Will AI replace New Accounts Clerks?

Not as a job, but it is already doing parts of the work. Across the 15 official task statements scored for New Accounts Clerks (United States, SOC 43-4141), 19% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 39 out of 100 (range 35–44, band: low). 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 “New Accounts Clerks” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Compile information about new accounts, enter account information into computers, and file related forms or other documents” (81/100, very high); “Obtain credit records from reporting agencies” (81/100, very high); “Duplicate records for distribution to branch offices” (69/100, high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.

Which tasks in “New Accounts Clerks” stay human?

About 38% 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: “Perform foreign currency transactions and sell traveler's checks” (0/100, minimal); “Issue initial and replacement safe-deposit keys to customers, and admit customers to vaults” (0/100, minimal); “Perform teller duties as required” (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 “New Accounts Clerks” do about AI?

Start from the ledger rather than the headline: 19% of this job's weighted core work is exposed, and roughly 38% 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 New Accounts Clerks 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 15 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.

US dataswitch to UK

New Accounts Clerks

performing teller duties, answering customers' questions and explaining available services and obtaining credit records from reporting agencies. If that's your week, this page is about your job.

The honest answer

AI is already taking a real slice of the routine work here: compiling information about new accounts. That is a slice of tasks, not of you.

Your move: what you can actually do about this ↓

Where the work sits, by task weight

shifting to AI: 19%
changing shape: 43%
staying human: 38%

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

Whole-job exposure score 39 out of 100 (35–44 allowing for uncertainty): low exposure, across 15 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 new accounts clerks 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.

That slice is not coming back; the core of the job, performing teller duties, stays yours. The tools change, the responsibility doesn't.

Your week, as this page understands it

Interview persons desiring to open accounts in financial institutions. Explain account services available to prospective customers and assist them in preparing applications. The job title says “new accounts clerks”. The real job is the part underneath: performing teller duties. 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 new accounts clerks is not one task. It is 15 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is performing teller duties, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 19%
changing shape: 43%
staying human: 38%

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.

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

5 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.

Compiling information about new accounts
This is reading one thing and writing another: information in, a record out. That is the shape today's tools are built for.
importance 5 · Core
Source: “Compile information about new accounts, enter account information into computers, and file related forms or other documents.” (O*NET task statement)
How this row was scored
Exposure score: 81 out of 100 (77–85 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Gathering and keying account details into the system is data entry that banking software already largely automates.
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.
Obtaining credit records from reporting agencies
This is reading one thing and writing another: credit records in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Obtain credit records from reporting agencies.” (O*NET 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 a credit file from a reporting agency is an automated lookup that already runs without 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.
Processing loan applications
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 5 · Supplemental
Source: “Process loan applications.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (62–70 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Processing a loan application means checking documents against set criteria, which software does to a standard staff accept.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Scheduling repairs for locks on safe-deposit boxes
This is reading one thing and writing another: repairs in, a record out. That is the shape today's tools are built for.
importance 3 · Supplemental
Source: “Schedule repairs for locks on safe-deposit boxes.” (O*NET 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: Booking a locksmith is scheduling and correspondence software can arrange from a desk.
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.

Changing shape

5 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.

Informing customers of procedures for applying
The software now makes the first pass at customers of procedures, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 5 · Core
Source: “Inform customers of procedures for applying for services, such as ATM cards, direct deposit of checks, and certificates of deposit.” (O*NET task statement)
How this row was scored
Exposure score: 53 out of 100 (49–57 allowing for uncertainty): partial 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 how to apply for a card or a certificate of deposit follows published procedures software can present clearly.
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 4/4.
Answering customers' questions and explaining available services
The software now makes the first pass at customers' questions, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Answer customers' questions and explain available services, such as deposit accounts, bonds, and securities.” (O*NET task statement)
How this row was scored
Exposure score: 42 out of 100 (38–46 allowing for uncertainty): partial 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: Product details are documented and easy to explain, though customers often want a person at the branch to answer.
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 1/4 · how much data exists 3/4.
Referring customers to appropriate bank personnel to meet their financial needs
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 4 · Core
Source: “Refer customers to appropriate bank personnel to meet their financial needs.” (O*NET task statement)
How this row was scored
Exposure score: 48 out of 100 (44–52 allowing for uncertainty): partial 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 which colleague a customer needs is a routing decision software makes well from their stated need.
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.

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.

Interviewing customers to obtain information needed for opening accounts or renting safe-deposit boxes
This work happens in the physical world: customers, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Interview customers to obtain information needed for opening accounts or renting safe-deposit boxes.” (O*NET 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: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Identity checks and forms automate well, but account-opening interviews are usually done in person at the branch.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Performing teller duties
This work happens in the physical world: teller duties, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Perform teller duties as required.” (O*NET 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: Teller work means handling cash and customers over a counter in the branch.
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 1/4 · how much data exists 2/4.
Collecting and recording customer deposits and fees and issuing receipts
This work happens in the physical world: customer deposits, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Collect and record customer deposits and fees and issue receipts, using computers.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (7–21 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 recording is easy to automate, but taking a customer's deposit over the counter needs someone there.
The five ratings: output a model can produce 3/4 · needs a body in a room 3/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.

Show the other 5 tasks

Duplicating records for distribution to branch offices
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 3 · Supplemental
Source: “Duplicate records for distribution to branch offices.” (O*NET 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: Copying records and sending them to other branches is a routine duplication job largely handled electronically.
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.
Investigating and correcting errors upon customers' request
changing shape
The software now makes the first pass at errors upon customers' request, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Investigate and correct errors upon customers' request, according to customer and bank records.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (52–60 allowing for uncertainty): partial 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: Tracing and fixing an error by comparing bank and customer records is exactly the kind of checking software does well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Executing wire transfers of funds
changing shape
The software now makes the first pass at wire transfers of funds, 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 4 · Core
Source: “Execute wire transfers of funds.” (O*NET 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: The transfer itself is a system action, but banks require an authorized employee to release the funds.
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.
Issuing initial and replacement safe-deposit keys
staying human
This work happens in the physical world: initial, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Issue initial and replacement safe-deposit keys to customers, and admit customers to vaults.” (O*NET 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: Handing over keys and letting a customer into the vault requires being physically present.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Performing foreign currency transactions and selling traveler's checks
staying human
This work happens in the physical world: foreign currency transactions, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Perform foreign currency transactions and sell traveler's checks.” (O*NET 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: Counting out foreign notes and traveler's checks is cash handling across a counter.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.

What this job pays, and how many people do it

Median pay: $47,670a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
People doing this job: 36,860in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)

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: credit records in, a record out. The rows above are exactly that shape: compiling information about new accounts and obtaining credit records from reporting agencies. What it cannot do is be there in the room, and that is still where teller duties get 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

Start with what does not change: performing teller duties is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 19% of this job's task weight sits in rows the software is already learning, 43% in rows that change shape rather than disappear, and 38% in rows it is nowhere near. That is the position, measured across 15 scored tasks. It is not a forecast about you.

So the thing worth your attention is not the job going away. It is the layer around it. Compiling information about new accounts is the part turning into software, and being the person who understands that layer is worth money.

This week: one thing

Ask the one question. Find whoever is bringing new software into your workplace (the manager, the office, whoever runs the system) and ask them what it is meant to do to credit records, and what it is not meant to touch. Ten minutes, this week, before anyone decides it for you.

What you end up holding: a straight answer about what is actually being rolled out, and when
How long it takes: ten minutes

If there’s nobody obvious to ask, or you’d rather not ask your manager: Put the same question to your union rep, your shift lead or the person who has been there longest, in person, over a break. Same ten minutes, same answer, and you will usually get a straighter one. Write down what they say. The note is the artifact, and it tells you whether teller duties are in scope or not. Nothing to log into, no license needed.

Over the next 90 days

Get inside the tool rollout rather than waiting for it. Over the next ninety days, ask to be in the group that tests, checks or signs off whatever new system arrives near informing customers of procedures for applying. It is usually an unglamorous seat that nobody fights for, and it is the one that decides how the software is used on your job rather than to it.

Over the next 12 months

On this evidence I would not retrain out of this job, and I will say that plainly rather than hedge it. The task list here is dominated by work that stays with a person. What I would do with a year is get formally recognised for the layer around it (the systems, the compliance, the planning), so you are the one who understands the software instead of the one it is done to. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, 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 US occupations to new accounts clerks (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was tellers: only about 5% of its durable work is work you already do. And on the numbers you do not need one. This job scores 39/100 here, with only 19% of the task list in the top band, and “inform customers of procedures for applying for services” is not work that hands over cleanly. None of them beats deepening what you already have.

How that was checked: this job was compared against all 830 US 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.

Tellers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already inform customers of procedures for applying for services, and their equivalent is to receive checks and cash for deposit, verify amounts, and check accuracy of deposit…. Across both published task lists that is about 5% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 5% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →
Loan Interviewers and Clerks
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already process loan applications, and their equivalent is to interview loan applicants to obtain personal and financial data and to assist in…. Across both published task lists that is about 4% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 4% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →
Cashiers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already collect and record customer deposits and fees and issue receipts, using computers, and their equivalent is to issue receipts, refunds, credits, or change due to customers. Across both published task lists that is about 4% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 4% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $32,880 against your $47,670, 31.0% less (OEWS May 2025 (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: 19% of its task weight, across 15 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The headlines about your trade disappearing
They are usually about the technology, not the timetable. Changes to work like performing teller duties arrive through rules, insurance and money, slowly and visibly. This page tracks the task evidence and will move when it moves.
Retraining out of a job that is holding up
On this evidence I would not spend money leaving. Spend it on the layer around the job instead: the tools, the paperwork, the planning. That is where the change actually is.
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 States figures

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

Switch to the United Kingdom page →partial match

The other groups this work is counted across:

In UK official statistics this job is counted as Pensions and insurance clerks and assistants, Finance officers and Financial administrative occupations n.e.c.. Pay is shown separately for each of those groups (medians cannot be averaged together), while the task list and the scores on this page are for this group only.

Your route through this

Where to go next, and what it costs

Free, and complete

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

Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
American Job Center locator
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
- CareerOneStop local help hub
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
CareerOneStop
Free

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

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

There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 19% of the work on this page is already inside what they can do.

Try The AI Authority free →

7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.

The AI Authority is a general community about working with AI, not a course for new accounts clerks. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.

Noted, and thank you. We’ll email you if a Space for new accounts clerks launches. Nothing else.

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No Space for new accounts clerks yet. Should there be one?

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

What a Space actually is, in full

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

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

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

Questions people ask about this job

Will AI replace New Accounts Clerks?: Not as a job, but it is already doing parts of the work. Across the 15 official task statements scored for New Accounts Clerks (United States, SOC 43-4141), 19% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 39 out of 100 (range 35–44, band: low). 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 “New Accounts Clerks” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Compile information about new accounts, enter account information into computers, and file related forms or other documents” (81/100, very high); “Obtain credit records from reporting agencies” (81/100, very high); “Duplicate records for distribution to branch offices” (69/100, high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
Which tasks in “New Accounts Clerks” stay human?: About 38% 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: “Perform foreign currency transactions and sell traveler's checks” (0/100, minimal); “Issue initial and replacement safe-deposit keys to customers, and admit customers to vaults” (0/100, minimal); “Perform teller duties as required” (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 “New Accounts Clerks” do about AI?: Start from the ledger rather than the headline: 19% of this job's weighted core work is exposed, and roughly 38% 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 New Accounts Clerks 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 15 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

Worth knowing about these figures

The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
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: onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
Task weights: onet-db (im-rt)
Scores: Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
Pay and employment: bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))

Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.

The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.

The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.

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Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.

Plain text

Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).

BibTeX

@misc{collab365futureproof2026q41,
  title        = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
  author       = {{Collab365}},
  year         = {2026},
  url          = {https://futureproof.collab365.com/data/2026-q4.1},
  note         = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}

Permalink

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

Data as of release 2026-q4.1, published 2026-08-05. Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.