US dataswitch to UK
Sales Representatives, Wholesale and Manufacturing, Technical and Scientific Products
preparing proposals, quotes, contracts or presentations for potential solar customers, preparing or reviewing detailed design drawings, providing feedback to product design teams so that products can be tailored to clients' needs and preparing sales presentations or proposals to explain product specifications or applications. If that's your week, this page is about your job.
The honest answer
This job is splitting in two: preparing proposals, quotes, contracts or presentations for potential solar customers is work AI now does quickly and cheaply, and visiting establishments to evaluate needs or to promote product or service sales is work it can't touch.
Which half fills your week decides your exposure. Moving toward the second half is a real, doable plan.
Your week, as this page understands it
Sell goods for wholesalers or manufacturers where technical or scientific knowledge is required in such areas as biology, engineering, chemistry, and electronics, normally obtained from at least 2 years of postsecondary education. The job title says “sales representatives”, “wholesale”, “manufacturing”, “technical” or “scientific products”: officially one job, several names. The real job is the part underneath: visiting establishments to evaluate needs or to promote product or service sales. 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 representatives, wholesale and manufacturing, technical and scientific products is not one task. It is 46 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is visiting establishments to evaluate needs or to promote product or service sales, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 46%
- changing shape
- 26%
- staying human
- 28%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 56 out of 100 (51–62 allowing for uncertainty): partial exposure, across 46 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 representatives, wholesale and manufacturing, technical and scientific products 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.
- 5 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
20 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.
Preparing proposals, quotes, contracts or presentations for potential solar customers
This is reading one thing and writing another: proposals, quotes, contracts or presentations in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Prepare proposals, quotes, contracts, or presentations for potential solar customers.” (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: Solar quotes and proposals follow standard templates and calculations, which software assembles to a high standard.
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.
Providing customers with information, such as quotes, orders, sales, shipping, warranties, credit, funding options, incentives or tax rebates
This is reading one thing and writing another: customers in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Provide customers with information, such as quotes, orders, sales, shipping, warranties, credit, funding options, incentives, or tax rebates.” (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: Incentives, rebates and warranty terms are published rules, so AI assembles accurate customer information from them.
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 1/4 · how much data exists 3/4.
Providing technical information about solar power
This is reading one thing and writing another: technical information in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Provide technical information about solar power, solar systems, equipment, and services to potential customers or dealers.” (O*NET task statement)
How this row was scored
Exposure score: 85 out of 100 (81–89 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: Solar technology is thoroughly documented in public, so AI answers technical questions about it very reliably.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 4/4.
Calculating potential solar resources or solar array production for a particular site considering issues
This is reading one thing and writing another: potential solar resources in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Calculate potential solar resources or solar array production for a particular site considering issues such as climate, shading, and roof orientation.” (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: Solar production modelling uses public climate and mapping data in standard tools, which software runs 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 4/4.
Changing shape
12 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.
Selecting solar energy products, systems or services for customers based on electrical energy requirements, site conditions, price or other factors
The software now makes the first pass at solar energy products, systems or services, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 5 · CoreSource: “Select solar energy products, systems, or services for customers based on electrical energy requirements, site conditions, price, or other factors.” (O*NET task statement)
How this row was scored
Exposure score: 42 out of 100 (35–49 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: Sizing a system from energy use and site data is calculation software does well, though roof conditions may need checking.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Gathering information from prospective customers to identify their solar energy needs
The software now makes the first pass at information, 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 5 · CoreSource: “Gather information from prospective customers to identify their solar energy needs.” (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: Structured questions gather most of it, but customers open up more with a person they 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.
Preparing or reviewing detailed design drawings
The software now makes the first pass at detailed design drawings, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Prepare or review detailed design drawings, specifications, or lists related to solar installations.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 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; someone qualified has to answer for it.
The rating behind it: Layout drawings and equipment lists follow set patterns AI drafts well, though a qualified person checks them before installation.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Staying human
14 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.
Assessing sites to determine suitability for solar equipment
This work happens in the physical world: sites, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Assess sites to determine suitability for solar equipment, using equipment such as tape measures, compasses, and computer software.” (O*NET task statement)
How this row was scored
Exposure score: 13 out of 100 (6–20 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Aerial imagery does part of the job, but measuring a roof and checking shading properly means visiting the property.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Contacting new or existing customers to discuss how specific products or services can meet their needs
The value here is that a specific person handles new or existing customers and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Contact new or existing customers to discuss how specific products or services can meet their needs.” (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: This is a consultative conversation that depends on the person having it.
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.
Generating solar energy customer leads to develop new accounts
The value here is that a specific person handles solar energy customer leads and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Generate solar energy customer leads to develop new accounts.” (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 finds and contacts likely customers efficiently, though turning interest into an account usually needs a 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.
Show the other 36 tasks
Maintaining customer records, using automated systems
shifting to AIThis is reading one thing and writing another: customer records in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Maintain customer records, using automated systems.” (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: Keeping customer records current is routine data work that sales systems already do automatically from calls and emails.
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.
Completing expense reports, sales reports or other paperwork
shifting to AIThis is reading one thing and writing another: expense reports, sales reports or other paperwork in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Complete expense reports, sales reports, or other paperwork.” (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: Expense and sales reporting is routine form-filling that software already completes from existing records.
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.
Studying documentation or other information for new scientific or technical products
shifting to AIThis is reading one thing and writing another: documentation in, a record out. That is the shape today's tools are built for.
importance 3 · CoreSource: “Study documentation or other information for new scientific or technical 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: Reading and digesting technical product documentation is one of the things AI does fastest and most reliably.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Verifying accuracy of materials lists
shifting to AIThis is reading one thing and writing another: accuracy of materials lists in, a record out. That is the shape today's tools are built for.
importance 4 · SupplementalSource: “Verify accuracy of materials lists.” (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: Checking a materials list against specifications is exactly the sort of careful comparison software does without tiring.
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.
Preparing and submitting sales contracts for orders
shifting to AIThis is reading one thing and writing another: sales contracts in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Prepare and submit sales contracts for orders.” (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 sales contract from a template and the order details is document work AI does at practitioner standard.
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.
Verifying customer credit ratings
shifting to AIThis is reading one thing and writing another: customer credit ratings in, a record out. That is the shape today's tools are built for.
importance 4 · SupplementalSource: “Verify customer credit ratings.” (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: Credit checks are automated lookups against reporting agencies, with a person confirming borderline decisions.
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.
Answering customers' questions about products
shifting to AIThis is reading one thing and writing another: customers' questions in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Answer customers' questions about products, prices, availability, or credit terms.” (O*NET task statement)
How this row was scored
Exposure score: 79 out of 100 (75–83 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: Product, price and availability questions are exactly what AI assistants answer well from a company's own catalogue.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Preparing sales presentations or proposals to explain product specifications or applications
shifting to AIThis is reading one thing and writing another: sales presentations in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Prepare sales presentations or proposals to explain product specifications or applications.” (O*NET task statement)
How this row was scored
Exposure score: 79 out of 100 (75–83 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: Drafting proposals and presentation decks from product information is a task AI performs to a high standard.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Informing customers of estimated delivery schedules
shifting to AIThis is reading one thing and writing another: customers of estimated delivery schedules in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Inform customers of estimated delivery schedules, service contracts, warranties, or other information pertaining to purchased products.” (O*NET task statement)
How this row was scored
Exposure score: 79 out of 100 (75–83 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: Sending customers delivery, warranty and contract updates is standard automated messaging from order systems.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Taking quote requests or orders from dealers or customers
shifting to AIThis is reading one thing and writing another: quote requests in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Take quote requests or orders from dealers or customers.” (O*NET task statement)
How this row was scored
Exposure score: 79 out of 100 (75–83 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: Taking and logging orders and quote requests is standard automated order-processing work.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Verifying that delivery schedules meet project deadlines
shifting to AIThis is reading one thing and writing another: delivery schedules meet project deadlines in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Verify that delivery schedules meet project deadlines.” (O*NET task statement)
How this row was scored
Exposure score: 79 out of 100 (75–83 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: Comparing promised delivery dates against project deadlines is a checking job systems do 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 1/4 · how much data exists 3/4.
Quoting prices, credit terms or other bid specifications
shifting to AIThis is reading one thing and writing another: prices, credit terms or other bid specifications in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Quote prices, credit terms, or other bid specifications.” (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: Generating a quote from price lists and terms is rules-based work software already handles inside sales systems.
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 1/4 · how much data exists 3/4.
Computing customer's installation or production costs and estimating savings from new services
shifting to AIThis is reading one thing and writing another: customer's installation in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Compute customer's installation or production costs and estimate savings from new services, products, or equipment.” (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: Cost and savings calculations follow set formulas from customer data, which software works out quickly and 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 1/4 · how much data exists 3/4.
Informing customers about issues related to responsible use and disposal of products
shifting to AIThis is reading one thing and writing another: customers in, a record out. That is the shape today's tools are built for.
importance 3 · SupplementalSource: “Inform customers about issues related to responsible use and disposal of products, such as waste reduction or product or byproduct recycling or disposal.” (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: Disposal and recycling guidance comes straight from published rules and product data, so AI produces reliable customer information.
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 1/4 · how much data exists 3/4.
Developing marketing or strategic plans for sales territories
shifting to AIThis is reading one thing and writing another: strategic plans in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Develop marketing or strategic plans for sales territories.” (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: Territory plans built from sales data and market information are exactly the kind of document AI drafts 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 1/4 · how much data exists 3/4.
Initiating sales campaigns to meet sales and production expectations
shifting to AIThis is reading one thing and writing another: sales campaigns in, a record out. That is the shape today's tools are built for.
importance 4 · SupplementalSource: “Initiate sales campaigns to meet sales and production expectations.” (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: Planning and launching a sales campaign, including the messaging and targeting, is well within what AI produces.
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.
Providing feedback to product design teams so that products can be tailored to clients' needs
changing shapeThe software now makes the first pass at feedback, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · SupplementalSource: “Provide feedback to product design teams so that products can be tailored to clients' needs.” (O*NET task statement)
How this row was scored
Exposure score: 57 out of 100 (50–64 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; mistakes that are cheap to catch.
The rating behind it: Turning customer comments into useful design feedback is largely writing up patterns, which software does well from records.
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 2/4.
Creating customized energy management packages to satisfy customer needs
changing shapeThe software now makes the first pass at customized energy management packages, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Create customized energy management packages to satisfy customer needs.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 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: Assembling a package from standard products and a customer's energy data is configuration work software handles well.
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 1/4 · how much data exists 3/4.
Emphasizing product features
changing shapeThe software now makes the first pass at product features, 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: “Emphasize product features, based on analyses of customers' needs and on technical knowledge of product capabilities and limitations.” (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: Matching product strengths to a customer's stated needs is analysis AI does well, though the pitch lands better in person.
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.
Collaborating with colleagues to exchange information
changing shapeThe software now makes the first pass at colleagues, 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 colleagues to exchange information, such as selling strategies or marketing information.” (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: Notes and summaries can be shared automatically, though swapping what actually works in the field is a colleague 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.
Consulting with engineers regarding technical problems with products
changing shapeThe software now makes the first pass at engineers regarding technical problems, 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 · SupplementalSource: “Consult with engineers regarding technical problems with products.” (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: AI can frame the technical problem clearly, though resolving it usually involves a back-and-forth between people.
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.
Presenting information to customers about the energy efficiency or environmental impact of scientific or technical products
changing shapeThe software now makes the first pass at information, 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 · SupplementalSource: “Present information to customers about the energy efficiency or environmental impact of scientific or technical products.” (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: Efficiency and impact information is documented and AI presents it clearly, though the presenting itself involves a person.
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.
Arranging for installation and testing of products or machinery
changing shapeThe software now makes the first pass at installation, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · SupplementalSource: “Arrange for installation and testing of products or machinery.” (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 installers and scheduling tests is coordination software does well, though someone attends the actual install.
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.
Attending sales or trade meetings or reading related publications to obtain information about market conditions
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: “Attend sales or trade meetings or read related publications to obtain information about market conditions, business trends, environmental regulations, or industry developments.” (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: AI keeps up with published market and regulatory news very well, though trade meetings give information not yet written down.
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.
Selecting or assisting customers in selecting products based on customer needs
changing shapeThe software now makes the first pass at customers, 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: “Select or assist customers in selecting products based on customer needs, product specifications, and applicable regulations.” (O*NET task statement)
How this row was scored
Exposure score: 46 out of 100 (39–53 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: Configurators and AI match products to requirements well, though customers often want a person confirming the choice.
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 2/4 · how much data exists 3/4.
Providing customers with ongoing technical support
staying humanThe value here is that a specific person handles customers and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Provide customers with ongoing technical support.” (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: AI resolves a good share of technical questions, though difficult cases still go to a person who knows the account.
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.
Identifying prospective customers, using business directories, leads from existing clients
staying humanThe value here is that a specific person handles prospective customers and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Identify prospective customers, using business directories, leads from existing clients, participation in organizations, or trade show or conference attendance.” (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: Building prospect lists from directories and data is quick for software, but referrals and trade shows depend on turning up.
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.
Advising customers on product usage to improve production
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 product usage to improve production.” (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: Usage guidance is well documented and AI explains it clearly, though improving a customer's line often means seeing it.
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.
Selling service contracts for technical or scientific products
staying humanThe value here is that a specific person handles service contracts and stands behind it. That is earned, not computed.
importance 4 · SupplementalSource: “Sell service contracts for technical or scientific products.” (O*NET task statement)
How this row was scored
Exposure score: 36 out of 100 (29–43 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 contract paperwork is easy to produce, but persuading a customer to commit to years of service rests on trust.
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 3/4 · how much data exists 3/4.
Selling technical and scientific products that are environmentally sound or designed for environmental remediation
staying humanThe value here is that a specific person handles technical and scientific products and stands behind it. That is earned, not computed.
importance 3 · SupplementalSource: “Sell technical and scientific products that are environmentally sound or designed for environmental remediation.” (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: Marketing material writes easily, but closing sales of specialist environmental equipment depends on a trusted relationship.
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.
Negotiating prices or terms of sales or service agreements
staying humanThe value here is that a specific person handles prices and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Negotiate prices or terms of sales or service agreements.” (O*NET task statement)
How this row was scored
Exposure score: 21 out of 100 (17–25 allowing for uncertainty): low exposure, high confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Haggling over price and terms turns on the working relationship and reading the other side live.
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.
Stocking or distributing resources, such as samples or promotional or educational materials
staying humanThis work happens in the physical world: resources, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Stock or distribute resources, such as samples or promotional or educational materials.” (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 rating behind it: Ordering and tracking materials is easy for software, but handing out samples and stocking displays is physical work.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Demonstrating use of solar and related equipment to customers or dealers
staying humanThis work happens in the physical world: use of solar, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Demonstrate use of solar and related equipment to customers or dealers.” (O*NET task statement)
How this row was scored
Exposure score: 7 out of 100 (0–14 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Guides and videos help, but showing someone how the equipment works in front of them needs a person there.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Demonstrating the operation or use of technical or scientific products
staying humanThis work happens in the physical world: the operation, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Demonstrate the operation or use of technical or scientific products.” (O*NET task statement)
How this row was scored
Exposure score: 7 out of 100 (0–14 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Videos and guides help, but showing a customer how a machine actually runs usually means being there with it.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Visiting establishments to evaluate needs or to promote product or service sales
staying humanThis work happens in the physical world: establishments, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Visit establishments to evaluate needs or to promote product or service sales.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: 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: This task is going to a customer's premises in person, which no software can do for you.
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.
Visiting establishments, such as pharmacies, to determine product sales
staying humanThis work happens in the physical world: establishments, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Visit establishments, such as pharmacies, to determine product sales.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world.
The rating behind it: This task is travelling to a customer's premises to see how a product is selling.
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 1/4 · how much data exists 3/4.
What this job pays, and how many people do it
- Median pay
- $104,920a 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
- 284,800in 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: proposals, quotes, contracts or presentations in, a record out. The rows above are exactly that shape: preparing proposals, quotes, contracts or presentations for potential solar customers and providing customers with information, such as quotes. What it cannot do is be there in the room, and that is still where establishments 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
The exposed part of your job is the biggest part, and I am not going to dress that up: preparing proposals, quotes, contracts or presentations for potential solar customers is work today's tools do quickly and cheaply, and that is not coming back.
So, given all that: 46% of this job's task weight sits in rows the software is already learning, 26% in rows that change shape rather than disappear, and 28% in rows it is nowhere near. That is the position, measured across 46 scored tasks. It is not a forecast about you.
What you have that the software does not is visiting establishments to evaluate needs or to promote product or service sales, plus the years of knowing when something looks wrong before you can say why. That is the raw material for everything below.
This week: one thing
Sit on the machine's side of the desk. Pick one real piece of proposals, quotes, contracts or presentations you would normally do yourself, let whatever software you already have take the first pass at it, and then go through what it produced and write down every single thing it got wrong. One evening this week. Do not fix anything yet. Just catch it.
- What you end up holding
- a written list of the machine’s mistakes, in your handwriting
- How long it takes
- an evening, or an hour if you pick one job rather than one client
If you can’t run software on your employer’s or your clients’ data: Do the same hunt on paper. Take one printed piece of proposals, quotes, contracts or presentations, work through it the way you always do, and mark every point where you made a call rather than followed a rule. Same evening, same list, nothing to log into and nobody to ask permission from. That list is the same artifact: it is the judgment written down.
Over the next 90 days
Change one sentence about what you do. Not on a CV. Out loud, to whoever pays you. From “my job is preparing proposals, quotes, contracts or presentations for potential solar customers” to “I check what the software does and tell you what it means.” Your error list from this week is what makes that sentence true instead of a claim, so use it: show it once, to one person, inside the next ninety days. Same skills, priced as judgment rather than as typing.
Over the next 12 months
Walk toward the end of this job that answers for things, and get it recognised. Pick the one part of visiting establishments to evaluate needs or to promote product or service sales you are already best at, and spend the year making it formal: a qualification, a named responsibility, a specialism people ask for by name. Price it honestly: that is evenings, it is months rather than weeks, and the seats are competitive because everyone in your position is looking at the same door. 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 representatives, wholesale and manufacturing, technical and scientific products (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was sales representatives of services, except advertising, insurance, financial services, and travel: only about 17% of its durable work is work you already do and it pays 33.3% less. Your own job splits about 46/54: 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 “select solar energy products, systems, or services for customers based on electrical…”, 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 of Services, Except Advertising, Insurance, Financial Services, and Travel
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “negotiate prices or terms of sales or service agreements”. Across the whole of both lists that adds up to about 17% 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 17% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on. It is a pay cut, in those words: $69,990 against your $104,920, 33.3% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
First-Line Supervisors of Construction Trades and Extraction Workers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already provide technical information about solar power, solar systems, equipment, and services to potential…, and their equivalent is to visit customer sites to determine solar system needs, requirements, or specifications. 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. It is a pay cut, in those words: $79,920 against your $104,920, 23.8% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
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 identify prospective customers, using business directories, leads from existing clients, participation in organizations…, and their equivalent is to identify prospective customers by using business directories, following leads from existing clients, participating…. 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. It is a pay cut, in those words: $72,080 against your $104,920, 31.3% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
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: 46% of its task weight, across 46 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
“It’s too late for me to become something else”
You are not starting from zero, and the page shows why: visiting establishments to evaluate needs or to promote product or service sales is work the software cannot do and you already do it. The move above is a repricing of what you know, not a new career. Nobody who has just left college has that.
“I should learn to code”
Almost certainly not. The value in your job is moving toward checking, deciding and answering for the output, not toward writing the software. A weekend of Python will not change your position; the error list from this week will.
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.
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 sales representatives / wholesale / manufacturing / technical / scientific products, 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 46% 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 representatives / wholesale / manufacturing / technical / scientific products. 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 representatives / wholesale / manufacturing / technical / scientific products 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 Sales Representatives, Wholesale and Manufacturing, Technical and Scientific Products?
- Not as a job, but it is already doing parts of the work. Across the 46 official task statements scored for Sales Representatives, Wholesale and Manufacturing, Technical and Scientific Products (United States, SOC 41-4011), 46% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 56 out of 100 (range 51–62, 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 Representatives, Wholesale and Manufacturing, Technical and Scientific Products” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Maintain customer records, using automated systems” (93/100, very high); “Complete expense reports, sales reports, or other paperwork” (93/100, very high); “Study documentation or other information for new scientific or technical products” (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 Representatives, Wholesale and Manufacturing, Technical and Scientific Products” stay human?
- About 28% 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: “Visit establishments, such as pharmacies, to determine product sales” (0/100, minimal); “Visit establishments to evaluate needs or to promote product or service sales” (0/100, minimal); “Demonstrate the operation or use of technical or scientific products” (7/100, 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 Representatives, Wholesale and Manufacturing, Technical and Scientific Products” do about AI?
- Start from the ledger rather than the headline: 46% of this job's weighted core work is exposed, and roughly 28% 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 Representatives, Wholesale and Manufacturing, Technical and Scientific Products 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 46 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.
- 5 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.