what they say. The note is the artifact, and it tells you whether work areas are in scope or not. Nothing to log into, no license needed.

Over the next 90 days

Get inside the tool rollout rather than waiting for it. Over the next ninety days, ask to be in the group that tests, checks or signs off whatever new system arrives near keeping records of the quantities of food. It is usually an unglamorous seat that nobody fights for, and it is the one that decides how the software is used on your job rather than to it.

Over the next 12 months

On this evidence I would not retrain out of this job, and I will say that plainly rather than hedge it. The task list here is dominated by work that stays with a person. What I would do with a year is get formally recognised for the layer around it (the systems, the compliance, the planning), so you are the one who understands the software instead of the one it is done to. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, and it is listed below with the rest of the free routes.

The roads out of here, and why I am not sending you down them

I looked at the obvious moves out of this job, and here is what I found.

I checked the 12 nearest US occupations to food preparation workers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was dishwashers: only about 16% of its durable work is work you already do. And on the numbers you do not need one. This job scores 3/100 here, with only 0% of the task list in the top band, and “clean and sanitize work areas, equipment, utensils, dishes, or silverware” 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.

Dishwashers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already carry food supplies, equipment, and utensils to and from storage and work areas, and their equivalent is to place clean dishes, utensils, or cooking equipment in storage areas. Across both published task lists that is about 16% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 16% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Look at that job’s page anyway →
Fast Food and Counter Workers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already clean and sanitize work areas, equipment, utensils, dishes, or silverware, and their equivalent is to clean or sanitize work areas, utensils, or equipment. Across both published task lists that is about 13% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 13% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on. It is a pay cut, in those words: $31,200 against your $35,320, 11.7% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →
Cooks, Restaurant
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already wash, peel, and cut various foods, and their equivalent is to wash, peel, cut, and seed fruits and vegetables to prepare them for consumption. 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 →

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: 0% of its task weight, across 31 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The headlines about your trade disappearing
They are usually about the technology, not the timetable. Changes to work like cleaning and sanitizing work areas arrive through rules, insurance and money, slowly and visibly. This page tracks the task evidence and will move when it moves.
Retraining out of a job that is holding up
On this evidence I would not spend money leaving. Spend it on the layer around the job instead: the tools, the paperwork, the planning. That is where the change actually is.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.

You are reading the United States figures

The United Kingdom splits this work across more than one official group, of which Kitchen and catering assistants 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:

Bar and catering supervisors

In UK official statistics this job is counted as Kitchen and catering assistants and Bar and catering supervisors. Pay is shown separately for each of those groups (medians cannot be averaged together), while the task list and the scores on this page are for this group only.

Your route through this

Where to go next, and what it costs

Free, and complete

The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.

Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
American Job Center locator
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
- CareerOneStop local help hub
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
CareerOneStop
Free

Why there is no community here

Collab365, who build this site, run paid Spaces for a small number of subjects, and none of them is built for this job. We are not going to point you at the nearest one and call it a fit.

So the free services listed on this page are the whole answer, and it is the same answer we would give a friend.

Noted, and thank you. We’ll email you if a Space for food preparation workers 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 preparation 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 food preparation 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 food preparation 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 Food Preparation Workers?: Not as a job, but it is already doing parts of the work. Across the 31 official task statements scored for Food Preparation Workers (United States, SOC 35-2021), 0% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 3 out of 100 (range 2–7, band: minimal). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
Which tasks in “Food Preparation Workers” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Keep records of the quantities of food used” (56/100, partial); “Inform supervisors when equipment is not working properly and when food and supplies are getting low, and order needed items” (24/100, low); “Take and record temperature of food and food storage areas, such as refrigerators and freezers” (10/100, minimal). 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 Preparation Workers” stay human?: About 98% 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: “Assemble meal trays with foods in accordance with patients' diets” (0/100, minimal); “Vacuum dining area and sweep and mop kitchen floor” (0/100, minimal); “Operate cash register, handle money, and give correct change” (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 Preparation Workers” do about AI?: Start from the ledger rather than the headline: 0% of this job's weighted core work is exposed, and roughly 98% 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 Preparation 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 31 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.
2 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.

How we score a job Download this release Look up another job

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.