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Craft and related trades workers · code 7549

Craft and related workers not elsewhere classified

Machines grind most lenses now. The specialist and hand-finished work is what's left.

AI barely touches either of its two tasks: moulding optical glass into lens blanks, then grinding and polishing them.

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

This group covers craft and trade occupations not classified elsewhere in Major Group 7: Craft and Related Trades Workers. For instance, the group includes those who mould, slice, grind and polish optical lenses and those who arrange flowers for display. In such cases tasks would include - (a) heating, moulding and pressing optical glass to make lens blanks; (b) grinding and polishing lens blanks. Examples of the occupations classified here: - Flower arranger - Optical lens finisher - Optical lens moulder

86 / 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

68 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 2 tasks for how much of it AI could do. They average 14.4 out of 100, so it holds up at 100 − 14.4 = 85.6.

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.

This job rates 47 out of 100 for how hands-on it is. The score above only looks at AI tools, not robots, but for work this far from the physical that matters less.

from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.8-observed-use

Man v Bot · compare

Who holds up better?

Craft and related workers not elsewhere classified 86

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.

  • Computer-controlled grinding and polishing.
  • Quality measurement.
  • Orders and production records.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Hand-finishing precision parts.
  • Custom and one-off pieces.
  • Checking quality by eye and touch.

Both

What's arriving

New work that only exists because the AI does.

  • Operating precision grinding machines.
  • Specialist optics for cameras and sensors.
  • Repair and refurbishment work.

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

29 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

47 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?

Less than half of this job is hands-on. Robots still matter, but for a smaller part of the work, so we don't sort it any further.

Robots hate fiddly work in awkward spaces. On that measure, this job scores 36 out of 100. The higher it is, the longer the robot waits.

47 How
hands-on
36 How fiddly
and cramped

Kind of hands-on work Less than half hands-on

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 47.4 · hand skill 42 · cramped spaces 17.5 · averaged · rule: hands-on under 50

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 15, against an average of 14. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 15

    Grinding and polishing lens blanks.

    Very Low
  2. 14

    Heating, moulding and pressing optical glass to make lens blanks

    Very Low

2 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
29

Sidekick wins, by 32 points.

How good a match is this?

2 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 3621, 3999

Meanwhile, in real life…

Everything else here is about what AI could do. This is what people actually did. When they asked Claude for help with this kind of work, did they hand the whole task over, or roll their sleeves up and work through it together?

Tiny sample alert This job makes up 0.03% of all the conversations: a tiny slice. People using AI for a job isn't the same as AI being able to do it.

Out of every 100 conversations

53
47

worked through it together handed it over

The small print

Anthropic publishes this about its own product, and it doesn't feed into any score here. These are people who use Claude, not workers in general, so little use here doesn't mean AI can't reach the job.

These two add up to 100. The bars elsewhere on the page don't, because each is scored on its own, so we don't put them side by side.

observed use Anthropic Economic Index release 2026-06-26, period beginning 2026-05-01 data 0.8-observed-use 2026-05-01 · Anthropic, about its own product

So, should lens grinders and specialist craft workers be worried?

Short answer: not really. Put the kettle on.

Not about AI. The only tasks listed, grinding and moulding lenses, rate Very Low. Precision machines already do much of this; specialist, custom and repair work stays with 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 →