Cashiers

O*NET-SOC code: 41-2011.00

Receive and disburse money in establishments other than financial institutions. May use electronic scanners, cash registers, or related equipment. May process credit or debit card transactions and validate checks.

AI exposure

Data source: BLSPublished: 2026-08
High· relative
LowFour relative bandsVery high
Group-level value
Scale, basis and source
Four relative bands (Low / Moderate / High / Very high)
831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band
Source dataset (XLSX download)
Data source: AnthropicPublished: 2026-03
0.085
0.000Range of values carried here0.745
Scale, basis and source
Observed exposure index, 0–1 as published
Mapped onto O*NET tasks
Published per SOC 2018 occupation; every O*NET occupation with the same SOC 2018 code carries this value
Source dataset (CSV download)
Data source: ILOPublished: 2025
0.39
0.09Range of values carried here0.70
Group-level value
Scale, basis and source
Generative AI exposure index, 0–1 as published
Published per ISCO-08 unit group. Linked to this occupation, wholly or in part, by applying U.S. Bureau of Labor Statistics crosswalks (ISCO-08 to 2010 SOC, 2010 SOC to 2018 SOC) as published
Source dataset (PDF download)

What kind of figure this source publishes

The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.

AI exposure (OpenAI rubric)

29 rated tasks · 9 tasks with β ≥ 0.5 (31.0%)

β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.

Source unit: O*NET 27.2 tasks → O*NET 31.0 occupation code
1 rated task is not in the O*NET 31.0 task list; its score is kept as published for O*NET 27.2.

Source: OpenAI "GPTs are GPTs" exposure rubric
Release: gh-main-0471612
License: MIT License, Copyright (c) 2024 OpenAI

Tasks

Task statements from the O*NET® 31.0 Database, core tasks first.

Task	Type	β (OpenAI)
Receive payment by cash, check, credit cards, vouchers, or automatic debits.	Core	0
Issue receipts, refunds, credits, or change due to customers.	Core	0
Greet customers entering establishments.	Core	0
Establish or identify prices of goods, services, or admission, and tabulate bills, using calculators, cash registers, or optical price scanners.	Core	0
Answer customers' questions, and provide information on procedures or policies.	Core	0.5
Process merchandise returns and exchanges.	Core	0.5
Request information or assistance, using paging systems.	Core	0
Monitor checkout stations to ensure they have adequate cash available and are staffed appropriately.	Core	0
Assist customers by providing information and resolving their complaints.	Core	0.5
Maintain clean and orderly checkout areas, and complete other general cleaning duties, such as mopping floors and emptying trash cans.	Core	0
Help customers find the location of products.	Core	0
Answer incoming phone calls.	Core	1
Count money in cash drawers at the beginning of shifts to ensure that amounts are correct and that there is adequate change.	Supplemental	0
Issue trading stamps, and redeem food stamps and coupons.	Supplemental	0
Cash checks for customers.	Supplemental	0
Weigh items sold by weight to determine prices.	Supplemental	0
Calculate total payments received during a time period, and reconcile this with total sales.	Supplemental	1
Compute and record totals of transactions.	Supplemental	1
Sell tickets and other items to customers.	Supplemental	0
Keep periodic balance sheets of amounts and numbers of transactions.	Supplemental	1
Bag, box, wrap, or gift-wrap merchandise, and prepare packages for shipment.	Supplemental	0
Sort, count, and wrap currency and coins.	Supplemental	0
Compile and maintain non-monetary reports and records.	Supplemental	1
Post charges against guests' or patients' accounts.	Supplemental	0.5
Offer customers carry-out service at the completion of transactions.	Supplemental	0
Assist with duties in other areas of the store, such as monitoring fitting rooms or bagging and carrying out customers' items.	Supplemental	0
Supervise others and provide on-the-job training.	Supplemental	0
Stock shelves, sort and reshelve returned items, and mark prices on items and shelves.	Supplemental	0

Occupation information

Korea classification links (KSCO)

Links from the current release of the Korea Occupation Direct Crosswalk v1.1. Relation values are read from the O*NET-SOC occupation side.

KSCO code	KSCO title	Relation	Status
52133	입장권 판매원	onet_broader	confirmed
52139	그 외 매표원 및 복권 판매원	onet_broader	confirmed
52141	매장 계산원	onet_broader	confirmed
52142	요금 정산원	onet_broader	confirmed

Relation and status definitions(kr-direct v1.1)

Sources and attribution

This page includes information from the O*NET® 31.0 Database (https://www.onetcenter.org/database.html) by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). O*NET® is a trademark of USDOL/ETA. AI Changing Work has modified all or some of this information: the O*NET-SOC code, title and task statements are reproduced in English without change; task-type labels are shown in the page's language and tasks are listed core first; any Korean occupation title shown on the Korean-language page is AI Changing Work's translation; any KSCO-8 unit groups linked to this occupation were paired with it by AI Changing Work's judgment, and the relation labels and statuses are AI Changing Work's additions. USDOL/ETA has not approved, endorsed, or tested these modifications.

Any AI exposure figures on this page are published by third parties, not by AI Changing Work, and none is part of the O*NET information. OpenAI publishes task-level scores (MIT License) for O*NET 27.2 task statements; each is shown next to the O*NET 31.0 task statement with the same task ID, whose wording can differ from the 27.2 statement that was scored. OpenAI also publishes occupation-level scores for O*NET-SOC codes in the same release, and any such score is shown on the O*NET occupation with the same code. Anthropic publishes an observed exposure index in the Anthropic Economic Index (CC-BY), and the U.S. Bureau of Labor Statistics publishes relative AI exposure categories (public domain); both are published per SOC code, and each value is shown on every O*NET occupation with that code. The International Labour Organization publishes a generative AI exposure index in ILO Working Paper 140 (CC BY 4.0) for ISCO-08 unit groups; AI Changing Work links those groups to O*NET occupations by applying the U.S. Bureau of Labor Statistics ISCO-08 to 2010 SOC and 2010 SOC to 2018 SOC crosswalks as published, without case-by-case selection, and these crosswalks match many groups only in part. Where several unit groups are linked, each group's published value is listed, and any summary shows only the lowest and highest of those values with the number of groups; no exposure figure is averaged or recalculated. Any employment figures are published by the U.S. Bureau of Labor Statistics for the SOC group containing this occupation. Each source is credited where its figures are shown.

O*NET OnLine: 41-2011.00 Cashiers

KSCO 코드·명칭: 한국표준직업분류(제8차 개정) — 통계청 고시 제2024-328호 (2024-07-01 고시, 2025-01-01 시행). 저작권법 제7조 제2호의 고시 항목이다. 명칭 표기(가운뎃점·띄어쓰기)는 해설서 2차 정오 반영판의 표기를 따랐으며, 고시 항목표와는 18개 명칭에서 가운뎃점 글리프나 띄어쓰기만 다르다. 통계청은 2025년 10월 국가데이터처로 개편되었다. 이 페이지의 KSCO 연결은 통계청·국가데이터처의 공식 연계표가 아니다.

Full attribution and licenses