US dataswitch to UK
Sales Managers
overseeing regional and local sales managers and their staffs, planning and directing staffing and determining price schedules and discount rates. If that's your week, this page is about your job.
The honest answer
This job is splitting in two: reviewing operational records and reports to project sales and determining profitability is work AI now does quickly and cheaply, and overseeing regional and local sales managers and their staffs is work it can't touch.
Which half fills your week decides your exposure. That is more in your control than it sounds.
Your week, as this page understands it
Plan, direct, or coordinate the actual distribution or movement of a product or service to the customer. Coordinate sales distribution by establishing sales territories, quotas, and goals and establish training programs for sales representatives. Analyze sales statistics gathered by staff to determine sales potential and inventory requirements and monitor the preferences of customers. The job title says “sales managers”. The real job is the part underneath: overseeing regional and local sales managers and their staffs. 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 sales managers is not one task. It is 17 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is overseeing regional and local sales managers and their staffs, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 35%
- changing shape
- 24%
- staying human
- 41%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 45 out of 100 (39–50 allowing for uncertainty): partial exposure, across 17 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 sales managers 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.
- 3 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
6 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.
Monitoring customer preferences to determine focus of sales efforts
This is reading one thing and writing another: customer preferences in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Monitor customer preferences to determine focus of sales efforts.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Spotting patterns in customer preferences is data analysis.
The five ratings: output a model can produce 3/4 · 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.
Reviewing operational records and reports to project sales and determining profitability
This is reading one thing and writing another: operational records in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Review operational records and reports to project sales and determine profitability.” (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: Projecting sales and profitability from operational records is number work software does at professional quality.
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.
Determining price schedules and discount rates
This is reading one thing and writing another: price schedules in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Determine price schedules and discount rates.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Price schedules and discounts follow from costs and market data, which software analyses well.
The five ratings: output a model can produce 3/4 · 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.
Preparing budgets and approving budget expenditures
This is reading one thing and writing another: budgets in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Prepare budgets and approve budget expenditures.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (62–70 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: Building a budget is number work, though a named person still approves the spending.
The five ratings: output a model can produce 3/4 · 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
4 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.
Planning and directing staffing training and performance evaluations to develop and control sales and service programs
The software now makes the first pass at performance evaluations, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Plan and direct staffing, training, and performance evaluations to develop and control sales and service programs.” (O*NET task statement)
How this row was scored
Exposure score: 40 out of 100 (33–47 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Plans and evaluation paperwork are easy to draft, but developing salespeople rests on knowing them personally.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Resolving customer complaints regarding sales and service
The software now makes the first pass at customer complaints regarding sales, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Resolve customer complaints regarding sales and service.” (O*NET task statement)
How this row was scored
Exposure score: 53 out of 100 (46–60 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; the value is that a specific person does it.
The rating behind it: Software resolves a lot of complaints already, though the ones that reach a manager usually need a person to rebuild trust.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Advising dealers and distributors on policies and operating procedures to ensure functional effectiveness of business
The software now makes the first pass at dealers, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 3 · CoreSource: “Advise dealers and distributors on policies and operating procedures to ensure functional effectiveness of business.” (O*NET task statement)
How this row was scored
Exposure score: 53 out of 100 (46–60 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; the value is that a specific person does it.
The rating behind it: Advising on policies and procedures is guidance drawn from written material, though dealers listen to people they know.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Staying human
7 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.
Overseeing regional and local sales managers and their staffs
The value here is that a specific person handles regional and stands behind it. That is earned, not computed.
importance 5 · CoreSource: “Oversee regional and local sales managers and their staffs.” (O*NET task statement)
How this row was scored
Exposure score: 13 out of 100 (9–17 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Leading other managers rests on a working relationship built face to face over time.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
Directing and coordinating activities involving sales of manufactured products
The value here is that a specific person handles activities involving sales of manufactured products and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Direct and coordinate activities involving sales of manufactured products, services, commodities, real estate, or other subjects of sale.” (O*NET task statement)
How this row was scored
Exposure score: 17 out of 100 (10–24 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Running a sales operation day to day is about directing people, which depends on personal standing.
The five ratings: output a model can produce 1/4 · 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 2/4.
Conferring with potential customers regarding equipment needs
The value here is that a specific person handles potential customers regarding equipment needs and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Confer with potential customers regarding equipment needs, and advise customers on types of equipment to purchase.” (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: the value is that a specific person does it.
The rating behind it: Advising a buyer on what equipment to purchase depends on them trusting the person recommending it.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
Show the other 7 tasks
Assessing marketing potential of new and existing store locations
shifting to AIThis is reading one thing and writing another: potential of new and existing store locations in, a record out. That is the shape today's tools are built for.
importance 3 · SupplementalSource: “Assess marketing potential of new and existing store locations, considering statistics and expenditures.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Assessing a store location's potential from statistics and spending patterns is analysis software does well.
The five ratings: output a model can produce 3/4 · 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.
Directing clerical staff to keep records of export correspondence
shifting to AIThis is reading one thing and writing another: clerical staff in, a record out. That is the shape today's tools are built for.
importance 3 · CoreSource: “Direct clerical staff to keep records of export correspondence, bid requests, and credit collections, and to maintain current information on tariffs, licenses, and restrictions.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Export records, tariffs and licence information are exactly the kind of data software keeps current automatically.
The five ratings: output a model can produce 3/4 · 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 3/4.
Directing, coordinating and reviewing sales and service accounting and record-keeping, as well as receiving and shipping
changing shapeThe software now makes the first pass at sales, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 3 · CoreSource: “Direct, coordinate, and review sales and service accounting and record-keeping, as well as receiving and shipping.” (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: Overseeing sales accounting and record-keeping is mostly checking figures, which software does well.
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.
Conferring or consulting with department heads to plan advertising services and to secure information on equipment and customer specifications
staying humanThe value here is that a specific person handles department heads and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Confer or consult with department heads to plan advertising services and to secure information on equipment and customer specifications.” (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 value is that a specific person does it.
The rating behind it: Planning advertising with other department heads happens through back-and-forth conversation between colleagues.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Directing foreign sales and service outlets of an organization
staying humanThe value here is that a specific person handles foreign sales and stands behind it. That is earned, not computed.
importance 3 · SupplementalSource: “Direct foreign sales and service outlets of an organization.” (O*NET task statement)
How this row was scored
Exposure score: 17 out of 100 (10–24 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Running overseas outlets depends on relationships and local knowledge that rarely appear in any system.
The five ratings: output a model can produce 1/4 · 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 2/4.
Visiting franchised dealers to stimulate interest in establishment or expansion of leasing programs
staying humanThis work happens in the physical world: franchised dealers, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Visit franchised dealers to stimulate interest in establishment or expansion of leasing programs.” (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: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Visiting dealers to build enthusiasm means turning up in person and winning them over.
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 3/4 · how much data exists 2/4.
Representing company at trade association meetings to promote products
staying humanThis work happens in the physical world: company, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Represent company at trade association meetings to promote products.” (O*NET task statement)
How this row was scored
Exposure score: 2 out of 100 (0–6 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: Representing the company at trade meetings is about being there in person.
The five ratings: output a model can produce 0/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
What this job pays, and how many people do it
- Median pay
- $148,270a 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
- 637,080in 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: operational records in, a record out. The rows above are exactly that shape: reviewing operational records and reports to project sales and determining profitability and monitoring customer preferences to determine focus of sales efforts. What it cannot do is be trusted in person, which is what regional runs on: someone specific doing it and standing behind 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
Your week is splitting in two, and which half fills it is the whole question. Reviewing operational records and reports to project sales and determining profitability is going; overseeing regional and local sales managers and their staffs is not.
So, given all that: 35% of this job's task weight sits in rows the software is already learning, 24% in rows that change shape rather than disappear, and 41% in rows it is nowhere near. That is the position, measured across 17 scored tasks. It is not a forecast about you.
The occupation is an average and you are not, so the first job below is finding out where your own week actually sits.
This week: one thing
Print the task ledger above and put your own hours next to each row. Roughly, in pen, in one sitting. Then look at which group your hours actually pile up in. Twenty minutes, this week.
- What you end up holding
- your own week, on one page, sorted into what is shifting and what is not
- How long it takes
- about twenty minutes
If printing it isn’t practical: Read the rows off this page and write the same list on the back of an envelope. Same twenty minutes, same page, and it works just as well said out loud to someone who knows the job. The point is your hours next to the rows, not the paper it is on.
Over the next 90 days
Volunteer toward the durable end, visibly. Over the next ninety days put your hand up for the work in the bottom group (overseeing regional and local sales managers and their staffs) and let people see you doing it. Not a new project: the same job, with your mix deliberately tilted. The point is that when the rota or the reorganisation comes, the version of you people picture is the one doing the part that stays.
Over the next 12 months
Claim a specialism at the durable end and let the other end go. Over a year, deliberately become the person who handles overseeing regional and local sales managers and their staffs, and deliberately stop being the first choice for the rows in the top group. That trade costs something, because the exposed work is often the comfortable work. Decide it on purpose rather than by drift. 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 sales managers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was advertising and promotions managers: only about 12% of its durable work is work you already do and there are far fewer of those jobs than of yours. Your own job splits about 35/65: that share of the list sits in the top exposure band and the rest does not. On this evidence the honest move is inside the job rather than out of it. Become the person who owns “oversee regional and local sales managers and their staffs”, and let the exposed end go.
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.
Advertising and Promotions Managers
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “represent company at trade association meetings to promote products”. Across the whole of both lists that adds up to about 12% of the work in that job the software is not taking.
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. And it is a narrow door: about 21,470 of those jobs against 637,080 of yours (OEWS May 2025), 3% as many seats.
Sales Engineers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already confer with potential customers regarding equipment needs, and advise customers on types of…, and their equivalent is to confer with customers and engineers to assess equipment needs and to determine system…. Across both published task lists that is about 7% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 7% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $124,900 against your $148,270, 15.8% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice. And it is a narrow door: about 51,790 of those jobs against 637,080 of yours (OEWS May 2025), 8% as many seats.
Marketing Managers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already plan and direct staffing, training, and performance evaluations to develop and control sales…, and their equivalent is to direct the hiring, training, or performance evaluations of marketing or sales staff and…. 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: 35% of its task weight, across 17 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The whole-job doom story
Nothing on this page says this job ends. It says the mix inside it moves. Half the rows above are unchanged or changing shape, and the plan is about which half your week sits in. That is a very different problem, and a solvable one.
Panic-buying a course
Do the twenty-minute sorting exercise first. Most people who buy a course before they have done it buy the wrong one, and the free services listed below will tell you the same thing without charging for it.
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 reviewing operational records and reports to project sales and determining profitability, 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 Marketing, sales and advertising directors 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 Marketing, sales and advertising directors, Sales accounts and business development managers and Marketing and commercial managers. 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
Two honest options, and no deadline on either
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
A nearby route
There's no Space built for sales managers yet.
Collab365 Spaces is built by the same people as this site. We find the problems that AI and automation are creating inside one kind of work, then solve them as short courses, briefings and Blueprints. Each Space is the community too, so the research and the people doing your job are in the same place.
The closest match is The AI Authority, a community for non-technical managers and domain experts turning one-off AI prompts into workflows a team can trust. It overlaps with the part of your job that is growing: briefing, checking and delegating AI-assisted work so it is repeatable rather than one person’s trick, and setting the rules that keep a team’s AI output consistent. It is a general professional Space: it covers no selling technique, no pipeline management and nothing about your market. If that overlap isn't you, the free route below covers the same ground.
- Problem: “I can use AI, but I can’t turn it into a workflow my team can trust”
- Problem: “I can’t hand off AI work without it falling apart”
7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.
After the trial it is a paid community, and you get identical data either way. If the overlap above is not your job, the moves above cost nothing and stand on their own.
Noted, and thank you. We’ll email you if a Space for sales managers 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 Sales Managers?
- Not as a job, but it is already doing parts of the work. Across the 17 official task statements scored for Sales Managers (United States, SOC 11-2022), 35% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 45 out of 100 (range 39–50, band: partial). 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 “Sales Managers” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Review operational records and reports to project sales and determine profitability” (93/100, very high); “Monitor customer preferences to determine focus of sales efforts” (75/100, high); “Determine price schedules and discount rates” (75/100, 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 “Sales Managers” stay human?
- About 41% 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: “Represent company at trade association meetings to promote products” (2/100, minimal); “Visit franchised dealers to stimulate interest in establishment or expansion of leasing programs” (7/100, minimal); “Oversee regional and local sales managers and their staffs” (13/100, 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 “Sales Managers” do about AI?
- Start from the ledger rather than the headline: 35% of this job's weighted core work is exposed, and roughly 41% 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 Sales Managers 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 17 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.
- 3 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 2026-08-05.
- 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.