Will AI replace Fast Food and Counter Workers?

Not as a job, but it is already doing parts of the work. Across the 46 official task statements scored for Fast Food and Counter Workers (United States, SOC 35-3023), 2% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 10 out of 100 (range 8–15, 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 “Fast Food and Counter Workers” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Create signs to advertise store products or events” (75/100, high); “Balance receipts and payments in cash registers” (41/100, partial); “Monitor and order supplies or food items, and restock as necessary to maintain inventory” (38/100, low). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.

Which tasks in “Fast Food and Counter Workers” stay human?

About 96% 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: “Arrange tables and decorations according to instructions” (0/100, minimal); “Deliver orders to kitchens, and pick up and serve food when it is ready” (0/100, minimal); “Add relishes and garnishes to food orders, according to instructions” (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 “Fast Food and Counter Workers” do about AI?

Start from the ledger rather than the headline: 2% of this job's weighted core work is exposed, and roughly 96% 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 Fast Food and Counter 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 46 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

Fast Food and Counter Workers

receiving and processing customer payments, notifying kitchen personnel of shortages or special orders and taking out garbage. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: preparing or serving hot or cold beverages 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: 2%
changing shape: 2%
staying human: 96%

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

Whole-job exposure score 10 out of 100 (8–15 allowing for uncertainty): minimal exposure, across 46 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 fast food and counter 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 creating signs to advertise store products or events: the overhead at the edges, not the middle you trained for.

Your week, as this page understands it

Perform duties such as taking orders and serving food and beverages. Serve customers at counter or from a steam table. May take payment. May prepare food and beverages. The job title says “fast food” or “counter workers”: officially one job, two names. The real job is the part underneath: preparing or serving hot or cold beverages. 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 fast food and counter workers is not one task. It is 46 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is preparing or serving hot or cold beverages, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 2%
changing shape: 2%
staying human: 96%

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.

5 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

1 task

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.

Creating signs to advertise store products or events
This is reading one thing and writing another: signs in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Create signs to advertise store products or events.” (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: Writing and designing promotional signs is straightforward design and copy work software does well.
The five ratings: output a model can produce 4/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.

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.

Balancing receipts and payments in cash registers
The software now makes the first pass at receipts, but part of it still happens in the physical world. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Balance receipts and payments in cash registers.” (O*NET task statement)
How this row was scored
Exposure score: 41 out of 100 (34–48 allowing for uncertainty): partial 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: Adding up takings and matching them to the till is arithmetic software does, though the cash itself still has to be counted.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.

Staying human

44 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.

Preparing or serving hot or cold beverages
This work happens in the physical world: hot, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Prepare or serve hot or cold beverages, such as coffee, espresso drinks, blended coffees, or teas.” (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 coffee and other drinks is hands-on work at the machine.
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.
Receiving and processing customer payments
This work happens in the physical world: customer payments, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Receive and process customer payments.” (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: Taking payment across a counter, including cash, is physical handling of money.
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 4/4.
Cleaning or 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 or sanitize work areas, utensils, or equipment.” (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 equipment and surfaces 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.
Describing menu items
This work happens in the physical world: menu items, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Describe menu items to customers, or suggest products that might appeal to them.” (O*NET task statement)
How this row was scored
Exposure score: 35 out of 100 (28–42 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Describing menu items and suggesting extras is the kind of information software produces well, though here it is said across the counter.
The five ratings: output a model can produce 4/4 · 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 4/4.
Taking customer orders and conveying them to other employees for preparation
This work happens in the physical world: customer orders, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Take customer orders and convey them to other employees for preparation.” (O*NET task statement)
How this row was scored
Exposure score: 35 out of 100 (28–42 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: Capturing an order and passing it to the team is routine information work that ordering systems already do.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 4/4.
Communicating with customers regarding orders
This work happens in the physical world: customers regarding orders, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Communicate with customers regarding orders, comments, and complaints.” (O*NET task statement)
How this row was scored
Exposure score: 26 out of 100 (19–33 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Handling orders and complaints is conversation software manages well, though at a counter it happens face to face.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Serving customers in eating places that specialize in fast service and inexpensive carry-out food
This work happens in the physical world: customers, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Serve customers in eating places that specialize in fast service and inexpensive carry-out food.” (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: Serving people quickly at a counter is the job of being there 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 2/4.
Serving prepared foods, such as muffins, biscotti or bagels
This work happens in the physical world: prepared foods, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Serve prepared foods, such as muffins, biscotti, or bagels.” (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 over prepared food is done in person 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 36 tasks

Monitoring and ordering supplies or food items
staying human
This work happens in the physical world: supplies, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Monitor and order supplies or food items, and restock as necessary to maintain inventory.” (O*NET task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Tracking stock levels and placing orders is system work, but putting supplies back on the shelf is done by hand.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Providing customers with product details
staying human
This work happens in the physical world: customers, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Provide customers with product details, such as coffee blend or preparation descriptions.” (O*NET task statement)
How this row was scored
Exposure score: 35 out of 100 (28–42 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: Coffee origins and brewing methods are well documented, though customers usually ask across the counter.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 4/4.
Requesting and recording customer orders
staying human
This work happens in the physical world: customer orders, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Request and record customer orders, and compute bills, using cash registers, multi-counting machines, or pencil and paper.” (O*NET task statement)
How this row was scored
Exposure score: 35 out of 100 (28–42 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: Taking an order and totalling a bill is routine information work, and voice ordering systems already do it in some restaurants.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 4/4.
Taking customers' orders and writing ordered items on tickets
staying human
This work happens in the physical world: customers' orders, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Take customers' orders and write ordered items on tickets, giving ticket stubs to customers when needed to identify filled orders.” (O*NET task statement)
How this row was scored
Exposure score: 35 out of 100 (28–42 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: Writing down an order and handing over a ticket number is routine information work software handles.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 4/4.
Notifying kitchen personnel of shortages or special orders
staying human
This work happens in the physical world: kitchen personnel of shortages, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Notify kitchen personnel of shortages or special orders.” (O*NET task statement)
How this row was scored
Exposure score: 32 out of 100 (25–39 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: Flagging a shortage or a special order is a short message that order systems already pass along, though it is often called out in the kitchen.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Performing personnel activities, such as supervising and training employees
staying human
This work happens in the physical world: personnel activities, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Perform personnel activities, such as supervising and training employees.” (O*NET task statement)
How this row was scored
Exposure score: 20 out of 100 (13–27 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Rotas and training material can be drafted by software, but showing a new starter the job happens shoulder to shoulder.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Ordering, receiving or stocking supplies or retail products
staying human
This work happens in the physical world: supplies, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Order, receive, or stock supplies or retail products.” (O*NET task statement)
How this row was scored
Exposure score: 19 out of 100 (12–26 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Placing supply orders is simple system work, but receiving deliveries and shelving stock is done by hand.
The five ratings: output a model can produce 3/4 · 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.
Planning, preparing and delivering meals to individuals with special dietary needs
staying human
This work happens in the physical world: meals, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Plan, prepare, and deliver meals to individuals with special dietary needs.” (O*NET task statement)
How this row was scored
Exposure score: 11 out of 100 (4–18 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Planning meals around dietary needs is something software does well, but cooking and delivering them is hands-on.
The five ratings: output a model can produce 2/4 · 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 3/4.
Checking temperatures of freezers, refrigerators or heating equipment to ensure proper functioning
staying human
This work happens in the physical world: temperatures of freezers, refrigerators or heating equipment, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Check temperatures of freezers, refrigerators, or heating equipment to ensure proper functioning.” (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: Checking fridge and heater temperatures means walking round with a thermometer or reading gauges on site.
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.
Accepting payment from customers and making change
staying human
This work happens in the physical world: payment, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Accept payment from customers, and make change as necessary.” (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: Handling notes and coins and giving change back across a counter is physical work with money.
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 4/4.
Demonstrating the use of retail equipment
staying human
This work happens in the physical world: the use of retail equipment, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Demonstrate the use of retail equipment, such as espresso machines.” (O*NET task statement)
How this row was scored
Exposure score: 9 out of 100 (5–13 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: Showing someone how an espresso machine works means standing at the machine with them.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Cleaning service or seating areas
staying human
This work happens in the physical world: service, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Clean service or seating 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: Cleaning seating and service areas is physical work done on site.
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.
Stocking customer service stations with paper products or beverage preparation items
staying human
This work happens in the physical world: customer service stations, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Stock customer service stations with paper products or beverage preparation 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: Stocking stations with cups, napkins and drink items is manual 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.
Taking out garbage
staying human
This work happens in the physical world: garbage, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Take out garbage.” (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 the rubbish 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.
Weighing, grinding or packing coffee beans for customers
staying human
This work happens in the physical world: coffee beans, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Weigh, grind, or pack coffee beans for 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: Weighing, grinding and packing beans is hands-on work with the machine.
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.
Wrapping, labelling or date food items for sale
staying human
This work happens in the physical world: date food items, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Wrap, label, or date food items for sale.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Wrapping, labelling and dating food is hands-on work with the items.
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 2/4.
Preparing or serving menu items
staying human
This work happens in the physical world: menu items, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Prepare or serve menu items, such as sandwiches or 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: Making up sandwiches and salads is food preparation 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 3/4.
Setting up or restock product displays
staying human
This work happens in the physical world: or restock product displays, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Set up or restock product displays.” (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: Building and refilling product displays means physically moving stock.
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.
Slicing fruits, vegetables, desserts or meats for use in food service
staying human
This work happens in the physical world: fruits, vegetables, desserts or meats, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Slice fruits, vegetables, desserts, or meats for use in food service.” (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: Slicing food is hands-on preparation with a knife.
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 1/4.
Scrubbing and polishing counters, steam tables and other equipment and cleaning glasses, dishes and fountain equipment
staying human
This work happens in the physical world: counters, steam tables and other equipment, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Scrub and polish counters, steam tables, and other equipment, and clean glasses, dishes, and fountain equipment.” (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: Scrubbing counters, steam tables and glassware is cleaning 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.
Performing cleaning duties, such as sweeping, mopping and washing dishes, to keep equipment and facilities sanitary
staying human
This work happens in the physical world: duties, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Perform cleaning duties, such as sweeping, mopping, and washing dishes, to keep equipment and facilities sanitary.” (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: Sweeping, mopping and washing up is physical work that needs someone with a mop.
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.
Serving food, beverages or desserts to customers in such settings as take-out counters of restaurants or lunchrooms
staying human
This work happens in the physical world: food, beverages or desserts, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Serve food, beverages, or desserts to customers in such settings as take-out counters of restaurants or lunchrooms, business or industrial establishments, hotel rooms, and cars.” (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 food and drinks to people is physical work done on the spot.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Preparing daily food items and cooking simple foods and beverages
staying human
This work happens in the physical world: food items, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Prepare daily food items, and cook simple foods and beverages, such as sandwiches, salads, soups, pizza, or coffee, using proper safety precautions and sanitary measures.” (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 sandwiches, soups and coffee is cooking, which needs hands 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.
Cleaning and organizing eating service and kitchen areas
staying human
This work happens in the physical world: service, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Clean and organize eating, service, and kitchen 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: Clearing and tidying eating and kitchen areas is physical work done on site.
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.
Brewing coffee and tea and filling containers with requested beverages
staying human
This work happens in the physical world: coffee, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Brew coffee and tea, and fill containers with requested beverages.” (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: Brewing drinks and filling containers is hands-on work at the machine.
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.
Collecting and returning dirty dishes to the kitchen for washing
staying human
This work happens in the physical world: dirty dishes, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Collect and return dirty dishes to the kitchen for washing.” (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: Gathering dirty dishes and carrying them to 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.
Washing dishes, glassware and silverware after meals
staying human
This work happens in the physical world: dishes, glassware and silverware after meals, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Wash dishes, glassware, and silverware after 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: Washing up after meals is done by hand at the sink.
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.
Wrapping menu items, sandwiches, hot entrees and desserts for serving or for takeout
staying human
This work happens in the physical world: menu items, sandwiches, hot entrees and desserts, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Wrap menu items such as sandwiches, hot entrees, and desserts for serving or for takeout.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Wrapping food for serving or takeaway is done by hand as orders come in.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Preparing and serving cold drinks
staying human
This work happens in the physical world: cold drinks, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Prepare and serve cold drinks, frozen milk drinks, or desserts, using drink-dispensing, milkshake, or frozen-custard 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: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Making up cold drinks and desserts on the machines is hands-on work 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 3/4.
Selecting food items from serving or storage areas and placing them in dishes
staying human
This work happens in the physical world: food items, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Select food items from serving or storage areas and place them in dishes, on serving trays, or in take-out bags.” (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: Picking food from the counter and putting it into dishes or bags 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.
Replenishing foods at serving stations
staying human
This work happens in the physical world: foods, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Replenish foods at serving stations.” (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: Topping up food at serving stations is physical work in the servery.
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 servers
staying human
This work happens in the physical world: food, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Distribute food to servers.” (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 food to servers is physical work in a busy 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.
Setting up dining areas
staying human
This work happens in the physical world: dining areas, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Set up dining areas for meals, and clear them following 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: Setting out and clearing dining areas means moving furniture and tableware yourself.
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 relishes and garnishes to food orders
staying human
This work happens in the physical world: relishes, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Add relishes and garnishes to food orders, according to instructions.” (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 garnishes to plates is done by hand as each order goes out.
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.
Delivering orders to kitchens and pick up and serving food when it is ready
staying human
This work happens in the physical world: orders, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Deliver orders to kitchens, and pick up and serve food when it is ready.” (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 orders to the kitchen and food back out 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 0/4 · how much data exists 2/4.
Arranging tables and decorations according to instructions
staying human
This work happens in the physical world: tables, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Arrange tables and decorations according to instructions.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Arranging tables and decorations means moving them yourself.
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.

What this job pays, and how many people do it

Median pay: $31,200a 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: 3,854,050in 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: signs in, a record out. The rows above are exactly that shape: creating signs to advertise store products or events and balancing receipts and payments in cash registers. What it cannot do is be there in the room, and that is still where hot 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

Start with what does not change: preparing or serving hot or cold beverages is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 2% of this job's task weight sits in rows the software is already learning, 2% in rows that change shape rather than disappear, and 96% in rows it is nowhere near. That is the position, measured across 46 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. Creating signs to advertise store products or events 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 signs, 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 customer payments 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 balancing receipts and payments in cash registers. 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 fast food and counter workers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was food preparation workers: only about 13% of its durable work is work you already do and there are far fewer of those jobs than of yours. And on the numbers you do not need one. This job scores 10/100 here, with only 2% of the task list in the top band, and “prepare or serve hot or cold beverages” 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.

Food Preparation Workers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already clean or sanitize work areas, utensils, or equipment, and their equivalent is to clean and sanitize work areas, equipment, utensils, dishes, or silverware. 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. And it is a narrow door: about 893,600 of those jobs against 3,854,050 of yours (OEWS May 2025), 23% as many seats.
Look at that job’s page anyway →
Dishwashers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already take out garbage, and their equivalent is to clean garbage cans with water or steam. 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. And it is a narrow door: about 477,450 of those jobs against 3,854,050 of yours (OEWS May 2025), 12% as many seats.
Look at that job’s page anyway →
Waiters and Waitresses
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already receive and process customer payments, and their equivalent is to collect payments from customers. Across both published task lists that is about 7% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 7% of the durable side of that job. That is a different job, not a next step.
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: 2% of its task weight, across 46 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The headlines about your trade disappearing
They are usually about the technology, not the timetable. Changes to work like preparing or serving hot or cold beverages 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

In UK official statistics this job is counted as Kitchen and catering assistants. Pay and employment stay on this page’s own group; the task list and the scores do not cross over.

Your route through this

Where to go next, and what it costs

Free, and complete

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

Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
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 fast food / counter 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 fast food / counter 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 fast food / counter 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 fast food / counter 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 Fast Food and Counter Workers?: Not as a job, but it is already doing parts of the work. Across the 46 official task statements scored for Fast Food and Counter Workers (United States, SOC 35-3023), 2% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 10 out of 100 (range 8–15, 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 “Fast Food and Counter Workers” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Create signs to advertise store products or events” (75/100, high); “Balance receipts and payments in cash registers” (41/100, partial); “Monitor and order supplies or food items, and restock as necessary to maintain inventory” (38/100, low). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
Which tasks in “Fast Food and Counter Workers” stay human?: About 96% 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: “Arrange tables and decorations according to instructions” (0/100, minimal); “Deliver orders to kitchens, and pick up and serve food when it is ready” (0/100, minimal); “Add relishes and garnishes to food orders, according to instructions” (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 “Fast Food and Counter Workers” do about AI?: Start from the ledger rather than the headline: 2% of this job's weighted core work is exposed, and roughly 96% 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 Fast Food and Counter 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 46 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.
5 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.