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Elementary occupations · code 9313

Building construction labourers

Building construction labourers perform routine tasks in connection with building construction and demolition work. Tasks include - (a) cleaning used building bricks and doing other simple work on demolition sites; (b) mixing, pouring and spreading materials such as concrete, plaster and mortar; (c) digging and filling holes and trenches using hand-held tools; (d) spreading sand, soil, gravel and similar materials; (e) loading and unloading construction materials, excavated material and equipment and transporting them around construction sites using wheelbarrows, hods and hand trucks; (f) cleaning work sites and removing obstructions. Examples of the occupations classified here: - Bricklayer’s assistant - Construction labourer (building work) - Demolition labourer - Hod carrier Some related occupations classified elsewhere: - House builder - 7111 - Bricklayer - 7112 - Building wrecker - 7119

None of this job's tasks scored high enough to count. It ranks 11 of 427 for holding up against AI.

Also known as

  • building construction worker

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

90.6
Holds up
against AI Not Exposed

AI could take on 9.4 of 100, on average
so it holds up at 100 − 9.4 = 90.6

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

74.9
How hands-on
out of 100

From O*NET, averaged across 7 US jobs , so treat it as rough

48.7
How fiddly
and cramped

finger skill 42.4 · hand skill 45.7 · cramped spaces 58.1 · averaged

Kind of hands-on work · hands-on 50+ · fiddly 39.4+ Hands-on, fiddly work in tight spaces

More fine handwork, and more time in cramped or awkward spots, than a typical hands-on job. That is exactly what machines find hardest: they do best in tidy, predictable places.

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 74.9 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 12, while the average is 9.4. 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. 12

    Mixing, pouring and spreading materials such as concrete, plaster and mortar

    Very Low
  2. 10.5

    Cleaning work sites and removing obstructions.

    Very Low
  3. 10

    Loading and unloading construction materials, excavated material and equipment and transporting them around construction sites using wheelbarrows, hods and hand trucks

    Very Low
  4. 8.6

    Spreading sand, soil, gravel and similar materials

    Very Low
  5. 8

    Cleaning used building bricks and doing other simple work on demolition sites

    Very Low
  6. 7.3

    Digging and filling holes and trenches using hand held tools

    Very Low

6 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.

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

AI helps you
40.6
AI does it for you
14.7

Helping wins by 25.9 points.

estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.7-work-setting matched to Australian jobs 8211, 8212, 8213, 8214, 8217, 8219, 8999

Compared with similar jobs

There are 33 jobs in the “Elementary occupations” group, averaging 84.8. This one is above that.