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Service and sales workers · code 5151

Cleaning and housekeeping supervisors in offices, hotels and other establishments

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

None of this job's tasks scored high enough to count. It ranks 169 of 427 for holding up against AI.

Also known as

  • 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
Holds up
against AI Not Exposed

AI could take on 22 of 100, on average
so it holds up at 100 − 22 = 78

That's the whole sum, and you can check it against the ILO's study.

55.9
How hands-on
out of 100

From O*NET, matched to one US job

29.5
How fiddly
and cramped

finger skill 30.3 · hand skill 30.3 · cramped spaces 28 · averaged

Kind of hands-on work · hands-on 50+ · caring 4+ of 7 Hands-on, helping and caring for others

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.

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 0.7-work-setting measures chosen by Frey & Osborne (2017) · the grouping is a sorting, not a measurement

This number is probably too high

This score only looks at AI tools like chatbots. It doesn't look at robots at all — and this job rates 55.9 out of 100 for how hands-on it is, which is exactly where robots come in.

Have a look at the tasks below and judge for yourself. The ILO scored them low because a chatbot can't do them. Whether a machine with hands could is a different question, and we can't answer it yet.

The tasks behind the score

The score is the average of these. A job is really a bundle of tasks, and an average can hide how uneven that bundle is.

The task AI could do most of scores 36, while the average is 22. A big gap means some of this job is wide open to AI and some of it barely at all. That's quite different from a job where everything sits somewhere in the middle, even when the averages match.

  1. 36

    Purchasing or controlling the purchase of supplies

    Low
  2. 35.8

    Controlling storage and issue of supplies

    Low
  3. 25.1

    Supervising general welfare and conduct of individuals in institutions

    Low
  4. 24.3

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

    Very Low
  5. 18.5

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

    Very Low
  6. 13.5

    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 0.7-work-setting

Helped, or replaced?

The score above can't tell a tool that makes you faster from one that does the task instead of you. Jobs and Skills Australia looked at those two things separately, and this is their result, matched to this job.

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

AI helps you
52.3
AI does it for you
23.7

Helping wins by 28.6 points.

estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.7-work-setting matched to Australian jobs 4314, 8112, 8114

Compared with similar jobs

There are 39 jobs in the “Service and sales workers” group, averaging 74.3. This one is above that.