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Clerical support workers · code 4412

Mail carriers and sorting clerks

Machines already sort most of the post. Knowing which dog to avoid is still the postie.

Delivery records and sorting and logging post are where AI could take a fair chunk. Serving at the counter and delivering to homes and businesses are mostly out of its reach.

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

Mail carriers and sorting clerks perform sorting, recording, delivery and other duties in connection with mail services from post offices or related organizations, as well as from or within an establishment. Tasks include - (a) performing mail-handling duties in public post offices or privately owned delivery establishments; (b) sorting and delivering mail to private houses and businesses; (c) providing delivery confirmation records when requested by the client; (d) sorting and keeping simple records of incoming and outgoing correspondence and dispatching outgoing mail in various establishments; Examples of the occupations classified here: - Mail clerk - Post carrier - Postman/woman

  • postman/postwoman
  • mail clerk

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

59 / 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

332 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 4 tasks for how much of it AI could do. They average 40.8 out of 100, so it holds up at 100 − 40.8 = 59.2.

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 57 out of 100 for how hands-on it is. The score above only looks at AI tools, not robots, and for work like this robots are the bigger question.

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?

Mail carriers and sorting clerks 59

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.

  • Sorting mail.
  • Delivery records.
  • Route planning.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Delivering to homes and businesses.
  • Handling parcels.
  • Knowing the local round.

Both

What's arriving

New work that only exists because the AI does.

  • More parcels, fewer letters.
  • Parcel lockers.
  • Electric delivery vans.

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

38 could do without you

It could take over some of the work, and help with more. It could help with 60 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Some

57 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 fine handwork and fewer cramped spaces than a typical hands-on job. That clears one hurdle for machines. It doesn't mean machines are doing this work yet.

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.

57 How
hands-on
36 How fiddly
and cramped

Kind of hands-on work Hands-on, less fiddly work

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 5 US jobs .

finger skill 41.1 · hand skill 42.5 · cramped spaces 25.6 · averaged · rule: hands-on 50+ · fiddly under 39.4

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 57, against an average of 41. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 56

    Providing delivery confirmation records when requested by the client

    Medium
  2. 51

    Sorting and keeping simple records of incoming and outgoing correspondence and dispatching outgoing mail in various establishments

    Medium
  3. 31

    Performing mail-handling duties in public post offices or privately owned delivery establishments

    Low
  4. 25

    Sorting and delivering mail to private houses and businesses

    Low

4 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
60
AI does it for you
38

Sidekick wins, by 22 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 5612, 5614

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, mostly the paperwork rather than the work. People using AI for a job isn't the same as AI being able to do it.

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.

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 postal workers be worried?

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

Parts of it are changing. Delivery records and sorting are rated Medium; mail handling and delivering are Low. Letters keep falling and sorting is automated, but parcel deliveries still need 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 29 jobs in the “Clerical support workers” family, averaging 46. This one is above the family average.

Pit this against any other job →