Share and intensity of work current AI systems can materially affect.
SOC 33-9011
Animal Control Workers AI displacement risk
Animal control workers capture stray and dangerous animals, investigate cruelty reports, and educate the public on welfare laws. Dispatch apps and license databases streamline the paperwork, but the work is physical capture, field investigation, and judgment about animal and human safety in unpredictable conditions.
Likely potential for exposed tasks to move to software after workflow integration.
Automation barely touches this role: no robot nets a frightened dog, and cruelty cases hinge on evidence gathered by an officer who can testify. Public demand for humane enforcement keeps growing.
Distribution
Where Animal Control Workers sits across 620 tracked roles
Displacement pressure 12 — higher than 2% of the 620 occupations tracked on displacement.ai.
Score version
This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-08-15. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.
16 O*NET task statements matched to SOC 33-9011. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $45,660 (May 2025, US national). The latest BLS row matched SOC 33-9011.
Scores are planning signals, not forecasts. Local hiring demand, employer-specific workflows, licensing, and credentials must be validated before making career decisions.
2030 economic stress test
How Anthropic's scenarios classify Animal Control Workers
SOC 33-9011 places this role in the paper's all-other occupation group. These group-level outcomes do not change the 12/100 role score and are not an occupation forecast.
+1.1% group wage
Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.
Economy-wide: +1.6% GDP and 3.9% unemployment.
+5.9% group wage
Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.
Economy-wide: +8.3% GDP and 4.6% unemployment.
+33.6% group wage
Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.
Economy-wide: +32.4% GDP and 11.9% unemployment.
Compare the assumptions and limitations across all three scenarios. Source: The Anthropic Institute Working Paper No. 2026-02.
Official task evidence
O*NET task matches for Animal Control Workers
The current evidence import matched 16 task statements from Task Statements 31.0 (August 2026). These rows are used as a grounding layer for judging which parts of the occupation are repeatable, language-heavy, analytical, social, physical, or compliance-sensitive.
Dataset31.0 (August 2026)
Matched tasks16
SOC33-9011
- Core task / ID 7968
Write reports of activities, and maintain files of impoundments and dispositions of animals.
- Core task / ID 7958
Investigate reports of animal attacks or animal cruelty, interviewing witnesses, collecting evidence, and writing reports.
- Core task / ID 7960
Examine animals for injuries or malnutrition, and arrange for any necessary medical treatment.
- Core task / ID 7967
Contact animal owners to inform them that their pets are at animal holding facilities.
- Core task / ID 7966
Educate the public about animal welfare, and animal control laws and regulations.
- Core task / ID 7961
Remove captured animals from animal-control service vehicles and place animals in shelter cages or other enclosures.
Source: O*NET Resource Center, Task Statements. Raw import target: data/raw/onet/task-statements-31-0.txt.
Task profile
Where AI changes the work
Capture and remove stray or abused animals
Exposure 14, automation 4%, augmentation 26%.
O*NET evidence: Capture and remove stray, uncontrolled, or abused animals from undesirable conditions, ... (ID 7959)
Investigate reports of animal attacks and cruelty
Exposure 22, automation 8%, augmentation 44%.
O*NET evidence: Investigate reports of animal attacks or animal cruelty, interviewing witnesses, collec... (ID 7958)
Educate the public on animal welfare laws
Exposure 22, automation 8%, augmentation 42%.
O*NET evidence: Educate the public about animal welfare, and animal control laws and regulations. (ID 7966)
Write reports and maintain impoundment files
Exposure 50, automation 27%, augmentation 58%.
O*NET evidence: Write reports of activities, and maintain files of impoundments and dispositions of ani... (ID 7968)
TaskExposureAutomationAugmentation
Capture and remove stray or abused animals144%26%
Investigate reports of animal attacks and cruelty228%44%
Educate the public on animal welfare laws228%42%
Write reports and maintain impoundment files5027%58%
Transition pathways
Adjacent moves that preserve existing skills
role redesign
LowAnimal Services Supervisor
Training horizon: 6-12 months. Skill overlap 64. Wage preservation signal 118.
- Lead field teams
- Manage shelter coordination
- Own ordinance enforcement
credentialed transition
LowHumane Investigations Officer
Training horizon: 12-24 months. Skill overlap 58. Wage preservation signal 116.
- Earn cruelty-investigation certification
- Build prosecutor relationships
- Document cases to trial standard
Comparison guides
Compare the next move before you commit
6-12 months
Animal Control Workers to Animal Services Supervisor
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Animal Control Workers into Animal Services Supervisor.
12-24 months
Animal Control Workers to Humane Investigations Officer
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Animal Control Workers into Humane Investigations Officer.
What the AI risk score means for Animal Control Workers
The displacement pressure score for Animal Control Workers is 12. That score blends task exposure, automation pressure, augmentation potential, wage vulnerability, transition feasibility, and source confidence. It is designed to help workers and workforce teams decide where to act first, not to claim a specific date when a job will disappear.
For this role, the clearest risk pattern is visible at the task level. Write reports and maintain impoundment files carries 27% automation pressure, while Write reports and maintain impoundment files carries 58% augmentation potential. That means the best response is usually a targeted redesign of work: move away from repeatable production tasks and toward judgment, exception handling, coordination, stakeholder context, and accountable use of AI tools.
Labor-market context and wage risk
Median wage: $45,660 (May 2025, US national). Employment context: Field enforcement role for animal welfare. Typical education: High school plus on-the-job training; certification available.
Wage vulnerability is 50, while transition feasibility is 60. A high wage-vulnerability score means workers should pay close attention to salary preservation before making a move. A high transition-feasibility score means there are adjacent paths that can reuse existing skills without requiring a complete career reset.
- Low displacement pressure
- Apps streamline dispatch and records
- Physical capture has no substitute
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Animal Control Workers, the strongest near-term skill priorities are listed below. These are useful whether the goal is to stay in the role, move to a redesigned version of the role, or transition into an adjacent occupation.
Animal handling
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Field investigation
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Public communication
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Report documentation
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
90-day transition plan
The most practical next step is not to wait for a layoff or a full role redesign. Use the next 90 days to create evidence that you can operate in a safer, more AI-augmented version of the work.
- In the first 30 days, document the repetitive tasks in your current work and identify where AI can reduce drafting, lookup, classification, or reporting time.
- By 60 days, complete one small project connected to Animal Services Supervisor, such as lead field teams.
- By 90 days, compare internal openings and external postings for Animal Services Supervisor or Humane Investigations Officer and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Animal Control Workers
Will AI replace Animal Control Workers?
Animal control workers capture stray and dangerous animals, investigate cruelty reports, and educate the public on welfare laws. Dispatch apps and license databases streamline the paperwork, but the work is physical capture, field investigation, and judgment about animal and human safety in unpredictable conditions. The better planning signal is not full replacement, but which tasks become automated, which tasks become AI-assisted, and which responsibilities still need human judgment.
Which parts of Animal Control Workers work are most exposed to AI?
Write reports and maintain impoundment files and Investigate reports of animal attacks and cruelty show the strongest automation pressure in this model. Write reports and maintain impoundment files and Investigate reports of animal attacks and cruelty are better treated as AI-augmented work.
What should Animal Control Workers learn next?
Start with Animal handling, Field investigation, Public communication. The most practical adjacent paths in this model are Animal Services Supervisor and Humane Investigations Officer.
How should this score be used?
Use it as a planning signal, not a prediction. Confirm local hiring demand, wages, licensing, credentials, and employer adoption before making a career move.
Sources
Evidence trail
OECD / 11 July 2023OECD Employment Outlook 2023: Artificial Intelligence and the Labour MarketO*NET Resource Center / Database 31.0 (August 2026)Occupation, Task, Skill, and Work-Activity DataUS Bureau of Labor Statistics / May 2025 estimates (released 15 May 2026)Occupational Employment and Wage Statistics