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Clerical support workers · code 4214

Debt-collectors and related workers

Automated messages already chase payments. Talking to someone who can't pay is still a person.

Recommending legal action when a debt goes unpaid is the one task AI could take a fair chunk of. Tracking down debtors and getting in touch to collect are mostly out of its reach.

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

Debt collectors and related workers collect payments on overdue accounts and bad cheques and collect charity payments. Tasks include - (a) tracing and locating debtors; (b) telephoning, visiting or writing to customers to collect money or arrange for later payments; (c) preparing reports including amounts collected, and maintaining records and files related to collection work; (d) recommending legal action or discontinuation of service when payment cannot be otherwise obtained; (e) asking for and collecting charity payments. Examples of the occupations classified here: - Bill and account collector - Charity collector - Debt collector

  • insurance collector
  • debt collector

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

57 / 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

340 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 42.6 out of 100, so it holds up at 100 − 42.6 = 57.4.

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 17.8 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?

Debt-collectors and related workers 57

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.

  • Payment reminders.
  • Records and reports.
  • Tracing debtors with data.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Conversations with people in difficulty.
  • Arranging fair payment plans.
  • Judgement about next steps.

Both

What's arriving

New work that only exists because the AI does.

  • AI voice agents for collections.
  • Rules protecting vulnerable customers.
  • Online payment plans.

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

69 could do without you

It could take over a lot of this job on its own. It could help with 70 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Lower

18 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 11 out of 100. The higher it is, the longer the robot waits.

18 How
hands-on
11 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 25 · hand skill 3.6 · cramped spaces 3 · 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 54, against an average of 43. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 54

    Recommending legal action or discontinuation of service when payment cannot be otherwise obtained

    Medium
  2. 45

    Preparing reports including amounts collected, and maintain records and files related to collection work

    Low
  3. 43

    Asking for and collecting charity payments.

    Low
  4. 37

    Tracing and locating debtors

    Low
  5. 35

    Telephoning, visiting, or writing to customers to collect money or arrange for later payments

    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
70
AI does it for you
69

Sidekick wins, by 1 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 5993

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 0.06% of all the conversations: a tiny slice. People using AI for a job isn't the same as AI being able to do it.

Out of every 100 conversations

64
36

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 debt collectors be worried?

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

Parts of it are exposed. Recommending legal action is rated Medium; reports, charity collections, tracing debtors and contacting customers are Low. Automated reminders, payment plans and AI calls take on routine chasing; difficult conversations stay 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 →