Share and intensity of work current AI systems can materially affect.
SOC 43-3071
Tellers AI displacement risk
Routine transactions left for apps and ATMs years ago, and AI assistants now absorb the service questions that justified remaining branch staff. Banks are converting teller lines into advisory roles, so the realistic path is upward into banker, lending, or operations tracks rather than defending the window.
Likely potential for exposed tasks to move to software after workflow integration.
Branches retain tellers for cash-intensive businesses, older customers, and trust-sensitive moments like fraud. Decline is steady rather than sudden, which leaves time to transition deliberately.
Distribution
Where Tellers sits across 620 tracked roles
Displacement pressure 76 — higher than 96% of the 620 occupations tracked on displacement.ai.
Score version
This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-06-12. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.
28 O*NET task statements matched to SOC 43-3071. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $43,030 (May 2025, US national). The latest BLS row matched SOC 43-3071.
Scores are planning signals, not forecasts. Local hiring demand, employer-specific workflows, licensing, and credentials must be validated before making career decisions.
2030 economic stress test
How Anthropic's scenarios classify Tellers
SOC 43-3071 places this role in the paper's cognitive occupation group. These group-level outcomes do not change the 76/100 role score and are not an occupation forecast.
+0.4% group wage
-0.5% cognitive employment since mid-2026; 2.9% cognitive unemployment.
Economy-wide: +1.6% GDP and 3.9% unemployment.
-0.3% group wage
-3.9% cognitive employment since mid-2026; 4.5% cognitive unemployment.
Economy-wide: +8.3% GDP and 4.6% unemployment.
-11.5% group wage
-21.5% cognitive employment since mid-2026; 17.9% cognitive unemployment.
Economy-wide: +32.4% GDP and 11.9% unemployment.
Compare the assumptions and limitations across all three scenarios. Source: The Anthropic Institute Working Paper No. 2026-02.
Official task evidence
O*NET task matches for Tellers
The current evidence import matched 28 task statements from Task Statements 31.0 (August 2026). These rows are used as a grounding layer for judging which parts of the occupation are repeatable, language-heavy, analytical, social, physical, or compliance-sensitive.
Dataset31.0 (August 2026)
Matched tasks28
SOC43-3071
- Core task / ID 2549
Balance currency, coin, and checks in cash drawers at ends of shifts and calculate daily transactions, using computers, calculators, or adding machines.
- Core task / ID 2551
Receive checks and cash for deposit, verify amounts, and check accuracy of deposit slips.
- Core task / ID 2563
Monitor bank vaults to ensure cash balances are correct.
- Core task / ID 2550
Cash checks and pay out money after verifying that signatures are correct, that written and numerical amounts agree, and that accounts have sufficient funds.
- Core task / ID 2554
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.
- Core task / ID 2553
Enter customers' transactions into computers to record transactions and issue computer-generated receipts.
Source: O*NET Resource Center, Task Statements. Raw import target: data/raw/onet/task-statements-31-0.txt.
Task profile
Where AI changes the work
Process deposits and withdrawals
Exposure 92, automation 80%, augmentation 14%.
O*NET evidence: Process transactions, such as term deposits, retirement savings plan contributions, aut... (ID 2558)
Answer account service questions
Exposure 78, automation 58%, augmentation 36%.
O*NET evidence: Answer telephones and assist customers with their questions. (ID 21076)
Spot fraud and verify identity
Exposure 50, automation 26%, augmentation 60%.
Refer customers to banking products
Exposure 42, automation 16%, augmentation 56%.
O*NET evidence: Carry out special services for customers, such as ordering bank cards and checks. (ID 2569)
TaskExposureAutomationAugmentation
Process deposits and withdrawals9280%14%
Answer account service questions7858%36%
Spot fraud and verify identity5026%60%
Refer customers to banking products4216%56%
Transition pathways
Adjacent moves that preserve existing skills
role redesign
HighUniversal Banker
Training horizon: 2-4 months. Skill overlap 80. Wage preservation signal 100.
- Cross-train on account opening and lending intake
- Earn an internal banker certification
- Practice needs-based conversations
adjacent role
HighLoan Processing Specialist
Training horizon: 3-6 months. Skill overlap 66. Wage preservation signal 100.
- Learn loan documentation requirements
- Shadow a processor through five files
- Build accuracy and compliance habits
Comparison guides
Compare the next move before you commit
2-4 months
Tellers to Universal Banker
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Tellers into Universal Banker.
3-6 months
Tellers to Loan Processing Specialist
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Tellers into Loan Processing Specialist.
What the AI risk score means for Tellers
The displacement pressure score for Tellers is 76. That score blends task exposure, automation pressure, augmentation potential, wage vulnerability, transition feasibility, and source confidence. It is designed to help workers and workforce teams decide where to act first, not to claim a specific date when a job will disappear.
For this role, the clearest risk pattern is visible at the task level. Process deposits and withdrawals carries 80% automation pressure, while Spot fraud and verify identity carries 60% augmentation potential. That means the best response is usually a targeted redesign of work: move away from repeatable production tasks and toward judgment, exception handling, coordination, stakeholder context, and accountable use of AI tools.
Labor-market context and wage risk
Median wage: $43,030 (May 2025, US national). Employment context: Long-declining branch workforce as transactions move digital. Typical education: High school diploma; on-the-job training.
Wage vulnerability is 80, while transition feasibility is 66. A high wage-vulnerability score means workers should pay close attention to salary preservation before making a move. A high transition-feasibility score means there are adjacent paths that can reuse existing skills without requiring a complete career reset.
- Teller employment in long-run decline
- Universal-banker conversions accelerating
- Branch networks still shrinking
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Tellers, the strongest near-term skill priorities are listed below. These are useful whether the goal is to stay in the role, move to a redesigned version of the role, or transition into an adjacent occupation.
Customer needs assessment
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Fraud and verification vigilance
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Banking product knowledge
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Digital banking support
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
90-day transition plan
The most practical next step is not to wait for a layoff or a full role redesign. Use the next 90 days to create evidence that you can operate in a safer, more AI-augmented version of the work.
- In the first 30 days, document the repetitive tasks in your current work and identify where AI can reduce drafting, lookup, classification, or reporting time.
- By 60 days, complete one small project connected to Universal Banker, such as cross-train on account opening and lending intake.
- By 90 days, compare internal openings and external postings for Universal Banker or Loan Processing Specialist and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Tellers
Will AI replace Tellers?
Routine transactions left for apps and ATMs years ago, and AI assistants now absorb the service questions that justified remaining branch staff. Banks are converting teller lines into advisory roles, so the realistic path is upward into banker, lending, or operations tracks rather than defending the window. The better planning signal is not full replacement, but which tasks become automated, which tasks become AI-assisted, and which responsibilities still need human judgment.
Which parts of Tellers work are most exposed to AI?
Process deposits and withdrawals and Answer account service questions show the strongest automation pressure in this model. Spot fraud and verify identity and Refer customers to banking products are better treated as AI-augmented work.
What should Tellers learn next?
Start with Customer needs assessment, Fraud and verification vigilance, Banking product knowledge. The most practical adjacent paths in this model are Universal Banker and Loan Processing Specialist.
How should this score be used?
Use it as a planning signal, not a prediction. Confirm local hiring demand, wages, licensing, credentials, and employer adoption before making a career move.
Sources
Evidence trail
World Economic Forum / 7 January 2025The Future of Jobs Report 2025International Labour Organization / 20 May 2025Generative AI and Jobs: A Refined Global Index of Occupational ExposureO*NET Resource Center / Database 31.0 (August 2026)Occupation, Task, Skill, and Work-Activity DataUS Bureau of Labor Statistics / May 2025 estimates (released 15 May 2026)Occupational Employment and Wage Statistics