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Service and sales workers · code 5151

Cleaning and housekeeping supervisors in offices, hotels and other establishments

Software can track the linen. Running a housekeeping team is still a people job.

Buying and keeping track of supplies are mostly out of AI's reach. It barely touches five of the eight tasks, including cleaning kitchens, floors and furniture.

What they actually do (and what else they get called)

Cleaning and housekeeping supervisors in offices, hotels and other establishments organize, supervise and carry out housekeeping functions in order to keep clean and tidy the interiors, fixtures and facilities in these establishments. Tasks include - (a) engaging, training, discharging, organizing and supervising helpers, cleaners and other housekeeping staff; (b) purchasing or controlling the purchase of supplies; (c) controlling storage and issue of supplies; (d) supervising general welfare and conduct of individuals in institutions; (e) sweeping or vacuum-cleaning, washing and polishing floors, furniture and other fixtures; (f) making beds, cleaning bathrooms, supplying towels, soap and related items; (g) cleaning kitchens and generally helping with kitchen work, including dishwashing; (h) restocking mini-bars and replenishing items such as drinking glasses and writing equipment. Examples of the occupations classified here: - Housekeeper (hotel) - Matron (housekeeping) Some related occupations classified elsewhere: - Hotel manager - 1411 - Bed and breakfast operator - 5152 - Domestic housekeeper - 5152 - Building caretaker - 5153 - Domestic cleaner - 9111

  • hotel butler
  • housekeeping supervisor

Job titles from the EU's ESCO list. Search for any of them on the jobs page and you'll end up here.

78 / 100

Mostly holds up against AI

AI can take a few chores off your plate, but most of the day is still yours.

Not the odds you keep your job. It's how much of the everyday work still needs a person, out of 100.

← Robot's turf Human's turf →

The ILO's official verdict: Not Exposed

169 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 8 tasks for how much of it AI could do. They average 22 out of 100, so it holds up at 100 − 22 = 78.

That's the whole sum. No black box, no secret sauce: you can check it against the ILO's study. ILO group “Not Exposed”: None of this job's tasks scored high enough to count.

from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.8-observed-use

Pinch of salt: this number is probably too rosy

It only asks what AI software could do, and this job is 56 out of 100 hands-on. A chatbot can't do that part. A robot might, one day, and nobody measures how close that is.

Man v Bot · compare

Who holds up better?

Cleaning and housekeeping supervisors in offices, hotels and other establishments 78

v

Go on, try your partner's job. Or your sibling's. We won't tell.

Man v Bot

Where the bot helps, and where the human wins

Bot

What AI takes

The routine stuff. You may not miss it.

  • Purchasing and stock control.
  • Room assignment apps.
  • Inspection records.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Training and supervising staff.
  • Keeping standards high.
  • Handling guest problems.

Both

What's arriving

New work that only exists because the AI does.

  • Housekeeping apps and room sensors.
  • Cleaning robots for corridors.
  • Higher hygiene standards.

Written by a human, from the ILO's task ratings below. Yes, we see the irony. Read it as one person's take.

Meet your two rivals

They're not the same machine. AI software can only reach the parts of a job done on a screen or in words. A chatbot can't climb a ladder. A robot might, one day, if it doesn't fall off.

The AI

Lives in a screen. Never had to fix a boiler.

Threat level: Low

24 could do without you

It could take over very little of the work on its own. It could help with 52 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Some

56 how hands-on

A fair part of this job is hands-on, so robots would be needed for that part, not just software.

So could a robot do the physical part?

Physical work where helping and caring for people is a big part of the job. For care work, whether a machine could do the movements is only half the question. The other half is whether anyone wants one to. The US data counts helping workmates too, so a few trades end up here.

Robots hate fiddly work in awkward spaces. On that measure, this job scores 30 out of 100. The higher it is, the longer the robot waits.

56 How
hands-on
30 How fiddly
and cramped

Kind of hands-on work Hands-on, helping and caring for others

The small print

They aren't a robot score, and nothing on this page is. Nobody measures how far robots have got well enough to put a number on it. These are the closest thing we have: how hands-on the job is, and how much fiddly, cramped work it takes, which is what Frey and Osborne found hardest for machines.

From O*NET, matched to one US job .

finger skill 30.3 · hand skill 30.3 · cramped spaces 28 · averaged · rule: hands-on 50+ · caring 4+ of 7

estimated O*NET 31.0 BLS occupational crosswalk chain ISCO-08 to 2010 SOC (Aug 2012, rev. Jun 2015); 2010 to 2018 SOC (Nov 2017); O*NET-SOC 2019 taxonomy data 0.8-observed-use measures chosen by Frey & Osborne (2017) · the grouping is a sorting, not a measurement

The job, task by task

Every job is really a bundle of tasks. Here's this one unpacked, with how much of each AI could do, out of 100. The score is the average, and averages can hide a lot.

AI's favourite task here scores 36, against an average of 22. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 36

    Purchasing or controlling the purchase of supplies

    Low
  2. 36

    Controlling storage and issue of supplies

    Low
  3. 25

    Supervising general welfare and conduct of individuals in institutions

    Low
  4. 24

    Engaging, training, discharging, organizing and supervising helpers, cleaners and other housekeeping staff

    Very Low
  5. 19

    Restocking mini-bars and replenishing items such as drinking glasses and writing equipment.

    Very Low
  6. 14

    Making beds, cleaning bathrooms and supplying towels, soap and related items

    Very Low
  7. 13

    Cleaning kitchens and generally helping with kitchen work, including dishwashing

    Very Low
  8. 10

    Sweeping or vacuum-cleaning, washing and polishing floors, furniture and other fixtures

    Very Low

8 tasks · the High to Very Low labels are the ILO's

from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.8-observed-use

Sidekick or replacement?

A tool that makes you faster is a very different thing from one that does the task while you watch. Jobs and Skills Australia measured the two separately, which is handy.

AI helps you
52
AI does it for you
24

Sidekick wins, by 29 points.

How good a match is this?

3 Australian jobs match this one, and we've simply averaged them. Treat the numbers as a rough guide.

estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.8-observed-use matched to Australian jobs 4314, 8112, 8114

Meanwhile, in real life…

Everything else here is about what AI could do. This is what people actually did. When they asked Claude for help with this kind of work, did they hand the whole task over, or roll their sleeves up and work through it together?

Out of every 100 conversations

57
43

worked through it together handed it over

The small print

Anthropic publishes this about its own product, and it doesn't feed into any score here. These are people who use Claude, not workers in general, so little use here doesn't mean AI can't reach the job. This job makes up 0.11% of the conversations.

These two add up to 100. The bars elsewhere on the page don't, because each is scored on its own, so we don't put them side by side.

observed use Anthropic Economic Index release 2026-06-26, period beginning 2026-05-01 data 0.8-observed-use 2026-05-01 · Anthropic, about its own product

So, should housekeeping supervisors be worried?

Short answer: not much. Some of the chores will change, and good riddance.

The stockroom admin is moving. Purchasing and controlling supplies are the most exposed tasks, both Low; supervising staff and cleaning rate Very Low. Housekeeping software assigns rooms and tracks stock; managing people and standards stays human.

Worth remembering: we score tasks, not jobs. When AI takes on a task, the job usually reshuffles around it rather than vanishing.

Where this job could lead

None of the new jobs we've written up start from here yet. Could be you're the first. See the jobs AI is creating →

How are the neighbours doing?

There are 39 jobs in the “Service and sales workers” family, averaging 74. This one is above the family average.

Pit this against any other job →