Skilled agricultural, forestry and fishery workers · code 6112

Tree and shrub crop growers

AI can predict the harvest date. Pruning the vines is still done by hand.

AI barely touches eight of the eleven tasks, including preparing the soil and keeping farm buildings and machinery going. Watching the market and arranging sales are mostly out of its reach too.

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

Tree and shrub crop growers plan, organize and perform farming operations to grow and harvest trees and shrubs such as fruit and nut trees, tea and coffee bushes, grape vines, berry-bearing bushes, cocoa trees and rubber trees, and to collect sap, for sale or delivery on a regular basis to wholesale buyers, marketing organizations or at markets. Tasks include - (a) monitoring market activity and conditions, determining types and quantities of crops to be grown, and planning and coordinating production accordingly; (b) preparing soil by hand or machine, and spreading fertilizers and manure; (c) selecting and sowing seeds, and planting seedlings; (d) maintaining crops by cultivating soil, by transplanting, pruning or thinning trees and shrubs, and by setting up and operating irrigation equipment; (e) controlling weeds, pests and diseases by applying herbicides and pesticides; (f) tending trees or bushes, collecting sap and harvesting crops; (g) inspecting, cleaning, grading, packaging, storing and loading crops for sale or delivery to market; (h) tending working animals and maintaining farm buildings, structures, equipment and water supply systems; (i) storing and carrying out some processing of produce; (j) promoting and marketing products, arranging the sale, purchase and transportation of produce and supplies, and maintaining and evaluating records of farm activities and transactions; (k) training and supervising workers in crop production, maintenance duties, and health and safety precautions, and hiring and discharging workers and contractors. Examples of the occupations classified here: - Fruit farmer - Rubber farmer - Rubber tapper - Tea grower - Viticulturist Some related occupations classified elsewhere: - Plantation manager - 1311 - Fruit picker - 9211

fruit production team leader
vineyard cellar master
vineyard manager
vineyard machinery operator
arboriculturist
hop farmer

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

97 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 11 tasks for how much of it AI could do. They average 17.1 out of 100, so it holds up at 100 − 17.1 = 82.9.

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 73 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?

Tree and shrub crop growers 83

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.

Deciding what to grow from market data.
Marketing, sales and records.
Monitoring crops with drones and sensors.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

Pruning, thinning and harvesting.
Judging ripeness and quality.
Managing workers through the season.

Both

What's arriving

New work that only exists because the AI does.

Harvesting and spraying robots.
Precision irrigation.
Selling direct, and through wine tourism.

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.

– could do without you

We don't have a measure of how much of this job AI could take over.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Higher

73 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.

73 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, averaged across 2 US jobs .

finger skill 39.3 · hand skill 41.1 · 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 43, 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.

43
Monitoring market activity and conditions, determining types and quantities of crops to be grown, and planning and coordinating production accordingly

Low
32
Promoting and marketing products, arranging the sale, purchase and transportation of produce and supplies and maintaining and evaluating records of farm activities and transactions

Low
26
Training and supervising workers in crop production, maintenance duties, and health and safety precautions, and hiring and discharging workers and contractors.

Low
14
Controlling weeds, pests and diseases by applying herbicides and pesticides

Very Low
14
Inspecting, cleaning, grading, packaging, storing and loading crops for sale or delivery to market

Very Low
12
Storing and carrying out some processing of produce

Very Low
12
Selecting and sowing seeds, and planting seedlings

Very Low
11
Maintaining crops by cultivating soil, by transplanting, pruning or thinning trees and shrubs, and by setting up and operating irrigation equipment

Very Low
10
Tending trees or bushes, collecting sap and harvesting crops

Very Low
9
Tending working animals and maintaining farm buildings, structures, equipment and water supply systems

Very Low
8
Preparing soil by hand or machine, and spreading fertilizers and manure

Very Low

11 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

So, should orchard and vineyard growers be worried?

Short answer: not really. Put the kettle on.

Parts of the business side are changing. Planning production and marketing are the most exposed, both Low; growing, pruning and harvesting rate Very Low. Drones, sensors and harvesting robots are arriving, but orchards and vineyards still need skilled people.

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 18 jobs in the “Skilled agricultural, forestry and fishery workers” family, averaging 84. This one is below the family average.

Pit this against any other job →