Will AI replace Financial administrative occupations n.e.c.?

Not as a job, but it is already doing parts of the work. Across the 113 official task statements scored for Financial administrative occupations n.e.c. (United Kingdom, SOC 4129), 58% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 62 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 “Financial administrative occupations n.e.c.” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Issue receipts” (93/100, very high); “Summarise recorded data to compile and maintain financial records” (93/100, very high); “Monitor customer accounts to ensure timely payment and adherence to credit terms” (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 “Financial administrative occupations n.e.c.” stay human?

About 22% 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: “Maintain clean and orderly till areas” (0/100, minimal); “Count banknotes and coins for cash handling operations” (0/100, minimal); “Greet guests entering the theatre or cinema” (0/100, 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 “Financial administrative occupations n.e.c.” do about AI?

Start from the ledger rather than the headline: 58% of this job's weighted core work is exposed, and roughly 22% 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 Financial administrative occupations n.e.c. 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 113 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

Financial administrative occupations n.e.c.

selling and checking tickets, recording loan information and fund disbursements and checking tax forms for correct names and National Insurance numbers. 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: summarising recorded data to compile and maintain financial records. 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: 21%
staying human: 22%

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

Whole-job exposure score 62 out of 100 (56–67 allowing for uncertainty): high exposure, across 113 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 financial administrative occupations n.e.c. 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; greeting guests entering the theatre or cinema is what this work rebuilds around. Your move starts there.

Your week, as this page understands it

Job holders in this unit group carry out a variety of finance-related administrative functions not elsewhere classified in minor group 412: Administrative occupations: finance. The job title says “financial administrative occupations n.e.c.”. The real job is the part underneath: greeting guests entering the theatre or cinema. 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 financial administrative occupations n.e.c. is not one task. It is 113 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is greeting guests entering the theatre or cinema, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 58%
changing shape: 21%
staying human: 22%

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.

17 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

64 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.

Maintaining records of contacts, accounts and orders
This is reading one thing and writing another: records of contacts, accounts and orders in, a record out. That is the shape today's tools are built for.
importance 70 · 4129/04, 4129/05
Source: “Maintain records of contacts, accounts, and orders.” (UK task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Keeping contact, account and order records up to date is ordinary database work.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Summarising recorded data to compile and maintain financial records
This is reading one thing and writing another: recorded data in, a record out. That is the shape today's tools are built for.
importance 60 · 4129/01, 4129/05
Source: “Summarise recorded data to compile and maintain financial records.” (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: Summarising figures into financial records is structured work that accounting software and AI already do very 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 0/4 · how much data exists 3/4.
Assessing loan applications to determine eligibility
This is reading one thing and writing another: loan applications in, a record out. That is the shape today's tools are built for.
importance 90 · 4129/03
Source: “Assess loan applications to determine eligibility.” (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: Loan eligibility runs on documented scoring rules that software applies at least as well as staff, ahead of formal approval.
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 loan agreements to ensure that they are complete and accurate according to policy
This is reading one thing and writing another: loan agreements in, a record out. That is the shape today's tools are built for.
importance 90 · 4129/03
Source: “Review loan agreements to ensure that they are complete and accurate according to policy.” (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: Checking loan agreements are complete and accurate against policy is structured document review AI performs 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.

Changing shape

23 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.

Calculating and authorising amounts of assistance
The software now makes the first pass at amounts of assistance, 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 90 · 4129/02
Source: “Calculate and authorise amounts of assistance for programmes including grants, monetary payments, and food vouchers.” (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: Working out the amount follows published rules, but authorising an award is a formal decision someone accountable must make.
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.
Resolving mortgage application problems in consultation with underwriters
The software now makes the first pass at mortgage application problems, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 90 · 4129/03
Source: “Resolve mortgage application problems in consultation with underwriters.” (UK task statement)
How this row was scored
Exposure score: 50 out of 100 (43–57 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; mistakes that are cheap to catch.
The rating behind it: Sorting out application problems is documented casework, but the answer depends on what the underwriter decides.
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 2/4.
Initiating procedures to grant, modify, deny or terminating assistance
The software now makes the first pass at procedures, 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 85 · 4129/02
Source: “Initiate procedures to grant, modify, deny, or terminate assistance.” (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: Starting, changing or stopping someone's assistance is a formal decision an accountable officer has to make.
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

26 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.

Selling and checking tickets
This work happens in the physical world: tickets, in a real place. Software cannot follow it there.
importance 95 · 4129/01
Source: “Sell and check tickets.” (UK task statement)
How this row was scored
Exposure score: 12 out of 100 (8–16 allowing for uncertainty): minimal exposure, high 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: Selling tickets at a counter and checking them at the door means being there in person.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Collecting money from customers and give change
This work happens in the physical world: money, in a real place. Software cannot follow it there.
importance 90 · 4129/01
Source: “Collect money from customers and give change.” (UK task statement)
How this row was scored
Exposure score: 12 out of 100 (5–19 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Handling cash needs someone at the till, though card and self-service payment already cover much of it.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Speaking with customers to organise repayments
The value here is that a specific person handles customers and stands behind it. That is earned, not computed.
importance 85 · 4129/03
Source: “Speak with customers to organise repayments.” (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: Agreeing how someone will repay takes a live conversation where reassurance and flexibility matter more than the calculation.
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.

Show the other 103 tasks

Issuing receipts
shifting to AI
This is reading one thing and writing another: receipts in, a record out. That is the shape today's tools are built for.
importance 80 · 4129/01
Source: “Issue receipts.” (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: Issuing a receipt is generated by the till system, with only the handover done by a person.
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.
Monitoring customer accounts to ensure timely payment and adherence to credit terms
shifting to AI
This is reading one thing and writing another: customer accounts in, a record out. That is the shape today's tools are built for.
importance 80 · 4129/03
Source: “Monitor customer accounts to ensure timely payment and adherence to credit terms.” (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: Watching accounts for late payment and breached terms is automatic monitoring software already performs.
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 loan information and fund disbursements
shifting to AI
This is reading one thing and writing another: loan information in, a record out. That is the shape today's tools are built for.
importance 80 · 4129/03
Source: “Record loan information and fund disbursements.” (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: Recording loan details and payouts is data entry that systems already do automatically.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Reviewing and verifying the accuracy of billing statements and invoices
shifting to AI
This is reading one thing and writing another: the accuracy of billing statements in, a record out. That is the shape today's tools are built for.
importance 80 · 4129/03
Source: “Review and verify the accuracy of billing statements and invoices.” (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: Checking billing statements and invoices for accuracy is exactly the structured verification software 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.
Updating and recategorising account records according to status changes
shifting to AI
This is reading one thing and writing another: account records in, a record out. That is the shape today's tools are built for.
importance 80 · 4129/03
Source: “Update and recategorise account records according to status changes.” (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: Updating and recategorising account records is structured system work software already does automatically.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Calculating detailed payment schedules for financial transactions
shifting to AI
This is reading one thing and writing another: detailed payment schedules in, a record out. That is the shape today's tools are built for.
importance 75 · 4129/03
Source: “Calculate detailed payment schedules for financial transactions.” (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 payment schedules is documented arithmetic that finance software produces 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.
Recording loan and crediting applications using computers
shifting to AI
This is reading one thing and writing another: loan in, a record out. That is the shape today's tools are built for.
importance 75 · 4129/03
Source: “Record loan and credit applications using 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: Keying application details into a system is data entry software now does from the documents themselves.
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.
Forwarding irreconcilable accounts to debt collectors for action
shifting to AI
This is reading one thing and writing another: irreconcilable accounts in, a record out. That is the shape today's tools are built for.
importance 60 · 4129/03
Source: “Forward irreconcilable accounts to debt collectors for action.” (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: Passing unrecoverable accounts to collectors is a rules-driven step systems already perform.
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.
Inputting tax return information into computers for processing
shifting to AI
This is reading one thing and writing another: tax return information in, a record out. That is the shape today's tools are built for.
importance 85 · 4129/04
Source: “Input tax return information into computers for processing.” (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 return information into the system is data entry that software handles directly.
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.
Checking tax forms for correct names and National Insurance numbers
shifting to AI
This is reading one thing and writing another: tax forms in, a record out. That is the shape today's tools are built for.
importance 80 · 4129/04
Source: “Check tax forms for correct names and National Insurance numbers.” (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: Matching names and National Insurance numbers against records is straightforward automated checking.
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.
Monitoring loans and accounts to ensure payments are up to date
shifting to AI
This is reading one thing and writing another: loans in, a record out. That is the shape today's tools are built for.
importance 75 · 4129/04
Source: “Monitor loans and accounts to ensure payments are up to date.” (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: Monitoring whether accounts are up to date is structured tracking software already does automatically.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Operating computerised accounting systems to manage financial records
shifting to AI
This is reading one thing and writing another: computerised accounting systems in, a record out. That is the shape today's tools are built for.
importance 85 · 4129/05
Source: “Operate computerised accounting systems to manage financial records.” (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: Running accounting software is routine, well-documented work that today's tools handle from end to end.
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.
Performing accounting tasks to manage financial records
shifting to AI
This is reading one thing and writing another: tasks in, a record out. That is the shape today's tools are built for.
importance 80 · 4129/05
Source: “Perform accounting tasks to manage financial records.” (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: General accounting tasks are structured, well-documented work that accounting software and AI already handle 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 0/4 · how much data exists 3/4.
Regularlying update databases, spreadsheets and records to ensure data accuracy
shifting to AI
This is reading one thing and writing another: update databases, spreadsheets and records in, a record out. That is the shape today's tools are built for.
importance 75 · 4129/05
Source: “Regularly update databases, spreadsheets, and records to ensure data accuracy.” (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: Keeping databases, spreadsheets and records accurate is routine data work software handles well.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Verifying and examining accuracy of closing documents
shifting to AI
This is reading one thing and writing another: accuracy of closing documents in, a record out. That is the shape today's tools are built for.
importance 85 · 4129/03
Source: “Verify and examine accuracy of closing documents.” (UK task statement)
How this row was scored
Exposure score: 88 out of 100 (84–92 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Checking closing documents against the rules is comparison work software does faster and more consistently.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Calculating interest, principal, payment and completion costs using computers or calculators
shifting to AI
This is reading one thing and writing another: interest, principal, payment and completion costs in, a record out. That is the shape today's tools are built for.
importance 80 · 4129/03
Source: “Calculate interest, principal, payment, and completion costs using computers or calculators.” (UK task statement)
How this row was scored
Exposure score: 88 out of 100 (84–92 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Interest and repayment calculations are pure arithmetic that software has always done accurately.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Examining records and documents for data verification
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 75 · 4129/03
Source: “Examine records and documents for data verification.” (UK task statement)
How this row was scored
Exposure score: 88 out of 100 (84–92 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Checking records and documents against each other is comparison work software does very accurately.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Preparing and typing legal documents
shifting to AI
This is reading one thing and writing another: legal documents in, a record out. That is the shape today's tools are built for.
importance 75 · 4129/03
Source: “Prepare and type legal documents, letters, forms, government notices, and cheques using computers.” (UK task statement)
How this row was scored
Exposure score: 88 out of 100 (84–92 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Producing standard legal documents, letters and forms from templates is exactly what AI does well.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Reviewing and correcting errors on interest
shifting to AI
This is reading one thing and writing another: errors in, a record out. That is the shape today's tools are built for.
importance 75 · 4129/03
Source: “Review and correct errors on interest, principal, payment, and completion costs.” (UK task statement)
How this row was scored
Exposure score: 88 out of 100 (84–92 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Finding and fixing errors in interest and cost figures is arithmetic checking software does 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 4/4.
Maintaining knowledge of tax code changes
shifting to AI
This is reading one thing and writing another: knowledge of tax code changes in, a record out. That is the shape today's tools are built for.
importance 80 · 4129/04
Source: “Maintain knowledge of tax code changes, and of accounting procedures and theory to properly evaluate financial information.” (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: Tax law changes are published in full, so keeping up to date is well suited to automatic summarising.
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.
Reviewing records for completeness, accuracy and compliance with regulations
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 85 · 4129/02
Source: “Review records for completeness, accuracy, and compliance with regulations.” (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: Checking records are complete and compliant is rule-based reviewing software does reliably, feeding a decision taken elsewhere.
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.
Preparing business or government forms for submission
shifting to AI
This is reading one thing and writing another: business in, a record out. That is the shape today's tools are built for.
importance 80 · 4129/02
Source: “Prepare business or government forms for submission.” (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 standard business and government forms is highly structured work AI does reliably before submission.
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 the payments of benefits throughout the duration of a claim
shifting to AI
This is reading one thing and writing another: the payments of benefits throughout the duration in, a record out. That is the shape today's tools are built for.
importance 75 · 4129/02
Source: “Monitor the payments of benefits throughout the duration of a claim.” (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: Watching benefit payments over the life of a claim is structured monitoring that systems flag automatically.
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.
Submitting loan applications with recommendation for underwriting approval
shifting to AI
This is reading one thing and writing another: loan applications in, a record out. That is the shape today's tools are built for.
importance 90 · 4129/03
Source: “Submit loan applications with recommendation for underwriting approval.” (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: Assembling a loan application with a recommendation is structured work AI does well, ahead of the underwriter's decision.
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 necessary documents, including title abstracts and loan forms, for loan closings
shifting to AI
This is reading one thing and writing another: necessary documents, including title abstracts and loan forms in, a record out. That is the shape today's tools are built for.
importance 85 · 4129/03
Source: “Compile necessary documents, including title abstracts and loan forms, for loan closings.” (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: Pulling together the standard documents for a loan completion is a checklist task software runs well.
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 credit and loan files
shifting to AI
This is reading one thing and writing another: credit in, a record out. That is the shape today's tools are built for.
importance 85 · 4129/03
Source: “Review credit and loan files.” (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: Reviewing credit and loan files against documented policy is structured checking software performs 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.
Processing payments to complete transactions
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 80 · 4129/03
Source: “Process payments to complete transactions.” (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: Processing a payment is a system transaction, with only occasional handling done by a person.
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 customer files to identify and select overdue accounts for collection
shifting to AI
This is reading one thing and writing another: customer files in, a record out. That is the shape today's tools are built for.
importance 75 · 4129/03
Source: “Review customer files to identify and select overdue accounts for collection.” (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: Picking out overdue accounts from customer files is rule-based selection collection systems already do automatically.
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 accounts to determine write-offs for collection agencies
shifting to AI
This is reading one thing and writing another: accounts in, a record out. That is the shape today's tools are built for.
importance 70 · 4129/03
Source: “Review accounts to determine write-offs for collection agencies.” (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: Deciding which accounts to write off follows documented policy applied to account data the system already holds.
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.
Ordering property insurance policies for protection against loss on mortgaged property
shifting to AI
This is reading one thing and writing another: property insurance policies in, a record out. That is the shape today's tools are built for.
importance 60 · 4129/03
Source: “Order property insurance policies for protection against loss on mortgaged property.” (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: Ordering the required property insurance is a routine transaction systems can complete automatically.
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.
Verifying computations and amounts against supporting documentation
shifting to AI
This is reading one thing and writing another: computations in, a record out. That is the shape today's tools are built for.
importance 85 · 4129/04
Source: “Verify computations and amounts against supporting documentation.” (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: Checking figures against supporting paperwork is exactly what automated matching does well, with sign-off happening elsewhere.
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.
Issuing a refund for overpayment
shifting to AI
This is reading one thing and writing another: a refund in, a record out. That is the shape today's tools are built for.
importance 75 · 4129/04
Source: “Issue a refund for overpayment.” (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: Issuing a refund for an overpayment is a rule-based system step, released by someone with the authority to do it.
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.
Sending notices to taxpayers when accounts are in arrears
shifting to AI
This is reading one thing and writing another: notices in, a record out. That is the shape today's tools are built for.
importance 75 · 4129/04
Source: “Send notices to taxpayers when accounts are in arrears.” (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: Arrears notices are templated letters generated automatically from the account record.
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.
Requesting that the HM Revenue & Customs prepare a return on a taxpayer's behalf in cases where taxes have not
shifting to AI
This is reading one thing and writing another: the HM revenue & customs prepare a return in, a record out. That is the shape today's tools are built for.
importance 60 · 4129/04
Source: “Request that the HM Revenue & Customs prepare a return on a taxpayer's behalf in cases where taxes have not been filed.” (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: Asking HMRC to raise a return where none was filed is a documented procedural step, generated from the account record.
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.
Examining financial records to ensure accuracy and compliance with regulations
shifting to AI
This is reading one thing and writing another: financial records in, a record out. That is the shape today's tools are built for.
importance 85 · 4129/05
Source: “Examine financial records to ensure accuracy and compliance with regulations.” (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: Examining records against accuracy and compliance rules is structured checking software performs reliably at scale.
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.
Arranging refunds
shifting to AI
This is reading one thing and writing another: refunds in, a record out. That is the shape today's tools are built for.
importance 90 · 4129/01
Source: “Arrange refunds.” (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: Processing a refund is a rules-based transaction that systems already handle end to end.
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.
Answering customers' general enquiries and providing relevant information
shifting to AI
This is reading one thing and writing another: customers' general enquiries in, a record out. That is the shape today's tools are built for.
importance 85 · 4129/01
Source: “Answer customers' general enquiries and provide relevant information.” (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 general enquiries with standard information is what automated assistants now do reliably.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Answering telephone calls and directing them to the appropriate department or individual
shifting to AI
This is reading one thing and writing another: telephone calls in, a record out. That is the shape today's tools are built for.
importance 80 · 4129/01
Source: “Answer telephone calls and direct them to the appropriate department or individual.” (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 and routing calls is something phone systems and automated assistants already do.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Providing information on company procedures or policies
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 · 4129/01
Source: “Provide information on company procedures or 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: Looking up and explaining company procedures is straightforward information work for AI.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Arranging interviews for benefits claimants to address eligibility queries
shifting to AI
This is reading one thing and writing another: interviews in, a record out. That is the shape today's tools are built for.
importance 70 · 4129/02
Source: “Arrange interviews for benefits claimants to address eligibility queries.” (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: Booking interviews around diaries and eligibility queries is scheduling work that software already handles well.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Contacting taxpayers by post or telephone to address discrepancies and to request supporting documentation
shifting to AI
This is reading one thing and writing another: taxpayers in, a record out. That is the shape today's tools are built for.
importance 65 · 4129/04
Source: “Contact taxpayers by post or telephone to address discrepancies and to request supporting documentation.” (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: Chasing discrepancies and asking for documents is standard correspondence that can be generated.
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.
Establishing prices of goods, services or admission
shifting to AI
This is reading one thing and writing another: prices of goods, services or admission in, a record out. That is the shape today's tools are built for.
importance 70 · 4129/01
Source: “Establish prices of goods, services, or admission.” (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 prices from costs, demand and competitor data is analysis 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.
Processing and maintaining records of customer loans
shifting to AI
This is reading one thing and writing another: records of customer loans in, a record out. That is the shape today's tools are built for.
importance 85 · 4129/03
Source: “Process and maintain records of customer loans.” (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 loan records up to date is straightforward record-keeping inside the bank's own systems.
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 potential loan markets
shifting to AI
This is reading one thing and writing another: potential loan markets in, a record out. That is the shape today's tools are built for.
importance 80 · 4129/03
Source: “Analyse potential loan markets.” (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: Analysing loan markets draws on published data and reports that AI summarises well, though local judgement shapes the conclusion.
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.
Monitoring new types of loans and other financial services and products to better meet customers' needs
shifting to AI
This is reading one thing and writing another: new types of loans in, a record out. That is the shape today's tools are built for.
importance 70 · 4129/03
Source: “Monitor new types of loans and other financial services and products to better meet customers' needs.” (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: Tracking new loan products draws on published market information AI summarises well, though judging customer fit needs local knowledge.
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 transaction mistakes when debits and credits do not balance
shifting to AI
This is reading one thing and writing another: transaction mistakes in, a record out. That is the shape today's tools are built for.
importance 80 · 4129/05
Source: “Identify transaction mistakes when debits and credits do not balance.” (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 where debits and credits fail to match is a reconciliation job that accounting software already performs quickly and accurately.
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.
Resolving discrepancies in accounting records
shifting to AI
This is reading one thing and writing another: discrepancies in, a record out. That is the shape today's tools are built for.
importance 80 · 4129/05
Source: “Resolve discrepancies in accounting records.” (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: Chasing down why an account does not balance needs judgement and access to records, though software narrows it quickly.
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.
Calculating total payments received during a time period
shifting to AI
This is reading one thing and writing another: total payments received during a time period in, a record out. That is the shape today's tools are built for.
importance 80 · 4129/01
Source: “Calculate total payments received during a time period, and reconcile this with total sales.” (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: Adding up payments received and matching them against sales is straightforward number work done from records.
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 0/4 · how much data exists 3/4.
Interpreting information, eligibility requirements, application details and payment methods
shifting to AI
This is reading one thing and writing another: information, eligibility requirements, application details and payment methods in, a record out. That is the shape today's tools are built for.
importance 75 · 4129/02
Source: “Interpret information including eligibility requirements, application details, and payment methods.” (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: Explaining eligibility rules, application steps and payment options is well-documented information work AI handles well.
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.
Completing loan applications and crediting analyses
shifting to AI
This is reading one thing and writing another: loan applications in, a record out. That is the shape today's tools are built for.
importance 90 · 4129/03
Source: “Complete loan applications and credit analyses.” (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; mistakes that are cheap to catch.
The rating behind it: Loan paperwork and credit analysis run on documented scoring rules that software applies at least as well as staff.
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.
Scheduling completions of mortgage transactions
shifting to AI
This is reading one thing and writing another: completions of mortgage transactions in, a record out. That is the shape today's tools are built for.
importance 85 · 4129/03
Source: “Schedule completions of mortgage transactions.” (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: Scheduling a completion date around several parties is coordination software handles well.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Calculating taxes owed and ensuring compliance with payment
shifting to AI
This is reading one thing and writing another: taxes in, a record out. That is the shape today's tools are built for.
importance 85 · 4129/04
Source: “Calculate taxes owed and ensure compliance with payment, reporting, or other tax requirements.” (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: Tax calculations follow published rules that software applies accurately, but the resulting liability carries a formal responsibility.
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.
Processing individual and corporate income tax returns
shifting to AI
This is reading one thing and writing another: individual in, a record out. That is the shape today's tools are built for.
importance 85 · 4129/04
Source: “Process individual and corporate income tax returns.” (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: Processing tax returns is highly structured work software does well, but filing carries a formal responsibility a person owns.
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.
Informing taxpayers of any overpayment or underpayment
shifting to AI
This is reading one thing and writing another: taxpayers of any overpayment in, a record out. That is the shape today's tools are built for.
importance 80 · 4129/04
Source: “Inform taxpayers of any overpayment or underpayment.” (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: Telling someone they have paid too much or too little is a standard notification software generates from the account.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Providing taxpayers with information and advice for correct tax form completion
shifting to AI
This is reading one thing and writing another: taxpayers in, a record out. That is the shape today's tools are built for.
importance 80 · 4129/04
Source: “Provide taxpayers with information and advice for correct tax form completion.” (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; mistakes that are cheap to catch.
The rating behind it: Helping people fill in tax forms draws on published guidance AI explains well, and tax advice itself is unlicensed in Britain.
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.
Completing vat returns
shifting to AI
This is reading one thing and writing another: vat returns in, a record out. That is the shape today's tools are built for.
importance 70 · 4129/04
Source: “Complete vat returns.” (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; someone qualified has to answer for it.
The rating behind it: VAT returns are prepared from accounting exports and software does this well, but the return is a formal declaration someone owns.
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.
Answering enquiries about application procedure
shifting to AI
This is reading one thing and writing another: enquiries in, a record out. That is the shape today's tools are built for.
importance 85 · 4129/02
Source: “Answer enquiries about application procedure.” (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: Application procedures are written down, so a system can answer most enquiries, though callers sometimes need a person.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Referring applicants to other agencies for assistance
shifting to AI
This is reading one thing and writing another: applicants in, a record out. That is the shape today's tools are built for.
importance 70 · 4129/02
Source: “Refer applicants to other agencies for assistance.” (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: Matching someone's situation to the right agency is a look-up task, but local knowledge still matters.
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.
Verifying applicants' employment and references by contacting previous employers
shifting to AI
This is reading one thing and writing another: applicants' employment in, a record out. That is the shape today's tools are built for.
importance 90 · 4129/03
Source: “Verify applicants' employment and references by contacting previous employers.” (UK task statement)
How this row was scored
Exposure score: 64 out of 100 (60–68 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Checking employment history and chasing references is routine verification work AI 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 1/4 · how much data exists 3/4.
Answering customers' queries about services
shifting to AI
This is reading one thing and writing another: customers' queries in, a record out. That is the shape today's tools are built for.
importance 85 · 4129/03
Source: “Answer customers' queries about services.” (UK task statement)
How this row was scored
Exposure score: 64 out of 100 (60–68 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Most service questions have documented answers that can be given automatically.
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.
Writing reports and keeping records on legal consultations
changing shape
The software now makes the first pass at reports, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 75 · 4129/02
Source: “Write reports and keep records on legal consultations.” (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; mistakes that are cheap to catch.
The rating behind it: Writing up notes of a legal consultation is drafting work AI does well, though the substance comes from a private meeting.
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 2/4.
Submitting contested tax decisions for appeals hearings
changing shape
The software now makes the first pass at contested tax decisions, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 80 · 4129/04
Source: “Submit contested tax decisions for appeals hearings.” (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; mistakes that are cheap to catch.
The rating behind it: Preparing and lodging appeal papers is documented procedure AI supports, though the hearing itself happens elsewhere.
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 2/4.
Evaluating recorded data to determine eligibility status
changing shape
The software now makes the first pass at recorded data, 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 · 4129/02
Source: “Evaluate recorded data to determine eligibility status.” (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: Applying eligibility rules to recorded data suits software, but the resulting entitlement decision is one an accountable officer 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 0/4 · how much data exists 3/4.
Interviewing loan applicants to obtain personal and financial data and to assist in completing applications
changing shape
The software now makes the first pass at loan applicants, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 85 · 4129/03
Source: “Interview loan applicants to obtain personal and financial data and to assist in completing applications.” (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: Gathering an applicant's details is increasingly done through online forms, though some people still want help filling them in.
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.
Resolving queries about applications with applicants or creditors
changing shape
The software now makes the first pass at queries, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 85 · 4129/03
Source: “Resolve queries about applications with applicants or creditors.” (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: Answering queries about an application draws on documented rules and the case file, though people often prefer speaking to someone.
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.
Informing customers about credit, funding options, incentives and tax rebates
changing shape
The software now makes the first pass at customers, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 80 · 4129/03
Source: “Inform customers about credit, funding options, incentives, and tax rebates.” (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: Explaining credit options, funding and rebates draws on published information AI summarises well, though customers often want a person.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Approving loans within specified limits
changing shape
The software now makes the first pass at loans within specified 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 · 4129/03
Source: “Approve loans within specified limits.” (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: Lending decisions inside set limits run largely on automated scoring, but someone accountable still has to own the approval.
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.
Setting credit limits
changing shape
The software now makes the first pass at credit 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 · 4129/03
Source: “Set credit limits.” (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: Credit scoring is already automated, though the firm needs an accountable person behind lending decisions.
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.
Matching individuals' needs and eligibility with available financial aid programmes to provide informed recommendations
changing shape
The software now makes the first pass at individuals' needs, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 70 · 4129/03
Source: “Match individuals' needs and eligibility with available financial aid programmes to provide informed recommendations.” (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: Matching someone's circumstances to available schemes follows published criteria AI applies well, though the person's details shape the answer.
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.
Promoting financial products and services
changing shape
The software now makes the first pass at financial products, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 70 · 4129/03
Source: “Promote financial products and services.” (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: Promoting financial products is documented marketing work AI supports, with the approved wording set by the firm.
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.
Reviewing taxpayer accounts to determine audit requirements
changing shape
The software now makes the first pass at taxpayer accounts, 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 85 · 4129/04
Source: “Review taxpayer accounts to determine audit requirements.” (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-scoring accounts is well suited to software, but choosing to open a compliance check is a decision an authorised officer takes.
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.
Reviewing filed tax returns to determine whether claimed tax reliefs and deductions are allowed by law
changing shape
The software now makes the first pass at filed tax returns, 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 · 4129/04
Source: “Review filed tax returns to determine whether claimed tax reliefs and deductions are allowed by law.” (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: Checking whether a relief is allowed follows published law, but ruling on someone's return is a formal official decision.
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.
Assisting customers with enquiries or service needs
changing shape
The software now makes the first pass at customers, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 85 · 4129/01
Source: “Assist customers with enquiries or service needs.” (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: Much customer help can be automated, though some of it means dealing with people at the venue.
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.
Collecting taxes from individuals or businesses according to prescribed laws and regulations
changing shape
The software now makes the first pass at taxes, 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 · 4129/04
Source: “Collect taxes from individuals or businesses according to prescribed laws and regulations.” (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: Tax collection follows published rules and runs largely through systems, but it is an official act under statutory powers.
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.
Imposing payment deadlines on delinquent taxpayers
changing shape
The software now makes the first pass at payment deadlines, 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 · 4129/04
Source: “Impose payment deadlines on delinquent taxpayers.” (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: Setting a deadline for an unpaid tax bill is a formal step taken under statutory powers, so an accountable officer decides 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 1/4 · how much data exists 3/4.
Tabulating bills using calculators, tills or optical price scanners
changing shape
The software now makes the first pass at bills, but part of it still happens in the physical world. So the job becomes checking and deciding rather than producing.
importance 70 · 4129/01
Source: “Tabulate bills using calculators, tills, or optical price scanners.” (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: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Totalling a bill is automatic, though scanning and handling the items is done by a person.
The five ratings: output a model can produce 4/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Assisting customers in completing mortgage applications
changing shape
The software now makes the first pass at customers, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 85 · 4129/03
Source: “Assist customers in completing mortgage applications.” (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: Filling in a mortgage application is form-work software handles, but the customer usually wants a person alongside them.
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.
Resolving customer complaints about mortgage processing
changing shape
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 · 4129/03
Source: “Resolve customer complaints about mortgage processing.” (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 responses can be drafted well by AI, though an unhappy customer usually wants 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 2/4 · how much data exists 3/4.
Presenting loan and repayment schedules to customers
changing shape
The software now makes the first pass at loan, 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 · 4129/03
Source: “Present loan and repayment schedules 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: Walking a customer through a repayment schedule is partly scripted, but people want a person to answer their worries.
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 the value of customer collateral for loan security purposes
changing shape
The software now makes the first pass at the value of customer collateral, 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 · 4129/03
Source: “Assess the value of customer collateral for loan security purposes.” (UK task statement)
How this row was scored
Exposure score: 42 out of 100 (35–49 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Automated valuation data gives a good estimate, though a qualified surveyor is usually needed for lending.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Assisting applicants in completing application forms for job referrals or Jobseeker's Allowance claims
staying human
The value here is that a specific person handles applicants and stands behind it. That is earned, not computed.
importance 60 · 4129/02
Source: “Assist applicants in completing application forms for job referrals or Jobseeker's Allowance claims.” (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; the value is that a specific person does it.
The rating behind it: Forms can be filled in with digital help, but many claimants need someone sitting with them.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Advising clients on prioritising their debts based on urgency and interest rates
staying human
The rules require a named, qualified person to answer for clients, and that person cannot be a piece of software.
importance 60 · 4129/03
Source: “Advise clients on prioritising their debts based on urgency and interest rates.” (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: Ranking debts by urgency follows published guidance, but giving debt advice in Britain requires a firm authorised to do 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.
Inspecting account books and accounting systems
staying human
The rules require a named, qualified person to answer for account books, and that person cannot be a piece of software.
importance 70 · 4129/04
Source: “Inspect account books and accounting systems for efficiency, effectiveness, and use of accepted accounting procedures to record transactions.” (UK task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; someone qualified has to answer for it.
The rating behind it: Software can test whole ledgers quickly, but judging whether procedures are sound needs someone accountable inside the organisation.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Granting extensions of credit on overdue accounts
staying human
The rules require a named, qualified person to answer for extensions of credit, and that person cannot be a piece of software.
importance 70 · 4129/03
Source: “Grant extensions of credit on overdue accounts.” (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: Giving someone more time to pay is a judgement a responsible person must make under conduct rules.
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.
Informing customers of application rejection
staying human
The value here is that a specific person handles customers of application rejection and stands behind it. That is earned, not computed.
importance 75 · 4129/03
Source: “Inform customers of application rejection by post, telephone, or in person.” (UK task statement)
How this row was scored
Exposure score: 34 out of 100 (27–41 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; the value is that a specific person does it.
The rating behind it: The letter is easy to draft, but telling someone in person that they were turned down is not.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Processing returns and exchanges of goods
staying human
This work happens in the physical world: returns, in a real place. Software cannot follow it there.
importance 80 · 4129/01
Source: “Process returns and exchanges of goods.” (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; work that happens in the physical world.
The rating behind it: The paperwork side is automatic, but taking goods back means someone receiving and checking them.
The five ratings: output a model can produce 3/4 · 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.
Determining appropriate methods of debt settlement
staying human
The rules require a named, qualified person to answer for appropriate methods of debt settlement, and that person cannot be a piece of software.
importance 70 · 4129/04
Source: “Determine appropriate methods of debt settlement, such as offers of compromise, attachment of earnings, or seizure and sale of property.” (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: someone qualified has to answer for it.
The rating behind it: Choosing between a settlement offer, an earnings order or seizure needs judgement about a person's circumstances and is an official decision.
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 2/4.
Resolving problems with tax returns in consultation with taxpayers or their representatives
staying human
The rules require a named, qualified person to answer for problems, and that person cannot be a piece of software.
importance 75 · 4129/04
Source: “Resolve problems with tax returns in consultation with taxpayers or their representatives.” (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: Sorting out a disputed return means a real conversation with the taxpayer, and the settlement reached is an official decision.
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.
Securing a taxpayer's agreement to settle a tax assessment
staying human
The rules require a named, qualified person to answer for a taxpayer's agreement, and that person cannot be a piece of software.
importance 70 · 4129/04
Source: “Secure a taxpayer's agreement to settle a tax assessment.” (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: Getting a taxpayer to agree a settlement depends on a live negotiation, and the agreement itself is an official one.
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.
Investigating potentially fraudulent claims
staying human
The rules require a named, qualified person to answer for fraudulent claims, and that person cannot be a piece of software.
importance 70 · 4129/02
Source: “Investigate potentially fraudulent claims.” (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: someone qualified has to answer for it.
The rating behind it: Software flags suspicious patterns, but proving a claim is fraudulent needs private evidence and a decision an accountable officer takes.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 2/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Advising clients on resolving their financial issues
staying human
The rules require a named, qualified person to answer for clients, and that person cannot be a piece of software.
importance 70 · 4129/03
Source: “Advise clients on resolving their financial issues.” (UK task statement)
How this row was scored
Exposure score: 21 out of 100 (14–28 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: Money advice depends on private circumstances and trust built in conversation, and in Britain giving debt advice needs a firm authorised to do it.
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 3/4 · how much data exists 2/4.
Interviewing and investigating applicants for public support to gather information pertinent to their applications
staying human
The rules require a named, qualified person to answer for applicants, and that person cannot be a piece of software.
importance 70 · 4129/02
Source: “Interview and investigate applicants for public support to gather information pertinent to their applications.” (UK task statement)
How this row was scored
Exposure score: 20 out of 100 (13–27 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: Interviewing and checking out applicants means meeting people, weighing private circumstances, and reaching a decision someone accountable owns.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 2/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Interviewing benefits recipients at specified intervals to certify their eligibility for continuing benefits
staying human
The rules require a named, qualified person to answer for benefits recipients, and that person cannot be a piece of software.
importance 65 · 4129/02
Source: “Interview benefits recipients at specified intervals to certify their eligibility for continuing benefits.” (UK task statement)
How this row was scored
Exposure score: 20 out of 100 (13–27 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: Re-checking someone's benefit entitlement means a real conversation, often in person, and the decision that follows is an official one.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 2/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Auditing cash drawers and counting money for ticket sales
staying human
This work happens in the physical world: cash drawers, in a real place. Software cannot follow it there.
importance 75 · 4129/01
Source: “Audit cash drawers and count money for ticket sales.” (UK task statement)
How this row was scored
Exposure score: 19 out of 100 (12–26 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: The audit calculation is simple for software, but the cash still has to be counted by hand.
The five ratings: output a model can produce 3/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Pricing stock and labelling items for sale
staying human
This work happens in the physical world: stock, in a real place. Software cannot follow it there.
importance 70 · 4129/01
Source: “Price stock and label items for sale.” (UK task statement)
How this row was scored
Exposure score: 14 out of 100 (10–18 allowing for uncertainty): minimal exposure, high 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: Working out prices is easy for software, but labels have to be put on the goods by hand.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Receiving payment by cash, cheque, credit cards, vouchers or directing debits
staying human
This work happens in the physical world: payment, in a real place. Software cannot follow it there.
importance 85 · 4129/01
Source: “Receive payment by cash, cheque, credit cards, vouchers, or direct debits.” (UK task statement)
How this row was scored
Exposure score: 12 out of 100 (8–16 allowing for uncertainty): minimal exposure, high 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: Taking cash, cheques and cards at a counter means handling money and people in person.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Meeting with clients' advisers to fully understand their financial goals and circumstances
staying human
The value here is that a specific person handles clients' advisers and stands behind it. That is earned, not computed.
importance 75 · 4129/03
Source: “Meet with clients' advisers to fully understand their financial goals and circumstances.” (UK task statement)
How this row was scored
Exposure score: 10 out of 100 (3–17 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Understanding a client's goals comes out of a meeting with the people who know them, which is not something software attends.
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 1/4.
Developing networks of solicitors, mortgage lenders and contractors for client referrals
staying human
The value here is that a specific person handles networks of solicitors, mortgage lenders and contractors and stands behind it. That is earned, not computed.
importance 70 · 4129/03
Source: “Develop networks of solicitors, mortgage lenders, and contractors for client referrals.” (UK task statement)
How this row was scored
Exposure score: 10 out of 100 (3–17 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Building a referral network is about relationships with named people, built up over time in person.
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 1/4.
Assisting customers in finding product locations
staying human
This work happens in the physical world: customers, in a real place. Software cannot follow it there.
importance 70 · 4129/01
Source: “Assist customers in finding product locations.” (UK task statement)
How this row was scored
Exposure score: 7 out of 100 (3–11 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Pointing a customer to the right aisle happens on the shop floor, with the assistant walking them there.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Monitoring checkout stations to ensure they have adequate cash available and are staffed appropriately
staying human
This work happens in the physical world: checkout stations, in a real place. Software cannot follow it there.
importance 70 · 4129/01
Source: “Monitor checkout stations to ensure they have adequate cash available and are staffed appropriately.” (UK task statement)
How this row was scored
Exposure score: 7 out of 100 (0–14 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Keeping an eye on registers and staffing levels means walking the front of the store and watching what happens.
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 1/4 · how much data exists 2/4.
Greeting guests entering the theatre or cinema
staying human
This work happens in the physical world: guests entering the theatre, in a real place. Software cannot follow it there.
importance 85 · 4129/01
Source: “Greet guests entering the theatre or cinema.” (UK task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Greeting people as they arrive is being physically present in the foyer.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Counting banknotes and coins for cash handling operations
staying human
This work happens in the physical world: banknotes, in a real place. Software cannot follow it there.
importance 80 · 4129/01
Source: “Count banknotes and coins for cash handling operations.” (UK task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Counting banknotes and coins means physically handling the money.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Maintaining clean and orderly till areas
staying human
This work happens in the physical world: clean, in a real place. Software cannot follow it there.
importance 75 · 4129/01
Source: “Maintain clean and orderly till areas.” (UK task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Keeping the till area clean and tidy is physical work in the space itself.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.

What this job pays, and how many people do it

Median pay: £29,000a 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: 178,300in 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: recorded data in, a record out. The rows above are exactly that shape: summarising recorded data to compile and maintain financial records and maintaining records of contacts, accounts and orders. What it cannot do is be there in the room, and that is still where guests entering the theatre 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: summarising recorded data to compile and maintain financial records 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, 21% in rows that change shape rather than disappear, and 22% in rows it is nowhere near. That is the position, measured across 113 scored tasks. It is not a forecast about you.

What you have that the software does not is greeting guests entering the theatre or cinema, 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 recorded data 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 recorded data, 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 summarising recorded data to compile and maintain financial records” 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 greeting guests entering the theatre or cinema 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 financial administrative occupations n.e.c. (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was national government administrative occupations: only about 10% of its durable work is work you already do. I am not going to pretend that is comfortable news: 58% of your own task list is already in the top exposure band. But the answer on this evidence is not a sideways jump into a job with the same problem. It is to walk toward the end of this one that answers for things. “sell and check tickets” is the part that stays with a person, and spending a year getting formally recognised for it beats a standing start somewhere else.

How that was checked: this job was compared against all 412 UK occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.

3 moves I checked and rejected

These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.

National government administrative occupations
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “calculate and authorise amounts of assistance for programmes”. 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 →
Retail cashiers and check-out operators
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “count banknotes and coins for cash handling operations”. Across the whole of both lists that adds up to about 8% 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 8% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: £24,622 against your £28,996, 15.1% less (ASHE Table 14.7a, 2025 provisional (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →
Local government administrative occupations
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “calculate and authorise amounts of assistance for programmes”. Across the whole of both lists that adds up to about 8% 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 8% 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: 58% of its task weight, across 113 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: greeting guests entering the theatre or cinema 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 Tax Examiners and Collectors, and Revenue Agents 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 Tax Examiners and Collectors, and Revenue Agents, First-Line Supervisors of Gambling Services Workers, Gambling Dealers, Gambling and Sports Book Writers and Runners, Gambling Service Workers, All Other, Gambling Cage Workers, Financial Clerks, All Other, Brokerage Clerks, Credit Authorizers, Checkers, and Clerks, Loan Interviewers and Clerks, New Accounts Clerks and Insurance Claims and Policy Processing 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

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 finance administrators 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 Power Automate Builders, a community for non-developers building the approvals, reminders and handoffs that keep working once real people use them. It overlaps with the part of your job that is growing: the routing and chasing around invoices, expenses and approvals, rather than the keying-in. If that overlap isn't you, the free route below covers the same ground.

Try Power Automate Builders 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 finance administrators 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 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 Financial administrative occupations n.e.c.?: Not as a job, but it is already doing parts of the work. Across the 113 official task statements scored for Financial administrative occupations n.e.c. (United Kingdom, SOC 4129), 58% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 62 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 “Financial administrative occupations n.e.c.” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Issue receipts” (93/100, very high); “Summarise recorded data to compile and maintain financial records” (93/100, very high); “Monitor customer accounts to ensure timely payment and adherence to credit terms” (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 “Financial administrative occupations n.e.c.” stay human?: About 22% 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: “Maintain clean and orderly till areas” (0/100, minimal); “Count banknotes and coins for cash handling operations” (0/100, minimal); “Greet guests entering the theatre or cinema” (0/100, 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 “Financial administrative occupations n.e.c.” do about AI?: Start from the ledger rather than the headline: 58% of this job's weighted core work is exposed, and roughly 22% 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 Financial administrative occupations n.e.c. 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 113 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.
17 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.