Will AI replace Finance officers?

Not as a job, but it is already doing parts of the work. Across the 45 official task statements scored for Finance officers (United Kingdom, SOC 4124), 89% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 79 out of 100 (range 74–84, 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 “Finance officers” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Operate calculators for financial calculations and record-keeping” (100/100, very high); “Calculate amounts due, including interest charges and balances” (93/100, very high); “Check figures, postings, and documents for correct entry, mathematical accuracy, and appropriate codes” (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 “Finance officers” stay human?

About 10% 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: “Operate photocopiers as part of general office or clerical work” (0/100, minimal); “Conduct financial audits to independently check an organisation's financial position” (27/100, low); “Adhere to, and support others to adhere to, relevant legislation and company vision, mission, values, policies and procedures” (28/100, low). 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 “Finance officers” do about AI?

Start from the ledger rather than the headline: 89% of this job's weighted core work is exposed, and roughly 10% 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 Finance officers 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 45 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

Finance officers

calculating amounts due, including interest charges and balances, preparing trial balances of books and reconciling issued payrolls to bank statements. 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: calculating amounts due, including interest charges and balances. The tasks, though, are not you.

Your move: three real directions from here ↓

Where the work sits, by task weight

shifting to AI: 89%
changing shape: 1%
staying human: 10%

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

Whole-job exposure score 79 out of 100 (74–84 allowing for uncertainty): high exposure, across 45 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 finance officers is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.

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

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

It would be a lie to soften that, and another lie to promise a rebuilt version of this job inside this job.

So the hope here is what you already carry: the judgment you bring to financial audits is real, and the moves below are built from it. The first step is down this page.

Your week, as this page understands it

Finance officers oversee book-keeping, general accounting and other financial and related clerical functions mainly within local government and a variety of public sector organisations. The job title says “finance officers”. The real job is the part underneath: conducting financial audits to independently check an organisation's financial position. 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 finance officers is not one task. It is 45 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is conducting financial audits to independently check an organisation's financial position, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 89%
changing shape: 1%
staying human: 10%

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

How we know this

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

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

Your job, task by task

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

7 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

39 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.

Calculating amounts due, including interest charges and balances
This is reading one thing and writing another: amounts due, including interest charges and balances in, a record out. That is the shape today's tools are built for.
importance 95 · 4124/00
Source: “Calculate amounts due, including interest charges and balances.” (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 balances and interest is documented arithmetic finance software does accurately every time.
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 figures, postings and documents for correct entry, mathematical accuracy and appropriate codes
This is reading one thing and writing another: figures, postings and documents in, a record out. That is the shape today's tools are built for.
importance 95 · 4124/00
Source: “Check figures, postings, and documents for correct entry, mathematical accuracy, and appropriate codes.” (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 postings, figures and codes is exactly the structured verification accounting software performs 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.
Classifying and recording numerical and financial data in journals
This is reading one thing and writing another: numerical in, a record out. That is the shape today's tools are built for.
importance 95 · 4124/00
Source: “Classify and record numerical and financial data in journals, ledgers, or 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: Classifying and recording financial data is structured, repetitive work that accounting 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.
Performing basic bookkeeping duties for financial record maintenance
This is reading one thing and writing another: basic bookkeeping duties in, a record out. That is the shape today's tools are built for.
importance 95 · 4124/00
Source: “Perform basic bookkeeping duties for financial record maintenance.” (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: Basic bookkeeping is highly structured, well-documented work that accounting software and AI already do to a high standard.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Calculating bills, invoices and financial statements according to established procedures
This is reading one thing and writing another: bills, invoices and financial statements in, a record out. That is the shape today's tools are built for.
importance 95 · 4124/00
Source: “Calculate bills, invoices, and financial statements according to established procedures.” (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: Producing bills and statements from set procedures is well-documented calculation work software does reliably, feeding a later sign-off.
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

1 task

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.

Filing documents as part of general office duties
The software now makes the first pass at documents, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 50 · 4124/00
Source: “File documents as part of general office duties.” (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: Filing is largely electronic now, though paper records still need someone to handle 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 0/4 · how much data exists 3/4.

Staying human

5 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.

Adhering to and supporting
The value here is that a specific person handles this work and stands behind it. That is earned, not computed.
importance 80 · 4124/00
Source: “Adhere to, and support others to adhere to, relevant legislation and company vision, mission, values, policies and procedures.” (UK task statement)
How this row was scored
Exposure score: 28 out of 100 (21–35 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Rules can be summarised easily, but following them and helping colleagues do so is a person's job.
The five ratings: output a model can produce 1/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Conducting financial audits to independently check an organisation's financial position
The rules require a named, qualified person to answer for financial audits, and that person cannot be a piece of software.
importance 80 · 4124/00
Source: “Conduct financial audits to independently check an organisation's financial position.” (UK task statement)
How this row was scored
Exposure score: 27 out of 100 (20–34 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: Testing and sampling can be automated, but an independent audit opinion rests with a qualified auditor.
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 3/4.
Sending cash, cheques or other forms of payment to banks
This work happens in the physical world: cash, cheques or other forms of payment, in a real place. Software cannot follow it there.
importance 70 · 4124/00
Source: “Send cash, cheques, or other forms of payment to banks.” (UK task statement)
How this row was scored
Exposure score: 29 out of 100 (22–36 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: Physically getting cash and cheques to the bank is a trip someone has to make.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Preparing cash receipts after establishments close
This work happens in the physical world: cash receipts after establishments close, in a real place. Software cannot follow it there.
importance 60 · 4124/00
Source: “Prepare cash receipts after establishments close.” (UK task statement)
How this row was scored
Exposure score: 29 out of 100 (22–36 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: Preparing the day's takings means counting and reconciling actual cash after closing.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.

Show the other 35 tasks

Operating calculators for financial calculations and record-keeping
shifting to AI
This is reading one thing and writing another: calculators in, a record out. That is the shape today's tools are built for.
importance 70 · 4124/00
Source: “Operate calculators for financial calculations and record-keeping.” (UK task statement)
How this row was scored
Exposure score: 100 out of 100 (96–100 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: Operating a calculator is pure arithmetic, which software has done faster and more accurately for decades.
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 4/4.
Compiling accounting and auditing tables for accounts payable and receivable
shifting to AI
This is reading one thing and writing another: tables in, a record out. That is the shape today's tools are built for.
importance 90 · 4124/00
Source: “Compile accounting and auditing tables for accounts payable and receivable.” (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: Building payables and receivables tables is structured reporting that accounting software produces 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.
Crediting accounts on computer spreadsheets and databases using specialised accounting software
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 90 · 4124/00
Source: “Credit accounts on computer spreadsheets and databases using specialised accounting software.” (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: Crediting accounts in accounting software is structured, repetitive entry work that systems already perform 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 90 · 4124/00
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.
Processing invoices for financial transactions and record-keeping
shifting to AI
This is reading one thing and writing another: invoices in, a record out. That is the shape today's tools are built for.
importance 90 · 4124/00
Source: “Process invoices for financial transactions and record-keeping.” (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: Invoice processing is structured, repetitive work that automated 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 0/4 · how much data exists 3/4.
Compiling budget data based on estimated revenues
shifting to AI
This is reading one thing and writing another: budget data in, a record out. That is the shape today's tools are built for.
importance 85 · 4124/00
Source: “Compile budget data based on estimated revenues, expenses, and previous budgets.” (UK task statement)
How this row was scored
Exposure score: 93 out of 100 (86–100 allowing for uncertainty): very high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Compiling budget figures from past budgets and estimates is structured spreadsheet 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.
Creating budget reports to monitor financial performance and ensure fiscal responsibility
shifting to AI
This is reading one thing and writing another: budget reports in, a record out. That is the shape today's tools are built for.
importance 85 · 4124/00
Source: “Create budget reports to monitor financial performance and ensure fiscal responsibility.” (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: Budget reports come straight out of the finance system in a standard format.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Preparing trial balances of books
shifting to AI
This is reading one thing and writing another: trial balances of books in, a record out. That is the shape today's tools are built for.
importance 85 · 4124/00
Source: “Prepare trial balances of books.” (UK task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Producing a trial balance is a defined accounting step that finance software performs 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.
Reconciling issued payrolls to bank statements
shifting to AI
This is reading one thing and writing another: issued payrolls in, a record out. That is the shape today's tools are built for.
importance 85 · 4124/00
Source: “Reconcile issued payrolls to bank statements.” (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: Reconciling payroll to bank statements is exactly the structured matching that finance software performs 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.
Documenting budget data for reference and analysis
shifting to AI
This is reading one thing and writing another: budget data in, a record out. That is the shape today's tools are built for.
importance 80 · 4124/00
Source: “Document budget data for reference and analysis.” (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: Documenting budget figures is structured spreadsheet work that software and AI 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 0/4 · how much data exists 3/4.
Matching order forms with invoices
shifting to AI
This is reading one thing and writing another: order forms in, a record out. That is the shape today's tools are built for.
importance 80 · 4124/00
Source: “Match order forms with 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: Matching orders to invoices is exactly the structured comparison that finance software performs 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.
Recording the necessary information from matched order forms and invoices
shifting to AI
This is reading one thing and writing another: the necessary information in, a record out. That is the shape today's tools are built for.
importance 80 · 4124/00
Source: “Record the necessary information from matched order forms 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: Copying details from matched orders and invoices is exactly the kind of structured data work software handles 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.
Summarising recorded data to compile and maintain financial records
shifting to AI
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 80 · 4124/00
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 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.
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 · 4124/00
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.
Calculating costs of materials, overheads and other expenses from estimates and price lists
shifting to AI
This is reading one thing and writing another: costs of materials, overheads and other expenses in, a record out. That is the shape today's tools are built for.
importance 70 · 4124/00
Source: “Calculate costs of materials, overheads, and other expenses from estimates and price lists.” (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: Costing from estimates and price lists is documented arithmetic that spreadsheets and AI handle accurately.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Determining discounts, equity and principal as part of financial calculations
shifting to AI
This is reading one thing and writing another: discounts, equity and principal in, a record out. That is the shape today's tools are built for.
importance 70 · 4124/00
Source: “Determine discounts, equity, and principal as part of financial calculations.” (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 discounts, equity and principal is documented arithmetic finance software does 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.
Filing expense account reports for financial accountability
shifting to AI
This is reading one thing and writing another: expense account reports in, a record out. That is the shape today's tools are built for.
importance 70 · 4124/00
Source: “File expense account reports for financial accountability.” (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: Filing expense reports is structured, repetitive record-keeping that expense software already automates.
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.
Composing letters as part of office duties
shifting to AI
This is reading one thing and writing another: letters in, a record out. That is the shape today's tools are built for.
importance 60 · 4124/00
Source: “Compose letters as part of office duties.” (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: Routine office letters are exactly what AI drafts well, using details already held in the finance system.
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.
Generating purchase orders for required goods
shifting to AI
This is reading one thing and writing another: purchase orders in, a record out. That is the shape today's tools are built for.
importance 60 · 4124/00
Source: “Generate purchase orders for required goods.” (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: Raising purchase orders is structured, rule-based work that finance systems already generate 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.
Producing product documentation and reports according to company policy
shifting to AI
This is reading one thing and writing another: product documentation in, a record out. That is the shape today's tools are built for.
importance 60 · 4124/00
Source: “Produce product documentation and reports according to company policy.” (UK task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Producing documentation to a set company policy is structured drafting work AI does to a high standard.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Producing financial forecasts
shifting to AI
This is reading one thing and writing another: financial forecasts in, a record out. That is the shape today's tools are built for.
importance 75 · 4124/00
Source: “Produce financial forecasts.” (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: Forecasting from historic figures suits software well, though the assumptions behind it are a judgement call.
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.
Calculating statutory contributions like pensions and National Insurance
shifting to AI
This is reading one thing and writing another: statutory contributions like pensions in, a record out. That is the shape today's tools are built for.
importance 90 · 4124/00
Source: “Calculate statutory contributions like pensions and National Insurance.” (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: National Insurance and pension calculations follow published rates that payroll software applies exactly, feeding a return filed 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.
Accessing computerised financial information to answer general questions
shifting to AI
This is reading one thing and writing another: computerised financial information in, a record out. That is the shape today's tools are built for.
importance 90 · 4124/00
Source: “Access computerised financial information to answer general questions.” (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 figures and answering general questions is something systems already do instantly.
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.
Delivering performance and progress reports to management teams
shifting to AI
This is reading one thing and writing another: performance in, a record out. That is the shape today's tools are built for.
importance 75 · 4124/00
Source: “Deliver performance and progress reports to management teams.” (UK task statement)
How this row was scored
Exposure score: 79 out of 100 (72–86 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: The reports themselves are easily produced, though delivering them to a management team is a person's job.
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.
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 90 · 4124/00
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.
Preparing reports on business activities
shifting to AI
This is reading one thing and writing another: reports in, a record out. That is the shape today's tools are built for.
importance 80 · 4124/00
Source: “Prepare reports on business activities, expenses, and budgets.” (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: Reports on activity, spend and budgets are drafted well from system data, though the commentary 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.
Logging transactions involving cash, cheques and vouchers
shifting to AI
This is reading one thing and writing another: transactions involving cash, cheques and vouchers in, a record out. That is the shape today's tools are built for.
importance 90 · 4124/00
Source: “Log transactions involving cash, cheques, and vouchers.” (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: Logging cash, cheque and voucher transactions is structured recording software handles, with some handling of the physical items.
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.
Handling VAT submissions and payments
shifting to AI
This is reading one thing and writing another: VAT submissions in, a record out. That is the shape today's tools are built for.
importance 85 · 4124/00
Source: “Handle VAT submissions and payments.” (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 calculated from digital records, though a responsible person still makes the submission to HMRC.
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.
Submitting completed tax forms, workers' compensation forms, pension contribution forms and other government documents
shifting to AI
This is reading one thing and writing another: completed tax forms, workers' compensation forms in, a record out. That is the shape today's tools are built for.
importance 85 · 4124/00
Source: “Submit completed tax forms, workers' compensation forms, pension contribution forms, and other government documents.” (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: Completing and filing government forms is highly structured work software does well, though filing 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.
Verifying amounts and checking accuracy of deposit slips
shifting to AI
This is reading one thing and writing another: amounts in, a record out. That is the shape today's tools are built for.
importance 85 · 4124/00
Source: “Verify amounts and check accuracy of deposit slips.” (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: Checking deposit slip totals is simple verification software does reliably, with only light handling of the paper itself.
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.
Transferring details from paper records into computer systems
shifting to AI
This is reading one thing and writing another: details in, a record out. That is the shape today's tools are built for.
importance 70 · 4124/00
Source: “Transfer details from paper records into computer systems.” (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: Scanning and typing up paper records is near-automatic now, though someone still has to handle the physical files.
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.
Addressing and resolving payment queries from external contractors
shifting to AI
This is reading one thing and writing another: payment queries in, a record out. That is the shape today's tools are built for.
importance 85 · 4124/00
Source: “Address and resolve payment queries from external contractors.” (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: Payment queries are answered from purchase ledger records, which software can look up and explain clearly.
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.
Responding to telephone enquiries as part of administrative support
shifting to AI
This is reading one thing and writing another: telephone enquiries in, a record out. That is the shape today's tools are built for.
importance 50 · 4124/00
Source: “Respond to telephone enquiries as part of administrative support.” (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 routine enquiries can be answered automatically, though callers 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 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Preparing and processing cheques for financial transactions
shifting to AI
This is reading one thing and writing another: cheques in, a record out. That is the shape today's tools are built for.
importance 85 · 4124/00
Source: “Prepare and process cheques for financial transactions.” (UK task statement)
How this row was scored
Exposure score: 61 out of 100 (54–68 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: Preparing cheques is largely automated, though someone must physically sign and send them and an authorised signatory approves.
The five ratings: output a model can produce 4/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Operating photocopiers as part of general office or clerical work
staying human
This work happens in the physical world: photocopiers, in a real place. Software cannot follow it there.
importance 50 · 4124/00
Source: “Operate photocopiers as part of general office or clerical work.” (UK task statement)
How this row was scored
Exposure score: 0 out of 100 (0–7 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Copying needs someone standing at the machine with the paper.
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: £31,900a 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: 44,900in 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: amounts due, including interest charges and balances in, a record out. The rows above are exactly that shape: calculating amounts due, including interest charges and balances and checking figures, postings and documents for correct entry, mathematical accuracy and appropriate codes. What it cannot do is be answerable: financial audits need a named person the rules will accept, and software cannot be that person. 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: calculating amounts due, including interest charges and balances is work today's tools do quickly and cheaply, and that is not coming back.

So, given all that: 89% of this job's task weight sits in rows the software is already learning, 1% in rows that change shape rather than disappear, and 10% in rows it is nowhere near. That is the position, measured across 45 scored tasks. It is not a forecast about you.

What you have that the software does not is conducting financial audits to independently check an organisation's financial position, 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 amounts due, including interest charges and balances 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 amounts due, including interest charges and balances, 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 calculating amounts due, including interest charges and balances” 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 conducting financial audits to independently check an organisation's financial position 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 finance officers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was financial and accounting technicians: only about 13% of its durable work is work you already do and it is under the same pressure this job is. I am not going to pretend that is comfortable news: 89% 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. “adhere to, and support others to adhere to, relevant legislation and company…” 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.

Financial and accounting technicians
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “prepare cash receipts after establishments close”. Across the whole of both lists that adds up to about 13% 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 13% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on. I will not move you off one melting floe onto another: 76% of its own task list already scores in the top exposure band (67/100 in this release), so the same software is eating it.
Look at that job’s page anyway →
Book-keepers, payroll managers and wages clerks
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “send cash, cheques, or other forms of payment to banks”. Across the whole of both lists that adds up to about 11% 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 11% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on. I will not move you off one melting floe onto another: 68% of its own task list already scores in the top exposure band (66/100 in this release), so the same software is eating it.
Look at that job’s page anyway →
Other administrative occupations n.e.c.
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “file documents as part of general office duties”. Across the whole of both lists that adds up to about 6% of the work in that job the software is not taking.
Why I am not recommending it: Almost none of it is work you already do: about 6% of the durable side of that job. That is a different job, not a next step. I will not move you off one melting floe onto another: 64% of its own task list already scores in the top exposure band (62/100 in this release), so the same software is eating it. It is a pay cut, in those words: £28,294 against your £31,943, 11.4% less (ASHE Table 14.7a, 2025 provisional (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →

What I’d stop worrying about

A friend tells you what not to spend fear on. This is that list.

The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 89% of its task weight, across 45 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: conducting financial audits to independently check an organisation's financial position 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 Financial Clerks, All Other 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 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 officers 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 Microsoft 365 Report Builders, a community for people who build business reports in Excel, Power Query and Power BI without a data team behind them. It overlaps with the part of your job that is growing: the reporting half of finance administration: clean data, defined measures, a pack that reconciles. If that overlap isn't you, the free route below covers the same ground.

Try Microsoft 365 Report 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 officers 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 Finance officers?: Not as a job, but it is already doing parts of the work. Across the 45 official task statements scored for Finance officers (United Kingdom, SOC 4124), 89% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 79 out of 100 (range 74–84, 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 “Finance officers” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Operate calculators for financial calculations and record-keeping” (100/100, very high); “Calculate amounts due, including interest charges and balances” (93/100, very high); “Check figures, postings, and documents for correct entry, mathematical accuracy, and appropriate codes” (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 “Finance officers” stay human?: About 10% 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: “Operate photocopiers as part of general office or clerical work” (0/100, minimal); “Conduct financial audits to independently check an organisation's financial position” (27/100, low); “Adhere to, and support others to adhere to, relevant legislation and company vision, mission, values, policies and procedures” (28/100, low). 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 “Finance officers” do about AI?: Start from the ledger rather than the headline: 89% of this job's weighted core work is exposed, and roughly 10% 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 Finance officers 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 45 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.
7 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.