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Professionals · code 2132

Farming, forestry and fisheries advisers

AI can draft the advisory report. Walking the farm with a worried farmer is still your job.

Writing reports and running advice sessions for farmers is the one task AI could take a fair chunk of. It barely touches five of the twelve, including studying how trees grow and where fish migrate.

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

Farming, forestry and fisheries advisers study and provide assistance and advice on farm, forestry and fisheries management, including cultivation, fertilization, harvesting, soil erosion and composition, disease prevention, nutrition, crop rotation and marketing. They develop techniques for increasing productivity, and study and develop plans and policies for land and fisheries management. Tasks include - (a) collecting and analysing data and samples related to produce, feed, soil, water quality and other factors affecting farm, forest or fishery production; (b) advising on techniques for improving the production of crops, livestock and fish, and alternative production options; (c) advising on livestock and crop disease, control of pests and weeds, soil improvement, animal husbandry and feeding programmes; (d) studying the environmental factors affecting commercial crop production, pasture growth, animal breeding, fish stocks and the growth and health of forest trees; (e) studying the effects of cultivation techniques, soils, insects, diseases and fisheries practices on animal, crop, forestry and fisheries yield; (f) studying fish migration, growth, feeding and spawning, and devising methods of collecting, fertilizing, incubating and hatching fish eggs; (g) researching into characteristics, use capability and productivity of soils, and applying findings to development of improved agricultural, horticultural and forestry practices; (h) developing procedures and techniques for solving agricultural problems and improving the efficiency of production; (i) managing forest and fisheries resources to maximize their long-term commercial, recreational and environmental benefits; (j) studying the propagation and culture of forest trees, methods for improving the growth of stock, and the effects of thinning on forest yields; (k) investigating, planning and implementing management procedures to cope with the effects of fires, floods, droughts, soil erosion, pests and diseases; (l) preparing scientific reports and conducting advisory information sessions and lectures for farming, forestry and fishing communities and other groups. Examples of the occupations classified here: - Agronomist - Fisheries adviser - Forestry adviser - Forestry scientist - Horticultural scientist - Silviculturist - Soil scientist

  • forestry adviser
  • fisheries adviser
  • agricultural scientist
  • aquaculture recirculation manager
  • agronomist
  • livestock advisor

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

72 / 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

230 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 12 tasks for how much of it AI could do. They average 28.5 out of 100, so it holds up at 100 − 28.5 = 71.5.

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 46.6 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?

Farming, forestry and fisheries advisers 72

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.

  • Reports and advisory materials.
  • Analysing crop, soil and fisheries data.
  • Research summaries.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Advising farmers and fishers in person.
  • Fieldwork and sampling.
  • Planning for floods, fires and droughts.

Both

What's arriving

New work that only exists because the AI does.

  • Advice delivered through apps.
  • Climate adaptation.
  • Precision farming data.

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

34 could do without you

It could take over very little of the work on its own. It could help with 74 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Some

47 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 24 out of 100. The higher it is, the longer the robot waits.

47 How
hands-on
24 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 3 US jobs .

finger skill 29.1 · hand skill 25 · cramped spaces 17.1 · 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 54, against an average of 29. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 54

    Preparing scientific reports and conducting advisory information sessions and lectures for farming, forestry and fishing communities and other groups.

    Medium
  2. 37

    Developing procedures and techniques for solving agricultural problems and improving the efficiency of production

    Low
  3. 35

    Advising on techniques for improving the production of crops, livestock and fish, and alternative production options

    Low
  4. 32

    Advising on livestock and crop disease, control of pests and weeds, soil improvement, animal husbandry and feeding programmes

    Low
  5. 31

    Managing forest and fisheries resources to maximize their long-term commercial, recreational and environmental benefits

    Low
  6. 28

    Studying the environmental factors affecting commercial crop production, pasture growth, animal breeding, fish stocks and the growth and health of forest trees

    Low
  7. 27

    Researching into characteristics, use capability and productivity of soils and applying findings to development of improved agricultural, horticultural and forestry practices

    Low
  8. 25

    Investigating, planning and implementing management procedures to cope with the effects of fires, floods, droughts, soil erosion, pests and diseases

    Very Low
  9. 24

    Studying the effects of cultivation techniques, soils, insects, diseases and fisheries practices on animal, crop, forestry and fisheries yield

    Very Low
  10. 20

    Collecting and analysing data and samples related to produce, feed, soil, water quality and other factors affecting farm, forest or fishery production

    Very Low
  11. 18

    Studying the propagation and culture of forest trees, methods for improving the growth of stock, and the effects of thinning on forest yields

    Very Low
  12. 14

    Studying fish migration, growth, feeding and spawning and devising methods of collecting, fertilizing, incubating and hatching fish eggs

    Very Low

12 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
74
AI does it for you
34

Sidekick wins, by 40 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 2341, 2343

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 0.04% 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.

The data is sorted by US job, and this one matches 2 of them. We've combined them, counting each by how often it comes up in the conversations, so the busiest one counts most.

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 agricultural and fisheries advisers be worried?

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

Parts of it are changing. Preparing reports and advisory sessions is rated Medium, and developing techniques, advising on production and disease, managing resources and research are Low; disaster planning, fieldwork and sampling rate Very Low. AI will help with reports and analysis; advice built on trust 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 92 jobs in the “Professionals” family, averaging 61. This one is above the family average.

Pit this against any other job →