Will AI replace Animal Control Workers?

Not as a job, but it is already doing parts of the work. Across the 16 official task statements scored for Animal Control Workers (United States, SOC 33-9011), 7% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 19 out of 100 (range 15–24, 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 Control Workers” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Answer inquiries from the public concerning animal control operations” (64/100, high); “Write reports of activities, and maintain files of impoundments and dispositions of animals” (56/100, partial); “Contact animal owners to inform them that their pets are at animal holding facilities” (53/100, 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 Control Workers” stay human?

About 79% 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: “Clean facilities and equipment such as dog pens and animal control trucks” (0/100, minimal); “Supply animals with food, water, and personal care” (0/100, minimal); “Euthanize rabid, unclaimed, or severely injured animals” (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 Control Workers” do about AI?

Start from the ledger rather than the headline: 7% of this job's weighted core work is exposed, and roughly 79% 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 Control 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 16 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 Control Workers

writing reports of activities, removing captured animals from animal-control service vehicles and placing animals in shelter cages or other enclosures and answering inquiries from the public concerning animal control operations. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: examining animals for injuries or malnutrition 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: 7%
changing shape: 14%
staying human: 79%

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

Whole-job exposure score 19 out of 100 (15–24 allowing for uncertainty): minimal exposure, across 16 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 control 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.

What shifts is answering inquiries from the public concerning animal control operations: the paper around the work, not the work.

Your week, as this page understands it

Handle animals for the purpose of investigations of mistreatment, or control of abandoned, dangerous, or unattended animals. The job title says “animal control workers”. The real job is the part underneath: examining animals for injuries or malnutrition. 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 control workers is not one task. It is 16 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is examining animals for injuries or malnutrition, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 7%
changing shape: 14%
staying human: 79%

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.

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.

Answering inquiries from the public concerning animal control operations
This is reading one thing and writing another: inquiries in, a record out. That is the shape today's tools are built for.
importance 5 · Core
Source: “Answer inquiries from the public concerning animal control operations.” (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: Answering common public questions about animal control is standard information handling.
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.

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.

Writing reports of activities and maintaining files of impoundments and dispositions of animals
The software now makes the first pass at reports of activities, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 5 · Core
Source: “Write reports of activities, and maintain files of impoundments and dispositions of animals.” (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: Writing activity reports and keeping impound files is standard record work computers handle 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.
Contacting animal owners to inform them that their pets are at animal holding facilities
The software now makes the first pass at animal owners, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 5 · Core
Source: “Contact animal owners to inform them that their pets are at animal holding facilities.” (O*NET task statement)
How this row was scored
Exposure score: 53 out of 100 (46–60 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; the value is that a specific person does it.
The rating behind it: Notifying owners is a standard message, though telling someone their pet was impounded needs some care.
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 2/4 · how much data exists 3/4.

Staying human

13 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.

Investigating reports of animal attacks or animal cruelty
This work happens in the physical world: reports of animal attacks, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Investigate reports of animal attacks or animal cruelty, interviewing witnesses, collecting evidence, and writing reports.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (1–15 allowing for uncertainty): minimal exposure, medium 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: Cruelty investigations mean going to the scene, seeing the animal, and reading people face to face.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 1/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Educating the public about animal welfare
The value here is that a specific person handles the public and stands behind it. That is earned, not computed.
importance 5 · Core
Source: “Educate the public about animal welfare, and animal control laws and regulations.” (O*NET task statement)
How this row was scored
Exposure score: 39 out of 100 (32–46 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Public education material on animal laws and welfare is easy to produce from published rules.
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 2/4 · how much data exists 3/4.
Examining animals for injuries or malnutrition
This work happens in the physical world: animals, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Examine animals for injuries or malnutrition, and arrange for any necessary medical treatment.” (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: Examining an animal for injury or malnutrition means putting hands 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.
Preparing for prosecutions related to animal treatment
This work happens in the physical world: prosecutions, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Prepare for prosecutions related to animal treatment, and give evidence in court.” (O*NET task statement)
How this row was scored
Exposure score: 13 out of 100 (6–20 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; someone qualified has to answer for it; the value is that a specific person does it.
The rating behind it: Case files can be prepared, but giving evidence in court has to be done in person by the officer involved.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 2/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Removing captured animals from animal-control service vehicles and placing animals in shelter cages or other enclosures
This work happens in the physical world: captured animals, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Remove captured animals from animal-control service vehicles and place animals in shelter cages or other enclosures.” (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: Lifting animals out of a truck and into shelter cages is physical handling.
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.
Issuing warnings or citations in connection with animal-related offenses
This work happens in the physical world: warnings, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Issue warnings or citations in connection with animal-related offenses, or contact police to report violations and request arrests.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (1–15 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; someone qualified has to answer for it.
The rating behind it: Issuing a citation is an official act carried out on the spot by an authorized officer.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 2/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Capturing and removing stray, uncontrolled or abused animals from undesirable conditions, using nets, nooses or tranquilizer darts
This work happens in the physical world: stray, uncontrolled or abused animals, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Capture and remove stray, uncontrolled, or abused animals from undesirable conditions, using nets, nooses, or tranquilizer darts as 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: Catching a frightened or aggressive animal with a net or noose is entirely physical.
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 6 tasks

Organizing the adoption of unclaimed animals
staying human
This work happens in the physical world: the adoption of unclaimed animals, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Organize the adoption of unclaimed animals.” (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: Listings and matching can be automated, but adoptions still involve meeting the animal and the family.
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.
Examining animal licenses and inspecting establishments housing animals for compliance with laws
staying human
This work happens in the physical world: animal licenses, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Examine animal licenses, and inspect establishments housing animals for compliance with laws.” (O*NET task statement)
How this row was scored
Exposure score: 11 out of 100 (4–18 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: Checking licenses is paperwork, but inspecting premises where animals are kept means visiting them.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Training police officers in dog handling and training techniques
staying human
This work happens in the physical world: police officers, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Train police officers in dog handling and training techniques for tracking, crowd control, and narcotics and bomb detection.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (0–13 allowing for uncertainty): minimal exposure, medium 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: Teaching officers to handle and train working dogs is hands-on instruction with dog and handler present.
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.
Euthanizing rabid, unclaimed or severely injured animals
staying human
This work happens in the physical world: rabid, unclaimed or severely injured animals, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Euthanize rabid, unclaimed, or severely injured 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: Euthanizing an animal is a physical, regulated act carried out 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.
Supplying animals with food, water and personal care
staying human
This work happens in the physical world: animals, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Supply animals with food, water, and personal care.” (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, watering and caring for animals is hands-on daily 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.
Cleaning facilities and equipment, dog pens and animal control trucks
staying human
This work happens in the physical world: facilities, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Clean facilities and equipment such as dog pens and animal control trucks.” (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: Cleaning pens and trucks is manual 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.

What this job pays, and how many people do it

Median pay: $45,660a 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: 12,070in 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: reports of activities in, a record out. The rows above are exactly that shape: answering inquiries from the public concerning animal control operations and writing reports of activities. 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: examining animals for injuries or malnutrition is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 7% of this job's task weight sits in rows the software is already learning, 14% in rows that change shape rather than disappear, and 79% in rows it is nowhere near. That is the position, measured across 16 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. Answering inquiries from the public concerning animal control operations 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 reports of activities, 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 reports of animal attacks 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 writing reports of activities and maintaining files of impoundments and dispositions of 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 control workers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was veterinarians: only about 7% of its durable work is work you already do and the 2.8× pay gap is the market pricing a barrier. And on the numbers you do not need one. This job scores 19/100 here, with only 7% of the task list in the top band, and “write reports of activities, and maintain files of impoundments and dispositions of…” 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.

Veterinarians
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already euthanize rabid, unclaimed, or severely injured animals, and their equivalent is to euthanize animals. 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. The pay gap is the market pricing a barrier: $130,100 against your $45,660 is 2.85× (OEWS May 2025 (both)), and you would be crossing it holding about 7% of their durable work. A gap that size with an overlap that small is a wish, not a route.
Look at that job’s page anyway →
Animal Trainers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already contact animal owners to inform them that their pets are at animal holding…, and their equivalent is to advise animal owners regarding the purchase of specific animals. Across both published task lists that is about 3% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 3% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $39,990 against your $45,660, 12.4% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →
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 supply animals with food, water, and personal care, and their equivalent is to feed and water livestock and monitor food and water supplies. Across both published task lists that is about 3% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 3% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $36,670 against your $45,660, 19.7% 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: 7% of its task weight, across 16 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 examining animals for injuries or malnutrition 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 Police community support officers 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 Police community support officers, Animal care services occupations n.e.c and Inspectors of standards and regulations. 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
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
American Job Center locator
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
- CareerOneStop local help hub
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
CareerOneStop
Free

No Space for this job, but one for what is happening to it

Nothing Collab365 runs is built for animal control 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 7% of the work on this page is already inside what they can do.

Try The AI Authority free →

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 animal control 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 animal control workers launches. Nothing else.

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No Space for animal control workers yet. Should there be one?

Collab365 Spaces is built by the same people as this site. We find the problems that AI and automation are creating inside one kind of work, then solve them as short courses, briefings and Blueprints. Each Space is the community too, so the research and the people doing your job are in the same place.

What a Space actually is, in full

Collab365 launches new communities where the need is real. If one for animal control workers existed, with researched problems, courses and people in the same boat, would you want in?

Your email

We use your email address for one thing: to tell you if a Space for animal control workers launches. We never sell it, never use it for unrelated marketing, and every email has a one-click unsubscribe. Our privacy policy has the full version.

This unlocks nothing. Every figure, every row and every step on this page is already yours, whether you fill this in or not.

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 Animal Control Workers?: Not as a job, but it is already doing parts of the work. Across the 16 official task statements scored for Animal Control Workers (United States, SOC 33-9011), 7% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 19 out of 100 (range 15–24, 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 Control Workers” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Answer inquiries from the public concerning animal control operations” (64/100, high); “Write reports of activities, and maintain files of impoundments and dispositions of animals” (56/100, partial); “Contact animal owners to inform them that their pets are at animal holding facilities” (53/100, 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 Control Workers” stay human?: About 79% 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: “Clean facilities and equipment such as dog pens and animal control trucks” (0/100, minimal); “Supply animals with food, water, and personal care” (0/100, minimal); “Euthanize rabid, unclaimed, or severely injured animals” (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 Control Workers” do about AI?: Start from the ledger rather than the headline: 7% of this job's weighted core work is exposed, and roughly 79% 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 Control 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 16 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.
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.