US dataswitch to UK
Parts Salespersons
receiving payment or obtaining credit authorization, reading catalogs and determining replacement parts. 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: managing shipments by researching shipping methods or costs and tracking packages. That is a slice of tasks, not of you.
That slice is not coming back; the core of the job, maintaining and cleaning work and inventory areas, stays yours. The tools change hands, the accountability doesn't.
Your week, as this page understands it
Sell spare and replacement parts and equipment in repair shop or parts store. The job title says “parts salespersons”. The real job is the part underneath: maintaining and cleaning work and inventory areas. That is the thing someone has to be right about.
The exposed part of this job is specific, and we won’t pretend it is coming back. But parts salespersons is not one task. It is 19 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is maintaining and cleaning work and inventory areas, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 17%
- changing shape
- 5%
- staying human
- 78%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 29 out of 100 (25–34 allowing for uncertainty): low exposure, across 19 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 parts 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
3 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.
Reading catalogs, microfiche viewers or computer displays to determine replacement part stock numbers and prices
This is reading one thing and writing another: catalogs, microfiche viewers or computer displays in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Read catalogs, microfiche viewers, or computer displays to determine replacement part stock numbers and prices.” (O*NET task statement)
How this row was scored
Exposure score: 69 out of 100 (65–73 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Looking up part numbers and prices in catalogues is search work software does far faster than flipping through pages.
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.
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 · CoreSource: “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.
Managing shipments by researching shipping methods or costs and tracking packages
This is reading one thing and writing another: shipments in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Manage shipments by researching shipping methods or costs and tracking packages.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 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: Comparing shipping options and tracking parcels is online lookup and record keeping software handles well.
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.
Changing shape
1 taskTasks 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.
Discussing use and features of various parts
The software now makes the first pass at use and features of various parts, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Discuss use and features of various parts, based on knowledge of machines or equipment.” (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: Part features and machine compatibility are documented, so software can explain them, with occasional need to point at the actual item.
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.
Staying human
15 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.
Receiving payment or obtaining credit authorization
This work happens in the physical world: payment, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Receive payment or obtain credit authorization.” (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: Payment and credit authorisation are system steps, but at a parts counter someone is usually standing there handing over a card.
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.
Assisting customers, such as responding to customer complaints and updating them about back-ordered parts
The value here is that a specific person handles customers and stands behind it. That is earned, not computed.
importance 5 · CoreSource: “Assist customers, such as responding to customer complaints and updating them about back-ordered parts.” (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: 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: Software drafts good order and back-order updates, though annoyed customers usually want a person who can sort it out.
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 2/4 · how much data exists 3/4.
Filling customer orders from stock
This work happens in the physical world: customer orders, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Fill customer orders from stock, and place orders when requested items are out of stock.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (10–18 allowing for uncertainty): minimal 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: Picking parts off shelves is hands-on work; only the reordering side happens in a system.
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 0/4 · how much data exists 3/4.
Locating and labelling parts and maintaining inventory of stock
This work happens in the physical world: parts, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Locate and label parts, and maintain inventory of stock.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (10–18 allowing for uncertainty): minimal 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: Finding, labelling and counting physical stock means being in the store with the parts in your hands.
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 0/4 · how much data exists 3/4.
Receiving and filling telephone orders for parts
This work happens in the physical world: telephone orders, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Receive and fill telephone orders for parts.” (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: Taking the order is easy to automate; picking the part off the shelf is not.
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.
Examining returned parts
This work happens in the physical world: returned parts, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Examine returned parts for defects, and exchange defective parts or refund money.” (O*NET task statement)
How this row was scored
Exposure score: 11 out of 100 (7–15 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Judging whether a returned part is faulty means handling and examining it 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 2/4.
Show the other 9 tasks
Advising customers on substitution or modification of parts when identical replacements are not available
staying humanThe value here is that a specific person handles customers and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Advise customers on substitution or modification of parts when identical replacements are not available.” (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: 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: Cross-reference data makes substitution advice easy to generate, though customers weigh it against the person's reputation for getting it right.
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 2/4 · how much data exists 3/4.
Determining replacement parts required, according to inspections of old parts, customer requests or customers' descriptions of malfunctions
staying humanThis work happens in the physical world: replacement parts, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Determine replacement parts required, according to inspections of old parts, customer requests, or customers' descriptions of malfunctions.” (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: Software can match a described fault to likely parts, but inspecting the old part means having it in front of you.
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.
Demonstrating equipment to customers and explaining functioning of equipment
staying humanThis work happens in the physical world: equipment, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Demonstrate equipment to customers, and explain functioning of equipment.” (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 value is that a specific person does it.
The rating behind it: Showing equipment working means having it there and operating it in front of the customer.
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 2/4 · how much data exists 3/4.
Marking and storing parts in stockrooms
staying humanThis work happens in the physical world: parts, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Mark and store parts in stockrooms, according to prearranged systems.” (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: Marking parts and putting them in the right place in a stockroom is physical work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Placing new merchandise on display
staying humanThis work happens in the physical world: new merchandise, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Place new merchandise on display.” (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: Putting new stock out on shelves and displays is physical work in the store.
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.
Measuring parts, using precision measuring instruments, to determine whether similar parts may be machined to required sizes
staying humanThis work happens in the physical world: parts, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Measure parts, using precision measuring instruments, to determine whether similar parts may be machined to required sizes.” (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: Measuring parts with calipers and gauges is hands-on work with the item 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.
Repairing parts or equipment
staying humanThis work happens in the physical world: parts, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Repair parts or equipment.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Repairing a part means working on it 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.
Picking up and delivering parts
staying humanThis work happens in the physical world: and delivering parts, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Pick up and deliver parts.” (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 and delivering parts is entirely about moving physical goods.
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.
Maintaining and cleaning work and inventory areas
staying humanThis work happens in the physical world: work, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Maintain and clean work and inventory areas.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Cleaning and tidying the counter and stockroom is entirely hands-on work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
What this job pays, and how many people do it
- Median pay
- $38,630a 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
- 270,070in 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: catalogs, microfiche viewers or computer displays in, a record out. The rows above are exactly that shape: managing shipments by researching shipping methods or costs and tracking packages and reading catalogs. What it cannot do is be there in the room, and that is still where work 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: maintaining and cleaning work and inventory areas is the middle of this job, and the evidence on this page says it stays with a person.
So, given all that: 17% of this job's task weight sits in rows the software is already learning, 5% in rows that change shape rather than disappear, and 78% in rows it is nowhere near. That is the position, measured across 19 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. Managing shipments by researching shipping methods or costs and tracking packages 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 catalogs, microfiche viewers or computer displays, and what it is not meant to touch. Ten minutes, this week, before anyone decides it for you.
- What you end up holding
- a straight answer about what is actually being rolled out, and when
- How long it takes
- ten minutes
If there’s nobody obvious to ask, or you’d rather not ask your manager: Put the same question to your union rep, your shift lead or the person who has been there longest, in person, over a break. Same ten minutes, same answer, and you will usually get a straighter one. Write down what they say. The note is the artifact, and it tells you whether work 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 discussing use and features of various parts. 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 parts salespersons (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was first-line supervisors of retail sales workers: only about 15% of its durable work is work you already do. And on the numbers you do not need one. This job scores 29/100 here, with only 17% of the task list in the top band, and “receive payment or obtain credit authorization” 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.
First-Line Supervisors of Retail Sales Workers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already assist customers, such as responding to customer complaints and updating them about back-ordered…, and their equivalent is to provide customer service by greeting and assisting customers and responding to customer inquiries…. 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.
Industrial Machinery Mechanics
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already demonstrate equipment to customers, and explain functioning of equipment, and their equivalent is to demonstrate equipment functions and features to machine operators. Across both published task lists that is about 8% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 8% of the durable side of that job. That is a different job, not a next step.
Order Clerks
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already assist customers, such as responding to customer complaints and updating them about back-ordered…, and their equivalent is to receive and respond to customer complaints. 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. I will not move you off one melting floe onto another: 68% of its own task list already scores in the top exposure band (72/100 in this release), so the same software is eating it.
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: 17% of its task weight, across 19 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 maintaining and cleaning work and inventory areas arrive through rules, insurance and money, slowly and visibly. This page tracks the task evidence and will move when it moves.
Retraining out of a job that is holding up
On this evidence I would not spend money leaving. Spend it on the layer around the job instead: the tools, the paperwork, the planning. That is where the change actually is.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.
You are reading the United States figures
The United Kingdom splits this work across more than one official group, of which 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.
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 parts 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 17% 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 parts 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 parts salespersons 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 Parts Salespersons?
- Not as a job, but it is already doing parts of the work. Across the 19 official task statements scored for Parts Salespersons (United States, SOC 41-2022), 17% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 29 out of 100 (range 25–34, 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 “Parts Salespersons” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Manage shipments by researching shipping methods or costs and tracking packages” (93/100, very high); “Prepare sales slips or sales contracts” (81/100, very high); “Read catalogs, microfiche viewers, or computer displays to determine replacement part stock numbers and prices” (69/100, 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 “Parts Salespersons” stay human?
- About 78% 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: “Maintain and clean work and inventory areas” (0/100, minimal); “Pick up and deliver parts” (0/100, minimal); “Repair parts or equipment” (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 “Parts Salespersons” do about AI?
- Start from the ledger rather than the headline: 17% of this job's weighted core work is exposed, and roughly 78% 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 Parts 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 19 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.