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Clerical support workers · code 4415

Filing and copying clerks

Digital files already replaced most filing cabinets. This one is changing fast.

Keeping track of what's filed and what's taken out is the one task AI could take a fair chunk of. Sorting and filing are mostly out of its reach, and photocopying and scanning it barely touches.

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

Filing and copying clerks file correspondence, cards, invoices, receipts and other records in alphabetical or numerical order or according to the filing system used. They locate and remove material from file when requested and photocopy, scan or fax documents. Tasks include - (a) sorting or classifying materials according to guidelines such as content, purpose, user criteria, or chronological, alphabetical or numerical order; (b) filing material in drawers, cabinets and storage boxes; (c) locating and remove materials from files when requested; (d) keeping records of materials filed and removed; (e) photocopying, scanning or faxing documents. Examples of the occupations classified here: - Copying clerk - Filing clerk

  • file clerk

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

297 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 5 tasks for how much of it AI could do. They average 36.9 out of 100, so it holds up at 100 − 36.9 = 63.1.

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 41.9 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?

Filing and copying clerks 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.

  • Records of files and documents.
  • Sorting and classifying documents.
  • Finding and retrieving files.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Handling sensitive physical records.
  • Judgement about what to keep.
  • Helping people find what they need.

Both

What's arriving

New work that only exists because the AI does.

  • Digitising paper archives.
  • Records and information management roles.
  • Data protection compliance.

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: High

76 could do without you

It could take over a lot of this job on its own. It could help with 74 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Some

42 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 27 out of 100. The higher it is, the longer the robot waits.

42 How
hands-on
27 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 39.3 · hand skill 35.7 · cramped spaces 5.2 · 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 60, 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. 60

    Keeping records of materials filed and removed

    Medium
  2. 43

    Sorting or classifying materials according to guidelines such as content, purpose, user criteria, or chronological, alphabetical, or numerical order

    Low
  3. 39

    Locating and remove materials from files when requested

    Low
  4. 25

    Filing material in drawers, cabinets and storage boxes

    Low
  5. 17

    Photocopying, scanning or faxing documents.

    Very Low

5 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
74
AI does it for you
76

Replacement wins, by 2 points. That's rare.

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 5613

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

25
75

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 0.17% 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 filing clerks be worried?

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

Yes, this is one of the most exposed jobs. Keeping records of files is rated Medium; sorting, locating and filing are Low; copying and scanning rate Very Low. Digital records and AI document management already do much of this work, so remaining roles lean towards archives and records management.

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 →