Skip to content
man bot
Compare

Elementary occupations · code 9121

Hand launderers and pressers

AI can track the order. Pressing a shirt by hand is still hands-on.

AI barely touches any of the four tasks: washing and pressing by hand, cleaning with solvents, small repairs and hanging things up for collection.

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

Hand launderers and pressers launder, press or dry-clean garments, linen and other textiles by hand. Tasks include - (a) laundering and pressing linen, clothing, fabrics and similar articles by hand in a laundry or other establishment; (b) cleaning, by hand and with chemical solutions, clothing, fabrics, leather goods and similar articles, in a dry-cleaning or other establishment; (c) replacing buttons and making minor repairs; (d) placing articles on shelves and hanging articles for delivery and collection. Examples of the occupations classified here: - Dry-cleaner (hand) - Hand launderer - Hand presser - Ironer Some related occupations classified elsewhere: - Dry-cleaning machine operator - 8157 - Laundry machine operator - 8157 - Pressing machine operator (laundry) - 8157

  • wearing apparel presser
  • linen room attendant

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

86 / 100

Strongly holds up against AI

Most of this job still needs an actual human. AI would mostly be making the tea.

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

70 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 4 tasks for how much of it AI could do. They average 14.4 out of 100, so it holds up at 100 − 14.4 = 85.6.

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 61 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?

Hand launderers and pressers 86

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.

  • Tracking orders and collections.
  • Bookings and payments by app.
  • Stock and chemical records.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Handling delicate fabrics.
  • Pressing and finishing by hand.
  • Repairs like buttons and seams.

Both

What's arriving

New work that only exists because the AI does.

  • Collection and delivery booked online.
  • Greener cleaning methods.
  • Repair services as people keep clothes longer.

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

19 could do without you

It could take over very little of the work on its own. It could help with 43 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Higher

61 how hands-on

Most of this job needs hands, a body or turning up. That's robot territory, and nobody measures how far robots have got well enough to give you a number. We won't make one up.

So could a robot do the physical part?

Less fine handwork and fewer cramped spaces than a typical hands-on job. That clears one hurdle for machines. It doesn't mean machines are doing this work yet.

Robots hate fiddly work in awkward spaces. On that measure, this job scores 35 out of 100. The higher it is, the longer the robot waits.

61 How
hands-on
35 How fiddly
and cramped

Kind of hands-on work Hands-on, less fiddly work

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 44.6 · hand skill 42.9 · cramped spaces 17.3 · averaged · rule: hands-on 50+ · fiddly under 39.4

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 18, against an average of 14. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 18

    Placing articles on shelves and hanging articles for delivery and collection.

    Very Low
  2. 15

    Laundering and pressing linen, clothing, fabrics and similar articles by hand in a laundry or other establishment

    Very Low
  3. 14

    Replacing buttons and making minor repairs

    Very Low
  4. 11

    Cleaning, by hand and with chemical solutions, clothing, fabrics, leather goods and similar articles, in a dry-cleaning or other establishment

    Very Low

4 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
43
AI does it for you
19

Sidekick wins, by 24 points.

How good a match is this?

One Australian job matches, but only partly: not everyone in it does this job. 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 8115

So, should launderers and pressers be worried?

Short answer: not really. Put the kettle on.

No. Every task rates Very Low, from pressing to minor repairs. Industrial laundries use more machines, but delicate items, repairs and dry cleaning stay with people.

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 33 jobs in the “Elementary occupations” family, averaging 85. This one is above the family average.

Pit this against any other job →