US dataswitch to UK
Sales Engineers
selling products requiring extensive technical expertise and supporting, planning and modifying product configurations to meet customer needs and recommending improved materials or machinery. If that's your week, this page is about your job.
The honest answer
This job is splitting in two: researching and identifying potential customers for products or services is work AI now does quickly and cheaply, and visiting prospective buyers at commercial is work it can't touch.
Which half fills your week decides your exposure. The ledger below shows which rows you can move toward.
Your week, as this page understands it
Sell business goods or services, the selling of which requires a technical background equivalent to a baccalaureate degree in engineering. The job title says “sales engineers”. The real job is the part underneath: visiting prospective buyers at commercial. 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 engineers is not one task. It is 25 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is visiting prospective buyers at commercial, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 40%
- changing shape
- 28%
- staying human
- 31%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 55 out of 100 (50–61 allowing for uncertainty): partial exposure, across 25 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 engineers is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.
How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.
Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.
Your job, task by task
These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.
- 1 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
10 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.
Developing, presenting or responding to proposals for specific customer requirements
This is reading one thing and writing another: proposals in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Develop, present, or respond to proposals for specific customer requirements, including request for proposal responses and industry-specific solutions.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (60–68 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: Proposal and tender responses are document work AI drafts well, though the customer relationship shapes what goes in.
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.
Keeping informed on industry news and trends
This is reading one thing and writing another: informed in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Keep informed on industry news and trends, products, services, competitors, relevant information about legacy, existing, and emerging technologies, and the latest product-line developments.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (76–90 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: Following industry news, competitors and product developments is reading and summarizing across published sources.
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 4/4.
Creating sales or service contracts for products or services
This is reading one thing and writing another: sales in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Create sales or service contracts for products or services.” (O*NET task statement)
How this row was scored
Exposure score: 88 out of 100 (84–92 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: Producing a contract from standard terms is template document work, with legal review happening afterwards.
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 4/4.
Researching and identifying potential customers for products or services
This is reading one thing and writing another: potential customers in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Research and identify potential customers for products or services.” (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: Finding companies that match a target profile is data search, which software does faster and more widely.
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
7 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.
Collaborating with sales teams to understand customer requirements
The software now makes the first pass at sales teams, 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: “Collaborate with sales teams to understand customer requirements, to promote the sale of company products, and to provide sales support.” (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: Supporting a sales team means live discussion about a specific customer, where judgment and rapport matter.
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.
Securing and renewing orders and arranging delivery
The software now makes the first pass at orders, 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: “Secure and renew orders and arrange delivery.” (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: Order paperwork and delivery scheduling are routine, but winning and renewing the order rests on the customer relationship.
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.
Identifying resale opportunities and supporting them to achieve sales plans
The software now makes the first pass at resale opportunities, 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: “Identify resale opportunities and support them to achieve sales plans.” (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: Spotting resale opportunities in account data is analysis AI does well, though pursuing them is a relationship job.
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
8 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.
Conferring with customers and engineers to assess equipment needs and to determine system requirements
The value here is that a specific person handles customers and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Confer with customers and engineers to assess equipment needs and to determine system requirements.” (O*NET task statement)
How this row was scored
Exposure score: 30 out of 100 (23–37 allowing for uncertainty): low 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: Working out what equipment a customer really needs comes from back-and-forth with their engineers.
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 2/4 · how much data exists 3/4.
Visiting prospective buyers at commercial
This work happens in the physical world: prospective buyers, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Visit prospective buyers at commercial, industrial, or other establishments to show samples or catalogs, and to inform them about product pricing, availability, and advantages.” (O*NET task statement)
How this row was scored
Exposure score: 10 out of 100 (3–17 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: Calling on buyers at their premises to show equipment means physically being there with the samples.
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.
Preparing and delivering technical presentations that explain products or services to customers and prospective customers
The value here is that a specific person handles technical presentations and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Prepare and deliver technical presentations that explain products or services to customers and prospective customers.” (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: The slides and technical content are easy to produce, but standing up and answering the room is personal.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Show the other 15 tasks
Writing technical documentation for products
shifting to AIThis is reading one thing and writing another: technical documentation in, a record out. That is the shape today's tools are built for.
importance 3 · SupplementalSource: “Write technical documentation for products.” (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: Product manuals and technical documentation are writing tasks where AI now produces publishable drafts.
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.
Documenting account activities, generate reports and keeping records of business transactions with customers and suppliers
shifting to AIThis is reading one thing and writing another: account activities in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Document account activities, generate reports, and keep records of business transactions with customers and suppliers.” (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: Logging account activity and generating reports is record keeping that customer systems already do.
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.
Maintaining sales forecasting reports
shifting to AIThis is reading one thing and writing another: sales forecasting reports in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Maintain sales forecasting reports.” (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: Sales forecasts are built from pipeline data, which is exactly what reporting tools compile 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 3/4.
Reporting to supervisors about prospective firms' credit ratings
shifting to AIThis is reading one thing and writing another: supervisors in, a record out. That is the shape today's tools are built for.
importance 3 · SupplementalSource: “Report to supervisors about prospective firms' credit ratings.” (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: Pulling a credit rating and reporting it to a manager is straightforward data lookup and summary.
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.
Planning and modifying product configurations to meet customer needs
shifting to AIThis is reading one thing and writing another: product configurations in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Plan and modify product configurations to meet customer needs.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 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: Configuring a product to fit stated requirements is rules-based work that configuration software already automates.
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.
Providing information needed for the development of custom-made machinery
shifting to AIThis is reading one thing and writing another: information in, a record out. That is the shape today's tools are built for.
importance 4 · SupplementalSource: “Provide information needed for the development of custom-made machinery.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 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: Writing up the specification a custom machine has to meet is documentation work AI drafts capably.
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.
Developing sales plans to introduce products in new markets
changing shapeThe software now makes the first pass at sales plans, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Develop sales plans to introduce products in new markets.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 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.
The rating behind it: Sales plans for new markets can be drafted from research, though the commercial calls still need reworking by a person.
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 0/4 · how much data exists 3/4.
Recommending improved materials or machinery
changing shapeThe software now makes the first pass at improved materials, 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: “Recommend improved materials or machinery to customers, documenting how such changes will lower costs or increase production.” (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: Building the cost-saving case is analysis and writing, though convincing the customer to change is a sales conversation.
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.
Providing technical and non-technical support and services to clients or other staff members regarding
changing shapeThe software now makes the first pass at technical and non-technical support and services, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · SupplementalSource: “Provide technical and non-technical support and services to clients or other staff members regarding the use, operation, and maintenance of 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: Answering technical questions about using and maintaining equipment is well-documented support work AI handles.
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.
Arranging for demonstrations or trial installations of equipment
changing shapeThe software now makes the first pass at demonstrations, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 3 · CoreSource: “Arrange for demonstrations or trial installations of 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: Booking demos and trial installs is scheduling and coordination work, though the equipment has to physically arrive.
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.
Training team members in the customer applications of technologies
staying humanThe value here is that a specific person handles team members and stands behind it. That is earned, not computed.
importance 3 · CoreSource: “Train team members in the customer applications of technologies.” (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: Training material is easy to generate, but coaching colleagues through real customer situations happens in person.
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.
Diagnosing problems with installed equipment
staying humanThis work happens in the physical world: problems, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Diagnose problems with installed equipment.” (O*NET task statement)
How this row was scored
Exposure score: 29 out of 100 (22–36 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: Diagnosing a fault often needs someone at the machine, though the manuals and fault codes are documented.
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 0/4 · how much data exists 3/4.
Attending company training seminars to become familiar with product lines
staying humanThe ratings behind this row put company training seminars well outside what today's tools can do on their own.
importance 4 · CoreSource: “Attend company training seminars to become familiar with product lines.” (O*NET task statement)
How this row was scored
Exposure score: 26 out of 100 (19–33 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over.
The rating behind it: Learning a product line is something the person has to absorb, even if AI can answer questions afterwards.
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 1/4 · how much data exists 3/4.
Selling products requiring extensive technical expertise and supporting
staying humanThe value here is that a specific person handles products requiring extensive technical expertise and stands behind it. That is earned, not computed.
importance 5 · SupplementalSource: “Sell products requiring extensive technical expertise and support for installation and use, such as material handling equipment, numerical-control machinery, or computer systems.” (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; the value is that a specific person does it.
The rating behind it: Selling complex machinery depends on the buyer trusting the person advising them over a long decision.
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 3/4.
Attending trade shows and seminars to promote products or to learn about industry developments
staying humanThis work happens in the physical world: trade shows, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Attend trade shows and seminars to promote products or to learn about industry developments.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Working a trade show floor means being there, meeting people and seeing equipment in person.
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 2/4 · how much data exists 3/4.
What this job pays, and how many people do it
- Median pay
- $124,900a 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
- 51,790in 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: potential customers in, a record out. The rows above are exactly that shape: researching and identifying potential customers for products or services and developing, presenting. What it cannot do is be there in the room, and that is still where prospective buyers 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
Your week is splitting in two, and which half fills it is the whole question. Researching and identifying potential customers for products or services is going; visiting prospective buyers at commercial is not.
So, given all that: 40% of this job's task weight sits in rows the software is already learning, 28% in rows that change shape rather than disappear, and 31% in rows it is nowhere near. That is the position, measured across 25 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 (visiting prospective buyers at commercial) 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 visiting prospective buyers at commercial, 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 engineers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was sales representatives, wholesale and manufacturing, except technical and scientific products: only about 8% of its durable work is work you already do and it pays 42.3% less. Your own job splits about 40/60: 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 “collaborate with sales teams to understand customer requirements, to promote the sale…”, 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.
Sales Representatives, Wholesale and Manufacturing, Except Technical and Scientific Products
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already prepare and deliver technical presentations that explain products or services to customers and…, and their equivalent is to contact regular and prospective customers to demonstrate products, explain product features, and solicit…. 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. It is a pay cut, in those words: $72,080 against your $124,900, 42.3% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Sales Representatives, Wholesale and Manufacturing, Technical and Scientific Products
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already create sales or service contracts for products or services, and their equivalent is to visit establishments to evaluate needs or to promote product or service sales. 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: $104,920 against your $124,900, 16.0% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Sales Managers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already confer with customers and engineers to assess equipment needs and to determine system…, and their equivalent is to confer with potential customers regarding equipment needs, and advise customers on types of…. 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.
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: 40% of its task weight, across 25 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.
You are reading the United States figures
The United Kingdom splits this work across more than one official group, of which Business sales executives is the closest. The pay and employment figures are not directly comparable, and we do not average them together.
Switch to the United Kingdom page →partial match
In UK official statistics this job is counted as Business sales executives. Pay and employment stay on this page’s own group; the task list and the scores do not cross over.
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No Space for this job, but one for what is happening to it
Nothing Collab365 runs is built for sales engineers, 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 40% 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 sales engineers. 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 sales engineers 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 Engineers?
- Not as a job, but it is already doing parts of the work. Across the 25 official task statements scored for Sales Engineers (United States, SOC 41-9031), 40% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 55 out of 100 (range 50–61, 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 Engineers” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Research and identify potential customers for products or services” (93/100, very high); “Write technical documentation for products” (93/100, very high); “Document account activities, generate reports, and keep records of business transactions with customers and suppliers” (93/100, 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 “Sales Engineers” stay human?
- About 31% 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: “Attend trade shows and seminars to promote products or to learn about industry developments” (0/100, minimal); “Visit prospective buyers at commercial, industrial, or other establishments to show samples or catalogs, and to inform them about product pricing, availabili…” (10/100, minimal); “Sell products requiring extensive technical expertise and support for installation and use, such as material handling equipment, numerical-control machinery,…” (24/100, low). 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 Engineers” do about AI?
- Start from the ledger rather than the headline: 40% of this job's weighted core work is exposed, and roughly 31% 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 Engineers 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 25 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.
- 1 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.