Skip to content
man bot
Compare

Craft and related trades workers · code 7512

Bakers, pastry-cooks and confectionery makers

AI can scale the recipe. It can't tell by touch when the dough is ready.

Checking the quality of ingredients is mostly out of AI's reach. It barely touches seven of the eight tasks, including watching the oven and icing and glazing.

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

Bakers, pastry-cooks and confectionery makers make various kinds of bread, cakes, and other flour products, as well as handmade chocolate and sugar confectionery. Tasks include - (a) making bread, cakes, biscuits, pastries, pies and other flour products; (b) making handmade confectionery from mixtures of sugar, chocolate and other ingredients, using hand tools and some machines; (c) combining measured ingredients in bowls of mixing, blending or cooking machinery; (d) checking the quality of raw materials to ensure that standards and specifications are met; (e) applying glazes, icings or other toppings to baked goods, using spatulas or brushes; (f) checking the cleanliness of equipment and operation of premises before production runs to ensure compliance with occupational health and safety regulations; (g) monitoring oven temperatures and product appearance to determine baking times; (h) coordinating the forming, loading, baking, unloading, de-panning and cooling of batches of bread, rolls, pastry and confectionery products. Examples of the occupations classified here: - Baker - Chocolate maker - Confectioner - Pastry-cook Some related occupations classified elsewhere: - Cook - 5120 - Bakery products machine operator - 8160 - Bread production machine operator - 8160 - Chocolate production machine operator - 8160

  • pastry maker
  • pasta maker
  • confectioner
  • baker
  • chocolatier

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

83 / 100

Strongly holds up against AI

Most of this job still needs an actual human. AI would mostly be making the tea.

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

93 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 8 tasks for how much of it AI could do. They average 16.9 out of 100, so it holds up at 100 − 16.9 = 83.1.

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.

from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.8-observed-use

Pinch of salt: this number is probably too rosy

It only asks what AI software could do, and this job is 54 out of 100 hands-on. A chatbot can't do that part. A robot might, one day, and nobody measures how close that is.

Man v Bot · compare

Who holds up better?

Bakers, pastry-cooks and confectionery makers 83

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.

  • Scaling recipes and costing.
  • Ordering and stock control.
  • Food safety and allergen records.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Judging dough, ovens and bakes by feel and eye.
  • Decorating and finishing by hand.
  • Creating new products.

Both

What's arriving

New work that only exists because the AI does.

  • Selling direct and online.
  • Allergen-free and dietary ranges.
  • Supervising automated lines in larger bakeries.

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

22 could do without you

It could take over very little of the work on its own. It could help with 54 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Some

54 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 fine handwork and fewer cramped spaces than a typical hands-on job. That clears one hurdle for machines. It doesn't mean machines are doing this work yet.

Robots hate fiddly work in awkward spaces. On that measure, this job scores 36 out of 100. The higher it is, the longer the robot waits.

54 How
hands-on
36 How fiddly
and cramped

Kind of hands-on work Hands-on, less fiddly work

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 41.1 · hand skill 42.9 · cramped spaces 24.3 · averaged · rule: hands-on 50+ · fiddly under 39.4

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 35, against an average of 17. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 35

    Checking the quality of raw materials to ensure that standards and specifications are met

    Low
  2. 19

    Checking the cleanliness of equipment and operation of premises before production runs to ensure compliance with occupational health and safety regulations

    Very Low
  3. 17

    Making handmade confectionery from mixtures of sugar, chocolate and other ingredients using hand tools and some machines

    Very Low
  4. 14

    Making bread, cakes, biscuits, pastries, pies and other flour products

    Very Low
  5. 14

    Combining measured ingredients in bowls of mixing, blending or cooking machinery

    Very Low
  6. 13

    Coordinating the forming, loading, baking, unloading, de-panning and cooling of batches of bread, rolls, pastry and confectionary products.

    Very Low
  7. 13

    Monitoring oven temperatures and product appearance to determine baking times

    Very Low
  8. 12

    Applying glazes, icings or other toppings to baked goods, using spatulas or brushes

    Very Low

8 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
54
AI does it for you
22

Sidekick wins, by 32 points.

How good a match is this?

2 Australian jobs match this one, and we've simply averaged them. 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 3511, 8311

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 0.03% of all the conversations: a tiny slice, mostly the paperwork rather than the work. People using AI for a job isn't the same as AI being able to do it.

Out of every 100 conversations

54
46

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 bakers and pastry chefs be worried?

Short answer: not really. Put the kettle on.

No. The most exposed task is checking raw materials, rated Low; baking, decorating and making confectionery rate Very Low. Big bakeries are highly automated, but craft baking and pastry work stay hands-on.

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 65 jobs in the “Craft and related trades workers” family, averaging 84. This one is below the family average.

Pit this against any other job →