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A closer look

Chef

AI can cost the menu. It still can't taste the sauce.

Cooking, seasoning and tasting AI barely touches. It gets closest in the kitchen office: planning menus, costing dishes and ordering supplies.

75 / 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

6 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 25.1 out of 100, so the job holds up at 100 − 25.1 = 74.9.

ILO group “Not Exposed”: None of this job's tasks scored high enough to count.

AI helps JSA 2025
65
Usually good news: more of the work gets quicker without the job going away.
AI takes over JSA 2025
31
This is what most people mean by “exposed”. We keep it apart from helping on purpose.
Hands-on O*NET 31.0
54.5
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?

Chef 75

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.

  • Ordering, stock control and costing a menu.
  • Rostering and compliance records.
  • Recipe development first drafts and allergen checking.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Tasting, and knowing what is missing.
  • Running a line under pressure with people who are also under pressure.
  • Judging produce that is never the same twice.

Both

What's arriving

New work that only exists because the AI does.

  • Menus built around supply volatility rather than tradition.
  • Automated prep in high-volume kitchens, and supervising it.
  • Provenance and dietary claims that have to hold up.

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: Low

31 could do without you

It could take over very little of the work on its own. It could help with 65 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Some

55 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?

More fine handwork, and more time in cramped or awkward spots, than a typical hands-on job. That is exactly what machines find hardest: they do best in tidy, predictable places.

Robots hate fiddly work in awkward spaces. On that measure, this job scores 46 out of 100. The higher it is, the longer the robot waits.

46 How fiddly
and cramped

Kind of hands-on work Hands-on, fiddly work in tight spaces

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 Chefs and Head Cooks. Its wider group, Chefs, lands somewhere else: hands-on, less fiddly work, because the group averages several US jobs together and this one doesn't. Both are right about what they describe.

finger skill 42.9 · hand skill 44.6 · cramped spaces 51 · hands-on 54.5 · caring 3.17 of 7 · rule: hands-on 50+ · fiddly 39.4+

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 0.01% 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

60
40

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 chefs be worried?

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

Not really. Cooking, seasoning and checking dishes rate Very Low. What AI takes is the office side of the kitchen: menus, costings, orders and allergen checks. High-volume kitchens may add more automated prep, and someone will need to run it.

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

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 →

Fancy a rematch?

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

Where this page's numbers come from