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Craft and related trades workers · code 7212

Welders and flamecutters

Robots already weld car bodies. Welding a pipe on a scaffold is a different job.

AI barely touches any of the eight tasks, from welding and cutting metal to watching for overheating and checking the finished piece.

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

Welders and flame cutters weld and cut metal parts using gas flame, electric arc and other sources of heat to melt and cut, or to melt and fuse metal. Tasks include - (a) welding metal parts using gas flame, or an electric arc, thermite compound or other methods; (b) operating resistance-welding machines; (c) using blowtorches to make and repair lead linings, pipes, floors and other lead fixtures; (d) brazing metal parts together; (e) cutting metal pieces using gas flame or an electric arc; (f) joining metal parts by hand soldering; (g) monitoring the fitting, burning and welding processes to avoid overheating of parts or warping, shrinking, distortion or expansion of material; (h) examining work pieces for defects and measuring work pieces with straight edges or templates to ensure conformity with specifications. Examples of the occupations classified here: - Brazier - Flame cutter - Welder

  • welding coordinator
  • brazier
  • solderer
  • welder

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

87 / 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

46 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 8 tasks for how much of it AI could do. They average 13 out of 100, so it holds up at 100 − 13 = 87.

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 60 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?

Welders and flamecutters 87

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.

  • Weld procedure paperwork and records.
  • Inspecting welds with cameras and sensors.
  • Programming welding robots for repetitive work.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Welding in awkward positions on site.
  • Repairs where every job is different.
  • Judging a weld pool by eye.

Both

What's arriving

New work that only exists because the AI does.

  • Programming and supervising welding robots.
  • Energy infrastructure and wind turbine work.
  • Digital inspection and certification.

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

24 could do without you

It could take over very little of the work on its own. It could help with 61 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Some

60 how hands-on

A fair part of this job is hands-on, so robots would be needed for that part, not just software.

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 43 out of 100. The higher it is, the longer the robot waits.

60 How
hands-on
43 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 2 US jobs .

finger skill 43.8 · hand skill 42.9 · cramped spaces 43.5 · 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 24, against an average of 13. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 24

    Monitoring the fitting, burning, and welding processes to avoid overheating of parts or warping, shrinking, distortion or expansion of material

    Very Low
  2. 16

    Examining work pieces for defects and measuring work pieces with straight edges or templates to ensure conformance with specifications.

    Very Low
  3. 13

    Operating resistance-welding machines

    Very Low
  4. 12

    Brazing metal parts together

    Very Low
  5. 12

    Joining metal parts by hand soldering

    Very Low
  6. 10

    Cutting metal pieces using gas flame or an electric arc

    Very Low
  7. 9

    Welding metal parts using gas flame, or an electric arc, thermite compound or other methods

    Very Low
  8. 9

    Using blowtorch to make and repair lead linings, pipes, floors and other lead 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 0.8-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
61
AI does it for you
24

Sidekick wins, by 37 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, 3232, 7123

So, should welders be worried?

Short answer: not really. Put the kettle on.

Not about AI software. Every task rates Very Low; the most exposed is watching for overheating and distortion. Robotic welding is common in factories, so demand leans towards skilled site, repair and specialist work.

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 →