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Craft and related trades workers · code 7214

Structural-metal preparers and erectors

AI can plan the steel frame. Riveting it together at height is still a person's job.

AI barely touches any of the six tasks, from marking and shaping steel to putting up frameworks for buildings, bridges and ships.

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

Structural metal preparers and erectors assemble, erect and dismantle structural metal frames of buildings and other structures. Tasks include - (a) marking metal framework as a guide when drilling cutting, and shaping metal stock for use in buildings, ships and other structures; (b) drilling, cutting and shaping structural steel in a workshop; (c) erecting steel framework for buildings, bridges and other constructions; (d) assembling and erecting the framework and other metal parts of ships’ structures; (e) shaping and fitting structural steel plates of ships under construction or repair; (f) riveting structural metal members by hand, machine or pneumatic riveter. Examples of the occupations classified here: - Erector, structural metal - Preparer, structural metal - Riveter Some related occupations classified elsewhere: - Rivet production machine operator - 7223

  • dismantling worker
  • shipwright
  • structural ironworker

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

89 / 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

20 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 6 tasks for how much of it AI could do. They average 11.1 out of 100, so it holds up at 100 − 11.1 = 88.9.

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 71 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?

Structural-metal preparers and erectors 89

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.

  • Cutting lists and drawings from digital models.
  • Machine-cut and drilled parts.
  • Inspection paperwork and quality records.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Fitting heavy parts that never quite line up.
  • Working safely at height.
  • Judging a joint on site.

Both

What's arriving

New work that only exists because the AI does.

  • Offshore wind and energy infrastructure.
  • Working with robotic welding in the workshop.
  • Digital inspection and sign-off.

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

18 could do without you

It could take over very little of the work on its own. It could help with 53 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Higher

71 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?

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.

Robots hate fiddly work in awkward spaces. On that measure, this job scores 49 out of 100. The higher it is, the longer the robot waits.

71 How
hands-on
49 How fiddly
and cramped

Kind of hands-on work Hands-on, fiddly work in tight spaces

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, averaged across 3 US jobs .

finger skill 47 · hand skill 48.9 · cramped spaces 51.6 · averaged · rule: hands-on 50+ · fiddly 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 14, against an average of 11. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 14

    Assembling and erecting the framework and other metal parts of ships' structures

    Very Low
  2. 12

    Shaping and fitting structural-steel plates of ships under construction or repair

    Very Low
  3. 11

    Riveting structural metal members by hand, machine or pneumatic riveter.

    Very Low
  4. 11

    Drilling, cutting and shaping structural steel in a workshop

    Very Low
  5. 10

    Marking metal framework as a guide when drilling, cutting and shaping metal stock for use in buildings, ships and other structures

    Very Low
  6. 9

    Erecting steel framework for buildings, bridges and other constructions

    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 0.8-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
53
AI does it for you
18

Sidekick wins, by 35 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 3223, 3991, 8217

So, should structural steel workers be worried?

Short answer: not really. Put the kettle on.

No. Assembling, shaping, drilling and erecting steel all rate Very Low. Design software and computer-controlled cutting shape parts in the workshop, but fitting and erecting them on a ship or building needs skilled 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 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 →