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Clerical support workers · code 4411

Library clerks

Self-service machines issue the books. Helping someone find what they need is still a library assistant.

Managing journal subscriptions, filing and word processing are where AI could take a fair chunk. Helping people find things is mostly out of its reach, and putting books back on the shelves it barely touches.

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

Library clerks issue and receive library materials, sort and shelve books, sound and vision recordings, periodicals, journals, magazines and newspapers and provide general library information to library users. Tasks include - (a) issuing and receiving library books and other materials; (b) placing books and other library materials on shelves; (c) performing clerical activities such as manual and electronic filing, word processing and occasional typing; (d) maintaining journal subscriptions; (e) assisting library users in accessing basic library materials and making interlibrary loans; (f) maintaining library records relating to the acquisition, issue and return of books and other materials. Examples of the occupations classified here: - Library clerk - Library filer

  • library assistant

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

54 / 100

Changing significantly

AI could do a real share of the everyday tasks. The job is changing shape, not vanishing.

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 2

360 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 6 tasks for how much of it AI could do. They average 46 out of 100, so it holds up at 100 − 46 = 54.

That's the whole sum. No black box, no secret sauce: you can check it against the ILO's study. ILO group “Exposed: Gradient 2”: A good share of the tasks are affected.

This job rates 36.9 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?

Library clerks 54

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.

  • Subscriptions and records.
  • Issuing and returns.
  • Clerical work.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Helping library users.
  • Shelving and organising.
  • Community activities.

Both

What's arriving

New work that only exists because the AI does.

  • Libraries as community hubs.
  • Digital skills help.
  • E-books and digital lending.

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

48 could do without you

It could take over some of the work, and help with more. It could help with 63 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Lower

37 how hands-on

Not much of this job needs hands, so the robot can sit this one out.

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

37 How
hands-on
24 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 32.2 · hand skill 30.3 · cramped spaces 8.5 · 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 67, against an average of 46. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 67

    Maintaining journal subscriptions

    Medium
  2. 60

    Performing clerical activities such as manual and electronic filing, word processing and occasional typing

    Medium
  3. 52

    Maintaining library records relating to the acquisition, issue and return of books and other materials.

    Medium
  4. 41

    Issuing and receiving library books and other materials

    Low
  5. 40

    Assisting library users in accessing basic library materials and making interlibrary loans

    Low
  6. 17

    Placing books and other library materials on shelves

    Very Low

6 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
63
AI does it for you
48

Sidekick wins, by 15 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 5997

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 1.5% of the conversations.

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 library assistants be worried?

Short answer: not worried, but paying attention. The job is changing.

Parts of it are exposed. Subscriptions, clerical work and library records are rated Medium; issuing books and helping users are Low; shelving rates Very Low. Library systems take on records; helping people 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 29 jobs in the “Clerical support workers” family, averaging 46. This one is above the family average.

Pit this against any other job →