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A closer look

Customer service representative

AI can answer the easy questions. The hard calls are coming to you.

AI could take a fair chunk of all six tasks: logging requests, sending documents, taking payments and passing work along. With nothing safely out of reach, it scores second lowest of the twenty.

42 / 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

19 of the 20 jobs up close

Why this score?

The ILO rated each task in this job for how much of it AI could do. They average 58.1 out of 100, so the job holds up at 100 − 58.1 = 41.9.

ILO group “Exposed: Gradient 3”: Most of the tasks are affected.

AI helps JSA 2025
73
Usually good news: more of the work gets quicker without the job going away.
AI takes over JSA 2025
75
This is what most people mean by “exposed”. We keep it apart from helping on purpose.
Hands-on O*NET 31.0
33.6
Software can't do hands-on work, but robots might one day. How far they've got isn't on this site, because nobody measures it well enough yet.

from the source Working Paper 140, Generative AI and Jobs 2025 index O*NET 31.0 Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.8-observed-use

Man v Bot · compare

Who holds up better?

Customer service representative 42

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.

  • Answering questions that have a documented answer.
  • Logging, categorising and routing contacts.
  • First-line triage of complaints and account changes.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • The call where somebody is distressed and the policy does not fit.
  • Recognising vulnerability, and the duty that comes with it.
  • Taking responsibility on behalf of an organisation that made a mistake.

Both

What's arriving

New work that only exists because the AI does.

  • Handling only the contacts that were escalated, all day, with no easy ones in between.
  • Supervising and correcting automated responses at volume.
  • Complaint handling that regulation increasingly requires a person for.

Written by a human, from the task data. 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

75 could do without you

It could take over a lot of this job on its own. It could help with 73 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Lower

34 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 17 out of 100. The higher it is, the longer the robot waits.

17 How fiddly
and cramped

Kind of hands-on work Less than half hands-on

The small print

It isn'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. This is the closest thing we have: how much fiddly handwork and cramped, awkward work the job takes, which is what Frey and Osborne found hardest for machines.

The numbers come straight from the US job database's entry for Customer Service Representatives. Its wider group, Contact centre information clerks, lands in the same place.

finger skill 30.3 · hand skill 19.7 · cramped spaces 2 · hands-on 33.6 · caring 2.45 of 7 · rule: hands-on under 50

from the source O*NET 31.0 data 0.8-observed-use measures chosen by Frey & Osborne (2017) · the grouping is a sorting, not a measurement

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 0.07% 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

66
34

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.

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 reps be worried?

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

This is one of the most exposed jobs here. All six tasks rate Medium, so AI will handle more and more of the routine contacts. What's left is harder: distressed callers, vulnerable customers and complaints that regulation says need a person. Several new jobs, like AI agent manager, start from exactly this experience.

Worth remembering: we score tasks, not jobs. When AI takes on a task, the job usually reshuffles around it rather than vanishing. Bank tellers survived the cash machine. The job just got more chatty.

Where this job could lead

Fancy a rematch?

Put customer service reps up against another job, then send the result to someone who needs a little humbling.

Where this page's numbers come from