Will AI replace Locker Room, Coatroom, and Dressing Room Attendants?
Estimated risk score: 14 out of 100
Very low replacement risk
Estimate from published task research, not reviewed by a person · how we estimate
Within about 19 points for 4 in 5 of the jobs we checked (0 to 33).
For the occupation as a whole, from ratings of its 23 O*NET tasks published in 2023 and calibrated to our hand scores. A specialty inside it can sit higher or lower.
O*NET-SOC 39-3093.00 · Personal Care and Service
Tasks rated in 2023 as ones AI could do or speed up
Tasks a GPT-4-class model could do, or do in half the time or less: 1 of its 23 rated tasks. In O*NET’s words.
- Answer customer inquiries or explain cost, availability, policies, and procedures of facilities.
Tasks rated in 2023 as not sped up by AI
Tasks such a model was rated as not speeding up or taking over: 22 of its 23 rated tasks; the first 6 are shown. In O*NET’s words.
- Assign dressing room facilities, locker space, or clothing containers to patrons of athletic or bathing establishments.
- Clean facilities such as floors or locker rooms.
- Maintain a lost-and-found collection.
- Monitor patrons' facility use to ensure that rules and regulations are followed, and safety and order are maintained.
- Provide towels and sheets to clients in public baths, steam rooms, and restrooms.
- Check supplies to ensure adequate availability, and order new supplies when necessary.
What the job is
Provide personal items to patrons or customers in locker rooms, dressing rooms, or coatrooms.
Also called: Spa Attendant, Locker Room Attendant, Athletic Equipment Manager, Ladies Locker Room Attendant, Doorkeeper, Hat Checker, Shoe Shiner, Club Steward.
Source. This site includes information from the O*NET 30.1 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license. O*NET® is a trademark of USDOL/ETA. USDOL/ETA has not approved, endorsed, or tested these modifications. (O*NET, CC BY 4.0.) Task ratings: Eloundou, Manning, Mishkin and Rock (2023), “GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models”, data used under the MIT licence (licence texts). Our change: we averaged the ratings over this occupation’s tasks and calibrated them to our 0–100 scale. It is not a prediction about any one person and not career advice. Disagree? Write to hello@yourstopwashit.com. How we estimate