US dataswitch to UK
First-Line Supervisors of Farming, Fishing, and Forestry Workers
assigning tasks, communicating with forestry personnel regarding forest harvesting or forest management plans and inspecting crops. If that's your week, this page is about your job.
The honest answer
AI is already taking a real slice of the routine work here: scheduling work crews, equipment or transportation for several different work locations. That is a slice of tasks, not of you.
That slice is not coming back; the core of the job, observing animals for signs of illness, stays yours. New tools, same person answering for it.
Your week, as this page understands it
Directly supervise and coordinate the activities of agricultural, forestry, aquacultural, and related workers. The job title says “first-line supervisors of farming”, “fishing” or “forestry workers”: officially one job, several names. The real job is the part underneath: observing animals for signs of illness. That is the thing someone has to be right about.
The exposed part of this job is specific, and we won’t pretend it is coming back. But first-line supervisors of farming, fishing, and forestry workers is not one task. It is 30 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is observing animals for signs of illness, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 17%
- changing shape
- 8%
- staying human
- 76%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 26 out of 100 (21–31 allowing for uncertainty): low exposure, across 30 scored tasks. The number is the support for the sentence above it, not a headline about anyone’s future.
How we know this
What is measured: Every published task statement for first-line supervisors of farming, fishing, and forestry workers is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.
How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.
Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.
Your job, task by task
These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.
- 1 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
Shifting to AI
6 tasksTasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.
Scheduling work crews, equipment or transportation for several different work locations
This is reading one thing and writing another: work crews, equipment or transportation in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Schedule work crews, equipment, or transportation for several different work locations.” (O*NET task statement)
How this row was scored
Exposure score: 68 out of 100 (61–75 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; mistakes that are cheap to catch.
The rating behind it: Building a crew and transport roster is exactly the kind of planning software does well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Requisitioning or purchasing supplies, such as insecticides, machine parts or lubricants or tools
This is reading one thing and writing another: supplies in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Requisition or purchase supplies, such as insecticides, machine parts or lubricants, or tools.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (62–70 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Ordering supplies is a documented purchasing process, though some chemicals need a licensed buyer.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Preparing and maintaining time or payroll reports
This is reading one thing and writing another: time in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Prepare and maintain time or payroll reports, as well as details of personnel actions, such as performance evaluations, hires, promotions, or disciplinary actions.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (60–68 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Time sheets, payroll figures and personnel records are routine paperwork built from data already in systems.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Reading inventory records, customer orders or shipping schedules to determine required activities
This is reading one thing and writing another: inventory records, customer orders or shipping schedules in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Read inventory records, customer orders, or shipping schedules to determine required activities.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Reading orders and inventory records to work out what needs doing is desk work on existing data.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Changing shape
2 tasksTasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.
Recording the numbers and types of fish or shellfish
The software now makes the first pass at the numbers, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Record the numbers and types of fish or shellfish reared, harvested, released, sold, and shipped.” (O*NET task statement)
How this row was scored
Exposure score: 49 out of 100 (42–56 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Recording catches and stock movements is routine data work, with returns checked by the manager.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Performing both supervisory and management functions
The software now makes the first pass at both supervisory, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Perform both supervisory and management functions, such as accounting, marketing, and personnel work.” (O*NET task statement)
How this row was scored
Exposure score: 48 out of 100 (41–55 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Accounts, marketing copy and personnel paperwork are standard office tasks with good tool support.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Staying human
22 tasksTasks that stay with a person, because they happen in the physical world, because the rules need someone accountable, or because the value is that a specific person does them.
Observing animals for signs of illness
This work happens in the physical world: animals, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Observe animals for signs of illness, injury, or unusual behavior, notifying veterinarians or managers as warranted.” (O*NET task statement)
How this row was scored
Exposure score: 5 out of 100 (1–9 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Noticing that an animal is off-color comes from being with the animals and years of feel.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 1/4.
Monitoring workers to ensure that safety regulations
This work happens in the physical world: workers, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Monitor workers to ensure that safety regulations are followed, warning or disciplining those who violate safety regulations.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (2–10 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Spotting unsafe behavior and correcting someone on the spot needs a supervisor physically watching.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Training workers in spawning, rearing, cultivating and harvesting methods and in the use of equipment
This work happens in the physical world: workers, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Train workers in spawning, rearing, cultivating, and harvesting methods, and in the use of equipment.” (O*NET task statement)
How this row was scored
Exposure score: 20 out of 100 (13–27 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Written training guides help, but the practical part is demonstrated at the tanks and ponds.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Assigning tasks, feeding and treatment of animals and cleaning and maintenance of animal quarters
The ratings behind this row put tasks, feeding and treatment of animals well outside what today's tools can do on their own.
importance 4 · CoreSource: “Assign tasks such as feeding and treatment of animals, and cleaning and maintenance of animal quarters.” (O*NET task statement)
How this row was scored
Exposure score: 32 out of 100 (25–39 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: A daily task list can be drafted, but who does what depends on local knowledge of the crew.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Show the other 20 tasks
Calculating or monitoring budgets for maintenance or development of collections
shifting to AIThis is reading one thing and writing another: budgets in, a record out. That is the shape today's tools are built for.
importance 3 · CoreSource: “Calculate or monitor budgets for maintenance or development of collections, grounds, or infrastructure.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Budget calculation and tracking is desk work built on figures already held in the accounting system.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Planning work schedules according to personnel and equipment availability
shifting to AIThis is reading one thing and writing another: work schedules in, a record out. That is the shape today's tools are built for.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Plan work schedules according to personnel and equipment availability.” (O*NET task statement)
How this row was scored
Exposure score: 68 out of 100 (61–75 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; mistakes that are cheap to catch.
The rating behind it: Matching shifts to available people and machines is a planning problem software handles well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Conferring with managers to evaluate weather or soil conditions
staying humanThe value here is that a specific person handles managers and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Confer with managers to evaluate weather or soil conditions, to develop plans or procedures, or to discuss issues such as changes in fertilizers, herbicides, or cultivating techniques.” (O*NET task statement)
How this row was scored
Exposure score: 30 out of 100 (23–37 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Weather and soil data can be summarized, but the decision is made in conversation between managers.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Conferring with managers to determine production requirements
staying humanThe value here is that a specific person handles managers and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Confer with managers to determine production requirements, conditions of equipment and supplies, and work schedules.” (O*NET task statement)
How this row was scored
Exposure score: 30 out of 100 (23–37 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Production figures can be prepared, but agreeing the plan happens in discussion with managers.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Communicating with forestry personnel regarding forest harvesting or forest management plans
staying humanThe value here is that a specific person handles forestry personnel regarding forest and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Communicate with forestry personnel regarding forest harvesting or forest management plans, procedures, or schedules.” (O*NET task statement)
How this row was scored
Exposure score: 26 out of 100 (19–33 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Schedules and plans can be drafted, though the coordination happens through back-and-forth with forestry staff.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Coordinating the selection and movement of logs from storage areas
staying humanThis work happens in the physical world: the selection, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Coordinate the selection and movement of logs from storage areas, according to transportation schedules or production requirements.” (O*NET task statement)
How this row was scored
Exposure score: 21 out of 100 (14–28 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: The scheduling half can be handled by software, but selecting and moving logs happens in the yard.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Monitoring operations to identify and solve problems
staying humanThis work happens in the physical world: operations, in a real place. Software cannot follow it there.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Monitor operations to identify and solve problems, improve work methods, and ensure compliance with safety, company, and government regulations.” (O*NET task statement)
How this row was scored
Exposure score: 21 out of 100 (14–28 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Compliance checklists can be prepared, but spotting operational problems means watching the work happen.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Training workers in tree felling or bucking
staying humanThis work happens in the physical world: workers, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Train workers in tree felling or bucking, operation of tractors or loading machines, yarding or loading techniques, or safety regulations.” (O*NET task statement)
How this row was scored
Exposure score: 20 out of 100 (13–27 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Course material can be drafted, but showing someone how to fell a tree safely happens in person.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Training workers in techniques, planting, harvesting, weeding or insect identification and in the use of safety measures
staying humanThis work happens in the physical world: workers, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Train workers in techniques such as planting, harvesting, weeding, or insect identification and in the use of safety measures.” (O*NET task statement)
How this row was scored
Exposure score: 20 out of 100 (13–27 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Guides and identification aids are strong, but the field demonstration still needs a person present.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Monitoring or overseeing construction projects
staying humanThis work happens in the physical world: construction projects, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Monitor or oversee construction projects, such as horticultural buildings or irrigation systems.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (7–21 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Watching a build progress and catching problems early needs someone on site.
The five ratings: output a model can produce 1/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Inspecting crops, fields or plant stock to determine conditions and need for cultivating, spraying, weeding or harvesting
staying humanThis work happens in the physical world: crops, fields or plant stock, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Inspect crops, fields, or plant stock to determine conditions and need for cultivating, spraying, weeding, or harvesting.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (4–12 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Judging whether a field needs spraying or harvesting comes from walking it and looking closely.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Inspecting buildings, fences, fields or ranges, supplies and equipment to determine work
staying humanThis work happens in the physical world: buildings, fences, fields or ranges, supplies and equipment, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Inspect buildings, fences, fields or ranges, supplies, and equipment to determine work to be performed.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (4–12 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Checking fences, fields and equipment means walking the property and looking at them.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Inspecting facilities to determine maintenance needs
staying humanThis work happens in the physical world: facilities, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Inspect facilities to determine maintenance needs.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (4–12 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Spotting what needs fixing in a building or yard requires being there to see it.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Issuing equipment, such as farm implements, machinery, ladders or containers to workers and collecting equipment when work is complete
staying humanThis work happens in the physical world: equipment, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Issue equipment, such as farm implements, machinery, ladders, or containers to workers, and collect equipment when work is complete.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (4–12 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Handing out and collecting tools and machinery is physical work at the yard.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Coordinating dismantling, moving and setting up equipment at new work sites
staying humanThis work happens in the physical world: equipment, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Coordinate dismantling, moving, and setting up equipment at new work sites.” (O*NET task statement)
How this row was scored
Exposure score: 7 out of 100 (3–11 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Moving and re-erecting equipment at a new site is physical work on the ground.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Transporting or arranging for transport of animals
staying humanThis work happens in the physical world: transport of animals, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Transport or arrange for transport of animals, equipment, food, animal feed, and other supplies to and from work sites.” (O*NET task statement)
How this row was scored
Exposure score: 7 out of 100 (3–11 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Moving animals, feed and equipment around is physical work, even when the booking part is not.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Directing or assisting with the adjustment or repair of equipment or machinery
staying humanThis work happens in the physical world: the adjustment, in a real place. Software cannot follow it there.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Direct or assist with the adjustment or repair of equipment or machinery.” (O*NET task statement)
How this row was scored
Exposure score: 7 out of 100 (3–11 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Adjusting or repairing machinery means hands on the machine.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Observing fish and beds or ponds to detect diseases
staying humanThis work happens in the physical world: fish, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Observe fish and beds or ponds to detect diseases, monitor fish growth, determine quality of fish, or determine completeness of harvesting.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (2–10 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Judging fish health and pond condition depends on being at the water and handling stock.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Treating animal illnesses or injuries
staying humanThis work happens in the physical world: animal illnesses, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Treat animal illnesses or injuries, following experience or instructions of veterinarians.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Treating a sick or injured animal is hands-on work with the animal.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 1/4.
Driving or operating farm machinery
staying humanThis work happens in the physical world: farm machinery, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Drive or operate farm machinery, such as trucks, tractors, or self-propelled harvesters, to transport workers or supplies or to cultivate or harvest fields.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Driving a tractor or harvester requires someone in the cab.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
What this job pays, and how many people do it
- Median pay
- $59,320a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
- People doing this job
- 27,960in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)
What is deliberately not here: a forecast of how many of these jobs exist in ten years. Where an official projection exists for a market we publish it with its vintage; where it does not, we leave the space empty rather than borrow the other country’s number.
Why this is shifting
The reason is boringly specific. Most of what is shifting here is reading one thing and writing another: work crews, equipment or transportation in, a record out. The rows above are exactly that shape: scheduling work crews, equipment or transportation for several different work locations and requisitioning or purchasing supplies, such as insecticides. What it cannot do is be there in the room, and that is still where animals get done. Which is why this page talks about your tasks changing, not your job ending.
Your move
Over a pint: what I’d tell you if you were my friend
Start with what does not change: observing animals for signs of illness is the middle of this job, and the evidence on this page says it stays with a person.
So, given all that: 17% of this job's task weight sits in rows the software is already learning, 8% in rows that change shape rather than disappear, and 76% in rows it is nowhere near. That is the position, measured across 30 scored tasks. It is not a forecast about you.
So the thing worth your attention is not the job going away. It is the layer around it. Scheduling work crews, equipment or transportation for several different work locations is the part turning into software, and being the person who understands that layer is worth money.
This week: one thing
Ask the one question. Find whoever is bringing new software into your workplace (the manager, the office, whoever runs the system) and ask them what it is meant to do to work crews, equipment or transportation, and what it is not meant to touch. Ten minutes, this week, before anyone decides it for you.
- What you end up holding
- a straight answer about what is actually being rolled out, and when
- How long it takes
- ten minutes
If there’s nobody obvious to ask, or you’d rather not ask your manager: Put the same question to your union rep, your shift lead or the person who has been there longest, in person, over a break. Same ten minutes, same answer, and you will usually get a straighter one. Write down what they say. The note is the artifact, and it tells you whether animals are in scope or not. Nothing to log into, no license needed.
Over the next 90 days
Get inside the tool rollout rather than waiting for it. Over the next ninety days, ask to be in the group that tests, checks or signs off whatever new system arrives near recording the numbers and types of fish or shellfish. It is usually an unglamorous seat that nobody fights for, and it is the one that decides how the software is used on your job rather than to it.
Over the next 12 months
On this evidence I would not retrain out of this job, and I will say that plainly rather than hedge it. The task list here is dominated by work that stays with a person. What I would do with a year is get formally recognised for the layer around it (the systems, the compliance, the planning), so you are the one who understands the software instead of the one it is done to. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, and it is listed below with the rest of the free routes.
The roads out of here, and why I am not sending you down them
I looked at the obvious moves out of this job, and here is what I found.
I checked the 12 nearest US occupations to first-line supervisors of farming, fishing, and forestry workers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was animal caretakers: only about 7% of its durable work is work you already do and it pays 40.4% less. And on the numbers you do not need one. This job scores 26/100 here, with only 17% of the task list in the top band, and “observe animals for signs of illness, injury, or unusual behavior, notifying veterinarians…” is not work that hands over cleanly. None of them beats deepening what you already have.
How that was checked: this job was compared against all 830 US occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.
3 moves I checked and rejected
These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.
Animal Caretakers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already observe animals for signs of illness, injury, or unusual behavior, notifying veterinarians or…, and their equivalent is to examine and observe animals to detect signs of illness, disease, or injury. Across both published task lists that is about 7% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 7% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $35,360 against your $59,320, 40.4% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Farmers, Ranchers, and Other Agricultural Managers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already inspect facilities to determine maintenance needs, and their equivalent is to inspect facilities and equipment for signs of disrepair, and perform necessary maintenance work. Across both published task lists that is about 7% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 7% of the durable side of that job. That is a different job, not a next step. And it is a narrow door: about 6,500 of those jobs against 27,960 of yours (OEWS May 2025), 23% as many seats.
Veterinary Assistants and Laboratory Animal Caretakers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already treat animal illnesses or injuries, following experience or instructions of veterinarians, and their equivalent is to assist veterinarians in examining animals to determine the nature of illnesses or injuries. Across both published task lists that is about 5% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 5% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $38,150 against your $59,320, 35.7% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
What I’d stop worrying about
A friend tells you what not to spend fear on. This is that list.
The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 17% of its task weight, across 30 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The headlines about your trade disappearing
They are usually about the technology, not the timetable. Changes to work like observing animals for signs of illness arrive through rules, insurance and money, slowly and visibly. This page tracks the task evidence and will move when it moves.
Retraining out of a job that is holding up
On this evidence I would not spend money leaving. Spend it on the layer around the job instead: the tools, the paperwork, the planning. That is where the change actually is.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.
If you run a team doing this job
If you run a team doing this job, the conversation you owe them is the one on this page, and sooner than feels comfortable. Show them the ledger rather than a reassurance: the rows moving toward the software are scheduling work crews, equipment or transportation for several different work locations, and the rows that are not are where you want your people visible. Ask each of them to do the this-week move and bring the list to your next one-to-one. It turns a rumour into a piece of work, and it tells you which parts of your team's week are actually at stake. And say the thing out loud that a team lead usually leaves unsaid: a shrinking team is your exposure too, so do the move yourself as well.
You are reading the United States figures
The United Kingdom splits this work across more than one official group, of which Farmers is the closest. The pay and employment figures are not directly comparable, and we do not average them together.
Switch to the United Kingdom page →partial match
The other groups this work is counted across:
In UK official statistics this job is counted as Farmers, Horticultural trades, Forestry and related workers and Farm workers. Pay is shown separately for each of those groups (medians cannot be averaged together), while the task list and the scores on this page are for this group only.
Your route through this
Where to go next, and what it costs
Free, and complete
The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.
Anywhere in the US:
CareerOneStop - Find local training
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Anywhere in the US:
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Anywhere in the US:
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Anywhere in the US:
Free
No Space for this job, but one for what is happening to it
Nothing Collab365 runs is built for first-line supervisors of farming / fishing / forestry workers, and we are not going to point you at the nearest one and call it a fit.
There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 17% of the work on this page is already inside what they can do.
7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.
The AI Authority is a general community about working with AI, not a course for first-line supervisors of farming / fishing / forestry workers. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.
Noted, and thank you. We’ll email you if a Space for first-line supervisors of farming / fishing / forestry workers launches. Nothing else.
That did not look like an email address, so nothing was saved. Have another go below.
We could not save that. The fault is ours, not yours, and your address was not stored. Please try again later.
No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.
Questions people ask about this job
- Will AI replace First-Line Supervisors of Farming, Fishing, and Forestry Workers?
- Not as a job, but it is already doing parts of the work. Across the 30 official task statements scored for First-Line Supervisors of Farming, Fishing, and Forestry Workers (United States, SOC 45-1011), 17% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 26 out of 100 (range 21–31, band: low). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
- Which tasks in “First-Line Supervisors of Farming, Fishing, and Forestry Workers” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Read inventory records, customer orders, or shipping schedules to determine required activities” (75/100, high); “Calculate or monitor budgets for maintenance or development of collections, grounds, or infrastructure” (75/100, high); “Schedule work crews, equipment, or transportation for several different work locations” (68/100, high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
- Which tasks in “First-Line Supervisors of Farming, Fishing, and Forestry Workers” stay human?
- About 76% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Drive or operate farm machinery, such as trucks, tractors, or self-propelled harvesters, to transport workers or supplies or to cultivate or harvest fields” (0/100, minimal); “Treat animal illnesses or injuries, following experience or instructions of veterinarians” (0/100, minimal); “Observe animals for signs of illness, injury, or unusual behavior, notifying veterinarians or managers as warranted” (5/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
- What should someone working in “First-Line Supervisors of Farming, Fishing, and Forestry Workers” do about AI?
- Start from the ledger rather than the headline: 17% of this job's weighted core work is exposed, and roughly 76% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.
- How is the AI exposure score for First-Line Supervisors of Farming, Fishing, and Forestry Workers calculated?
- Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 30 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.
Where these numbers come from
Worth knowing about these figures
- The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
- 1 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
- Task statements
- onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
- Task weights
- onet-db (im-rt-with-imputed)
- Scores
- Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
- Pay and employment
- bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))
Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.
The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.
The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.
Using these figures?
Cite this
Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.
Plain text
Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).
BibTeX
@misc{collab365futureproof2026q41,
title = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
author = {{Collab365}},
year = {2026},
url = {https://futureproof.collab365.com/data/2026-q4.1},
note = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}Data as of release 2026-q4.1, published . Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.