Will AI replace Call and contact centre occupations?

Not as a job, but it is already doing parts of the work. Across the 35 official task statements scored for Call and contact centre occupations (United Kingdom, SOC 7211), 58% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 61 out of 100 (range 56–67, 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 “Call and contact centre occupations” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Enter and update customers' records on computers” (93/100, very high); “Enter change of address orders into computers that process forwarding address labels” (93/100, very high); “Record details of customer enquiries, complaints, or comments in the company database” (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 “Call and contact centre occupations” stay human?

About 24% 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: “Use clear and engaging communication to establish a good rapport with customers and ask relevant questions to determine their needs” (4/100, minimal); “Demonstrate knowledge of the organization's brand values and core values in service delivery” (11/100, minimal); “Provide excellent customer service by understanding the needs and expectations of customers” (11/100, 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 “Call and contact centre occupations” do about AI?

Start from the ledger rather than the headline: 58% of this job's weighted core work is exposed, and roughly 24% 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 Call and contact centre occupations 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 35 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

Call and contact centre occupations

responding to customer enquiries, analysing the quality of customer service and organizing and prioritizing own workload to meet deadlines. 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: entering and updating customers' records on computers. The tasks, though, are not you.

Your move: three real directions from here ↓

Where the work sits, by task weight

shifting to AI: 58%
changing shape: 18%
staying human: 24%

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

Whole-job exposure score 61 out of 100 (56–67 allowing for uncertainty): high exposure, across 35 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 call and contact centre occupations 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; using clear and engaging communication to establish a good rapport with customers and ask relevant questions to determine their needs is what this work rebuilds around. Your move starts there.

Your week, as this page understands it

Call and contact centre occupations receive and respond to telephone calls from potential clients and existing customers regarding the products and services offered by an organisation. The job title says “call” or “contact centre occupations”: officially one job, two names. The real job is the part underneath: using clear and engaging communication to establish a good rapport with customers and ask relevant questions to determine their needs. 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 call and contact centre occupations is not one task. It is 35 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is using clear and engaging communication to establish a good rapport with customers and ask relevant questions to determine their needs, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 58%
changing shape: 18%
staying human: 24%

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

21 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.

Responding to customer enquiries
This is reading one thing and writing another: customer enquiries in, a record out. That is the shape today's tools are built for.
importance 90 · 7211/00
Source: “Respond to customer enquiries.” (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: Answering customer questions from known information is something software already does at speed and 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 1/4 · how much data exists 3/4.
Entering and updating customers' records on computers
This is reading one thing and writing another: customers' records in, a record out. That is the shape today's tools are built for.
importance 85 · 7211/00
Source: “Enter and update customers' records on computers.” (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: Typing and updating customer details in a system is routine data entry that software already does 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.
Assisting customers with order placement and providing account information
This is reading one thing and writing another: customers in, a record out. That is the shape today's tools are built for.
importance 85 · 7211/00
Source: “Assist customers with order placement and provide account information.” (UK 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: Placing orders and reading back account details is exactly the kind of contact-centre work software already completes.
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.
Handling web chat enquiries from customers
This is reading one thing and writing another: web chat enquiries in, a record out. That is the shape today's tools are built for.
importance 80 · 7211/00
Source: “Handle web chat enquiries from customers.” (UK 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: Written chat enquiries are exactly what current chat tools handle at or above normal 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 4/4.

Changing shape

6 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 90 · 7211/00
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.
Adapting communication style to effectively manage customer expectations
The software now makes the first pass at communication style, 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 · 7211/00
Source: “Adapt communication style to effectively manage customer expectations.” (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: Software can adjust tone and wording, but managing expectations works because a person is listening and responding.
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.
Resolving customer complaints through phone or online communication
The software now makes the first pass at customer complaints, 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 · 7211/00
Source: “Resolve customer complaints through phone or online communication.” (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: Complaint replies can be drafted well, but calming an unhappy customer still often needs 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.

Staying human

8 tasks

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.

Making telesales and marketing research calls to new and existing customers
The value here is that a specific person handles telesales and stands behind it. That is earned, not computed.
importance 85 · 7211/00
Source: “Make telesales and market research calls to new and existing customers.” (UK 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: These are live calls where the response depends on the person making them.
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.
Seeking sales of new or additional services or products
The value here is that a specific person handles sales of new or additional services or products and stands behind it. That is earned, not computed.
importance 85 · 7211/00
Source: “Seek sales of new or additional services or products.” (UK 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 same decision, made over and over; the value is that a specific person does it.
The rating behind it: Recommendations can be generated, but persuading someone to buy an extra product is still largely a human sell.
The five ratings: output a model can produce 2/4 · 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.
Delivering high-quality products and services to customers using various channels
The value here is that a specific person handles high-quality products and stands behind it. That is earned, not computed.
importance 85 · 7211/00
Source: “Deliver high-quality products and services to customers using various channels such as face-to-face, telephone, digital, and written communication.” (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: Written and digital contact can be automated, but the face-to-face part depends on the person handling it.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.

Show the other 25 tasks

Entering change of address orders into computers that process forwarding address labels
shifting to AI
This is reading one thing and writing another: change of address orders in, a record out. That is the shape today's tools are built for.
importance 75 · 7211/00
Source: “Enter change of address orders into computers that process forwarding address labels.” (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: Keying a change of address into a system is straightforward data entry.
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.
Recording details of customer enquiries
shifting to AI
This is reading one thing and writing another: details of customer enquiries in, a record out. That is the shape today's tools are built for.
importance 75 · 7211/00
Source: “Record details of customer enquiries, complaints, or comments in the company database.” (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: Writing up what a customer said into the database is note-taking that tools do accurately.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Determining charges for services
shifting to AI
This is reading one thing and writing another: charges in, a record out. That is the shape today's tools are built for.
importance 70 · 7211/00
Source: “Determine charges for services requested.” (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: Working out charges from a price list is straightforward calculation software handles 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.
Preparing invoices for goods returned by customers
shifting to AI
This is reading one thing and writing another: invoices in, a record out. That is the shape today's tools are built for.
importance 70 · 7211/00
Source: “Prepare invoices for goods returned by customers.” (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: Producing a credit invoice from returns data is routine calculation and paperwork.
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.
Processing email orders as per business requirements
shifting to AI
This is reading one thing and writing another: email orders in, a record out. That is the shape today's tools are built for.
importance 75 · 7211/00
Source: “Process email orders as per business requirements.” (UK task statement)
How this row was scored
Exposure score: 83 out of 100 (76–90 allowing for uncertainty): very high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Reading an emailed order and entering it into the system is exactly the sort of task software automates.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Completing contract forms using computers
shifting to AI
This is reading one thing and writing another: contract forms in, a record out. That is the shape today's tools are built for.
importance 70 · 7211/00
Source: “Complete contract forms using computers.” (UK task statement)
How this row was scored
Exposure score: 81 out of 100 (77–85 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Filling in contract forms from held details is template work software already completes accurately.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Analysing the quality of customer service
shifting to AI
This is reading one thing and writing another: the quality of customer service in, a record out. That is the shape today's tools are built for.
importance 80 · 7211/00
Source: “Analyse the quality of customer service provided.” (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: Reviewing call and chat records against quality standards is analysis that tools do quickly and consistently.
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.
Checking to ensure that appropriate changes were made to resolve customers' problems
shifting to AI
This is reading one thing and writing another: ensure in, a record out. That is the shape today's tools are built for.
importance 80 · 7211/00
Source: “Check to ensure that appropriate changes were made to resolve customers' problems.” (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: Checking that a change actually went through means comparing records, which 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 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Organizing and prioritizing own workload to meet deadlines
shifting to AI
This is reading one thing and writing another: own workload in, a record out. That is the shape today's tools are built for.
importance 80 · 7211/00
Source: “Organize and prioritize own workload to meet deadlines.” (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: Sorting and prioritising a work queue against deadlines is scheduling work that software does well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Arranging for billing of services
shifting to AI
This is reading one thing and writing another: billing of services in, a record out. That is the shape today's tools are built for.
importance 75 · 7211/00
Source: “Arrange for billing of services.” (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: Setting up billing follows fixed rules in a system, which software handles reliably.
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.
Identifying possible causes
shifting to AI
This is reading one thing and writing another: possible causes in, a record out. That is the shape today's tools are built for.
importance 70 · 7211/00
Source: “Identify possible causes for complaints, such as extreme weather conditions.” (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: Spotting patterns behind a spike in complaints, such as bad weather, is data analysis tools handle 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.
Issuing service discontinuation orders using computers
shifting to AI
This is reading one thing and writing another: service discontinuation orders in, a record out. That is the shape today's tools are built for.
importance 70 · 7211/00
Source: “Issue service discontinuation orders using computers.” (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: Raising a cancellation order in a system follows fixed steps that software can carry out.
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.
Assisting customers in resolving computer issues
shifting to AI
This is reading one thing and writing another: customers in, a record out. That is the shape today's tools are built for.
importance 70 · 7211/00
Source: “Assist customers in resolving computer issues.” (UK task statement)
How this row was scored
Exposure score: 70 out of 100 (66–74 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: Common computer problems are extremely well documented, so tools give good step-by-step 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 4/4.
Informing customers about the status of their insurance claims
shifting to AI
This is reading one thing and writing another: customers in, a record out. That is the shape today's tools are built for.
importance 75 · 7211/00
Source: “Inform customers about the status of their insurance claims.” (UK task statement)
How this row was scored
Exposure score: 69 out of 100 (65–73 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Looking up a claim's status and explaining it in plain words is well within what current tools do.
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.
Reviewing information to assess validity of complaints
shifting to AI
This is reading one thing and writing another: information in, a record out. That is the shape today's tools are built for.
importance 75 · 7211/00
Source: “Review information to assess validity of complaints.” (UK task statement)
How this row was scored
Exposure score: 66 out of 100 (62–70 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Judging whether a complaint stands up means checking records against policy, which software does well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Responding to public enquiries
shifting to AI
This is reading one thing and writing another: public enquiries in, a record out. That is the shape today's tools are built for.
importance 80 · 7211/00
Source: “Respond to public enquiries.” (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: Answering common public questions is documented work already handled by automated services.
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.
Collecting payments from customers
shifting to AI
This is reading one thing and writing another: payments in, a record out. That is the shape today's tools are built for.
importance 75 · 7211/00
Source: “Collect payments from 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: Over the phone this is card details typed into a system, which automated payment lines already handle end to end.
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.
Issuing refunds or compensation to customers
changing shape
The software now makes the first pass at refunds, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 80 · 7211/00
Source: “Issue refunds or compensation to customers.” (UK 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: Refund decisions follow written policy and system records, though sign-off usually stays with a person.
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.
Maintaining clear communication during service recovery processes
changing shape
The software now makes the first pass at clear communication during service recovery processes, 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 75 · 7211/00
Source: “Maintain clear communication during service recovery processes.” (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: Update messages can be written automatically, but keeping a wronged customer onside often needs 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.
Providing expert advice on specific products and services to customers
changing shape
The software now makes the first pass at expert advice, 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 80 · 7211/00
Source: “Provide expert advice on specific products and services to customers.” (UK 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: Product answers can be produced from documentation, but customers often want a knowledgeable person on the line.
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.
Delivering services to customers and colleagues based on regulatory requirements and organizational policies
staying human
The rules require a named, qualified person to answer for services, and that person cannot be a piece of software.
importance 80 · 7211/00
Source: “Deliver services to customers and colleagues based on regulatory requirements and organizational policies, providing clear and concise advice.” (UK 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; someone qualified has to answer for it; the value is that a specific person does it.
The rating behind it: Regulated advice can be drafted from the rulebook, but a responsible person normally has to give it.
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 2/4 · how much data exists 3/4.
Utilising systems, equipment and technology to meet customer needs
staying human
This work happens in the physical world: systems, equipment and technology, in a real place. Software cannot follow it there.
importance 75 · 7211/00
Source: “Utilise systems, equipment, and technology to meet customer needs.” (UK 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; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Some of this is screen work, but much of it means operating tills and scanners in the shop.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Providing excellent customer service by understanding the needs and expectations of customers
staying human
This work happens in the physical world: excellent customer service, in a real place. Software cannot follow it there.
importance 85 · 7211/00
Source: “Provide excellent customer service by understanding the needs and expectations of customers.” (UK task statement)
How this row was scored
Exposure score: 11 out of 100 (4–18 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Good service here comes from reading the customer standing in front of you.
The five ratings: output a model can produce 1/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Demonstrating knowledge of the organization's brand values and core values in service delivery
staying human
This work happens in the physical world: knowledge of the organization's brand values, in a real place. Software cannot follow it there.
importance 75 · 7211/00
Source: “Demonstrate knowledge of the organization's brand values and core values in service delivery.” (UK task statement)
How this row was scored
Exposure score: 11 out of 100 (4–18 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Showing what the brand stands for happens through how staff behave with customers in person.
The five ratings: output a model can produce 1/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Using clear and engaging communication to establish a good rapport with customers and ask relevant questions to determine their needs
staying human
This work happens in the physical world: clear, in a real place. Software cannot follow it there.
importance 80 · 7211/00
Source: “Use clear and engaging communication to establish a good rapport with customers and ask relevant questions to determine their needs.” (UK task statement)
How this row was scored
Exposure score: 4 out of 100 (0–11 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Building rapport with a customer happens face to face in the moment.
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 3/4 · how much data exists 2/4.

What this job pays, and how many people do it

Median pay: £27,000a 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: 81,500in 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' records in, a record out. The rows above are exactly that shape: entering and updating customers' records on computers and responding to customer enquiries. What it cannot do is be there in the room, and that is still where clear gets done. Which is why this page talks about your tasks changing, not your job ending.

Your move

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

The exposed part of your job is the biggest part, and I am not going to dress that up: entering and updating customers' records on computers is work today's tools do quickly and cheaply, and that is not coming back.

So, given all that: 58% of this job's task weight sits in rows the software is already learning, 18% in rows that change shape rather than disappear, and 24% in rows it is nowhere near. That is the position, measured across 35 scored tasks. It is not a forecast about you.

What you have that the software does not is using clear and engaging communication to establish a good rapport with customers and ask relevant questions to determine their needs, 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' records 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' records, 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 entering and updating customers' records on computers” 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 using clear and engaging communication to establish a good rapport with customers and ask relevant questions to determine their needs 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

Now the roads out, with the honest bill on each one. One route survived the checks. The rest are below with the reason they did not.

Call and contact centre occupationsLegal associate professionals
a year or morematched on shared tasks
Working out who is actually right from the paperwork, and writing it up so it holds, is the same skill whether the file is a complaint or a case.
The escalation nobody else wanted is the closest thing on your floor to legal work - and it's the part the bots can't take.
The work the two jobs share
- You already do
  “Obtain and examine all relevant information to assess validity of complaints and to determine possible causes...”
  They do
  “Investigate facts and law of cases and search pertinent sources... to determine causes of action and to prepare cases.”
What you would not already have: Court and tribunal procedure is entirely new work.
The honest bill
Pay: £34,700 against your £27,000 (ONS ASHE Table 14.7a, 2025 provisional (both)).
- Credential: Same default-closed credential barrier as uk.7219->3520. Banded year-plus.
- Is the target job itself holding up: Cannot be evaluated - no UK occupational projection exists. Stated as a gap.
- What you live on meanwhile: Qualification study alongside work; nation-scoped free careers advice first.
How long: A year or more of part-time qualification study alongside work.
See what AI is doing to legal associate professionals

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.

Customer service supervisors
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “issue refunds or compensation to customers”. Across the whole of both lists that adds up to about 10% 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 10% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Look at that job’s page anyway →
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: “use clear and engaging communication to establish a good rapport with customers and ask relevant questions…”. Across the whole of both lists that adds up to about 10% 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 10% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Look at that job’s page anyway →
Travel agents
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already provide excellent customer service by understanding the needs and expectations of customers, and their equivalent is to provide excellent customer service throughout the full customer journey. Across both published task lists that is about 9% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 9% 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: 55% of its own task list already scores in the top exposure band (60/100 in this release), so the same software is eating it.
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: 58% of its task weight, across 35 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: using clear and engaging communication to establish a good rapport with customers and ask relevant questions to determine their needs 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 Customer Service Representatives 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

The other groups this work is counted across:

Receptionists and Information Clerks

In US official statistics this job is counted as Customer Service Representatives and Receptionists and Information Clerks. Pay is shown separately for each of those groups (medians cannot be averaged together), while the task list and the scores on this page are for this group only.

Your route through this

Where to go next, and what it costs

Free, and complete

The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.

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 contact centre adviser, and we are not going to point you at the nearest one and call it a fit.

The working behind that

No support or contact-centre Space exists.

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 58% 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 contact centre adviser. 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.

Nearby moves

The jobs above, as pages you can read the same way as this one. Your job shares its core work with these. That is what the match is, and it is all it is.

Legal associate professionals →The escalation nobody else wanted is the closest thing on your floor to legal work - and it's the part the bots can't take.

Noted, and thank you. We’ll email you if a Space for contact centre and customer service work launches. Nothing else.

That did not look like an email address, so nothing was saved. Have another go below.

We could not save that. The fault is ours, not yours, and your address was not stored. Please try again later.

No Space for contact centre and customer service work 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 contact centre and customer service work 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 contact centre and customer service work 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 Call and contact centre occupations?: Not as a job, but it is already doing parts of the work. Across the 35 official task statements scored for Call and contact centre occupations (United Kingdom, SOC 7211), 58% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 61 out of 100 (range 56–67, 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 “Call and contact centre occupations” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Enter and update customers' records on computers” (93/100, very high); “Enter change of address orders into computers that process forwarding address labels” (93/100, very high); “Record details of customer enquiries, complaints, or comments in the company database” (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 “Call and contact centre occupations” stay human?: About 24% 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: “Use clear and engaging communication to establish a good rapport with customers and ask relevant questions to determine their needs” (4/100, minimal); “Demonstrate knowledge of the organization's brand values and core values in service delivery” (11/100, minimal); “Provide excellent customer service by understanding the needs and expectations of customers” (11/100, 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 “Call and contact centre occupations” do about AI?: Start from the ledger rather than the headline: 58% of this job's weighted core work is exposed, and roughly 24% 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 Call and contact centre occupations 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 35 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.

How we score a job Download this release Look up another job

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}
}

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.