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Service and sales workers · code 5132

Bartenders

An app can take the order. It can't cut someone off when they've had enough.

Taking orders and payment are mostly out of AI's reach. It barely touches six of the ten tasks, including washing glasses, wiping down the bar and changing kegs.

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

Bartenders prepare, mix and serve alcoholic and non-alcoholic drinks directly to customers over a bar or counter, or through waiters. Tasks include - (a) taking beverage orders from serving staff or directly from patrons; (b) preparing and serving alcoholic and non-alcoholic drinks at a bar; (c) washing used glassware, cleaning and maintaining bar service areas, tea- and coffee-making areas and equipment such as espresso machines; (d) collecting payment for sales, operating cash registers and balancing cash receipts; (e) tapping kegs and attaching supply lines; (f) assisting in keeping the bar properly stocked and arranging bottles and glasses; (g) checking identification of customers to verify age requirements for purchase of alcohol; (h) taking steps to limit problems related to excessive drinking, such as persuading customers to stop drinking, declining further service or ordering transportation; (i) mixing ingredients to prepare cocktails and other drinks; (j) serving snacks or other food items to customers at the bar. Examples of the occupations classified here: - Bartender Some related occupations classified elsewhere: - Café manager - 1412 - Restaurant manager - 1412 - Waiter - 5131 Notes Operators of small cafés, restaurants and bars for whom the management and supervision of staff is not a significant component of the work are classified in Unit Groups 5120: Cooks, 5131: Waiters or 5132: Bartenders, depending on the main tasks performed.

  • bartender

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

74 / 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: Not Exposed

206 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 10 tasks for how much of it AI could do. They average 26.1 out of 100, so it holds up at 100 − 26.1 = 73.9.

That's the whole sum. No black box, no secret sauce: you can check it against the ILO's study. ILO group “Not Exposed”: None of this job's tasks scored high enough to count.

This job rates 43.9 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?

Bartenders 74

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.

  • Orders through apps and table QR codes.
  • Payments and till work.
  • Digital ID checks.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Making drinks and cocktails.
  • Managing customers who've had too much.
  • Creating an atmosphere.

Both

What's arriving

New work that only exists because the AI does.

  • App ordering and table service.
  • Low and no-alcohol drinks.
  • Cocktail bars as experiences.

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: Low

24 could do without you

It could take over very little of the work on its own. It could help with 49 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Some

44 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?

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

44 How
hands-on
38 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, matched to one US job .

finger skill 42.9 · hand skill 42.9 · cramped spaces 27 · 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 47, against an average of 26. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 47

    Taking beverage orders from serving staff or directly from patrons

    Low
  2. 41

    Collecting payment for sales, operating cash registers and balancing cash receipts

    Low
  3. 37

    Checking identification of customers to verify age requirements for purchase of alcohol

    Low
  4. 27

    Preparing and serving alcoholic and non-alcoholic drinks at a bar

    Low
  5. 24

    Assisting in keeping bar properly stocked and arranging bottles and glasses

    Very Low
  6. 24

    Taking steps to limit problems related to excessive drinking such, as persuading customers to stop drinking, declining further service and ordering transportation

    Very Low
  7. 24

    Serving snacks or other food items to customers at the bar.

    Very Low
  8. 16

    Mixing ingredients to prepare cocktails and other drinks

    Very Low
  9. 12

    Washing used glassware, cleaning and maintaining bar service areas, tea and coffee-making areas and equipment such as espresso machines

    Very Low
  10. 10

    Tapping kegs and attaching supply lines

    Very Low

10 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
49
AI does it for you
24

Sidekick wins, by 25 points.

How good a match is this?

One Australian job matches, but only partly: not everyone in it does this job. 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 4311

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 0.02% 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

53
47

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 bartenders be worried?

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

Some of it is changing. Taking orders, taking payment, checking ID and making drinks are the most exposed tasks, all Low; stocking, managing drunk customers and cleaning rate Very Low. Ordering apps and card payments help; hospitality and judgement 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 39 jobs in the “Service and sales workers” family, averaging 74. This one is below the family average.

Pit this against any other job →