Will AI replace Tellers?
In theory, AI could do about 54% of the work in Tellers. In practice, as of late 2025, almost no one is actually using it that way — yet.
O*NET-SOC 43-3071
How your 19 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a moderate share of this job's tasks (~54%). By late 2025, real-world AI use had reached about 2% of its task activity (still rare). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
Don't trust a single AI-risk score here
For this job, the signals disagree sharply. AI's theoretical reach looks moderate (~54%), but real-world use is only ~2%, and how much AI "can" do shifts wildly by model — one 2026 study found the share of "high-risk" jobs swung 2.7% to 51.5% just by changing which AI did the rating. This page shows the spread instead of pretending there's one number.
See all 19 tasks, ratedBased on real task-level AI scores — click to collapse
- Balance currency, coin, and checks in cash drawers at ends of shifts and calculate daily transactions, using computers, calculators, or adding machines.
- Enter customers' transactions into computers to record transactions and issue computer-generated receipts.
- Answer telephones and assist customers with their questions.
- Identify transaction mistakes when debits and credits do not balance.
- Receive checks and cash for deposit, verify amounts, and check accuracy of deposit slips.
- Cash checks and pay out money after verifying that signatures are correct, that written and numerical amounts agree, and that accounts have sufficient funds.
- 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.
- Resolve problems or discrepancies concerning customers' accounts.
- Prepare and verify cashier's checks.
- Process transactions, such as term deposits, retirement savings plan contributions, automated teller transactions, night deposits, and mail deposits.
- Carry out special services for customers, such as ordering bank cards and checks.
- Order a supply of cash to meet daily needs.
- Receive mortgage, loan, or public utility bill payments, verifying payment dates and amounts due.
- 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.
- Monitor bank vaults to ensure cash balances are correct.
- 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.
- Sort and file deposit slips and checks.
- Receive and count daily inventories of cash, drafts, and travelers' checks.
- Arrange monies received in cash boxes and coin dispensers according to denomination.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.