Balance currency, coin, and checks in cash drawers at ends of shifts and calculate daily transactions, using computers, calculators, or adding machines.[2]
Where your edge is
Time Machine
Tellers
Scrub through 245 years of this role's history — from when it first emerged, through every wave of technology that reshaped it, to the cited projections for where it's heading next.
180018251850187519001925195019752000now
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2026
Known today as Tellers (BLS SOC 43-3071)
US Employment
347K
BLS National Employment Matrix 2024 baseline for SOC 43-3071, used in the 2024-34 employment projections cycle. This is a further decline from the 2022 figure (364,100), continuing the post-peak contraction. The 2024 baseline represents a 43% decline from the 2006 employment peak. BLS projects a further -12.9% decline to approximately 302,500 by 2034.
Median Annual Wage
$38,040
Source: BLS-OEWS
Tool of the era · COVID branch closures + AI teller chat + relationship banking imperative
COVID-19 branch closures in spring 2020 accelerated digital banking adoption more in three months than the prior decade's gradual shift had achieved. Millions of customers used mobile and online banking for the first time out of necessity and many did not return to branch-dependent habits. The remaining teller workforce has shifted significantly toward relationship banking functions: the teller of 2024 spends more time on account opening, product referrals, financial guidance, fraud escalation, and complex customer situations than on cash counting. Automated teller machines and ITMs (Interactive Teller Machines, which connect customers to remote human tellers by video) are absorbing the remaining routine cash transactions. Several major banks have piloted teller-free branch formats ('micro-branches') where no teller is stationed and all transactions are handled at ATM kiosks or via video appointment. BLS projects a further -12.9% decline through 2034 — from 347,400 (2024) to approximately 302,500 (2034).
BLS projects teller employment to fall to approximately 302,500 by 2034 — a total decline of more than 50% from the 2006-2007 peak. The occupation is not projected to vanish entirely because the relationship banking and complex-transaction functions that remain are genuinely resistant to full automation. But the mass-employment role of the 1980s-2000s is unlikely to return.
Projection cone · present → 2034
What credible sources project
Scrub the slider past now to anchor each scenario on the scrubber. The spread you see below is the range of futures credible sources project for this role.
Bessen (2015) / relationship-banking optimistic scenario
→ 2034
-5%
The optimistic tail of the uncertainty cone, grounded in Bessen's core insight: technology changes the composition of teller work rather than eliminating it. In this scenario, AI and ITMs (Interactive Teller Machines) absorb routine cash transactions, but the resulting cost reduction enables banks to deploy tellers in a genuinely advisory role — financial health coaching, small business support, elder care banking services — that generates new demand for human-banker hours even as per-transaction teller labor falls. Several community banks and credit unions are piloting this model explicitly as a differentiator against big-bank self-service. If relationship banking can sustain enough transaction value, employment decline stabilizes at -5% rather than -13% through 2034.
BLS National Employment Matrix 2024-34
→ 2034
-13%
BLS Employment Projections 2024-34 cycle (most current). Baseline: 347,400 (2024). Projected 2034: approximately 302,500. Numeric change: -44,900. Percent change: -12.9% (rounded to -13% here). BLS cites mobile banking growth and continued branch consolidation as the primary drivers. The -13% projection is among the steepest decline rates in the BLS major occupation set and one of the larger absolute-number declines. Annual average job openings are still substantial (~50,000+) because replacement need from retirements and voluntary departures outweighs net decline in any single year, but these are replacement openings, not growth.
Eloundou et al. — "GPTs are GPTs" (2023)
→ 2028
-20%
GPT-4 task-by-task LLM exposure labeling on O*NET tasks for 43-3071. Tellers score moderately high on LLM exposure for the information-processing tasks (explaining account features, resolving disputes, answering balance queries) but lower for physical cash-handling tasks (which LLMs cannot perform). The -20% estimate represents the near-term displacement component from AI adoption on the tasks that remain: AI-powered chat for routine account queries, automated fraud screening, and AI-assisted referral generation reduce the human-hours of teller work needed per transaction. The physical cash dispensing is already handled by ATMs; the remaining LLM exposure is concentrated in the customer-service and information-delivery functions.
Frey & Osborne (2013)
→ 2033
-98%
Gaussian-process classifier on O*NET task features. Frey & Osborne rated bank tellers at approximately 0.98 probability of computerization — placing them in the top few percent of most-automatable occupations among the 702 studied. The bottleneck factors scored unfavorably: the core tasks (cash counting, form processing, account lookup) were highly routine, rule-governed, and already being partially automated by ATMs in 2013. The -98% figure represents the F&O ceiling finding, not a precise employment-loss forecast. In reality, employment declined ~43% from the 2006 peak by 2024 rather than ~98%. F&O was correct about direction and high risk; it overestimated the speed and completeness of displacement, primarily because it did not model the relationship-banking functions that proved resilient.
Today, in this role
What's shifting in the work right now
The historical view above shows how this role has moved. This is the present-day detail: which AI tools are picking up which tasks, where the edge still is, and the natural directions this work can grow.
What's changing in your day
Three parts of your work where AI is already doing real lifting — and what stays yours.
Receive mortgage, loan, or public utility bill payments, verifying payment dates and amounts due.[2]
Where your edge is
Cash checks and pay out money after verifying that signatures are correct, that written and numerical amounts agree, and that accounts have sufficient funds.[2]
Where your edge is
Present-day sources
Sources
Every claim on this page traces back to one of the following. Updated 2026-05-30.
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