US dataswitch to UK
Taxi Drivers
determining fares based on trip distances and times, turning the taximeter on when passengers enter the cab and driving taxicabs or privately owned vehicles to transport passengers. If that's your week, this page is about your job.
The honest answer
AI changes the edges of this job, not the middle: driving taxicabs or privately owned vehicles to transport passengers is work software can't reach.
What shifts is the routine end of the work: the overhead at the edges, not the middle you trained for.
Your week, as this page understands it
Drive a motor vehicle to transport passengers on an unplanned basis and charge a fare, usually based on a meter. The job title says “taxi drivers”. The real job is the part underneath: driving taxicabs or privately owned vehicles to transport passengers. 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 taxi drivers is not one task. It is 16 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is driving taxicabs or privately owned vehicles to transport passengers, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 0%
- changing shape
- 0%
- staying human
- 100%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 13 out of 100 (10–18 allowing for uncertainty): minimal exposure, across 16 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 taxi drivers 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 2026-08-05. Read the full method.
Your job, task by task
These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.
Shifting to AI
0 tasksTasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.
Nothing in this job’s scored task list landed in this group. That is the measurement, not an editorial choice, and it is worth knowing either way.
Changing shape
0 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.
Nothing in this job’s scored task list landed in this group. That is the measurement, not an editorial choice, and it is worth knowing either way.
Staying human
16 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.
Determining fares based on trip distances and times
This work happens in the physical world: fares, in a real place. Software cannot follow it there.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Determine fares based on trip distances and times, using taximeters and fee schedules, and announce fares to passengers.” (O*NET task statement)
How this row was scored
Exposure score: 39 out of 100 (32–46 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: The meter already calculates the fare; telling the passenger is the part that needs somebody in the cab.
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 1/4 · how much data exists 3/4.
Providing passengers with information or advice about the local area
This work happens in the physical world: passengers, in a real place. Software cannot follow it there.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Provide passengers with information or advice about the local area, points of interest, hotels, or restaurants.” (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: Local recommendations are exactly what map and review services already provide, though passengers often prefer asking the driver.
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.
Completing accident reports
This work happens in the physical world: accident reports, in a real place. Software cannot follow it there.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Complete accident reports when necessary.” (O*NET task statement)
How this row was scored
Exposure score: 33 out of 100 (26–40 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: Accident forms follow a set format software can complete, but the account must come from the person who was there.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Communicating with dispatchers
This work happens in the physical world: dispatchers, in a real place. Software cannot follow it there.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Communicate with dispatchers by radio, telephone, or computer to exchange information and receive requests for passenger service.” (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: Exchanging job details with dispatch is routine messaging already handled by apps, though the driver is at the wheel.
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.
Notifying dispatchers or company mechanics of vehicle problems
This work happens in the physical world: dispatchers, in a real place. Software cannot follow it there.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Notify dispatchers or company mechanics of vehicle problems.” (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: Passing a fault to dispatch or the garage is quick messaging, though spotting it means being with the vehicle.
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.
Turning the taximeter on when passengers enter the cab
This work happens in the physical world: the taximeter, in a real place. Software cannot follow it there.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Turn the taximeter on when passengers enter the cab, and turn it off when they reach the final destination.” (O*NET task statement)
How this row was scored
Exposure score: 23 out of 100 (16–30 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: Apps already start and stop the meter automatically, but the driver is the one in the cab doing it.
The five ratings: output a model can produce 4/4 · 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.
Collecting fares or vouchers from passengers
This work happens in the physical world: fares, in a real place. Software cannot follow it there.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Collect fares or vouchers from passengers, and make change or issue receipts as necessary.” (O*NET task statement)
How this row was scored
Exposure score: 12 out of 100 (5–19 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Card systems handle payment automatically, but taking cash, giving change and issuing receipts happens hand to hand.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Driving taxicabs or privately owned vehicles to transport passengers
This work happens in the physical world: taxicabs, in a real place. Software cannot follow it there.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Drive taxicabs or privately owned vehicles to transport passengers.” (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: Driving passengers is the job itself, done behind the wheel.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 1/4.
Following relevant safety regulations and state laws governing vehicle operation
This work happens in the physical world: relevant safety regulations, in a real place. Software cannot follow it there.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Follow relevant safety regulations and state laws governing vehicle operation, and ensure that passengers follow safety regulations.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–7 allowing for uncertainty): minimal exposure, high confidence, and it moved between repeat runs, so the range is widened.
Why it sits in this group: work that happens in the physical world; someone qualified has to answer for it.
The rating behind it: Following road law and keeping passengers to safety rules happens inside the vehicle while it is being driven.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 3/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Performing minor vehicle repairs, such as cleaning spark plugs or taking vehicles to mechanics for servicing
This work happens in the physical world: minor vehicle repairs, in a real place. Software cannot follow it there.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Perform minor vehicle repairs, such as cleaning spark plugs, or take vehicles to mechanics for servicing.” (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: Minor repairs and garage trips are physical work 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.
Show the other 6 tasks
Performing routine vehicle maintenance, such as regulating tire pressure and adding gasoline, oil and water
staying humanThis work happens in the physical world: routine vehicle maintenance, in a real place. Software cannot follow it there.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Perform routine vehicle maintenance, such as regulating tire pressure and adding gasoline, oil, and water.” (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 fuel, oil and water 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.
Picking up passengers at prearranged locations
staying humanThis work happens in the physical world: passengers, in a real place. Software cannot follow it there.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Pick up passengers at prearranged locations, at taxi stands, or by cruising streets in high-traffic 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: Picking passengers up means being in the car where they are.
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.
Providing passengers with assistance entering and exiting vehicles
staying humanThis work happens in the physical world: passengers, in a real place. Software cannot follow it there.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Provide passengers with assistance entering and exiting vehicles, and help them with any luggage.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Helping someone into a vehicle and lifting their luggage is physical assistance given 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 2/4 · how much data exists 1/4.
Reporting to taxicab services or garages to receive vehicle assignments
staying humanThis work happens in the physical world: taxicab services, in a real place. Software cannot follow it there.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Report to taxicab services or garages to receive vehicle assignments.” (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: Collecting a vehicle assignment means going to the garage.
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.
Testing vehicle equipment, such as lights, brakes, horns or windshield wipers, to ensure proper operation
staying humanThis work happens in the physical world: vehicle equipment, in a real place. Software cannot follow it there.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Test vehicle equipment, such as lights, brakes, horns, or windshield wipers, to ensure proper operation.” (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 lights, brakes, horns and wipers means physically operating and checking them 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.
Vacuuming and cleaning interiors and washing and polish exteriors of automobiles
staying humanThis work happens in the physical world: interiors, in a real place. Software cannot follow it there.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Vacuum and clean interiors and wash and polish exteriors of automobiles.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Vacuuming and washing the cab 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.
What this job pays, and how many people do it
- Median pay
- $42,100a 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
- 41,050in 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. Almost none of this job is reading one thing and writing another (the shape today's tools are built for), because the work turns on taxicabs, which happens with people and things rather than on a screen. The rows above are the evidence rather than the reassurance: determining fares based on trip distances and times and providing passengers with information or advice about the local area. The parts that are changing are the paperwork and the tools around the job, not the middle of it, 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: driving taxicabs or privately owned vehicles to transport passengers is the middle of this job, and the evidence on this page says it stays with a person.
So, given all that: 0% of this job's task weight sits in rows the software is already learning, 0% in rows that change shape rather than disappear, and 100% in rows it is nowhere near. That is the position, measured across 16 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. The routine end of the work 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 the routine work, 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 taxicabs 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 determining fares based on trip distances and times. 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 taxi drivers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was shuttle drivers and chauffeurs: it pays 11.4% less. And on the numbers you do not need one. This job scores 13/100 here, with only 0% of the task list in the top band, and “collect fares or vouchers from passengers, and make change or issue receipts…” 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.
Shuttle Drivers and Chauffeurs
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “test vehicle equipment, such as lights, brakes, horns, or windshield wipers, to ensure proper operation”. Across the whole of both lists that adds up to about 47% of the work in that job the software is not taking.
Why I am not recommending it: It is a pay cut, in those words: $37,290 against your $42,100, 11.4% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Bus Drivers, School
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already test vehicle equipment, such as lights, brakes, horns, or windshield wipers, to ensure…, and their equivalent is to check the condition of a vehicle's tires, brakes, windshield wipers, lights, oil, fuel…. 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.
Bus Drivers, Transit and Intercity
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already collect fares or vouchers from passengers, and make change or issue receipts as…, and their equivalent is to collect tickets or cash fares from passengers. Across both published task lists that is about 5% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 5% of the durable side of that job. That is a different job, not a next step.
What I’d stop worrying about
A friend tells you what not to spend fear on. This is that list.
The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 0% of its task weight, across 16 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 driving taxicabs or privately owned vehicles to transport passengers 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.
If you run a team doing this job
If you run a team doing this job, the conversation you owe them is the one on this page, and sooner than feels comfortable. Show them the ledger rather than a reassurance: the rows moving toward the software are the routine work, and the rows that are not are where you want your people visible. Ask each of them to do the this-week move and bring the list to your next one-to-one. It turns a rumour into a piece of work, and it tells you which parts of your team's week are actually at stake. And say the thing out loud that a team lead usually leaves unsaid: a shrinking team is your exposure too, so do the move yourself as well.
You are reading the United States figures
The United Kingdom splits this work across more than one official group, of which Taxi and cab drivers and chauffeurs is the closest. The pay and employment figures are not directly comparable, and we do not average them together.
Switch to the United Kingdom page →partial match
The other groups this work is counted across:
In UK official statistics this job is counted as Taxi and cab drivers and chauffeurs, Road transport drivers n.e.c. and Delivery drivers and couriers. Pay is shown separately for each of those groups (medians cannot be averaged together), while the task list and the scores on this page are for this group only.
Your route through this
Where to go next, and what it costs
Free, and complete
The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.
Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
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
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 taxi drivers 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 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 Taxi Drivers?
- Not as a job, but it is already doing parts of the work. Across the 16 official task statements scored for Taxi Drivers (United States, SOC 53-3054), 0% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 13 out of 100 (range 10–18, 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 “Taxi Drivers” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Determine fares based on trip distances and times, using taximeters and fee schedules, and announce fares to passengers” (39/100, low); “Provide passengers with information or advice about the local area, points of interest, hotels, or restaurants” (35/100, low); “Complete accident reports when necessary” (33/100, 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 “Taxi Drivers” stay human?
- About 100% 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: “Vacuum and clean interiors and wash and polish exteriors of automobiles” (0/100, minimal); “Test vehicle equipment, such as lights, brakes, horns, or windshield wipers, to ensure proper operation” (0/100, minimal); “Report to taxicab services or garages to receive vehicle assignments” (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 “Taxi Drivers” do about AI?
- Start from the ledger rather than the headline: 0% of this job's weighted core work is exposed, and roughly 100% 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 Taxi Drivers 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 16 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
About the data on this page
- O*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
- One task scored differently between repeat runs, so its range on this page is wider. We would rather show the wobble than hide it.
- The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
- 10 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-with-imputed)
- Scores
- Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
- 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.