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Craft and related trades workers · code 7133

Building structure cleaners

AI can write the asbestos report. It won't climb the chimney.

AI barely touches any of the three tasks: cleaning building exteriors, sweeping chimneys and flues, and clearing asbestos, mould and fire damage.

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

Building structure cleaners clean exterior surfaces of buildings and other structures, and remove soot from chimneys. Tasks include - (a) cleaning exterior surfaces of stone, brick, metal or similar materials by means of chemicals, or a jet of steam or sand applied under high pressure; (b) removing soot from flues, chimneys and connecting pipes; (c) removing asbestos, mould and fire-damaged surfaces from buildings. Examples of the occupations classified here: - Building exteriors cleaner - Chimney sweep - Sandblaster (building exteriors) Some related occupations classified elsewhere: - Graffiti cleaner - 9129 - Water blaster - 9129

  • decontamination worker
  • chimney sweep
  • chimney sweep supervisor
  • building exterior cleaner
  • asbestos abatement worker

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

91 / 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

6 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 3 tasks for how much of it AI could do. They average 9.2 out of 100, so it holds up at 100 − 9.2 = 90.8.

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 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?

Building structure cleaners 91

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.

  • Quotes, method statements and risk assessments.
  • Booking jobs and keeping safety records.
  • Identifying damage or materials from photos.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Working at height or in confined, contaminated spaces.
  • Choosing a cleaning method that won't damage old stone.
  • Following strict safety procedures on the day.

Both

What's arriving

New work that only exists because the AI does.

  • Drone surveys of facades before work starts.
  • Decontamination and retrofit work on older buildings.
  • Stricter rules on chemicals and waste.

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

17 could do without you

It could take over very little of the work on its own. It could help with 48 of 100.

The robot

The wildcard. Has hands, still working out stairs.

– how hands-on

We don't have a hands-on measure for this job.

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 10, against an average of 9. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 10

    Cleaning exterior surfaces of stone, brick, metal or similar materials by means of chemicals, or a jet of steam or sand applied under high pressure

    Very Low
  2. 9

    Removing soot from flues, chimneys and connecting pipes

    Very Low
  3. 8

    Removing asbestos, mould and fire-damaged surfaces from buildings.

    Very Low

3 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
48
AI does it for you
17

Sidekick wins, by 31 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 7119, 8112, 8116

So, should building structure cleaners be worried?

Short answer: not really. Put the kettle on.

No. Cleaning facades, sweeping flues and removing asbestos all rate Very Low. AI can help with quotes, method statements and safety paperwork. The work itself is hazardous, physical and different on every building.

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 65 jobs in the “Craft and related trades workers” family, averaging 83. This one is above the family average.

Pit this against any other job →