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The AI Resilience Report helps you understand how AI is likely to impact your current or future career. Drawing on data from over 1,500 occupations, it provides a clear snapshot to support informed career decisions.
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Last Update: 4/23/2026
Your role’s AI Resilience Score is
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Low
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Med
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
Low
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
There are a reasonable number of sources for this result, but there is some disagreement between them.
Contributing sources
Tellers are less resilient to AI impacts than most occupations, according to our analysis of 7 sources.
The career of a bank teller is labeled as "Not Very Resilient" because many of their traditional tasks, like processing routine transactions and counting cash, are now done by machines like ATMs and banking apps. This automation reduces the need for human tellers in basic tasks, although there are still opportunities for human interaction in areas like customer service and handling complex issues.
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Learn more about how you can thrive in this position
This role is not very resilient
The career of a bank teller is labeled as "Not Very Resilient" because many of their traditional tasks, like processing routine transactions and counting cash, are now done by machines like ATMs and banking apps. This automation reduces the need for human tellers in basic tasks, although there are still opportunities for human interaction in areas like customer service and handling complex issues.
Read full analysisAnalysis of Current AI Resilience
Tellers
Updated Quarterly • Last Update: 2/17/2026

Bank tellers traditionally “process routine transactions, such as cashing checks and depositing money” and count cash drawers [1] [1]. Today much of that routine work is automated. For example, Automatic Teller Machines (ATMs) and smartphone apps let customers deposit and withdraw money without a person.
Banks even let customers scan a check image to deposit (called remote deposit capture [2]), so tellers don’t have to count every check by hand. Industry reports back this up: a recent survey found many banks already save a lot of money by automating front-office tasks [3]. At the same time, some teller duties stay human.
The BLS notes that tellers still “answer questions from customers about their accounts” and handle special items (like foreign currency or savings bonds) [1]. In practice, banks use software to count and balance cash drawers, but rely on people to greet customers, explain products in person, and solve tricky problems. In short, basic data-entry and counting tasks are largely done by machines, while human tellers focus on service, advice, and complicated transactions.

Banks have clear reasons to use more AI: it can cut costs and serve tech-savvy customers. For example, one report found over half of banks expect big savings from automating customer-facing work [3], and financial news notes that banks are closing many branches as customers move online [4]. Cheaper labor and competition from fintech push banks to try AI and self-service tools.
At the same time, banking is a highly regulated, trust‐sensitive industry. Customers often want a real person for important money decisions, and regulators demand accuracy. For these reasons, banks usually start AI on simple tasks (like fraud alerts or answering routine questions) and keep humans for the rest.
In fact, experts long ago noted that “Bank Teller” is a job that can be automated [3], but that mainly means tellers may shift to higher‐touch work. Overall, banks move carefully: AI can improve efficiency, but personal skills – friendliness, clear explanations and building trust – remain very important. This means tellers may spend less time crunching numbers and more time helping people.

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They assist customers at banks by handling deposits, withdrawals, and answering questions about their accounts.
Median Wage
$39,340
Jobs (2024)
347,400
Growth (2024-34)
-12.9%
Annual Openings
29,800
Education
High school diploma or equivalent
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
AI-generated estimates of task resilience over the next 3 years
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.
Resolve problems or discrepancies concerning customers' accounts.
Order a supply of cash to meet daily needs.
Perform clerical tasks, such as typing, filing, and microfilm photography.
Cash checks and pay out money after verifying that signatures are correct, that written and numerical amounts agree, and that accounts have sufficient funds.
Obtain and process information required for the provision of services, such as opening accounts, savings plans, and purchasing bonds.
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.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.

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