Will AI replace Animal Breeders?

Not as a job, but it is already doing parts of the work. Across the 21 official task statements scored for Animal Breeders (United States, SOC 45-2021), 4% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 15 out of 100 (range 13–20, band: minimal). 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 “Animal Breeders” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Maintain logs of semen specimens used and animals bred” (75/100, high); “Select animals to be bred, and semen specimens to be used, according to knowledge of animals, genealogies, traits, and desired offspring characteristics” (56/100, partial); “Record animal characteristics such as weights, growth patterns, and diets” (41/100, partial). 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 “Animal Breeders” stay human?

About 84% 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: “Exercise animals to keep them in healthy condition” (0/100, minimal); “Bathe and groom animals” (0/100, minimal); “Brand, tattoo, or tag animals to allow animal identification” (0/100, 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 “Animal Breeders” do about AI?

Start from the ledger rather than the headline: 4% of this job's weighted core work is exposed, and roughly 84% 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 Animal Breeders 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 21 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.

US dataswitch to UK

Animal Breeders

feeding and watering animals, selecting animals and adjusting controls to maintain specific building temperatures required for animals' health and safety. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: feeding and watering animals and cleaning and disinfect pens, cages, yards and hutches is work software can't reach.

Your move: what you can actually do about this ↓

Where the work sits, by task weight

shifting to AI: 4%
changing shape: 12%
staying human: 84%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

Whole-job exposure score 15 out of 100 (13–20 allowing for uncertainty): minimal exposure, across 21 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 animal breeders 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.

What shifts is maintaining logs of semen specimens used and animals: the paper around the work, not the work.

Your week, as this page understands it

Select and breed animals according to their genealogy, characteristics, and offspring. May require knowledge of artificial insemination techniques and equipment use. May involve keeping records on heats, birth intervals, or pedigree. The job title says “animal breeders”. The real job is the part underneath: feeding and watering animals and cleaning and disinfect pens, cages, yards and hutches. 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 animal breeders is not one task. It is 21 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is feeding and watering animals and cleaning and disinfect pens, cages, yards and hutches, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 4%
changing shape: 12%
staying human: 84%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

How we know this

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.

3 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

1 task

Tasks 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.

Maintaining logs of semen specimens used and animals
This is reading one thing and writing another: logs of semen specimens in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Maintain logs of semen specimens used and animals bred.” (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: Semen and breeding logs are structured records that software keeps easily.
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 tasks

Tasks 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.

Selecting animals
The software now makes the first pass at animals, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Select animals to be bred, and semen specimens to be used, according to knowledge of animals, genealogies, traits, and desired offspring characteristics.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 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: Breeding choices already run on pedigree and genetic records, which software ranks well.
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 0/4 · how much data exists 3/4.
Recording animal characteristics, weights, growth patterns and diets
The software now makes the first pass at animal characteristics, weights, growth patterns and diets, but part of it still happens in the physical world. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Record animal characteristics such as weights, growth patterns, and diets.” (O*NET task statement)
How this row was scored
Exposure score: 41 out of 100 (34–48 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Weights and growth data are structured records, though getting the animal onto the scales is physical.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.

Staying human

18 tasks

Tasks 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.

Feeding and watering animals and cleaning and disinfect pens, cages, yards and hutches
This work happens in the physical world: animals, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Feed and water animals, and clean and disinfect pens, cages, yards, and hutches.” (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: Feeding animals and cleaning pens is physical work in the barn.
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 2/4.
Observing animals in heat to detect approach of estrus and exercise animals to induce or hasten estrus
This work happens in the physical world: animals, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Observe animals in heat to detect approach of estrus and exercise animals to induce or hasten estrus, if necessary.” (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: Spotting when an animal is coming into heat takes watching and handling it in person.
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.
Purchasing and stocking supplies of feed and medicines
This work happens in the physical world: supplies, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Purchase and stock supplies of feed and medicines.” (O*NET task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Ordering feed and medicines is routine purchasing work; the stocking still happens on the farm.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Examining animals to detect symptoms of illness or injury
This work happens in the physical world: animals, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Examine animals to detect symptoms of illness or injury.” (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: Spotting illness means handling the animal and feeling for problems.
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 2/4.
Treating minor injuries and ailments and contacting veterinarians to obtain treatment for animals with serious illnesses or injuries
This work happens in the physical world: minor injuries, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Treat minor injuries and ailments and contact veterinarians to obtain treatment for animals with serious illnesses or injuries.” (O*NET task statement)
How this row was scored
Exposure score: 7 out of 100 (0–14 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Treating an injury is hands-on, even though calling the vet is only a phone call.
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.
Branding tattoo or tag animals to allow animal identification
This work happens in the physical world: tattoo, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Brand, tattoo, or tag animals to allow animal identification.” (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: Marking an animal for identification is a physical procedure.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Building hutches, pens and fenced yards
This work happens in the physical world: hutches, pens and fenced yards, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Build hutches, pens, and fenced yards.” (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: Building hutches, pens and fencing is construction work.
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.

Show the other 11 tasks

Adjusting controls to maintain specific building temperatures required for animals' health and safety
staying human
This work happens in the physical world: controls, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Adjust controls to maintain specific building temperatures required for animals' health and safety.” (O*NET task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Modern barn controllers hold temperature automatically, though someone still checks the building.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Arranging for sale of animals and eggs
staying human
The value here is that a specific person handles sale of animals and stands behind it. That is earned, not computed.
importance 4 · Supplemental
Source: “Arrange for sale of animals and eggs to hospitals, research centers, pet shops, and food processing plants.” (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: Sales can be arranged by message, but buyers deal with a breeder they know.
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.
Packaging and labelling semen to be used for artificial insemination
staying human
This work happens in the physical world: semen, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Package and label semen to be used for artificial insemination, recording information such as the date, source, quality, and concentration.” (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: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: The recording part is easy for software, but packaging and labeling straws is bench work.
The five ratings: output a model can produce 2/4 · 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 3/4.
Examining semen microscopically to assess and record density and motility of gametes
staying human
This work happens in the physical world: semen, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Examine semen microscopically to assess and record density and motility of gametes, and dilute semen with prescribed diluents, according to formulas.” (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: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Analysis software can read sperm motility, but the sample must be prepared and put under the microscope.
The five ratings: output a model can produce 2/4 · 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 3/4.
Placing vaccines in drinking water
staying human
This work happens in the physical world: vaccines, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Place vaccines in drinking water, inject vaccines, or dust air with vaccine powder to protect animals from diseases.” (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: Vaccinating animals is hands-on work in the shed.
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 2/4.
Exhibiting animals at shows
staying human
This work happens in the physical world: animals, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Exhibit animals at shows.” (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: Showing animals means handling them in the ring.
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 2/4.
Clipping or shearing hair on animals
staying human
This work happens in the physical world: hair, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Clip or shear hair on animals.” (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: Clipping and shearing is hand work on 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 0/4 · how much data exists 1/4.
Measuring specified amounts of semen into calibrated syringes
staying human
This work happens in the physical world: specified amounts of semen, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Measure specified amounts of semen into calibrated syringes, and insert syringes into inseminating guns.” (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: Drawing measured doses into syringes is bench work by hand.
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.
Injecting prepared animal semen into female animals for breeding purposes
staying human
This work happens in the physical world: prepared animal semen, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Inject prepared animal semen into female animals for breeding purposes, by inserting nozzle of syringe into vagina and depressing syringe plunger.” (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: Insemination is a physical procedure performed on 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 0/4 · how much data exists 2/4.
Bathing and grooming animals
staying human
This work happens in the physical world: animals, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Bathe and groom animals.” (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: Bathing and grooming animals is physical work.
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.
Exercising animals to keep them in healthy condition
staying human
This work happens in the physical world: animals, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Exercise animals to keep them in healthy condition.” (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: Exercising animals means being with them and moving them about.
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: $51,130a 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: 1,330in 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: logs of semen specimens in, a record out. The rows above are exactly that shape: maintaining logs of semen specimens used and animals and selecting animals. 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: feeding and watering animals and cleaning and disinfect pens, cages, yards and hutches is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 4% of this job's task weight sits in rows the software is already learning, 12% in rows that change shape rather than disappear, and 84% in rows it is nowhere near. That is the position, measured across 21 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. Maintaining logs of semen specimens used and animals 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 logs of semen specimens, 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 selecting animals. 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 animal breeders (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was farmworkers, farm, ranch, and aquacultural animals: only about 16% of its durable work is work you already do and it pays 28.3% less. And on the numbers you do not need one. This job scores 15/100 here, with only 4% of the task list in the top band, and “feed and water animals, and clean and disinfect pens, cages, yards, and…” 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.

Farmworkers, Farm, Ranch, and Aquacultural Animals
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already examine animals to detect symptoms of illness or injury, and their equivalent is to examine animals to detect illness, injury, or disease, and to check physical characteristics. Across both published task lists that is about 16% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 16% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on. It is a pay cut, in those words: $36,670 against your $51,130, 28.3% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →
Animal Caretakers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already examine animals to detect symptoms of illness or injury, 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 16% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 16% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on. It is a pay cut, in those words: $35,360 against your $51,130, 30.8% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →
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 examine animals to detect symptoms of illness or injury, and their equivalent is to examine animals to detect behavioral changes or clinical symptoms that could indicate illness…. Across both published task lists that is about 9% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 9% 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 $51,130, 25.4% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →

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: 4% of its task weight, across 21 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 feeding and watering animals and cleaning and disinfect pens, cages, yards and hutches 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.

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:

Farm workers

In UK official statistics this job is counted as Farmers 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.

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Why there is no community here

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No Space for animal breeders yet. Should there be one?

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Questions people ask about this job

Will AI replace Animal Breeders?: Not as a job, but it is already doing parts of the work. Across the 21 official task statements scored for Animal Breeders (United States, SOC 45-2021), 4% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 15 out of 100 (range 13–20, band: minimal). 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 “Animal Breeders” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Maintain logs of semen specimens used and animals bred” (75/100, high); “Select animals to be bred, and semen specimens to be used, according to knowledge of animals, genealogies, traits, and desired offspring characteristics” (56/100, partial); “Record animal characteristics such as weights, growth patterns, and diets” (41/100, partial). 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 “Animal Breeders” stay human?: About 84% 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: “Exercise animals to keep them in healthy condition” (0/100, minimal); “Bathe and groom animals” (0/100, minimal); “Brand, tattoo, or tag animals to allow animal identification” (0/100, 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 “Animal Breeders” do about AI?: Start from the ledger rather than the headline: 4% of this job's weighted core work is exposed, and roughly 84% 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 Animal Breeders 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 21 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.
3 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)
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.

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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}
}

Permalink

https://futureproof.collab365.com/data/2026-q4.1

Data as of release 2026-q4.1, published 2026-08-05. 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.