First-Line Supervisors of Housekeeping and Janitorial Workers
In short: today's best AI models could do about 43% 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 conversations, in-person and hands-on work, about 57% of the time, stays with people.
Directly supervise and coordinate work activities of cleaning personnel in hotels, hospitals, offices, and other establishments.
178,760 people do this job in the US. $49,100 a year.
Reviewed on September 30, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on4 h
- A person checks AI's work13 h
- Desk work AI can't do yet0 h
- Stays with people23 h
First-Line Supervisors of Housekeeping and Janitorial Workers, now: of a 40-hour week, AI could take on 4 hours, 13 hours become checking its work, 0 hours are desk work it can't do yet, and 23 hours stay with people.
The largest pieces: Establish department standards (about 4 h, a person checks); Forecast staffing and stock (about 3 h, a person checks); Prepare activity and personnel reports (about 2 h).
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.
- 35%
- 8%
- 10%
- 24%
- 23%
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.
What handing it over would take, now
The 43% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
is conversation short enough by length. This site leaves conversation with people, so it is not in the total.
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, 1%. With Claude Mythos Preview (early), measured in April 2026, 24%. Today's estimate: 43%.
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, 0.095% went to this job's tasks in May 2026, the 169th largest of the 447 jobs that showed up at all; 1 of its 26 tasks showed up. Within each of Anthropic's methods, never across a change: 0.057% to 0.074% (released February and March 2025); 0.083% to 0.11% (August 2025 to February 2026); 0.1% to 0.095% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.057% | 252 of 708 | 7 of 26 |
| Released March 2025 | 0.074% | 202 of 703 | 5 of 26 |
| The week of Aug 4, 2025 (released September 2025) | 0.083% | 175 of 655 | 4 of 26 |
| The week of Nov 13, 2025 (released January 2026) | 0.092% | 164 of 672 | 7 of 26 |
| The week of Feb 5, 2026 (released March 2026) | 0.11% | 149 of 677 | 5 of 26 |
| April 2026 (released June 2026) | 0.1% | 162 of 434 | 1 of 26 |
| May 2026 (released June 2026) | 0.095% | 169 of 447 | 1 of 26 |
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 49% of this job's working time as physical work. For 8% of the working time, a robot has been shown doing most of the task somewhere: 6% in a purpose-built cell, 2% in a structured facility. 0.11 of 3, the 510th highest of the 923 jobs.
- Not physical 51%
- No robot shown 41%
- In a purpose-built cell 6%
- In a structured facility 2%
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.
What changes for the people in this job
From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.
What stays with people
56% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Establish department standards, the in-person work, 6%
- Inspect facilities to plan work, the hands-on work, 6%
- Inspect cleaning work, the hands-on work, 5%
- Help with cleaning, the hands-on work, 5%
- Direct infection control, the in-person work, 4%
- Supervise laundry and other services, the in-person work, 4%
What becomes checking the machine
32% of the working time: desk work a model could do by then, in tasks where a mistake costs something or a licensed person signs. A person checks it. Another 11% is desk work that is small if wrong, which can be handed over with lighter checks.
- Establish department standards, costly if wrong, 9%
- Forecast staffing and stock, costly if wrong, 7%
- Direct infection control, severe if wrong, 3%
- Select and order equipment and supplies, costly if wrong, 2%
- Arrange repairs and renovations, costly if wrong, 2%
- Estimate costs and manage budgets, costly if wrong, 2%
What to learn
- Reviewing work you did not do yourself. The tasks under What becomes checking the machine, where a mistake costs something, stay a person's to check: spotting what a draft gets wrong is a skill of its own.
- Briefing a model and checking its drafts. About 35% of the time is documents and data, the part models reach first: writing a clear brief, giving the right material, and checking what comes back.
- The conversations. About 33% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
- The hands-on craft. About 23% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- Judgment where errors are severe. Some tasks are severe if wrong. Knowing when not to trust an output matters more there than speed.
Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).
The tasks
Sorted by . 26 tasks from .
| Task | ||||
|---|---|---|---|---|
| Establish and implement operational standards and procedures for the departments supervised.Standards and procedures written, then put in place with the crew.Done daily by most who do it. | 15% | 3.3 h1.7 h to 6.7 h | Documents 60%, in person 40% | 60%Desk part half by now |
| Direct activities for stopping the spread of infections in facilities, such as hospitals.Directing the crew on site, with the procedures on paper.Done daily by most who do it. | 7% | 1.7 h25 min to 3.3 h | In person 60%, documents 40% | 39%Desk part half by now |
| Forecast necessary levels of staffing and stock at different times to facilitate effective scheduling and ordering.Working out staffing and stock levels on paper.Done daily by most who do it. | 7% | 1.7 h50 min to 3.3 h | Documents 100% | 100%Half by now |
| Recommend or arrange for additional services, such as painting, repair work, renovations, and the replacement of furnishings and equipment.Calls to contractors, with the requests written up.Done daily by most who do it. | 6% | 1.7 h25 min to 3.3 h | Conversation 60%, documents 40% | 39%Desk part half by now |
| Prepare reports on activity, personnel, and information, such as occupancy, hours worked, facility usage, work performed, and departmental expenses.Reports written from the hours, occupancy and expense figures.Done daily by most who do it. | 6% | 1.7 h25 min to 3.3 h | Documents 60%, systems 40% | 99%Half by now |
| Inspect and evaluate the physical condition of facilities to determine the type of work required.Walking the building to see what work it needs.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 6% | 1.3 h25 min to 2.5 h | Hands-on 100% | Stays with people |
| Supervise in-house services, such as laundries, maintenance and repair, dry cleaning, or valet services.Leading the crews on site, with the planning behind it.Done daily by most who do it. | 5% | 50 min25 min to 2.5 h | In person 70%, documents 30% | 30%Desk part half by now |
| Inspect work performed to ensure that it meets specifications and established standards.Walking the rooms and areas to check the work.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 5% | 38 min13 min to 2.5 h | Hands-on 100% | Stays with people |
| Perform or assist with cleaning duties as necessary.Cleaning by hand when needed.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 5% | 50 min25 min to 1.7 h | Hands-on 100% | Stays with people |
| Recommend changes that could improve service and increase operational efficiency.Written recommendations, with conversations about them.Done more than monthly by most who do it. AI observed on this task. | 4% | 1.3 h25 min to 2.5 h | Documents 70%, conversation 30% | 70%Desk part half by now |
| Instruct staff in work policies and procedures, and the use and maintenance of equipment.Showing the crew the procedures and the equipment.Done daily by most who do it. | 4% | 1.3 h25 min to 2.5 h | In person 100% | Stays with people |
| Coordinate activities with other departments to ensure that services are provided in an efficient and timely manner.Calls and radio with the front desk, maintenance and the other departments.Done daily by most who do it. | 3% | 38 min13 min to 1.7 h | Conversation 100% | 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. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% 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.
- First-Line Supervisors of Office and Administrative Support Workers54% now, 58% by 2028
- First-Line Supervisors of Mechanics, Installers, and Repairers47% now, 57% by 2028
- First-Line Supervisors of Entertainment and Recreation Workers, Except Gambling Services27% now, 28% by 2028
- First-Line Supervisors of Production and Operating Workers48% now, 54% by 2028
- First-Line Supervisors of Personal Service Workers31% now, 32% by 2028
- First-Line Supervisors of Food Preparation and Serving Workers48% now, 48% by 2028
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 First-Line Supervisors of Housekeeping and Janitorial Workers is within reach of AI now?
- An estimated 43% of the working time is within reach of AI models now and 44% 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 First-Line Supervisors of Housekeeping and Janitorial Workers 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: Establish department standards (60% of the task's time now); Forecast staffing and stock (100% of the task's time now); and Prepare activity and personnel reports (99% of the task's time now).
- Which tasks of First-Line Supervisors of Housekeeping and Janitorial Workers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Inspect facilities to plan work; Inspect cleaning work; and Help with cleaning. Together such tasks are about 32% of the working time, and the people and body parts of the other tasks stay with people too.
- What should First-Line Supervisors of Housekeeping and Janitorial Workers learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are reviewing work you did not do yourself; briefing a model and checking its drafts; and the conversations. By the end of 2028 on the long-run pace at four in five, about 56% of the working time stays with people, 32% becomes checking a model's work and 11% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
- Do people already use AI for the work of First-Line Supervisors of Housekeeping and Janitorial Workers?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.095% went to this job's tasks, the 169th largest share of the 447 jobs that showed up; 1 of its 26 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 4%. 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 First-Line Supervisors of Housekeeping and Janitorial Workers?
- Anthropic's robot exposure rating (September 2026) finds 49% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 8% of the working time, 2% in a structured facility. Its index is 0.11 of 3. One example: Scythe Robotics M.52 for "do grounds maintenance". 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 26 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on September 30, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), 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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