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Craft and related trades workers · code 7311

Precision-instrument makers and repairers

Software can test the watch. Repairing the movement is still tweezers and patience.

Testing how accurate watches, meters and gauges are is mostly out of AI's reach. It barely touches seven of the twelve tasks, including cleaning watch parts and repairing instrument casings.

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

Precision-instrument makers and repairers make, calibrate, repair, maintain, adjust and install mechanical watches and clocks, and nautical, meteorological, optical and other precision instruments and equipment, and set them for correct performance. Tasks include - (a) repairing, cleaning and adjusting mechanisms of timing instruments such as watches and clocks; (b) adjusting timing regulators, using calipers, watch-rate recorders and tweezers; (c) cleaning, rinsing and drying timepiece parts, using solutions and ultrasonic or mechanical watch-cleaning machines; (d) testing timepiece accuracy and performance, using meters and other electronic instruments; (e) testing accuracy of meters, gauges, indicators, or other recording or controlling instruments to locate defective components and for conformity with standards; (f) calibrating instruments or scales, using hand tools, computer or electronic devices; (g) inspecting components, connections and drive mechanisms to detect defects; (h) assembling instruments and devices such as barometers, control valves, gyroscopes, hygrometers, speedometers, tachometers and thermostats; (i) testing, calibrating and adjusting electronic, mercurial, aneroid and other types of meteorological instruments for compliance with printed specifications and schematic diagrams, using voltmeters, oscilloscopes, tube testers and other test instruments; (j) adjusting and repairing masts, supporting structures, clearance lights, control panels, control cabling and wiring, and other electrical and mechanical devices; (k) repairing and setting optical instruments such as microscopes, telescopes, theodolites and sextants; (l) checking whether assembled units conform to specifications and ensuring stipulated performance and sensitivity by standard tests. Examples of the occupations classified here: - Instrument/meteorological maker - Photographic equipment repairer - Surgical instrument maker - Watchmaker Some related occupations classified elsewhere: - Orthopaedic appliance maker - 3214 - Locksmith - 7222 - Machine tool operator - 7223 - Watch assembler - 8212

  • optical instrument repairer
  • clock and watchmaker
  • surgical instrument maker
  • watch and clock repairer
  • optical instrument assembler
  • precision instrument assembler

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

79 / 100

Mostly holds up against AI

AI can take a few chores off your plate, but most of the day is still yours.

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

160 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 12 tasks for how much of it AI could do. They average 21.4 out of 100, so it holds up at 100 − 21.4 = 78.6.

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 48 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?

Precision-instrument makers and repairers 79

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.

  • Electronic testing and calibration.
  • Checking assemblies against specifications.
  • Service records.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Repairing fine mechanisms.
  • Adjusting and regulating by hand.
  • Restoring vintage instruments.

Both

What's arriving

New work that only exists because the AI does.

  • Smartwatch and electronic repairs.
  • Restoring and servicing luxury watches.
  • Calibrating sensors for new industries.

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

28 could do without you

It could take over very little of the work on its own. It could help with 64 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Some

48 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 44 out of 100. The higher it is, the longer the robot waits.

48 How
hands-on
44 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 4 US jobs .

finger skill 56.3 · hand skill 44.6 · cramped spaces 30.4 · 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 32, against an average of 21. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 32

    Testing timepiece accuracy and performance, using meters and other electronic instruments

    Low
  2. 30

    Testing accuracy of meters, gauges, indicators or other recording or controlling instruments to locate defective components and for conformance to standards

    Low
  3. 30

    Testing, calibrating and adjusting electronic, mercurial, aneroid and other types of meteorological instruments for compliance with printed specifications and schematic diagrams, using voltmeters, oscilloscopes, tube testers, and other test instruments

    Low
  4. 28

    Checking whether assembled units conform to specifications and ensuring stipulated performance and sensitivity by standard tests.

    Low
  5. 26

    Calibrating instruments or scales, using hand tools and computer or electronic devices

    Low
  6. 21

    Adjusting timing regulators, using calipers, watch-rate recorders and tweezers

    Very Low
  7. 20

    Inspecting components, connections and drive mechanisms to detect defects

    Very Low
  8. 14

    Assembling instruments and devices such as barometers, control valves, gyroscopes, hygrometers, speedometers, tachometers and thermostats

    Very Low
  9. 14

    Repairing, cleaning and adjusting mechanisms of timing instruments such as watches and clocks

    Very Low
  10. 14

    Repairing and setting optical instruments such as microscopes, telescopes, theodolites and sextants

    Very Low
  11. 14

    Adjusting and repairing masts, supporting structures, clearance lights, control panels, control cabling and wiring, and other electrical and mechanical devices

    Very Low
  12. 13

    Cleaning, rinsing and drying timepiece parts, using solutions and ultrasonic or mechanical watch-cleaning machines

    Very Low

12 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
64
AI does it for you
28

Sidekick wins, by 36 points.

How good a match is this?

One Australian job matches, but only partly: not everyone in it does this job. 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 3233

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 under 0.01% 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

37
63

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.

The data is sorted by US job, and this one matches 2 of them. We've combined them, counting each by how often it comes up in the conversations, so the busiest one counts most.

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 watchmakers and instrument repairers be worried?

Short answer: not much. Some of the chores will change, and good riddance.

Somewhat. Testing and calibrating instruments are the most exposed tasks, all Low; adjusting, repairing and assembling rate Very Low. Electronic testing and calibration keep improving; fine repair and restoration stay hands-on.

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 84. This one is below the family average.

Pit this against any other job →