US dataswitch to UK
Retail Salespersons
greeting customers and ascertain what each customer wants or needs, preparing sales slips or sales contracts and describing merchandise and explaining. If that's your week, this page is about your job.
The honest answer
AI is already taking a real slice of the routine work here: maintaining knowledge of current sales and promotions. That is a slice of tasks, not of you.
That slice is not coming back; the core of the job, greeting customers and ascertain what each customer wants or needs, stays yours. The tools change, the responsibility doesn't.
Your week, as this page understands it
Sell merchandise, such as furniture, motor vehicles, appliances, or apparel to consumers. The job title says “retail salespersons”. The real job is the part underneath: greeting customers and ascertain what each customer wants or needs. 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 retail salespersons is not one task. It is 24 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is greeting customers and ascertain what each customer wants or needs, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 18%
- changing shape
- 12%
- staying human
- 70%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 31 out of 100 (26–36 allowing for uncertainty): low exposure, across 24 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 retail salespersons 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.
- 2 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
Shifting to AI
4 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.
Maintaining knowledge of current sales and promotions
This is reading one thing and writing another: knowledge of current sales in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Maintain knowledge of current sales and promotions, policies regarding payment and exchanges, and security practices.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (86–100 allowing for uncertainty): very high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Keeping up with current prices, promotions and store policies is remembering and looking up written information, which software does reliably.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Placing special orders or call other stores to find desired items
This is reading one thing and writing another: special orders in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Place special orders or call other stores to find desired items.” (O*NET task statement)
How this row was scored
Exposure score: 85 out of 100 (78–92 allowing for uncertainty): very high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Placing an order or checking another branch's stock is a straightforward system lookup and message that software handles end to end.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 4/4.
Maintaining records related to sales
This is reading one thing and writing another: records in, a record out. That is the shape today's tools are built for.
importance 5 · SupplementalSource: “Maintain records related to sales.” (O*NET task statement)
How this row was scored
Exposure score: 100 out of 100 (96–100 allowing for uncertainty): very 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: Sales records are structured numbers that tills and spreadsheets already keep automatically.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Preparing sales slips or sales contracts
This is reading one thing and writing another: sales slips in, a record out. That is the shape today's tools are built for.
importance 4 · SupplementalSource: “Prepare sales slips or sales contracts.” (O*NET task statement)
How this row was scored
Exposure score: 81 out of 100 (77–85 allowing for uncertainty): very 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: Filling in a sales slip or standard contract from set details is form-filling that software does accurately.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Changing shape
3 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.
Describing merchandise and explaining
The software now makes the first pass at merchandise, but part of it still happens in the physical world. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Describe merchandise and explain use, operation, and care of merchandise to customers.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 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: Explaining what a product does and how to care for it is written information software produces well, though here it is said in person.
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 4/4.
Inventorying stock and requisition new stock
The software now makes the first pass at stock, but part of it still happens in the physical world. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Inventory stock and requisition new stock.” (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: Stock counts and reorder requests are largely handled by inventory systems, though someone still walks the aisles to check what is really there.
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.
Estimating quantity and cost of merchandise
The software now makes the first pass at quantity, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · SupplementalSource: “Estimate quantity and cost of merchandise required, such as paint or floor covering.” (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: Working out how much paint or flooring a room needs is a calculation from measurements, which software does quickly and accurately.
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
17 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.
Greeting customers and ascertain what each customer wants or needs
This work happens in the physical world: customers, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Greet customers and ascertain what each customer wants or needs.” (O*NET task statement)
How this row was scored
Exposure score: 7 out of 100 (0–14 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Software can work out what a shopper needs, but greeting people as they walk into a store still takes a person on the floor.
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 2/4 · how much data exists 3/4.
Recommending, selecting and help locate or obtaining merchandise based on customer needs and desires
This work happens in the physical world: help locate, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Recommend, select, and help locate or obtain merchandise based on customer needs and desires.” (O*NET task statement)
How this row was scored
Exposure score: 24 out of 100 (17–31 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Suggesting the right product is something software does well, but walking to the shelf and putting the item in someone's hands is not.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Answering questions regarding the store and its merchandise
This work happens in the physical world: questions regarding the store, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Answer questions regarding the store and its merchandise.” (O*NET task statement)
How this row was scored
Exposure score: 32 out of 100 (28–36 allowing for uncertainty): low exposure, high 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: Answering questions about stock and store details is what chat assistants do, though in a shop the answers are given 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 1/4 · how much data exists 3/4.
Show the other 14 tasks
Computing sales prices, total purchases and receiving and processing cash or crediting payment
staying humanThis work happens in the physical world: sales prices, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Compute sales prices, total purchases, and receive and process cash or credit payment.” (O*NET task statement)
How this row was scored
Exposure score: 35 out of 100 (31–39 allowing for uncertainty): low exposure, high 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: Working out prices and totals is arithmetic that tills already handle; taking cash across a counter still needs a person.
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.
Selling or arranging
staying humanThe value here is that a specific person handles this work and stands behind it. That is earned, not computed.
importance 4 · SupplementalSource: “Sell or arrange for delivery, insurance, financing, or service contracts for merchandise.” (O*NET task statement)
How this row was scored
Exposure score: 34 out of 100 (27–41 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Arranging delivery, finance or a service contract is paperwork and system entry, though customers often want reassurance from a person.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Estimating and quoting trade-in allowances
staying humanThis work happens in the physical world: trade-in allowances, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Estimate and quote trade-in allowances.” (O*NET task statement)
How this row was scored
Exposure score: 24 out of 100 (17–31 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Guide prices for trade-ins are published data, but judging the condition of the item in front of you needs eyes on it.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Estimating cost of repair or alteration of merchandise
staying humanThis work happens in the physical world: cost of repair, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Estimate cost of repair or alteration of merchandise.” (O*NET task statement)
How this row was scored
Exposure score: 21 out of 100 (14–28 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Pricing a repair or alteration depends on inspecting the actual item and judging the work needed, which is hard to do remotely.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Exchanging merchandise for customers and accept returns
staying humanThis work happens in the physical world: merchandise, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Exchange merchandise for customers and accept returns.” (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: Deciding whether a return is allowed is a rules question, but taking the item back and handling it happens at the counter.
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.
Renting merchandise to customers
staying humanThis work happens in the physical world: merchandise, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Rent merchandise to customers.” (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: The booking side is simple system work, but handing over the item and checking it back in happens in person.
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.
Watching for and recognizing security risks and thefts and know how to prevent or handle these situations
staying humanThis work happens in the physical world: and recognizing security risks, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Watch for and recognize security risks and thefts and know how to prevent or handle these situations.” (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: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Cameras and software can flag suspicious behaviour, but noticing and dealing with it on the shop floor needs someone present.
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 2/4.
Opening and closing cash registers
staying humanThis work happens in the physical world: cash registers, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Open and close cash registers, performing tasks such as counting money, separating charge slips, coupons, and vouchers, balancing cash drawers, and making deposits.” (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: Counting notes and coins, sorting slips and making up a deposit means handling money by hand.
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.
Demonstrating use or operation of merchandise
staying humanThis work happens in the physical world: use or operation of merchandise, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Demonstrate use or operation of merchandise.” (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 a product works means handling it in front of them, so a person has to be there with the item.
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.
Ticketing, arranging and displaying merchandise to promote sales
staying humanThis work happens in the physical world: merchandise, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Ticket, arrange, and display merchandise to promote sales.” (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: Pricing labels, arranging shelves and building displays is physical work done by hand in the store.
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 0/4 · how much data exists 2/4.
Cleaning shelves, counters and tables
staying humanThis work happens in the physical world: shelves, counters and tables, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Clean shelves, counters, and tables.” (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 shelves, counters and tables is physical work that needs a person with a cloth.
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.
Bagging or packaging purchases and wrapping gifts
staying humanThis work happens in the physical world: purchases, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Bag or package purchases and wrap gifts.” (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: Bagging shopping and wrapping gifts is done with your hands 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.
Helping customers try on or fitting merchandise
staying humanThis work happens in the physical world: customers try, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Help customers try on or fit merchandise.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Helping someone try on or fit an item means being physically alongside them.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 1/4.
Preparing merchandise for purchase or rental
staying humanThis work happens in the physical world: merchandise, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Prepare merchandise for purchase or rental.” (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: This is handling the goods themselves, tagging, folding and boxing, which is hands-on work in the shop.
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
- $35,410a 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
- 3,897,860in 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: knowledge of current sales in, a record out. The rows above are exactly that shape: maintaining knowledge of current sales and promotions and placing special orders or call other stores to find desired items. What it cannot do is be there in the room, and that is still where customers get done. Which is why this page talks about your tasks changing, not your job ending.
Your move
Over a pint: what I’d tell you if you were my friend
Start with what does not change: greeting customers and ascertain what each customer wants or needs is the middle of this job, and the evidence on this page says it stays with a person.
So, given all that: 18% of this job's task weight sits in rows the software is already learning, 12% in rows that change shape rather than disappear, and 70% in rows it is nowhere near. That is the position, measured across 24 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. Maintaining knowledge of current sales and promotions 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 knowledge of current sales, 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 help locate 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 describing merchandise and explaining. 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 retail salespersons (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was counter and rental clerks: only about 24% 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 31/100 here, with only 18% of the task list in the top band, and “greet customers and ascertain what each customer wants or needs” 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.
Counter and Rental Clerks
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already prepare merchandise for purchase or rental, and their equivalent is to prepare merchandise for display or for purchase or rental. Across both published task lists that is about 24% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 24% 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 400,810 of those jobs against 3,897,860 of yours (OEWS May 2025), 10% as many seats.
Parts Salespersons
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already ticket, arrange, and display merchandise to promote sales, and their equivalent is to place new merchandise on display. Across both published task lists that is about 15% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 15% 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 270,070 of those jobs against 3,897,860 of yours (OEWS May 2025), 7% as many seats.
Stockers and Order Fillers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already answer questions regarding the store and its merchandise, and their equivalent is to answer customers' questions about merchandise and advise customers on merchandise selection. Across both published task lists that is about 12% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 12% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
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: 18% of its task weight, across 24 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 greeting customers and ascertain what each customer wants or needs 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 Vehicle and parts salespersons and advisers 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 Vehicle and parts salespersons and advisers and Sales and retail assistants. 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.
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Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
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Anywhere in the US:
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No Space for this job, but one for what is happening to it
Nothing Collab365 runs is built for retail salespersons, 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 18% 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 retail salespersons. 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 retail salespersons launches. Nothing else.
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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 Retail Salespersons?
- Not as a job, but it is already doing parts of the work. Across the 24 official task statements scored for Retail Salespersons (United States, SOC 41-2031), 18% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 31 out of 100 (range 26–36, band: low). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
- Which tasks in “Retail Salespersons” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Maintain records related to sales” (100/100, very high); “Maintain knowledge of current sales and promotions, policies regarding payment and exchanges, and security practices” (93/100, very high); “Place special orders or call other stores to find desired items” (85/100, very high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
- Which tasks in “Retail Salespersons” stay human?
- About 70% 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: “Prepare merchandise for purchase or rental” (0/100, minimal); “Help customers try on or fit merchandise” (0/100, minimal); “Bag or package purchases and wrap gifts” (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 “Retail Salespersons” do about AI?
- Start from the ledger rather than the headline: 18% of this job's weighted core work is exposed, and roughly 70% 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 Retail Salespersons 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 24 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.
Where these numbers come from
Worth knowing about these figures
- The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
- 2 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
- Task statements
- onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
- Task weights
- onet-db (im-rt)
- Scores
- Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-04.
- Pay and employment
- bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))
Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.
The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.
The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.
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.