Will AI replace Telephone salespersons?

Not as a job, but it is already doing parts of the work. Across the 13 official task statements scored for Telephone salespersons (United Kingdom, SOC 7113), 66% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 64 out of 100 (range 58–70, band: high). 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 “Telephone salespersons” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Obtain names and telephone numbers of potential customers from various sources” (93/100, very high); “Obtain customers' names, addresses, billing information, product numbers, and specifications of items to be purchased, and enter this information on order forms” (79/100, high); “Respond to customer correspondence by writing letters” (79/100, high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.

Which tasks in “Telephone salespersons” stay human?

About 9% 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: “Sell additional merchandise or services to prospective or current customers by telephone or through visits” (26/100, low); “Follow up initial sales contacts by telephone” (40/100, partial); “Answer telephone calls from potential customers who have been solicited through advertisements” (53/100, partial). 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 “Telephone salespersons” do about AI?

Start from the ledger rather than the headline: 66% of this job's weighted core work is exposed, and roughly 9% 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 Telephone salespersons calculated?

Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 13 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.

UK dataswitch to US

Telephone salespersons

explaining products, services and prices and answering customer queries, selling additional merchandise or services to prospective or current customers by telephone or through visits and adjusting sales scripts to better target the needs and interests of specific individuals. If that's your week, this page is about your job.

The honest answer

Most tasks in this job are the kind AI has learned to do: obtaining customers' names, addresses, billing information, product numbers and specifications of items to be purchased and entering this information on order forms. The tasks, though, are not you.

Your move: three real directions from here ↓

Where the work sits, by task weight

shifting to AI: 66%
changing shape: 26%
staying human: 9%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

Whole-job exposure score 64 out of 100 (58–70 allowing for uncertainty): high exposure, across 13 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 telephone salespersons is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-04. Read the full method.

It would be a lie to soften that; selling additional merchandise or services to prospective or current customers by telephone or through visits is what this work rebuilds around. The plan below starts there.

Your week, as this page understands it

Telephone salespersons obtain, receive, process and record telephone orders for goods and services. The job title says “telephone salespersons”. The real job is the part underneath: selling additional merchandise or services to prospective or current customers by telephone or through visits. 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 telephone salespersons is not one task. It is 13 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is selling additional merchandise or services to prospective or current customers by telephone or through visits, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 66%
changing shape: 26%
staying human: 9%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

How we know this

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.

12 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

9 tasks

Tasks 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.

Explaining products, services and prices and answering customer queries
This is reading one thing and writing another: products, services and prices and answering customer queries in, a record out. That is the shape today's tools are built for.
importance 95 · 7113/00
Source: “Explain products, services, and prices, and answer customer queries.” (UK 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: Product and price explanations are documented and already handled well by automated help.
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.
Obtaining customers' names, addresses, billing information, product numbers and specifications of items to be purchased and entering this information on order forms
This is reading one thing and writing another: customers' names, addresses, billing information in, a record out. That is the shape today's tools are built for.
importance 90 · 7113/00
Source: “Obtain customers' names, addresses, billing information, product numbers, and specifications of items to be purchased, and enter this information on order forms.” (UK 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 down customer details and typing them onto an order form is exactly the sort of structured data entry software handles well.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Adjusting sales scripts to better target the needs and interests of specific individuals
This is reading one thing and writing another: sales scripts in, a record out. That is the shape today's tools are built for.
importance 85 · 7113/00
Source: “Adjust sales scripts to better target the needs and interests of specific individuals.” (UK 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: Tailoring a script to a particular person from what is known about them is writing work AI does well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Recording names, addresses, purchases and reactions of prospects
This is reading one thing and writing another: names, addresses, purchases and reactions of prospects in, a record out. That is the shape today's tools are built for.
importance 85 · 7113/00
Source: “Record names, addresses, purchases, and reactions of prospects contacted.” (UK task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Logging names, addresses and reactions into the system is routine record keeping.
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.
Maintaining records of contacts, accounts and orders
This is reading one thing and writing another: records of contacts, accounts and orders in, a record out. That is the shape today's tools are built for.
importance 80 · 7113/00
Source: “Maintain records of contacts, accounts, and orders.” (UK 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: Keeping contact, account and order records up to date is ordinary database work.
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.
Obtaining names and telephone numbers of potential customers from various sources
This is reading one thing and writing another: names in, a record out. That is the shape today's tools are built for.
importance 75 · 7113/00
Source: “Obtain names and telephone numbers of potential customers from various sources.” (UK 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: Gathering names and numbers from available sources is exactly the kind of searching software does at scale.
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

3 tasks

Tasks 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.

Answering phone enquiries and providing relevant information or assistance
The software now makes the first pass at phone enquiries, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 95 · 7113/00
Source: “Answer phone enquiries and provide relevant information or assistance.” (UK task statement)
How this row was scored
Exposure score: 59 out of 100 (52–66 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Answering routine phone enquiries about opening times, menus and directions is well handled by automated systems.
The five ratings: output a model can produce 4/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Answering telephone calls from potential customers who have been solicited through advertisements
The software now makes the first pass at telephone calls, 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 90 · 7113/00
Source: “Answer telephone calls from potential customers who have been solicited through advertisements.” (UK 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: Answering enquiry calls is routine spoken work that automated systems increasingly handle, though some callers want 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.
Following up initial sales contacts by telephone
The software now makes the first pass at initial sales contacts, 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 85 · 7113/00
Source: “Follow up initial sales contacts by telephone.” (UK 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: Follow-up calls can be partly automated, but a live conversation is still what moves the sale.
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.

Staying human

1 task

Tasks 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.

Selling additional merchandise or services to prospective or current customers by telephone or through visits
The value here is that a specific person handles additional merchandise and stands behind it. That is earned, not computed.
importance 90 · 7113/00
Source: “Sell additional merchandise or services to prospective or current customers by telephone or through visits.” (UK 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 value is that a specific person does it.
The rating behind it: Selling extra products depends on reading the customer in the moment, which a phone call or visit from a person still does best.
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 2/4.

Show the other 3 tasks

Responding to customer correspondence by writing letters
shifting to AI
This is reading one thing and writing another: customer correspondence in, a record out. That is the shape today's tools are built for.
importance 50 · 7113/00
Source: “Respond to customer correspondence by writing letters.” (UK 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: Replying to correspondence with letters is exactly the kind of writing software produces well.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Arranging meetings for sales representatives with potential customers
shifting to AI
This is reading one thing and writing another: meetings in, a record out. That is the shape today's tools are built for.
importance 70 · 7113/00
Source: “Arrange meetings for sales representatives with potential customers.” (UK 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: Booking and confirming customer meetings is routine scheduling and outreach.
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.
Carrying out client or marketing surveys to obtain information about potential customers
shifting to AI
This is reading one thing and writing another: client in, a record out. That is the shape today's tools are built for.
importance 60 · 7113/00
Source: “Carry out client or market surveys to obtain information about potential customers.” (UK 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: Writing surveys and analysing the answers is standard desk work, though some customer contact still 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 1/4 · how much data exists 3/4.

What this job pays, and how many people do it

Median pay: £30,500a year, before tax, the middle of the range, so half earn more and half earn less.ashe-t14, 2025 · ASHE 2025 provisional (reference April 2025)Provisional, because the ONS revises this figure in the autumn.
How we know this
Source: ashe-t14
Reference period: ASHE 2025 provisional (reference April 2025)
Rounding: Shown to the nearest £100. The exact published figure is in the downloadable dataset. We do not render pounds the survey cannot support.
People doing this job: 17,700in the UK, 2026.nomis-aps · Apr 2025-Mar 2026 (latest APS 12-month period)This headcount comes from a survey, not a census, so treat it as a good estimate rather than an exact count.

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: customers' names, addresses, billing information in, a record out. The rows above are exactly that shape: obtaining customers' names, addresses, billing information and explaining products, services and prices and answering customer queries. What it cannot do is be trusted in person, which is what additional merchandise runs on: someone specific doing it and standing behind it. Which is why this page talks about your tasks changing, not your job ending.

Your move

Over a pint: what I’d tell you if you were my friend

The exposed part of your job is the biggest part, and I am not going to dress that up: obtaining customers' names, addresses, billing information is work today's tools do quickly and cheaply, and that is not coming back.

So, given all that: 66% of this job's task weight sits in rows the software is already learning, 26% in rows that change shape rather than disappear, and 9% in rows it is nowhere near. That is the position, measured across 13 scored tasks. It is not a forecast about you.

What you have that the software does not is selling additional merchandise or services to prospective or current customers by telephone or through visits, 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 customers' names, addresses, billing information 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 customers' names, addresses, billing information, 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 obtaining customers' names, addresses, billing information, product numbers and specifications of items to be purchased and entering this information on order forms” 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 selling additional merchandise or services to prospective or current customers by telephone or through visits 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, spend an hour with National Careers Service. It is free and government-funded, 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 UK occupations to telephone salespersons (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was sales administrators: only about 6% of its durable work is work you already do. I am not going to pretend that is comfortable news: 66% of your own task list is already in the top exposure band. But the answer on this evidence is not a sideways jump into a job with the same problem. It is to walk toward the end of this one that answers for things. “answer phone enquiries and provide relevant information or assistance” is the part that stays with a person, and spending a year getting formally recognised for it beats a standing start somewhere else.

How that was checked: this job was compared against all 412 UK 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 administrators
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “sell additional merchandise or services to prospective or current customers by telephone or through visits”. Across the whole of both lists that adds up to about 6% of the work in that job the software is not taking.
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.
Look at that job’s page anyway →
Business sales executives
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already adjust sales scripts to better target the needs and interests of specific individuals, and their equivalent is to achieve sales targets. Across both published task lists that is about 4% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 4% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →
Call and contact centre occupations
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “answer phone enquiries and provide relevant information or assistance”. Across the whole of both lists that adds up to about 3% of the work in that job the software is not taking.
Why I am not recommending it: Almost none of it is work you already do: about 3% of the durable side of that job. That is a different job, not a next step. I will not move you off one melting floe onto another: 58% of its own task list already scores in the top exposure band (61/100 in this release), so the same software is eating it. It is a pay cut, in those words: £27,035 against your £30,495, 11.3% less (ASHE Table 14.7a, 2025 provisional (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →

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: 66% of its task weight, across 13 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: selling additional merchandise or services to prospective or current customers by telephone or through visits 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 Kingdom figures

The United States splits this work across more than one official group, of which Telemarketers is the closest. The pay and employment figures are not directly comparable, and we do not average them together.

Switch to the United States page →partial match

In US official statistics this job is counted as Telemarketers. 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.

In England:
National Careers Service
A free hour with a government-funded careers adviser is worth more than another evening of reading. In England that's the National Careers Service.
Free, government-funded
- Discover your skills and careers (the skills assessment)
In England:
National Careers Service - Find a course
Search what's actually running near you before you spend anything.
Free to search; individual courses vary
In England:
Free courses for jobs (Level 3 qualifications)
A free Level 3 qualification you already qualify for beats a paid course you don't need.
Free for eligible adults
In England:
Skills Bootcamps
Free, up to 16 weeks, and you get a job interview at the end. In England these are Skills Bootcamps - search what's running near you.
Free for eligible adults in England
- Skills Bootcamps - what they are and who can do them (DfE, Skills for Careers)
- Skills Bootcamps - JobHelp (DWP)
In Scotland:
My World of Work (Skills Development Scotland)
In Scotland it's My World of Work, from Skills Development Scotland.
Free, publicly funded
- Skills Development Scotland
In Wales:
Careers Wales
In Wales it's Careers Wales.
Free, Welsh Government-funded
In Northern Ireland:
Careers Service Northern Ireland
In Northern Ireland it's the Careers Service on nidirect.
Free, Department for the Economy-funded

No Space for this job, but one for what is happening to it

Nothing Collab365 runs is built for telephone salespersons, and we are not going to point you at the nearest one and call it a fit.

There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 66% of the work on this page is already inside what they can do.

Try The AI Authority free →

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 telephone salespersons. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.

Noted, and thank you. We’ll email you if a Space for telephone salespersons launches. Nothing else.

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No Space for telephone salespersons yet. Should there be one?

Collab365 Spaces is built by the same people as this site. We find the problems that AI and automation are creating inside one kind of work, then solve them as short courses, briefings and Blueprints. Each Space is the community too, so the research and the people doing your job are in the same place.

What a Space actually is, in full

Collab365 launches new communities where the need is real. If one for telephone salespersons existed, with researched problems, courses and people in the same boat, would you want in?

Your email

We use your email address for one thing: to tell you if a Space for telephone salespersons launches. We never sell it, never use it for unrelated marketing, and every email has a one-click unsubscribe. Our privacy policy has the full version.

This unlocks nothing. Every figure, every row and every step on this page is already yours, whether you fill this in or not.

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 Telephone salespersons?: Not as a job, but it is already doing parts of the work. Across the 13 official task statements scored for Telephone salespersons (United Kingdom, SOC 7113), 66% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 64 out of 100 (range 58–70, band: high). 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 “Telephone salespersons” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Obtain names and telephone numbers of potential customers from various sources” (93/100, very high); “Obtain customers' names, addresses, billing information, product numbers, and specifications of items to be purchased, and enter this information on order forms” (79/100, high); “Respond to customer correspondence by writing letters” (79/100, high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
Which tasks in “Telephone salespersons” stay human?: About 9% 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: “Sell additional merchandise or services to prospective or current customers by telephone or through visits” (26/100, low); “Follow up initial sales contacts by telephone” (40/100, partial); “Answer telephone calls from potential customers who have been solicited through advertisements” (53/100, partial). 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 “Telephone salespersons” do about AI?: Start from the ledger rather than the headline: 66% of this job's weighted core work is exposed, and roughly 9% 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 Telephone salespersons calculated?: Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 13 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

About the data on this page

Provisional, because the ONS revises this figure in the autumn.
This headcount comes from a survey, not a census, so treat it as a good estimate rather than an exact count.
The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
12 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: gaisi-indexProcessing: catalogue-bridge → ssc-relatedness-weighting → task-scoring → score-aggregation
Task weights: gaisi-index (relatedness)
Scores: Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
Pay and employment: ashe-t14 (ASHE 2025 provisional (reference April 2025))nomis-aps (Apr 2025-Mar 2026 (latest APS 12-month period))

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.

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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}
}

Permalink

https://futureproof.collab365.com/data/2026-q4.1

Data as of release 2026-q4.1, published 2026-08-05. 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.