Ushers, Lobby Attendants, and Ticket Takers

Personal Care and Service Occupations
O*NET-SOC code
39-3031.00

Assist patrons at entertainment events by performing duties, such as collecting admission tickets and passes from patrons, assisting in finding seats, searching for lost articles, and helping patrons locate such facilities as restrooms and telephones.

AI exposure

  • Data source: BLSPublished: 2026-08

    Moderate· 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

    0.000

    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

    0.29

    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)

23 rated tasks · 4 tasks with β ≥ 0.5 (17.4%)

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
  • All rated tasks are in the O*NET 31.0 task list.
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.

TaskTypeβ (OpenAI)
Greet patrons attending entertainment events.Core0
Examine tickets or passes to verify authenticity, using criteria such as color or date issued.Core0.5
Guide patrons to exits or provide other instructions or assistance in case of emergency.Core0
Maintain order and ensure adherence to safety rules.Core0
Provide assistance with patrons' special needs, such as helping those with wheelchairs.Core0
Refuse admittance to undesirable persons or persons without tickets or passes.Core0
Settle seating disputes or help solve other customer concerns.Core0
Search for lost articles or for parents of lost children.Core0
Sell or collect admission tickets, passes, or facility memberships from patrons at entertainment events.Core0
Clean facilities.Core0
Assist patrons by giving directions to points in or outside of the facility or providing information about local attractions.Core1
Assist patrons in finding seats, lighting the way with flashlights, if necessary.Supplemental0
Count and record number of tickets collected.Supplemental0
Operate refreshment stands during intermission or obtain refreshments for press box patrons during performances.Supplemental0
Verify credentials of patrons desiring entrance into press box and permit only authorized persons to enter.Supplemental0
Distribute programs to patrons.Supplemental0
Work with others to change advertising displays.Supplemental0
Manage inventory or sale of artist merchandise.Supplemental1
Give door checks to patrons who are temporarily leaving establishments.Supplemental0
Manage informational kiosks or displays of event signs or posters.Supplemental0
Page individuals wanted at the box office.Supplemental0
Lead tours and answer visitors' questions about the exhibits.Supplemental0
Schedule or manage staff, such as volunteer usher corps.Supplemental1

Occupation information

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: 39-3031.00 Ushers, Lobby Attendants, and Ticket Takers

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