US dataswitch to UK
Automotive and Watercraft Service Attendants
collecting cash payments from customers, cleaning windshields and cleaning parking areas, offices, restrooms or equipment and removing trash. If that's your week, this page is about your job.
The honest answer
AI changes the edges of this job, not the middle: checking tire pressure and levels of fuel is work software can't reach.
What shifts is preparing daily reports of fuel: the paper around the work, not the work.
Your week, as this page understands it
Service automobiles, buses, trucks, boats, and other automotive or marine vehicles with fuel, lubricants, and accessories. Collect payment for services and supplies. May lubricate vehicle, change motor oil, refill antifreeze, or replace lights or other accessories, such as windshield wiper blades or fan belts. May repair or replace tires. The job title says “automotive” or “watercraft service attendants”: officially one job, two names. The real job is the part underneath: checking tire pressure and levels of fuel. 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 automotive and watercraft service attendants is not one task. It is 14 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is checking tire pressure and levels of fuel, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 5%
- changing shape
- 8%
- staying human
- 87%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 9 out of 100 (7–13 allowing for uncertainty): minimal exposure, across 14 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 automotive and watercraft service attendants is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.
How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.
Release: 2026-q4.1, scores computed 2026-08-04. Read the full method.
Your job, task by task
These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.
- 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 taskTasks 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.
Preparing daily reports of fuel
This is reading one thing and writing another: reports of fuel in, a record out. That is the shape today's tools are built for.
importance 4 · SupplementalSource: “Prepare daily reports of fuel, oil, and accessory sales.” (O*NET task statement)
How this row was scored
Exposure score: 69 out of 100 (62–76 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Daily fuel and sales totals come straight from till and pump data, which software already tallies and writes up.
The five ratings: output a model can produce 4/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Changing shape
2 tasksTasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.
Maintaining customer records and following up periodically with telephone
The software now makes the first pass at customer records, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · SupplementalSource: “Maintain customer records and follow up periodically with telephone, mail, or personal reminders of services due.” (O*NET task statement)
How this row was scored
Exposure score: 48 out of 100 (41–55 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Customer records and service reminders are exactly what booking and messaging systems handle, though some follow-up calls stay personal.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Providing customers with information about local roads or highways
The software now makes the first pass at customers, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 2 · SupplementalSource: “Provide customers with information about local roads or highways.” (O*NET task statement)
How this row was scored
Exposure score: 59 out of 100 (52–66 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: Directions and route advice are something mapping tools answer instantly, even though the driver is standing there asking.
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 1/4 · how much data exists 3/4.
Staying human
11 tasksTasks that stay with a person, because they happen in the physical world, because the rules need someone accountable, or because the value is that a specific person does them.
Checking tire pressure and levels of fuel
This work happens in the physical world: tire pressure, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Check tire pressure and levels of fuel, motor oil, transmission, radiator, battery, or other fluids, adding air or fluids as required.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Checking tires and topping up fluids needs hands on the vehicle.
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.
Greasing and lubricating vehicles or specified units
This work happens in the physical world: vehicles, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Grease and lubricate vehicles or specified units, such as springs, universal joints, or steering knuckles, using grease guns or spray lubricants.” (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: Greasing and lubricating parts is physical work with a grease gun.
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.
Selling and installing accessories, such as batteries, windshield wiper blades, fan belts, bulbs or headlamps
This work happens in the physical world: accessories, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Sell and install accessories, such as batteries, windshield wiper blades, fan belts, bulbs, or headlamps.” (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: Fitting batteries, blades or bulbs to a customer vehicle needs hands on the car.
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.
Performing minor repairs, such as adjusting brakes, replacing spark plugs or changing engine oil or filters
This work happens in the physical world: minor repairs, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Perform minor repairs, such as adjusting brakes, replacing spark plugs, or changing engine oil or filters.” (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: Changing oil, plugs or brakes is hands-on work under the hood.
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.
Collecting cash payments from customers
This work happens in the physical world: cash payments, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Collect cash payments from customers, and make change or charge purchases to customers' credit cards, providing customers with receipts.” (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 cash or cards and handing over receipts happens face to face at the pump or counter.
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.
Rotating, testing and repairing or replacing tires
This work happens in the physical world: tires, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Rotate, test, and repair or replace tires.” (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: Rotating, repairing and replacing tires is done by hand with tools.
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.
Cleaning parking areas, offices, restrooms or equipment and removing trash
This work happens in the physical world: areas, offices, restrooms or equipment and removing trash, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Clean parking areas, offices, restrooms, or equipment, and remove trash.” (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 forecourts, restrooms and equipment is physical work in a specific place.
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.
Show the other 4 tasks
Ordering stock and price and shelve incoming goods
staying humanThis work happens in the physical world: stock, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Order stock, and price and shelve incoming goods.” (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: Software can suggest what to reorder and at what price, but someone still has to put stock on shelves.
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.
Activating fuel pumps and filling fuel tanks of vehicles with gasoline or diesel fuel to specified levels
staying humanThis work happens in the physical world: fuel pumps, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Activate fuel pumps and fill fuel tanks of vehicles with gasoline or diesel fuel to specified levels.” (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: Filling a fuel tank means standing at the pump holding the nozzle.
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.
Testing and charging batteries
staying humanThis work happens in the physical world: batteries, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Test and charge batteries.” (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: Testing and charging a battery needs the battery and a charger in front of you.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Cleaning windshields
staying humanThis work happens in the physical world: windshields, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Clean windshields.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Cleaning a windshield is a physical job at the vehicle.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
What this job pays, and how many people do it
- Median pay
- $35,670a 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
- 102,010in 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: reports of fuel in, a record out. The rows above are exactly that shape: preparing daily reports of fuel and maintaining customer records and following up periodically with telephone. What it cannot do is be there in the room, and that is still where tire pressure 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: checking tire pressure and levels of fuel is the middle of this job, and the evidence on this page says it stays with a person.
So, given all that: 5% of this job's task weight sits in rows the software is already learning, 8% in rows that change shape rather than disappear, and 87% in rows it is nowhere near. That is the position, measured across 14 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. Preparing daily reports of fuel 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 reports of fuel, 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 tire pressure is 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 maintaining customer records and following up periodically with telephone. 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 automotive and watercraft service attendants (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was taxi drivers: only about 6% of its durable work is work you already do. And on the numbers you do not need one. This job scores 9/100 here, with only 5% of the task list in the top band, and “check tire pressure and levels of fuel, motor oil, transmission, radiator, battery…” 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.
Taxi Drivers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already perform minor repairs, such as adjusting brakes, replacing spark plugs, or changing engine…, and their equivalent is to perform minor vehicle repairs. Across both published task lists that is about 6% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 6% of the durable side of that job. That is a different job, not a next step.
Cashiers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already collect cash payments from customers, and make change or charge purchases to customers'…, and their equivalent is to issue receipts, refunds, credits, or change due to customers. Across both published task lists that is about 4% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 4% of the durable side of that job. That is a different job, not a next step.
Motorboat Mechanics and Service Technicians
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already perform minor repairs, such as adjusting brakes, replacing spark plugs, or changing engine…, and their equivalent is to perform routine engine maintenance on motorboats. Across both published task lists that is about 4% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 4% of the durable side of that job. That is a different job, not a next step. And it is a narrow door: about 23,220 of those jobs against 102,010 of yours (OEWS May 2025), 23% as many seats.
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: 5% of its task weight, across 14 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 checking tire pressure and levels of fuel 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 Retail cashiers and check-out operators 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 Retail cashiers and check-out operators. Pay and employment stay on this page’s own group; the task list and the scores do not cross over.
Your route through this
Where to go next, and what it costs
Free, and complete
The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.
Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
Free
No Space for this job, but one for what is happening to it
Nothing Collab365 runs is built for automotive / watercraft service attendants, and we are not going to point you at the nearest one and call it a fit.
There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 5% of the work on this page is already inside what they can do.
7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.
The AI Authority is a general community about working with AI, not a course for automotive / watercraft service attendants. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.
Noted, and thank you. We’ll email you if a Space for automotive / watercraft service attendants launches. Nothing else.
That did not look like an email address, so nothing was saved. Have another go below.
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No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.
Questions people ask about this job
- Will AI replace Automotive and Watercraft Service Attendants?
- Not as a job, but it is already doing parts of the work. Across the 14 official task statements scored for Automotive and Watercraft Service Attendants (United States, SOC 53-6031), 5% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 9 out of 100 (range 7–13, 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 “Automotive and Watercraft Service Attendants” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Prepare daily reports of fuel, oil, and accessory sales” (69/100, high); “Provide customers with information about local roads or highways” (59/100, partial); “Maintain customer records and follow up periodically with telephone, mail, or personal reminders of services due” (48/100, partial). 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 “Automotive and Watercraft Service Attendants” stay human?
- About 87% 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: “Clean windshields” (0/100, minimal); “Check tire pressure and levels of fuel, motor oil, transmission, radiator, battery, or other fluids, adding air or fluids as required” (0/100, minimal); “Test and charge batteries” (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 “Automotive and Watercraft Service Attendants” do about AI?
- Start from the ledger rather than the headline: 5% of this job's weighted core work is exposed, and roughly 87% 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 Automotive and Watercraft Service Attendants 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 14 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.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
- Task statements
- onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
- Task weights
- onet-db (im-rt)
- Scores
- Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-04.
- Pay and employment
- bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))
Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.
The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.
The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.
Using these figures?
Cite this
Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.
Plain text
Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).
BibTeX
@misc{collab365futureproof2026q41,
title = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
author = {{Collab365}},
year = {2026},
url = {https://futureproof.collab365.com/data/2026-q4.1},
note = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}Data as of release 2026-q4.1, published . Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.