US dataswitch to UK
Tellers
balancing currency, processing transactions, such as term deposits and answering telephones and assisting customers with their questions. 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: identifying transaction mistakes when debits and credits do not balance. That is a slice of tasks, not of you.
That slice is not coming back; the core of the job, counting currency, coins and checks received, by hand or using currency-counting machine, stays yours. New tools, same person answering for it.
Your week, as this page understands it
Receive and pay out money. Keep records of money and negotiable instruments involved in a financial institution's various transactions. The job title says “tellers”. The real job is the part underneath: counting currency, coins and checks received, by hand or using currency-counting machine. 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 tellers is not one task. It is 28 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is counting currency, coins and checks received, by hand or using currency-counting machine, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 28%
- changing shape
- 23%
- staying human
- 50%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 41 out of 100 (36–46 allowing for uncertainty): partial exposure, across 28 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 tellers is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.
How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.
Release: 2026-q4.1, scores computed 2026-08-04. Read the full method.
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.
- 5 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
9 tasksTasks 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.
Answering telephones and assisting customers with their questions
This is reading one thing and writing another: telephones in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Answer telephones and assist customers with their questions.” (O*NET 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: Answering routine account questions by phone is well suited to automated help, though some callers still prefer a human voice.
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.
Resolving problems or discrepancies concerning customers' accounts
This is reading one thing and writing another: problems in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Resolve problems or discrepancies concerning customers' accounts.” (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: Tracing an account discrepancy is desk research in the bank's own records, though customers still want a person to explain it.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Identifying transaction mistakes when debits and credits do not balance
This is reading one thing and writing another: transaction mistakes in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Identify transaction mistakes when debits and credits do not balance.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Spotting where debits and credits fail to match is a reconciliation job that accounting software already performs quickly and accurately.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Carrying out special services
This is reading one thing and writing another: special services in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Carry out special services for customers, such as ordering bank cards and checks.” (O*NET 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: Ordering a replacement card or chequebook is a short system request that self-service and automated tools handle routinely.
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
6 tasksTasks 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.
Entering customers' transactions into computers to record transactions and issue computer-generated receipts
The software now makes the first pass at customers' transactions, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 5 · CoreSource: “Enter customers' transactions into computers to record transactions and issue computer-generated receipts.” (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: Keying transactions and printing receipts is routine data entry that systems already largely automate.
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.
Processing transactions, such as term deposits, retirement savings plan contributions
The software now makes the first pass at transactions, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 5 · CoreSource: “Process transactions, such as term deposits, retirement savings plan contributions, automated teller transactions, night deposits, and mail deposits.” (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: Most of these deposit and contribution transactions already run through automated systems, with the teller mainly starting and checking 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.
Examining checks for endorsements and to verify other information
The software now makes the first pass at checks, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 5 · CoreSource: “Examine checks for endorsements and to verify other information, such as dates, bank names, identification of the persons receiving payments, and the legality of the documents.” (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: Reading a cheque for dates, names, endorsements and correctness is exactly the kind of document check software now does reliably.
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
13 tasksTasks 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.
Balancing currency, coin and checks in cash drawers at ends of shifts and calculating daily transactions, using computers, calculators or adding machines
This work happens in the physical world: currency, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Balance currency, coin, and checks in cash drawers at ends of shifts and calculate daily transactions, using computers, calculators, or adding machines.” (O*NET task statement)
How this row was scored
Exposure score: 29 out of 100 (25–33 allowing for uncertainty): low exposure, high confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Counting the physical drawer needs hands, but the arithmetic and the daily transaction totals are already done by the branch computer system.
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.
Receiving checks and cash
This work happens in the physical world: checks, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Receive checks and cash for deposit, verify amounts, and check accuracy of deposit slips.” (O*NET task statement)
How this row was scored
Exposure score: 24 out of 100 (17–31 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Taking cash and cheques across the counter needs a person present, though checking that amounts and slips agree is routine computer work.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Cashing checks and pay out money after verifying that signatures
This work happens in the physical world: checks, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Cash checks and pay out money after verifying that signatures are correct, that written and numerical amounts agree, and that accounts have sufficient funds.” (O*NET task statement)
How this row was scored
Exposure score: 24 out of 100 (20–28 allowing for uncertainty): low exposure, high confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Handing out money happens in person, but verifying signatures, matching amounts and checking the balance is standard automated checking.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Show the other 18 tasks
Computing financial fees, interest and service charges
shifting to AIThis is reading one thing and writing another: financial fees, interest and service charges in, a record out. That is the shape today's tools are built for.
importance 4 · SupplementalSource: “Compute financial fees, interest, and service charges.” (O*NET 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 fees, interest and service charges from a rate schedule is arithmetic that computers do faster and more 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.
Quoting unit exchange rates, following daily international rate sheets or computer displays
shifting to AIThis is reading one thing and writing another: unit exchange rates in, a record out. That is the shape today's tools are built for.
importance 3 · SupplementalSource: “Quote unit exchange rates, following daily international rate sheets or computer displays.” (O*NET task statement)
How this row was scored
Exposure score: 85 out of 100 (81–89 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Quoting exchange rates simply reads published daily rates, which software does 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 4/4.
Ordering a supply of cash to meet daily needs
shifting to AIThis is reading one thing and writing another: a supply of cash in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Order a supply of cash to meet daily needs.” (O*NET 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: Working out how much cash the branch will need and placing the order is forecasting from past figures, which software does well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Processing and maintaining records of customer loans
shifting to AIThis is reading one thing and writing another: records of customer loans in, a record out. That is the shape today's tools are built for.
importance 4 · SupplementalSource: “Process and maintain records of customer loans.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Keeping loan records up to date is straightforward record-keeping inside the bank's own systems.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Informing customers about foreign currency regulations and computing transaction fees for currency exchanges
shifting to AIThis is reading one thing and writing another: customers in, a record out. That is the shape today's tools are built for.
importance 3 · SupplementalSource: “Inform customers about foreign currency regulations and compute transaction fees for currency exchanges.” (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: Currency rules are published and the fees are simple arithmetic, so explaining them is well within what automated help can do.
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.
Composing type and mail customer statements and other correspondence related to issues, discrepancies and outstanding unpaid items
changing shapeThe software now makes the first pass at type, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · SupplementalSource: “Compose, type, and mail customer statements and other correspondence related to issues such as discrepancies and outstanding unpaid items.” (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: Drafting a clear customer letter about a discrepancy is standard writing work; only the posting needs a person.
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.
Obtaining and processing information required for the provision of services
changing shapeThe software now makes the first pass at information, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · SupplementalSource: “Obtain and process information required for the provision of services, such as opening accounts, savings plans, and purchasing bonds.” (O*NET task statement)
How this row was scored
Exposure score: 48 out of 100 (41–55 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Collecting and keying the details needed to open an account is form-filling that online banking already handles for many customers.
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.
Explaining, promoting or selling products or services, such as travelers' checks, savings bonds, money orders and cashier's checks
changing shapeThe software now makes the first pass at products, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Explain, promote, or sell products or services, such as travelers' checks, savings bonds, money orders, and cashier's checks, using computerized information about customers to tailor recommendations.” (O*NET task statement)
How this row was scored
Exposure score: 40 out of 100 (33–47 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Software can suggest which products suit a customer, but persuading someone to take one is a live conversation.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Preparing and verifying cashier's checks
staying humanThis work happens in the physical world: cashier's checks, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Prepare and verify cashier's checks.” (O*NET task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Working out and issuing a cashier's cheque is partly a system transaction and partly printing and handing over a physical document.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Performing clerical tasks, such as typing, filing and microfilm photography
staying humanThis work happens in the physical world: clerical tasks, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Perform clerical tasks, such as typing, filing, and microfilm photography.” (O*NET task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Typing is easily automated, but filing and photographing paper documents still needs someone handling them.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Issuing checks to bond owners in settlement of transactions
staying humanThis work happens in the physical world: checks, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Issue checks to bond owners in settlement of transactions.” (O*NET task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Calculating and issuing a settlement cheque is half system work and half printing and handing over a physical document.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Receiving mortgage, loan or public utility bill payments, verifying payment dates and amounts due
staying humanThis work happens in the physical world: mortgage, loan or public utility bill payments, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Receive mortgage, loan, or public utility bill payments, verifying payment dates and amounts due.” (O*NET task statement)
How this row was scored
Exposure score: 32 out of 100 (25–39 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Checking payment dates and amounts is routine system work, but taking the payment over the counter still needs someone there.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Monitoring bank vaults to ensure cash balances
staying humanThis work happens in the physical world: bank vaults, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Monitor bank vaults to ensure cash balances are correct.” (O*NET 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: Checking vault balances mixes counting real cash with comparing figures on record; software handles the figures, a person handles the money.
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.
Counting, verifying and posting armored car deposits
staying humanThis work happens in the physical world: armored car deposits, in a real place. Software cannot follow it there.
importance 5 · SupplementalSource: “Count, verify, and post armored car deposits.” (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: Counting an armoured car delivery is hands-on; only posting the totals afterwards is desk work.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Counting currency, coins and checks received, by hand or using currency-counting machine
staying humanThis work happens in the physical world: currency, coins and checks, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Count currency, coins, and checks received, by hand or using currency-counting machine, to prepare them for deposit or shipment to branch banks or the Federal Reserve Bank.” (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: This is hands-on work: physically counting notes and coins and packing them for shipment cannot be done by software.
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.
Arranging monies received in cash boxes and coin dispensers according to denomination
staying humanThis work happens in the physical world: monies, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Arrange monies received in cash boxes and coin dispensers according to denomination.” (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: Sorting notes and coins into boxes and dispensers by denomination is purely physical handling.
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.
Sorting and filing deposit slips and checks
staying humanThis work happens in the physical world: deposit slips, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Sort and file deposit slips and 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: Sorting and filing paper slips and cheques is physical handling of documents, which needs hands rather than software.
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.
Receiving and counting daily inventories of cash
staying humanThis work happens in the physical world: inventories of cash, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Receive and count daily inventories of cash, drafts, and travelers' 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: Receiving and counting the day's cash and travellers' cheques is hands-on work with physical items.
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
- $43,030a 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
- 329,480in 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: transaction mistakes in, a record out. The rows above are exactly that shape: identifying transaction mistakes when debits and credits do not balance and answering telephones and assisting customers with their questions. What it cannot do is be there in the room, and that is still where currency, coins and checks 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
Your week is splitting in two, and which half fills it is the whole question. Identifying transaction mistakes when debits and credits do not balance is going; counting currency, coins and checks received, by hand or using currency-counting machine is not.
So, given all that: 28% of this job's task weight sits in rows the software is already learning, 23% in rows that change shape rather than disappear, and 50% in rows it is nowhere near. That is the position, measured across 28 scored tasks. It is not a forecast about you.
The occupation is an average and you are not, so the first job below is finding out where your own week actually sits.
This week: one thing
Print the task ledger above and put your own hours next to each row. Roughly, in pen, in one sitting. Then look at which group your hours actually pile up in. Twenty minutes, this week.
- What you end up holding
- your own week, on one page, sorted into what is shifting and what is not
- How long it takes
- about twenty minutes
If printing it isn’t practical: Read the rows off this page and write the same list on the back of an envelope. Same twenty minutes, same page, and it works just as well said out loud to someone who knows the job. The point is your hours next to the rows, not the paper it is on.
Over the next 90 days
Volunteer toward the durable end, visibly. Over the next ninety days put your hand up for the work in the bottom group (counting currency, coins and checks received, by hand or using currency-counting machine) and let people see you doing it. Not a new project: the same job, with your mix deliberately tilted. The point is that when the rota or the reorganisation comes, the version of you people picture is the one doing the part that stays.
Over the next 12 months
Claim a specialism at the durable end and let the other end go. Over a year, deliberately become the person who handles counting currency, coins and checks received, by hand or using currency-counting machine, and deliberately stop being the first choice for the rows in the top group. That trade costs something, because the exposed work is often the comfortable work. Decide it on purpose rather than by drift. 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 tellers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was bookkeeping, accounting, and auditing clerks: only about 14% of its durable work is work you already do and it is under the same pressure this job is. Your own job splits about 28/72: that share of the list sits in the top exposure band and the rest does not. On this evidence the honest move is inside the job rather than out of it. Become the person who owns “balance currency, coin, and checks in cash drawers at ends of shifts…”, and let the exposed end go.
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.
Bookkeeping, Accounting, and Auditing Clerks
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already receive checks and cash for deposit, verify amounts, and check accuracy of deposit…, and their equivalent is to receive, record, and bank cash, checks, and vouchers. Across both published task lists that is about 14% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 14% 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: that job is projected to shrink 5.8% between 2024 and 2034 (BLS Employment Projections), and 71% of its own task list already scores in the top exposure band (75/100 in this release), so the same software is eating it.
New Accounts Clerks
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already enter customers' transactions into computers to record transactions and issue computer-generated receipts, and their equivalent is to collect and record customer deposits and fees and issue receipts, using computers. Across both published task lists that is about 10% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 10% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on. And it is a narrow door: about 36,860 of those jobs against 329,480 of yours (OEWS May 2025), 11% as many seats.
Cashiers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already answer telephones and assist customers with their questions, and their equivalent is to answer customers' questions, and provide information on procedures or policies. Across both published task lists that is about 9% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 9% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $32,880 against your $43,030, 23.6% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
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: 28% of its task weight, across 28 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The whole-job doom story
Nothing on this page says this job ends. It says the mix inside it moves. Half the rows above are unchanged or changing shape, and the plan is about which half your week sits in. That is a very different problem, and a solvable one.
Panic-buying a course
Do the twenty-minute sorting exercise first. Most people who buy a course before they have done it buy the wrong one, and the free services listed below will tell you the same thing without charging for it.
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 Bank and post office clerks 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
In UK official statistics this job is counted as Bank and post office clerks. Pay and employment stay on this page’s own group; the task list and the scores do not cross over.
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:
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
Free
No Space for this job, but one for what is happening to it
Nothing Collab365 runs is built for tellers, 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 28% of the work on this page is already inside what they can do.
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 tellers. 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 tellers 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 Tellers?
- Not as a job, but it is already doing parts of the work. Across the 28 official task statements scored for Tellers (United States, SOC 43-3071), 28% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 41 out of 100 (range 36–46, band: partial). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
- Which tasks in “Tellers” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Compute financial fees, interest, and service charges” (93/100, very high); “Quote unit exchange rates, following daily international rate sheets or computer displays” (85/100, very high); “Identify transaction mistakes when debits and credits do not balance” (75/100, 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 “Tellers” stay human?
- About 50% 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: “Receive and count daily inventories of cash, drafts, and travelers' checks” (0/100, minimal); “Sort and file deposit slips and checks” (0/100, minimal); “Arrange monies received in cash boxes and coin dispensers according to denomination” (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 “Tellers” do about AI?
- Start from the ledger rather than the headline: 28% of this job's weighted core work is exposed, and roughly 50% 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 Tellers 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 28 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.
- 5 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
- 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 2026-08-04.
- 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.
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}
}Data as of release 2026-q4.1, published . 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.