Will AI replace Insurance underwriters?

Not as a job, but it is already doing parts of the work. Across the 56 official task statements scored for Insurance underwriters (United Kingdom, SOC 3532), 52% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 57 out of 100 (range 51–63, band: partial). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.

Which tasks in “Insurance underwriters” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Monitor changes in the insurance market relevant to client services” (93/100, very high); “Communicate latest industry developments effectively within the organisation” (85/100, very high); “Analyse market trends to compare products and assess competitor strategies” (83/100, 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 “Insurance underwriters” stay human?

About 27% 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: “Establish and maintain strong collaborative relationships with customers, suppliers, and stakeholders” (10/100, minimal); “Develop and manage relationships with clients, colleagues, and senior management to achieve desired business outcomes” (13/100, minimal); “Develop working relationships with brokers to facilitate insurance underwriting and administration” (13/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.

What should someone working in “Insurance underwriters” do about AI?

Start from the ledger rather than the headline: 52% of this job's weighted core work is exposed, and roughly 27% 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 Insurance underwriters 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 56 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

Insurance underwriters

analysing and interpreting data, using specialist software programs, helping administer insurance and operating within approved financial limits and escalate underwriting issues beyond own authority. If that's your week, this page is about your job.

The honest answer

This job is splitting in two: analysing market trends to compare products and assess competitor strategies is work AI now does quickly and cheaply, and developing working relationships with brokers to facilitate insurance underwriting and administration is work it can't touch.

Your move: what you can actually do about this ↓

Where the work sits, by task weight

shifting to AI: 52%
changing shape: 21%
staying human: 27%

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

Whole-job exposure score 57 out of 100 (51–63 allowing for uncertainty): partial exposure, across 56 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 insurance underwriters is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.

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

Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.

Which half fills your week decides your exposure. Moving toward the second half is a real, doable plan.

Your week, as this page understands it

Insurance underwriters identify and measure the risks associated with an activity, determine whether this risk is insurable and issue insurance policies which provide financial compensation in the event of loss. The job title says “insurance underwriters”. The real job is the part underneath: developing working relationships with brokers to facilitate insurance underwriting and administration. 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 insurance underwriters is not one task. It is 56 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is developing working relationships with brokers to facilitate insurance underwriting and administration, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 52%
changing shape: 21%
staying human: 27%

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 2026-08-05. Read the full method.

Your job, task by task

These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.

16 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

29 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.

Analysing and interpreting data, using specialist software programs
This is reading one thing and writing another: data in, a record out. That is the shape today's tools are built for.
importance 85 · 3532/00
Source: “Analyse and interpret data, using specialist software programs.” (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: Working through data in specialist software is exactly the kind of analysis computers 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.
Obtaining and analysing relevant information and data to evaluate performance and influence business results using it software and systems
This is reading one thing and writing another: relevant information in, a record out. That is the shape today's tools are built for.
importance 85 · 3532/00
Source: “Obtain and analyse relevant information and data to evaluate performance and influence business results using it software and systems.” (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: Pulling business data out of company systems and turning it into performance insight is a well trodden task for software.
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.
Assessing insurance proposals to determine cover terms and premiums
This is reading one thing and writing another: insurance proposals in, a record out. That is the shape today's tools are built for.
importance 85 · 3532/00
Source: “Assess insurance proposals to determine cover terms and premiums.” (UK task statement)
How this row was scored
Exposure score: 69 out of 100 (62–76 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; someone qualified has to answer for it.
The rating behind it: Deciding cover terms and premiums is the underwriting act itself, committing the insurer, so authorised staff must own it.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Handling personal, confidential and sensitive information with strict adherence to legal and organisational confidentiality policies
This is reading one thing and writing another: personal, confidential and sensitive information in, a record out. That is the shape today's tools are built for.
importance 85 · 3532/00
Source: “Handle personal, confidential, and sensitive information with strict adherence to legal and organisational confidentiality policies.” (UK task statement)
How this row was scored
Exposure score: 66 out of 100 (59–73 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: Data protection duties are written down and systems enforce much of the handling, though an accountable person answers for breaches.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.

Changing shape

12 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.

Conducting risk assessments and developing strategies
The software now makes the first pass at risk assessments, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 80 · 3532/00
Source: “Conduct risk assessments and develop strategies to manage, mitigate, and transfer risks.” (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; someone qualified has to answer for it.
The rating behind it: Risk assessment methods are documented and software drafts them, but accepting and transferring risk commits the insurer, needing authorised staff.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Helping administer insurance, annuity and pension schemes, determining financial soundness and calculating premiums
The software now makes the first pass at administer insurance, annuity and pension schemes, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 75 · 3532/00
Source: “Help administer insurance, annuity and pension schemes, determining financial soundness and calculating premiums.” (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; someone qualified has to answer for it.
The rating behind it: Scheme administration and premium sums are largely systematised, but judging financial soundness commits the insurer and needs authorised staff.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Operating within approved financial limits and escalate underwriting issues beyond own authority
The software now makes the first pass at within approved financial limits, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 75 · 3532/00
Source: “Operate within approved financial limits and escalate underwriting issues beyond own authority.” (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; someone qualified has to answer for it.
The rating behind it: Authority limits are written rules software can apply, though the escalation itself sits with an accountable underwriter.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.

Staying human

15 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.

Ensuring compliance with regulations and providing advice and solutions to potential security risks
The ratings behind this row put compliance well outside what today's tools can do on their own.
importance 85 · 3532/00
Source: “Ensure compliance with regulations and provide advice and solutions to potential security risks, understanding local, national, and international regulations.” (UK task statement)
How this row was scored
Exposure score: 32 out of 100 (25–39 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.
The rating behind it: Regulations are well documented, but judging which ones bite in a specific situation still needs a person.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Negotiating terms with policyholders or their brokers
The rules require a named, qualified person to answer for terms, and that person cannot be a piece of software.
importance 80 · 3532/00
Source: “Negotiate terms with policyholders or their brokers.” (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: someone qualified has to answer for it; the value is that a specific person does it.
The rating behind it: Agreeing terms binds the insurer, so it needs someone holding underwriting authority, and the haggling itself happens live with a broker.
The five ratings: output a model can produce 2/4 · 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 2/4.
Developing working relationships with brokers to facilitate insurance underwriting and administration
The value here is that a specific person handles relationships and stands behind it. That is earned, not computed.
importance 80 · 3532/00
Source: “Develop working relationships with brokers to facilitate insurance underwriting and administration.” (UK task statement)
How this row was scored
Exposure score: 13 out of 100 (6–20 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Broker relationships are built over time between particular people, which is not something software can hold.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.

Show the other 46 tasks

Monitoring changes in the insurance market relevant to client services
shifting to AI
This is reading one thing and writing another: changes in, a record out. That is the shape today's tools are built for.
importance 60 · 3532/00
Source: “Monitor changes in the insurance market relevant to client services.” (UK task statement)
How this row was scored
Exposure score: 93 out of 100 (86–100 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: Market developments are public and easily summarised, though judging which changes matter to particular clients uses the underwriter's own knowledge.
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.
Communicating latest industry developments effectively within the organisation
shifting to AI
This is reading one thing and writing another: latest industry developments effectively within the organisation in, a record out. That is the shape today's tools are built for.
importance 60 · 3532/00
Source: “Communicate latest industry developments effectively within the organisation.” (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: Summarising industry news for colleagues is exactly the sort of writing software does quickly and 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 4/4.
Analysing market trends to compare products and assess competitor strategies
shifting to AI
This is reading one thing and writing another: market trends in, a record out. That is the shape today's tools are built for.
importance 80 · 3532/00
Source: “Analyse market trends to compare products and assess competitor strategies.” (UK task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 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: Comparing products and competitor strategies uses widely available published information.
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.
Developing policies to guide organisational operations
shifting to AI
This is reading one thing and writing another: policies in, a record out. That is the shape today's tools are built for.
importance 55 · 3532/00
Source: “Develop policies to guide organisational operations.” (UK task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 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: Policy drafting draws on abundant published examples AI can adapt to the organisation.
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.
Keeping up to date with financial products and legislation
shifting to AI
This is reading one thing and writing another: to date in, a record out. That is the shape today's tools are built for.
importance 55 · 3532/00
Source: “Keep up to date with financial products and legislation.” (UK task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Keeping track of new products and legislation is exactly the kind of monitoring 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 4/4.
Gathering, analysing and interpreting data relevant to insurance products and services
shifting to AI
This is reading one thing and writing another: this work in, a record out. That is the shape today's tools are built for.
importance 80 · 3532/00
Source: “Gather, analyse and interpret data relevant to insurance products and services.” (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: Gathering and interpreting insurance data is documented analysis run on available information, with underwriting decisions made separately.
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.
Calculating possible insurance risks
shifting to AI
This is reading one thing and writing another: possible insurance risks in, a record out. That is the shape today's tools are built for.
importance 75 · 3532/00
Source: “Calculate possible insurance risks.” (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: Risk calculation runs on models and data, which is exactly what software is built for.
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.
Maintaining detailed and accurate records of underwritten policies and decisions
shifting to AI
This is reading one thing and writing another: detailed in, a record out. That is the shape today's tools are built for.
importance 75 · 3532/00
Source: “Maintain detailed and accurate records of underwritten policies and decisions.” (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: Recording underwriting decisions is routine system work software does accurately, with the decisions themselves made separately.
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.
Monitoring account profitability to ensure financial targets are met
shifting to AI
This is reading one thing and writing another: account profitability in, a record out. That is the shape today's tools are built for.
importance 65 · 3532/00
Source: “Monitor account profitability to ensure financial targets are met.” (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: Tracking profitability against targets is reporting on numbers already sitting in the systems.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Reviewing company records to determine amount of insurance in force on single risk or group of closely related risks
shifting to AI
This is reading one thing and writing another: company records in, a record out. That is the shape today's tools are built for.
importance 60 · 3532/00
Source: “Review company records to determine amount of insurance in force on single risk or group of closely related risks.” (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: Adding up exposure across company records is a database question software answers reliably.
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.
Compiling patients' medical records to document condition and treatment
shifting to AI
This is reading one thing and writing another: patients' medical records in, a record out. That is the shape today's tools are built for.
importance 55 · 3532/00
Source: “Compile patients' medical records to document condition and treatment.” (UK task statement)
How this row was scored
Exposure score: 81 out of 100 (74–88 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: For an underwriter this is assembling medical evidence supplied with consent, a document task software does well, not a clinical act.
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.
Writing to others to explain company underwriting policies
shifting to AI
This is reading one thing and writing another: this work in, a record out. That is the shape today's tools are built for.
importance 80 · 3532/00
Source: “Write to others to explain company underwriting policies.” (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: Explaining a written policy in a letter is straightforward writing that 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.
Maintaining records using IT systems
shifting to AI
This is reading one thing and writing another: records in, a record out. That is the shape today's tools are built for.
importance 80 · 3532/00
Source: “Maintain records using IT systems.” (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: Keeping system records current is screen work with abundant documentation behind it.
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.
Analysing statistics from actuaries and other sources
shifting to AI
This is reading one thing and writing another: statistics in, a record out. That is the shape today's tools are built for.
importance 75 · 3532/00
Source: “Analyse statistics from actuaries and other sources.” (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: Analysing statistics from several sources is data work software does quickly and 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.
Assisting in the formulation of policies and procedures
shifting to AI
This is reading one thing and writing another: the formulation of policies in, a record out. That is the shape today's tools are built for.
importance 60 · 3532/00
Source: “Assist in the formulation of policies and procedures.” (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: Drafting policies and procedures from existing guidance is strong ground for software, with officers and councillors deciding.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Preparing quotes for brokers or business clients
shifting to AI
This is reading one thing and writing another: quotes in, a record out. That is the shape today's tools are built for.
importance 70 · 3532/00
Source: “Prepare quotes for brokers or business clients.” (UK task statement)
How this row was scored
Exposure score: 74 out of 100 (70–78 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: Turning risk details into a priced quote is standard, rule-driven work that software produces quickly.
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 4/4.
Developing computer systems to improve data collection and analysis efficiency
shifting to AI
This is reading one thing and writing another: computer systems in, a record out. That is the shape today's tools are built for.
importance 65 · 3532/00
Source: “Develop computer systems to improve data collection and analysis efficiency.” (UK task statement)
How this row was scored
Exposure score: 70 out of 100 (63–77 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: Building data and analysis tools is well-documented technical work that software now drafts effectively.
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.
Calculating insurance quote premiums
shifting to AI
This is reading one thing and writing another: insurance quote premiums in, a record out. That is the shape today's tools are built for.
importance 80 · 3532/00
Source: “Calculate insurance quote premiums.” (UK task statement)
How this row was scored
Exposure score: 69 out of 100 (62–76 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; someone qualified has to answer for it.
The rating behind it: Here the underwriter actually prices the risk and commits the insurer, so someone holding underwriting authority must own the figure.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Assessing risk by reviewing background information
shifting to AI
This is reading one thing and writing another: risk in, a record out. That is the shape today's tools are built for.
importance 70 · 3532/00
Source: “Assess risk by reviewing background information, reports, and medical records.” (UK task statement)
How this row was scored
Exposure score: 69 out of 100 (62–76 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; someone qualified has to answer for it.
The rating behind it: Reviewing reports and medical evidence to price risk is document analysis software does well, but the risk decision commits the insurer.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Decreasing value of policy when risk is substandard using reference materials
shifting to AI
This is reading one thing and writing another: value of policy in, a record out. That is the shape today's tools are built for.
importance 55 · 3532/00
Source: “Decrease value of policy when risk is substandard using reference materials.” (UK task statement)
How this row was scored
Exposure score: 69 out of 100 (62–76 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; someone qualified has to answer for it.
The rating behind it: Applying loadings from reference tables is rule-following work, though the change sits under someone’s authority.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Assessing documents to evaluate risk based on health
shifting to AI
This is reading one thing and writing another: documents in, a record out. That is the shape today's tools are built for.
importance 80 · 3532/00
Source: “Assess documents to evaluate risk based on health, financial status, and property condition.” (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: Reading documents and turning them into a risk view is desk work software can now largely draft.
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.
Assessing market conditions to set competitive premiums
shifting to AI
This is reading one thing and writing another: market conditions in, a record out. That is the shape today's tools are built for.
importance 75 · 3532/00
Source: “Assess market conditions to set competitive premiums.” (UK task statement)
How this row was scored
Exposure score: 66 out of 100 (59–73 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: Pricing draws on market and claims data software reads well, though the final call reflects the firm’s appetite.
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.
Developing organisational policies in accordance with regulatory and ethical standards
shifting to AI
This is reading one thing and writing another: organisational policies in, a record out. That is the shape today's tools are built for.
importance 60 · 3532/00
Source: “Develop organisational policies in accordance with regulatory and ethical standards.” (UK task statement)
How this row was scored
Exposure score: 66 out of 100 (59–73 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: Regulatory and ethical standards are published, so software drafts policy text, with the insurer's own governance approving it.
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.
Implementing and monitoring risk management strategies to mitigate potential risks
shifting to AI
This is reading one thing and writing another: risk management strategies in, a record out. That is the shape today's tools are built for.
importance 60 · 3532/00
Source: “Implement and monitor risk management strategies to mitigate potential risks.” (UK task statement)
How this row was scored
Exposure score: 66 out of 100 (59–73 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: Risk management methods are documented and monitoring is automated, though putting strategies into effect is agreed and owned internally.
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.
Specifying conditions to be imposed on different types of policies
shifting to AI
This is reading one thing and writing another: conditions in, a record out. That is the shape today's tools are built for.
importance 50 · 3532/00
Source: “Specify conditions to be imposed on different types of policies, such as requiring a burglar alarm installation.” (UK task statement)
How this row was scored
Exposure score: 66 out of 100 (59–73 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: Standard conditions like requiring a burglar alarm come from well-known risk rules software can apply.
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.
Evaluating and adjusting insurance policies and terms to reflect changes in risk exposure and marketing conditions
changing shape
The software now makes the first pass at insurance policies, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 70 · 3532/00
Source: “Evaluate and adjust insurance policies and terms to reflect changes in risk exposure and market conditions.” (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; someone qualified has to answer for it.
The rating behind it: Repricing and adjusting cover uses documented method on available data, but changing policy terms commits the insurer to authorised staff.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Identifying issues and concerns and recommending actions for resolution
changing shape
The software now makes the first pass at issues, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 70 · 3532/00
Source: “Identify issues and concerns, and recommend actions for resolution.” (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: Spotting issues in insurance files and proposing fixes is well-documented analysis software drafts, with a manager deciding what happens.
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.
Specifying applicable endorsements or applying rating to ensure safe
changing shape
The software now makes the first pass at applicable endorsements, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 55 · 3532/00
Source: “Specify applicable endorsements or apply rating to ensure safe, profitable distribution of risks.” (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; someone qualified has to answer for it.
The rating behind it: Rating and endorsements follow documented rules, though the final wording stays with an accountable underwriter.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Identifying problem-solving techniques applicable in a given situation and taking ownership through to resolution
changing shape
The software now makes the first pass at techniques applicable, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 65 · 3532/00
Source: “Identify problem-solving techniques applicable in a given situation and take ownership through to resolution.” (UK task statement)
How this row was scored
Exposure score: 49 out of 100 (42–56 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Suggesting approaches is easy, but owning a problem through to resolution stays with the person.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Coordinating and overseeing claims operations to ensure efficient and accurate processing of claims
changing shape
The software now makes the first pass at claims operations, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 70 · 3532/00
Source: “Coordinate and oversee claims operations to ensure efficient and accurate processing of claims.” (UK task statement)
How this row was scored
Exposure score: 48 out of 100 (41–55 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Overseeing claims handling needs someone accountable within the insurer, though the tracking and quality checks behind it are automatable.
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 1/4 · how much data exists 3/4.
Evaluating and improving operational processes to enhance customer experience
changing shape
The software now makes the first pass at operational processes, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 65 · 3532/00
Source: “Evaluate and improve operational processes to enhance customer experience.” (UK task statement)
How this row was scored
Exposure score: 48 out of 100 (41–55 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Looking at how the operation runs and finding improvements is analysis software supports well.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Declining excessive risks
changing shape
The software now makes the first pass at excessive risks, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 60 · 3532/00
Source: “Decline excessive risks.” (UK task statement)
How this row was scored
Exposure score: 48 out of 100 (41–55 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: The signals that make a risk unacceptable are largely codified, but declining business is a decision the firm owns.
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 1/4 · how much data exists 3/4.
Managing client concerns, complaints and compliments, escalating them
changing shape
The software now makes the first pass at client concerns, complaints and compliments, escalating them, 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 70 · 3532/00
Source: “Manage client concerns, complaints, and compliments, escalating them as necessary.” (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: Complaint handling follows set rules and templates, though upset customers still want a person to respond.
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.
Assessing and analysing the complex and changing needs of the insurance market and recommending appropriate products and services
changing shape
The software now makes the first pass at the complex, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 70 · 3532/00
Source: “Assess and analyse the complex and changing needs of the insurance market and recommend appropriate products and services.” (UK task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Market analysis is desk research software helps with, though judging what the firm should sell needs experience.
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 1/4 · how much data exists 3/4.
Resolving customer complaints about insurance policies
staying human
The rules require a named, qualified person to answer for customer complaints, and that person cannot be a piece of software.
importance 65 · 3532/00
Source: “Resolve customer complaints about insurance policies.” (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: Complaint rules are clear and replies draftable, but regulated complaint handling keeps a responsible person in the loop.
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.
Assessing and deciding on sharing risk with a reinsurer
staying human
The rules require a named, qualified person to answer for sharing risk, and that person cannot be a piece of software.
importance 65 · 3532/00
Source: “Assess and decide on sharing risk with a reinsurer.” (UK task statement)
How this row was scored
Exposure score: 37 out of 100 (30–44 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: The numbers are calculable, but deciding to pass risk to a reinsurer is a judgement the underwriter owns.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Authorising reinsurance of policy when risk is high
staying human
The rules require a named, qualified person to answer for reinsurance of policy, and that person cannot be a piece of software.
importance 65 · 3532/00
Source: “Authorise reinsurance of policy when risk is high.” (UK task statement)
How this row was scored
Exposure score: 36 out of 100 (29–43 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Authorising reinsurance is a decision the firm requires a named, accountable underwriter to make.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 3/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Supporting and managing business processes and workforce to ensure adherence to operational objectives
staying human
The value here is that a specific person handles business processes and stands behind it. That is earned, not computed.
importance 75 · 3532/00
Source: “Support and manage business processes and workforce to ensure adherence to operational objectives.” (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: Software can draft plans and track process, but managing people and holding them to it stays human.
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.
Developing and executing operational plans in alignment with organisational objectives
staying human
The value here is that a specific person handles operational plans and stands behind it. That is earned, not computed.
importance 70 · 3532/00
Source: “Develop and execute operational plans in alignment with organisational objectives, demonstrating a keen understanding of strategic planning.” (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: Software can draft an operational plan, but agreeing and driving it through a business rests on people.
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.
Coordinating with specialists for risk assessment tasks
staying human
The value here is that a specific person handles specialists and stands behind it. That is earned, not computed.
importance 65 · 3532/00
Source: “Coordinate with specialists for risk assessment tasks.” (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: Software can prepare the questions and pull the data, but the exchange with specialists is a working conversation.
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.
Negotiating agreements with external and internal organizations and stakeholders using effective communication skills
staying human
The value here is that a specific person handles agreements and stands behind it. That is earned, not computed.
importance 55 · 3532/00
Source: “Negotiate agreements with external and internal organizations and stakeholders using effective communication skills.” (UK task statement)
How this row was scored
Exposure score: 28 out of 100 (21–35 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: Reaching agreement with other organisations depends on live negotiation between people.
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 3/4 · how much data exists 2/4.
Conducting loss assessments and coordinating insurance payouts to policyholders
staying human
The value here is that a specific person handles loss assessments and stands behind it. That is earned, not computed.
importance 75 · 3532/00
Source: “Conduct loss assessments and coordinate insurance payouts to policyholders.” (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 same decision, made over and over; the value is that a specific person does it.
The rating behind it: Assessing a loss often needs someone to look at what happened and reassure the policyholder while settling it.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Collaborating with internal and external stakeholders to facilitate reinsurance transactions and agreements
staying human
The rules require a named, qualified person to answer for internal and external stakeholders, and that person cannot be a piece of software.
importance 70 · 3532/00
Source: “Collaborate with internal and external stakeholders to facilitate reinsurance transactions and agreements.” (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: someone qualified has to answer for it; the value is that a specific person does it.
The rating behind it: Reinsurance deals come together through negotiation between firms, and committing to them needs someone with authority to bind the insurer.
The five ratings: output a model can produce 2/4 · 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 2/4.
Collaborating with the wider organization
staying human
The value here is that a specific person handles the wider organization and stands behind it. That is earned, not computed.
importance 65 · 3532/00
Source: “Collaborate with the wider organization, team, communities, and external partners to achieve business objectives.” (UK task statement)
How this row was scored
Exposure score: 23 out of 100 (16–30 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: Working with partners and communities towards shared goals rests on relationships rather than documents.
The five ratings: output a model can produce 1/4 · 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.
Developing and managing relationships with clients
staying human
The value here is that a specific person handles relationships and stands behind it. That is earned, not computed.
importance 75 · 3532/00
Source: “Develop and manage relationships with clients, colleagues, and senior management to achieve desired business outcomes.” (UK task statement)
How this row was scored
Exposure score: 13 out of 100 (9–17 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Business relationships are built over time between specific people, which software cannot stand in for.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
Establishing and maintaining strong collaborative relationships with customers
staying human
The value here is that a specific person handles strong collaborative relationships and stands behind it. That is earned, not computed.
importance 75 · 3532/00
Source: “Establish and maintain strong collaborative relationships with customers, suppliers, and stakeholders.” (UK task statement)
How this row was scored
Exposure score: 10 out of 100 (6–14 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Long-term working relationships with customers and suppliers are the whole point of this task.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 4/4 · how much data exists 2/4.

What this job pays, and how many people do it

Median pay: £41,600a 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: 37,600in 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: market trends in, a record out. The rows above are exactly that shape: analysing market trends to compare products and assess competitor strategies and analysing and interpreting data, using specialist software programs. What it cannot do is be trusted in person, which is what relationships run 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: analysing market trends to compare products and assess competitor strategies is work today's tools do quickly and cheaply, and that is not coming back.

So, given all that: 52% of this job's task weight sits in rows the software is already learning, 21% in rows that change shape rather than disappear, and 27% in rows it is nowhere near. That is the position, measured across 56 scored tasks. It is not a forecast about you.

What you have that the software does not is developing working relationships with brokers to facilitate insurance underwriting and administration, 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 market trends 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 market trends, 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 analysing market trends to compare products and assess competitor strategies” 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 developing working relationships with brokers to facilitate insurance underwriting and administration 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 insurance underwriters (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was pensions and insurance clerks and assistants: only about 10% of its durable work is work you already do, it is under the same pressure this job is and it pays 27.3% less. Your own job splits about 52/48: that share of the list sits in the top exposure band and the rest does not. On this evidence the honest move is inside the job rather than out of it. Become the person who owns “ensure compliance with regulations and provide advice and solutions to potential security…”, and let the exposed end go.

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.

Pensions and insurance clerks and assistants
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “develop working relationships with brokers to facilitate insurance underwriting and administration”. 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. I will not move you off one melting floe onto another: 65% of its own task list already scores in the top exposure band (65/100 in this release), so the same software is eating it. It is a pay cut, in those words: £30,269 against your £41,610, 27.3% less (ASHE Table 14.7a, 2025 provisional (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →
Brokers
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “negotiate terms with policyholders or their brokers”. 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 and financial project management professionals
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “collaborate with the wider organization, team, communities, and external partners to achieve business objectives”. 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 →

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: 52% of its task weight, across 56 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: developing working relationships with brokers to facilitate insurance underwriting and administration 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 Insurance Underwriters 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:

In US official statistics this job is counted as Insurance Underwriters, First-Line Supervisors of Non-Retail Sales Workers and Insurance Sales Agents. Pay is shown separately for each of those groups (medians cannot be averaged together), while the task list and the scores on this page are for this group only.

Your route through this

Two honest options, and no deadline on either

Free, and complete

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

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

A nearby route

There's no Space built for insurance underwriters yet.

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

What a Space actually is, in full

The closest match is The AI Authority, a community for non-technical managers and domain experts turning one-off AI prompts into workflows a team can trust. It overlaps with the part of your job that is growing: checking AI-drafted assessments and write-ups before they carry your name, and deciding what can safely be put into an AI in the first place. It covers no underwriting rules, no risk pricing and nothing about your underwriting system. If that overlap isn't you, the free route below covers the same ground.

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.

After the trial it is a paid community, and you get identical data either way. If the overlap above is not your job, the moves above cost nothing and stand on their own.

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

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

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No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.

Questions people ask about this job

Will AI replace Insurance underwriters?: Not as a job, but it is already doing parts of the work. Across the 56 official task statements scored for Insurance underwriters (United Kingdom, SOC 3532), 52% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 57 out of 100 (range 51–63, band: partial). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
Which tasks in “Insurance underwriters” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Monitor changes in the insurance market relevant to client services” (93/100, very high); “Communicate latest industry developments effectively within the organisation” (85/100, very high); “Analyse market trends to compare products and assess competitor strategies” (83/100, 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 “Insurance underwriters” stay human?: About 27% 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: “Establish and maintain strong collaborative relationships with customers, suppliers, and stakeholders” (10/100, minimal); “Develop and manage relationships with clients, colleagues, and senior management to achieve desired business outcomes” (13/100, minimal); “Develop working relationships with brokers to facilitate insurance underwriting and administration” (13/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
What should someone working in “Insurance underwriters” do about AI?: Start from the ledger rather than the headline: 52% of this job's weighted core work is exposed, and roughly 27% 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 Insurance underwriters 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 56 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.
16 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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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.