66
/100

SOC 39-3031

Ushers, Lobby Attendants, and Ticket Takers

High RiskFrey/Osborne: 96.0%

Risk Score

โš ๏ธ

66/100

High Risk

US Employment

๐Ÿ‘ฅ

119,210

Total workers

Median Wage

๐Ÿ’ฐ

$31K

$23K โ€“ $40K

Projected Growth

๐Ÿ“ˆ

+1.2%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

61/100

High exposure

How we calculate these numbers โ†’

๐Ÿ’ก Ushers, Lobby Attendants, and Ticket Takers face a risk score of 66/100 โ€” 22 points above the national average of 44. With 61/100 GenAI exposure, this occupation faces significant pressure from AI tools despite strong projected growth. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $31K. The 3 recommended career transitions all maintain competitive wages while reducing automation exposure. Explore transition paths โ†’

๐Ÿ” AI Impact Analysis

With a risk score of 66/100, Ushers, Lobby Attendants, and Ticket Takers faces moderate automation pressure. While tasks like large language model automation of analysis tasks are increasingly handled by AI, the role retains significant human elements. The 119,210 workers in this occupation should focus on strengthening skills in adapting techniques to individual body types and preferences and emotional support and active listening during sessions to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Ushers, Lobby Attendants, and Ticket Takers?

Read our full analysis with verdict, risk factors, safe tasks, and career transition paths โ†’

โš ๏ธ Top Risk Factors

1

Large language model automation of analysis tasks

2

Automated booking and client management platforms

3

Virtual try-on technology reducing in-person consultations

4

AI-powered research and literature review tools

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Adapting techniques to individual body types and preferences

โœ“

Emotional support and active listening during sessions

โœ“

Creative aesthetic judgment for individual clients

๐Ÿ“Š Task Automation Breakdown

Based on O*NET task analysis and GenAI exposure scoring. Shows the estimated proportion of this occupation's core tasks that are automatable by current AI, augmented by AI tools, or require essential human skills.

๐Ÿ“‹ O*NET Task Profile

โ€ข

Greet patrons attending entertainment events.

โ€ข

Sell or collect admission tickets, passes, or facility memberships from patrons at entertainment events.

โ€ข

Clean facilities.

โ€ข

Settle seating disputes or help solve other customer concerns.

โ€ข

Examine tickets or passes to verify authenticity, using criteria such as color or date issued.

๐Ÿ’ป Technology Skills

โ€ข

Spreadsheet software

โ€ข

Office suite software

โ€ข

Electronic mail software

โ€ข

Presentation software

โ€ข

Operating system software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Customer and Personal Service

โ€ข

English Language

โ€ข

Public Safety and Security

โ€ข

Communications and Media

โ€ข

Sales and Marketing

๐Ÿ“Š vs National Average

Median Wage$31K
$-15K

National avg: $46K

Risk Score66/100
+22

National avg: 44/100

GenAI Exposure61/100
+23

National avg: 38/100

Projected Growth1.2%
-2.5%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
Tour and Travel Guides27$37K78%
Concierges29$37K74%
Social Workers, All Other22$69K53%