Locker Room, Coatroom, and Dressing Room Attendants
In short: today's best AI models could do about 3% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about the same by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 97% of the time, stays with people.
Provide personal items to patrons or customers in locker rooms, dressing rooms, or coatrooms.
15,560 people do this job in the US. $36,300 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on1 h
- A person checks AI's work0 h
- Desk work AI can't do yet0 h
- Stays with people39 h
Locker Room, Coatroom, and Dressing Room Attendants, now: of a 40-hour week, AI could take on 1 hours, 0 hours become checking its work, 0 hours are desk work it can't do yet, and 39 hours stay with people.
The largest pieces: Answer customer inquiries or explain cost, availability, policies, and procedures of facilities (under an hour); Refer guest problems or complaints to supervisors (under an hour); Assign dressing room facilities, locker space, or clothing containers to patrons of athletic or bathing establishments (under an hour).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 3%
- 0%
- 97%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 2%. With Claude Mythos Preview (early), measured in April 2026, 3%. Today's estimate: 3%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, 0.59% went to this job's tasks in May 2026, the 44th largest of the 447 jobs that showed up at all; 1 of its 24 tasks showed up. Within each of Anthropic's methods, never across a change: 0.033% to 0.016% (released February and March 2025); 0.012% to 0.0092% (August 2025 to February 2026); 0.6% to 0.59% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.033% | 348 of 708 | 2 of 24 |
| Released March 2025 | 0.016% | 452 of 703 | 1 of 24 |
| The week of Aug 4, 2025 (released September 2025) | 0.012% | 443 of 655 | 1 of 24 |
| The week of Nov 13, 2025 (released January 2026) | 0.0058% | 559 of 672 | 2 of 24 |
| The week of Feb 5, 2026 (released March 2026) | 0.0092% | 509 of 677 | 1 of 24 |
| April 2026 (released June 2026) | 0.6% | 41 of 434 | 1 of 24 |
| May 2026 (released June 2026) | 0.59% | 44 of 447 | 1 of 24 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates 71% of this job's working time as physical work. For 68% of the working time, a robot has been shown doing most of the task somewhere: 46% in a purpose-built cell, 22% in a structured facility. 0.90 of 3, the 179th highest of the 923 jobs.
- Not physical 29%
- No robot shown 3%
- In a purpose-built cell 46%
- In a structured facility 22%
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
The tasks
Sorted by . 24 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Clean facilities such as floors or locker rooms.Done daily by most who do it. Robots: in a structured facility, Pudu CC1 (deployed by Robot Industries at GymOne fitness chain) (deployed). Anthropic's rating. | 16% | 38 min13 min to 1.7 h | Stays with people | |
| Attend to needs of athletic teams in clubhouses.Done daily by most who do it.Robots: in a purpose-built cell, Chicago Dryer Genesis Automatic Towel Machine (ATM) with Air Chicago folders (sold). Anthropic's rating. | 8% | 50 min25 min to 2.5 h | Stays with people | |
| Operate washing machines and dryers to clean soiled apparel and towels.Done several times a day by most who do it.Robots: in a purpose-built cell, Kannegiesser PowerTrans batch washer / SmartLaundry automated linen flow (monorail bag storage, press, lift shuttle, dryer) (Herbert Kannegiesser GmbH) (sold). Anthropic's rating. | 8% | 33 min17 min to 1.1 h | Stays with people | |
| Collect soiled linen or clothing for laundering.Done daily by most who do it. Robots: in a purpose-built cell, Inwatec THOR robot separator (sold). Anthropic's rating. | 8% | 17 min8 min to 38 min | Stays with people | |
| Monitor patrons' facility use to ensure that rules and regulations are followed, and safety and order are maintained.Done daily by most who do it. | 8% | 25 min13 min to 50 min | Stays with people | |
| Maintain inventories of clothing or uniforms, accessories, equipment, or linens.Done daily by most who do it. Robots: in a purpose-built cell, Towel Tracker (deployed). Anthropic's rating. | 8% | 38 min17 min to 1.7 h | Stays with people | |
| Provide towels and sheets to clients in public baths, steam rooms, and restrooms.Done hourly or more by most who do it. Robots: in a purpose-built cell, Figure 02 with Helix VLA (demonstrated). Anthropic's rating. | 7% | 13 min4 min to 25 min | Stays with people | |
| Check supplies to ensure adequate availability, and order new supplies when necessary.Done daily by most who do it. Robots: in a structured facility, Tally (Simbe Robotics) (deployed). Anthropic's rating. | 7% | 25 min13 min to 50 min | Stays with people | |
| Maintain a lost-and-found collection.Done daily by most who do it. Robots: in a purpose-built cell, Amazon Robotics Pick workcell (deployed). Anthropic's rating. | 4% | 25 min8 min to 1.3 h | Stays with people | |
| Clean and polish footwear, using brushes, sponges, cleaning fluid, polishes, waxes, liquid or sole dressing, and daubers.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 4% | 13 min8 min to 25 min | Stays with people | |
| Procure beverages, food, and other items as requested.Done daily by most who do it.Robots: in a structured facility, Relay / Relay2 (Savioke / Relay Robotics) (deployed). Anthropic's rating. | 3% | 17 min8 min to 33 min | Stays with people | |
| Maintain or repair athletic equipment.Done more than monthly by most who do it. | 3% | 38 min8 min to 1.7 h | Stays with people |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Locker Room, Coatroom, and Dressing Room Attendants is within reach of AI now?
- An estimated 3% of the working time is within reach of AI models now and 3% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Locker Room, Coatroom, and Dressing Room Attendants come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Answer customer inquiries or explain cost, availability, policies, and procedures of facilities (100% of the task's time now); Refer guest problems or complaints to supervisors (100% of the task's time now); and Assign dressing room facilities, locker space, or clothing containers to patrons of athletic or bathing establishments (100% of the task's time now).
- Which tasks of Locker Room, Coatroom, and Dressing Room Attendants stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Clean facilities such as floors or locker rooms; Attend to needs of athletic teams in clubhouses; and Operate washing machines and dryers to clean soiled apparel and towels. Together such tasks are about 97% of the working time.
- Do people already use AI for the work of Locker Room, Coatroom, and Dressing Room Attendants?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.59% went to this job's tasks, the 44th largest share of the 447 jobs that showed up; 1 of its 24 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 0%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Locker Room, Coatroom, and Dressing Room Attendants?
- Anthropic's robot exposure rating (September 2026) finds 71% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 68% of the working time, 22% in a structured facility. Its index is 0.90 of 3. One example: Pudu CC1 (deployed by Robot Industries at GymOne fitness chain) for "clean facilities such as floors or locker rooms". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 24 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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