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Managers · code 1311

Agricultural and forestry production managers

AI can run the farm budget. It can't walk the fields and see what the weather did overnight.

AI barely touches seven of the twelve tasks, including organising the farm and directing planting and harvest. Budgets and production records are the one task it could take a fair chunk of.

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

Agricultural and forestry production managers plan, direct and coordinate production in large-scale agricultural, horticultural and forestry operations such as plantations, large ranches, collective farms and agricultural cooperatives to grow and harvest crops, and breed and raise livestock. Tasks include - (a) monitoring agricultural and forestry market activity and planning production to meet contract requirements and market demand; (b) establishing and managing budgets, monitoring production output and costs, recording information such as farm management practices, and preparing financial and operational reports; (c) conferring with buyers to arrange for the sale of crops and livestock; (d) contracting with farmers or independent owners for production of crops and livestock, or for management of production; (e) planning the type, intensity and sequence of farm operations (e.g. determining the best times for planting, spraying and harvesting); (f) analysing soil to determine types and quantities of fertilizer required for maximum production; (g) purchasing machinery, equipment and supplies such as tractors, seed, fertilizer and chemicals; (h) identifying and controlling agricultural and forest environmental toxins, weeds, pests and diseases; (i) organizing farming operations such as maintaining buildings, water supply systems and equipment; (j) directing and coordinating activities such as planting, irrigation, chemical application, harvesting and grading; (k) inspecting plantations and fields to determine maturity dates of crops, or to estimate potential crop damage from weather; (l) overseeing the selection, training and performance of agricultural and forestry workers and contractors. Examples of the occupations classified here: - Forestry manager - Plantation manager - Ranch manager

  • forester

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

73 / 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: Minimal Exposure

211 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 27 out of 100, so it holds up at 100 − 27 = 73.

That's the whole sum. No black box, no secret sauce: you can check it against the ILO's study. ILO group “Minimal Exposure”: A few tasks are affected, but the heart of the job isn't.

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 62 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?

Agricultural and forestry production managers 73

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.

  • Budgets, costs and production records.
  • Planning operations around markets and weather.
  • Soil analysis and fertiliser plans.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Inspecting crops and forests in person.
  • Managing workers and contractors.
  • Decisions when the season goes wrong.

Both

What's arriving

New work that only exists because the AI does.

  • Precision farming data from sensors and drones.
  • Carbon and biodiversity schemes.
  • Climate adaptation planning.

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: Medium

38 could do without you

It could take over some of the work, and help with more. It could help with 69 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Higher

62 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 34 out of 100. The higher it is, the longer the robot waits.

62 How
hands-on
34 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 35.7 · hand skill 35.7 · cramped spaces 31.3 · 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 57, against an average of 27. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 56

    Establishing and managing budgets, monitoring production output and costs, recording information such as farm management practices, and preparing financial and operational reports

    Medium
  2. 42

    Monitoring agricultural and forestry market activity and planning production to meet contract requirements and market demand

    Low
  3. 40

    Planning the type, intensity and sequence of farm operations (e.g. determining the best times for planting, spraying and harvesting)

    Low
  4. 26

    Conferring with buyers to arrange for the sale of crops and livestock

    Low
  5. 25

    Analysing soil to determine types and quantities of fertilizer required for maximum production

    Low
  6. 25

    Inspecting plantations and fields to determine maturity dates of crops, or to estimate potential crop damage from weather

    Very Low
  7. 24

    Contracting with farmers or independent owners for production of crops and livestock, or for management of production

    Very Low
  8. 22

    Overseeing the selection, training and performance of agricultural and forestry workers and contractors.

    Very Low
  9. 19

    Identifying and controlling agricultural and forest environmental toxins, weeds, pests and diseases

    Very Low
  10. 18

    Purchasing machinery, equipment, and supplies such as tractors, seed, fertilizer, and chemicals

    Very Low
  11. 14

    Organizing farming operations such as maintaining buildings, water supply systems and equipment

    Very Low
  12. 14

    Directing and coordinating activities such as planting, irrigation, chemical application, harvesting, and grading

    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
69
AI does it for you
38

Sidekick wins, by 31 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 1213, 1215, 1216, 1217, 1335

So, should farm and forestry managers be worried?

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

The office side is moving. Budgets and production records are rated Medium, and market planning, scheduling operations, sales and soil analysis are Low; inspecting fields, managing workers and controlling pests rate Very Low. Farm software will take on more planning; running the land 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 30 jobs in the “Managers” family, averaging 64. This one is above the family average.

Pit this against any other job →