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Clerical support workers · code 4224

Hotel receptionists

You can check in on an app. Guests still want someone at the desk when something goes wrong.

AI could take a fair chunk of seven of the nine tasks, including answering guests' questions and taking payment at checkout. Passing on housekeeping and maintenance requests is mostly out of its reach.

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

Hotel receptionists welcome and register guests in hotels and other establishments that provide accommodation services. They assign rooms, issue keys, provide information concerning the services provided, make room reservations, keep a record of rooms available for occupancy, present statements of charges to departing guests and receive payment. Tasks include - (a) maintaining an inventory of rooms available for occupancy, reservations and room assignments; (b) registering arriving guests, assigning rooms, verifying customers’ credit and issuing room keys; (c) providing information regarding hotel services and services available in the community; (d) providing information about availability of accommodation and making room reservations; (e) responding to guests’ requests for housekeeping and maintenance services as well as to complaints; (f) contacting housekeeping or maintenance services when guests report problems; (g) compiling and checking guest accounts for charges using computerized or manual systems; (h) receiving and forwarding messages in person or using telephones or telephone switchboards; (i) reviewing statements of charges to departing guests and receiving payment. Examples of the occupations classified here: - Hotel front desk clerk - Hotel receptionist

  • hospitality establishment receptionist

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

49 / 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

381 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 9 tasks for how much of it AI could do. They average 51.4 out of 100, so it holds up at 100 − 51.4 = 48.6.

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 28.3 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?

Hotel receptionists 49

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.

  • Reservations and check-in.
  • Billing.
  • Answering questions.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Welcoming guests.
  • Complaints and problems.
  • Coordinating with housekeeping.

Both

What's arriving

New work that only exists because the AI does.

  • Mobile check-in and digital keys.
  • AI chat for guests.
  • Smaller front desk teams.

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 67 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Lower

28 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 13 out of 100. The higher it is, the longer the robot waits.

28 How
hands-on
13 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 17.9 · hand skill 15.2 · cramped spaces 5.8 · 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 63, against an average of 51. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 63

    Providing information regarding hotel services and services available in the community

    Medium
  2. 56

    Reviewing statements of charges to departing guests and receiving payment.

    Medium
  3. 55

    Providing information about availability of accommodation and making room reservations

    Medium
  4. 54

    Compiling and checking guest accounts for charges using computerized or manual systems

    Medium
  5. 53

    Maintaining an inventory of rooms available for occupancy, reservations and room assignments

    Medium
  6. 51

    Registering arriving guests, assigning rooms; verifying customer’s credit and issuing room keys

    Medium
  7. 50

    Receiving and forwarding messages in person or using telephone or telephone switchboard

    Medium
  8. 44

    Contacting housekeeping or maintenance services when guests report problems

    Low
  9. 39

    Responding to guests’ requests for housekeeping and maintenance services as well as complaints

    Low

9 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
67
AI does it for you
66

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 5421

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 0.01% 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

23
77

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 hotel receptionists be worried?

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

Much of the desk work is exposed. Information, billing, reservations, accounts, room inventory, check-in and messages are rated Medium; problems and complaints are Low. Online check-in and AI chat take on routine tasks; welcoming guests stays 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 47. This one is above the family average.

Pit this against any other job →