Clerical support workers · code 4225

Enquiry clerks

AI chatbots answer the easy questions. The hard ones still come to you.

AI could take a fair chunk of four of the five tasks, including answering enquiries and logging complaints. Handing tricky cases to the experts is mostly out of its reach.

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

Inquiry clerks respond to personal, written and electronic mail as well as telephone inquiries and complaints about the organization’s goods, services and policies, provide information and refer people to other sources. They are employed in locations which put them in direct contact with clients or with the production of the goods and services provided. Tasks include - (a) answering inquiries about goods, services and policy and providing information about their availability, location, price and related issues; (b) responding to inquiries about problems and providing advice, information and assistance; (c) recording information about inquiries and complaints; (d) referring complex inquiries to team leaders or expert advisers; (e) issuing relevant forms, information kits and brochures to interested parties. Examples of the occupations classified here: - Counter inquiries clerk - Information clerk

customer service representative

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

43 / 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 3

408 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 57.4 out of 100, so it holds up at 100 − 57.4 = 42.6.

That's the whole sum. No black box, no secret sauce: you can check it against the ILO's study. ILO group “Exposed: Gradient 3”: Most of the tasks are affected.

This job rates 22.5 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?

Enquiry clerks 43

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.

Routine questions.
Sending information.
Recording complaints.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

Complex problems.
Upset customers.
Judgement about exceptions.

Both

What's arriving

New work that only exists because the AI does.

AI chat and voice agents.
Checking AI answers.
Customer experience 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: High

66 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

23 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 12 out of 100. The higher it is, the longer the robot waits.

23 How
hands-on

12 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 22.3 · hand skill 12.4 · cramped spaces 2.3 · 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 67, against an average of 57. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

67
Responding to inquiries about problems and providing advice, information and assistance

Medium
66
Issuing relevant forms, information kits and brochures to interested parties.

Medium
56
Answering inquiries about goods services, and policy and providing information about their availability, location, price and related issues

Medium
52
Recording information about inquiries and complaints

Medium
47
Referring complex inquiries to team leaders or expert advisers

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: 66

Sidekick wins, by 4 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 5412

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

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 0.76% of the conversations.

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 customer service advisers be worried?

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

Much of the job is exposed. Answering enquiries, sending information, product questions and recording complaints are rated Medium; referring complex enquiries is Low. AI chat and voice agents take on routine questions, so the job leans towards complex cases.

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 47. This one is below the family average.

Pit this against any other job →