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Plant and machine operators, and assemblers · code 8155

Fur and leather preparing machine operators

The machines split and dye the hides. People keep the machines, and the leather, right.

AI barely touches any of the eleven tasks, from splitting hides and removing flesh and fat to trimming hair and treating pelts by machine.

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

Fur and leather preparing machine operators monitor and operate various machines that prepare leather or treat fur- or wool-bearing pelts. They trim, scrape, clean, tan, buff and dye animal hides, pelts or skins to produce leather stock and finished furs. Tasks include - (a) operating and monitoring machines which remove flesh and fat from hides or pelts to clean and soften them prior to processing; (b) operating and monitoring machines which remove long coarse hair from fur pelts, trim hair to even length and dye, stretch and smooth dressed pelts; (c) operating and monitoring machines to remove epidermis hair roots, pigment cells and lime salts from the grain side of skin; (d) operating and monitoring machines to reduce thickness of hide or skin to uniform size; (e) operating and monitoring machines to polish or roughen hides or skins to specified finishes; (f) operating and monitoring machines which separate residual wool from skins, or flesh and hair from hides; (g) operating and monitoring machines in which hides are split edgeways to form two or more pieces or to give uniform thickness; (h) operating and monitoring machines which treat hides and skins in solutions to convert them into leather; (i) treating surfaces of leather with oil and operating glazing machines to give glossy finishes to leather; (j) operating and monitoring machines which apply dyes and stains to leather; (k) maintaining and repairing vats and other machinery. Examples of the occupations classified here: - Hide dehairing machine operator - Leather staining machine operator - Tanning machine operator Some related occupations classified elsewhere: - Pelt dresser - 7535 - Tanner - 7535

  • leather production machine operator

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

85 / 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

72 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 11 tasks for how much of it AI could do. They average 14.6 out of 100, so it holds up at 100 − 14.6 = 85.4.

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?

Fur and leather preparing machine operators 85

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.

  • Machine settings and batch recipes.
  • Quality inspection with cameras.
  • Production and chemical records.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Watching machines and spotting faults.
  • Maintaining vats and machinery.
  • Judging finish and quality by eye.

Both

What's arriving

New work that only exists because the AI does.

  • Supervising more automated tannery lines.
  • Chemical and environmental compliance.
  • Records of where hides came from.

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 56 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 17, against an average of 15. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 17

    Operating and monitoring machines in which hides are split edgeways to form two or more pieces or to give uniform thickness

    Very Low
  2. 17

    Operating and monitoring machines which remove flesh and fat from hides or pelts to clean and soften them prior to processing

    Very Low
  3. 17

    Operating and monitoring machines which apply dyes and stains to leather

    Very Low
  4. 16

    Operating and monitoring machines which separate residual wool from skins, or flesh and hair from hides

    Very Low
  5. 16

    Operating and monitoring machines which treat hides and skins in solutions to convert them into leather

    Very Low
  6. 16

    Operating and monitoring machines to reduce thickness of hide or skin to uniform size

    Very Low
  7. 16

    Operating and monitoring machines to polish or roughen hides or skins to specified finishes

    Very Low
  8. 14

    Maintaining and repairing vats and other machinery

    Very Low
  9. 12

    Treating surface of leather with oil and operating glazing machine to give glossy finishes to leather

    Very Low
  10. 11

    Operating and monitoring machines which remove long coarse hair from fur pelts, trim hair to even length and dye, stretch and smooth dressed pelts

    Very Low
  11. 11

    Operating and monitoring machines to remove epidermis hair roots, pigment cells and lime salts from grain side of skin

    Very Low

11 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
56
AI does it for you
24

Sidekick wins, by 32 points.

How good a match is this?

One Australian job matches this one closely, so this is about as reliable as it gets here.

estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.8-observed-use matched to Australian jobs 7117

So, should leather machine operators be worried?

Short answer: not really. Put the kettle on.

Not about AI software. Every task rates Very Low: running machines that split, clean, dye and finish hides. More automation in tanneries shifts the work towards supervising and maintaining the machines.

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 39 jobs in the “Plant and machine operators, and assemblers” family, averaging 80. This one is above the family average.

Pit this against any other job →