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Technicians and associate professionals · code 3433

Gallery, museum and library technicians

AI can catalogue the collection. Mounting a fragile object for display is still careful hands.

Entering data and checking catalogue records are where AI could take a fair chunk. Mounting displays and packing and unpacking exhibits it barely touches.

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

Gallery, museum and library technicians prepare artworks, specimens and artefacts for collections, arrange and construct gallery exhibits, and assist librarians to organize and operate systems for handling recorded material and files. Tasks include - (a) mounting and preparing objects for display; (b) designing and arranging exhibit furnishings, display cases and display areas; (c) assisting in setting up lighting and display equipment; (d) receiving, shipping, packing and unpacking exhibits; (e) ordering new library materials and maintaining library records and circulation systems; (f) cataloguing printed and recorded material; (g) entering data into databases and editing computer records; (h) operating audiovisual and reprographic equipment; (i) searching and verifying bibliographic data. Examples of the occupations classified here: - Gallery technician - Library technician - Museum technician - Taxidermist

  • taxidermist
  • big data archive librarian
  • art handler

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

63 / 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: Exposed: Gradient 1

298 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 9 tasks for how much of it AI could do. They average 37 out of 100, so it holds up at 100 − 37 = 63.

That's the whole sum. No black box, no secret sauce: you can check it against the ILO's study. ILO group “Exposed: Gradient 1”: The mildest of the ILO’s four “exposed” groups.

This job rates 48.5 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?

Gallery, museum and library technicians 63

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.

  • Database entry and records.
  • Cataloguing and bibliographic checks.
  • Ordering and circulation systems.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Handling and mounting objects.
  • Packing and shipping exhibits.
  • Installing displays.

Both

What's arriving

New work that only exists because the AI does.

  • Digitising collections.
  • AI search across archives.
  • Interactive and digital exhibitions.

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: Medium

47 could do without you

It could take over some of the work, and help with more. It could help with 68 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Some

49 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 35 out of 100. The higher it is, the longer the robot waits.

49 How
hands-on
35 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 3 US jobs .

finger skill 48.8 · hand skill 39.2 · cramped spaces 16 · 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 70, against an average of 37. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 70

    Entering data into databases and editing computer records

    Medium
  2. 61

    Searching and verifying bibliographic data.

    Medium
  3. 56

    Ordering new library materials and maintaining library records and circulation systems

    Medium
  4. 35

    Cataloguing printed and recorded material

    Low
  5. 28

    Operating audiovisual and reprographic equipment

    Low
  6. 25

    Designing and arranging exhibit furnishings, display cases and display areas

    Low
  7. 25

    Assisting in setting up lighting and display equipment

    Low
  8. 17

    Mounting and preparing objects for display

    Very Low
  9. 17

    Receiving, shipping, packing and unpacking exhibits

    Very Low

9 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
68
AI does it for you
47

Sidekick wins, by 21 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 3993

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?

Out of every 100 conversations

50
50

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. This job makes up 1.64% of the conversations.

The data is sorted by US job, and this one matches 3 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 museum, gallery and library technicians be worried?

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

Parts of it are changing. Data entry, checking bibliographic data and library records are rated Medium; cataloguing, AV equipment and display design are Low; mounting and handling objects rate Very Low. AI will take on cataloguing and records; handling collections stays human.

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 82 jobs in the “Technicians and associate professionals” family, averaging 65. This one is below the family average.

Pit this against any other job →