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Craft and related trades workers · code 7514

Fruit, vegetable and related preservers

AI can cost the recipe. Getting the jam to set is still judgement.

AI barely touches any of the five tasks, from mixing preserving ingredients and pressing juice and oil to filling jars and bottles.

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

Fruit, vegetable and related preservers process or preserve fruit, nuts and related foods in various ways including cooking, drying and salting, or juice or oil extraction. Tasks include - (a) extracting juices from various fruits; (b) extracting oils from oil-bearing seeds, nuts or fruits; (c) cooking, salting or drying fruit, vegetables and related foods; (d) mixing and adding ingredients such as pectin, sugar, spices and vinegar to assist preservation and enhance texture, appearance and flavour; (e) transferring preserved foods to sterile jars, bottles or other containers. Examples of the occupations classified here: - Chutney maker - Fruit preserver - Jam maker - Oil expeller - Vegetable and fruit pickler - Vegetable preserver Some related occupations classified elsewhere: - Canning machine operator - 8183

  • fruit and vegetable preserver
  • oilseed presser
  • oil mill operator

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

85 / 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

73 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 5 tasks for how much of it AI could do. They average 14.8 out of 100, so it holds up at 100 − 14.8 = 85.2.

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 63 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?

Fruit, vegetable and related preservers 85

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.

  • Recipe costing and batch planning.
  • Food safety and labelling records.
  • Stock and supplier orders.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Judging ripeness, flavour and texture.
  • Cooking and preserving in small batches.
  • Keeping food safe by hand and eye.

Both

What's arriving

New work that only exists because the AI does.

  • Artisan and local food sold online.
  • Stricter allergen and labelling rules.
  • Supervising automated bottling and packing.

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

21 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: Higher

63 how hands-on

Most of this job needs hands, a body or turning up. That's robot territory, and nobody measures how far robots have got well enough to give you a number. We won't make one up.

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

63 How
hands-on
30 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 32.1 · hand skill 35.7 · cramped spaces 21.3 · 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 21, against an average of 15. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 21

    Mixing and adding ingredients such as pectin, sugar, spices and vinegar to assist preservation and enhance texture, appearance and flavour

    Very Low
  2. 15

    Extracting juices from various fruits

    Very Low
  3. 14

    Cooking, salting or drying fruit, vegetables and related foods

    Very Low
  4. 14

    Transferring preserved foods to sterile jars, bottles or other containers.

    Very Low
  5. 10

    Extracting oils from oil-bearing seeds, nuts or fruits

    Very Low

5 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
21

Sidekick wins, by 33 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 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 under 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

47
53

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 food preservers be worried?

Short answer: not really. Put the kettle on.

No. Every task rates Very Low; the most exposed is mixing ingredients to preserve and flavour food. Processing lines are increasingly automated, but small-batch and artisan production stays 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 83. This one is above the family average.

Pit this against any other job →