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Elementary occupations · code 9623

Meter readers and vending-machine collectors

Smart meters read themselves. That's why this job scores as it does.

Reading and recording meters is a task AI could do most of, and it could take a fair chunk of the stock and takings records. Collecting coins and refilling vending machines it barely touches.

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

Meter readers and vending-machine collectors stock vending machines and collect money from them or from parking meters and other coinboxes, or read electricity, gas or water meters. Tasks include - (a) filling storage areas of vending machines and collecting money from their containers; (b) collecting money from parking meters and similar coinboxes; (c) reading electricity, gas or water meters and recording consumption; (d) keeping records of merchandise distributed and money collected; (e) proceeding along established routes to take readings of meter dials; (f) verifying readings in cases where consumption appears to be abnormal, and recording possible reasons for fluctuations; (g) inspecting meters for unauthorized connections, defects and damage such as broken seals. Examples of the occupations classified here: - Meter reader - Vending-machine collector

  • vending machine operator
  • meter reader

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

62 / 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

308 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 7 tasks for how much of it AI could do. They average 37.7 out of 100, so it holds up at 100 − 37.7 = 62.3.

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 52.5 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?

Meter readers and vending-machine collectors 62

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.

  • Meter readings from smart meters.
  • Sales and cash records.
  • Routes and schedules.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Inspecting for tampering and damage.
  • Restocking machines.
  • Checking unusual readings.

Both

What's arriving

New work that only exists because the AI does.

  • Installing and maintaining smart meters.
  • Cashless vending.
  • Field service roles.

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 55 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Some

53 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?

More fine handwork, and more time in cramped or awkward spots, than a typical hands-on job. That is exactly what machines find hardest: they do best in tidy, predictable places.

Robots hate fiddly work in awkward spaces. On that measure, this job scores 39 out of 100. The higher it is, the longer the robot waits.

53 How
hands-on
39 How fiddly
and cramped

Kind of hands-on work Hands-on, fiddly work in tight spaces

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 39.3 · cramped spaces 39.7 · averaged · rule: hands-on 50+ · fiddly 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 75, against an average of 38. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 75

    Reading electricity, gas or water meters and recording consumption

    High
  2. 58

    Keeping records of merchandise distributed and money collected

    Medium
  3. 35

    Verifying readings in cases where consumption appears to be abnormal, and record possible reasons for fluctuations

    Low
  4. 32

    Proceeding along established routes to take readings of meter dials

    Low
  5. 27

    Inspecting meters for unauthorized connections, defects and damage such as broken seals.

    Low
  6. 19

    Collecting money from parking meters and similar coinboxes

    Very Low
  7. 18

    Filling storage areas of vending machines and collecting money from their containers

    Very Low

7 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
55
AI does it for you
38

Sidekick wins, by 17 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 5619, 8997

So, should meter readers and vending machine collectors be worried?

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

Yes, this is one of the most exposed jobs. Reading meters is rated High, and keeping sales records is Medium; verifying readings, routes and inspections are Low; collecting money and restocking rate Very Low. Smart meters and cashless machines are replacing much of this work.

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 33 jobs in the “Elementary occupations” family, averaging 86. This one is below the family average.

Pit this against any other job →