Often handed to AI
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
- Write reports, maintain research information, or perform clerical duties. · 0.4%
Occupation · SOC 31-9096.00
Feed, water, and examine pets and other nonfarm animals for signs of illness, disease, or injury in laboratories and animal hospitals and clinics. Clean and disinfect cages and work areas, and sterilize laboratory and surgical equipment. May provide routine postoperative care, administer medication orally or topically, or prepare samples for laboratory examination under the supervision of veterinary or laboratory animal technologists or technicians, veterinarians, or scientists.
Also called: Animal Care Provider · Animal Caregiver · Certified Veterinary Assistant · Veterinarian Assistant (Vet Assistant) · Avian Keeper · Emergency Veterinary Assistant · Inpatient Technician Assistant · Kennel Vet Assistant (Kennel Veterinary Assistant) · Research Animal Attendant · Small Animal Caretaker · Animal Care Service Worker · Animal Care Specialist
Job family: Healthcare Support Occupations
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-31-9096-00/context.md directly.
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
Task areas where people work with AI — iterating, learning, or checking — staying in the loop rather than handing the task off.
Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Independent published positions, read together — not a forecast.
20th-percentile task overlap — yet about 22,200 openings a year (+8.7% projected, BLS), and observed AI use leans 5417% copilot, not hand-off (AEI) . What exposure means →
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| Overall AI exposure (Felten et al.) Low | 26th | -0.8 | |
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 34th | 0.3 | |
| AI assistant applicability (Microsoft) Low | 6th | 0.0 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.2), and including AI-powered software (γ 0.3). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.
Mixed signals. Today's AI/LLM studies show relatively low exposure for this job, but the older (2013) Frey–Osborne work rated it higher for computerization and robotics. Different eras, different technologies — the AI measures above reflect the current state.
A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.
Frey–Osborne probability 0.9 · 72nd percentile among occupations · High
Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.
| Educate or advise clients on animal health care, nutrition, or behavior problems. | 2.0% | |
| Write reports, maintain research information, or perform clerical duties. | 0.9% | |
| Perform accounting duties, such as bookkeeping, billing customers for services, or maintaining inventories. | 0.8% |
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | Growing fast · +8.7% by 2034 |
| Projected annual openings | 22,200 |
| Employment 2024 → 2034 | 117,800 → 128,100 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international 2 occupations below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Veterinary Technicians and Assistants · 3240 | 14% | Not exposed |
| Pet Groomers and Animal Care Workers · 5164 | 14% | Not exposed |
Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.
How people actually apply AI to this occupation's tasks, from Claude.ai (Free and Pro) conversations in the Anthropic Economic Index, 2026-01-15. This is one AI assistant's consumer sample — not all AI, not the whole workforce. Autonomy and the collaboration mix are model-rated estimates; figures below the sample floor are hidden.
| Augmentation vs. automation | 54.2% working with AI · 29.8% handed to AI |
| Most common way people use AI here | Learning · you ask AI to explain or teach |
| Typical AI autonomy | 3.5 / 5 · higher = AI acts more independently |
| Used for work (vs. personal / coursework) | 5.8% |
The role's most common tasks in AI conversations, each tagged with how people work with the AI on it. “Usage” is the share of observed conversations, not of the job.
| Task | How | Usage |
|---|---|---|
| Educate or advise clients on animal health care, nutrition, or behavior problems. | Learning | 2.7% |
| Write reports, maintain research information, or perform clerical duties. | Directive | 0.4% |
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Educate or advise clients on animal health care, nutrition, or behavior problems. | 96.7% | |
| Write reports, maintain research information, or perform clerical duties. | 90.5% |
Example prompts phrased from the tasks people most often delegate to AI in this occupation (Anthropic Economic Index). Each shows the underlying measured task and its share of observed AI use. They are suggested phrasings of real tasks — starting points, not endorsed instructions.
Help me educate or advise clients on animal health care, nutrition, or behavior problems. From: Educate or advise clients on animal health care, nutrition, or behavior problems. · 2.7% of measured AI use · learning
Help me write reports, maintain research information, or perform clerical duties. From: Write reports, maintain research information, or perform clerical duties. · 0.4% of measured AI use · directive
All 28 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
O*NET importance rating, from 1 (not important) to 5 (extremely important).
| Customer and Personal Service | 4.3 | |
| English Language | 3.8 | |
| Biology | 3.6 | |
| Administrative | 3.5 | |
| Medicine and Dentistry | 3.5 | |
| Computers and Electronics | 3.2 |
| Active Listening | 3.5 | |
| Critical Thinking | 3.3 | |
| Reading Comprehension | 3.1 | |
| Writing | 3.1 | |
| Monitoring | 3.1 | |
| Speaking | 3.0 | |
| Active Learning | 2.9 |
| Oral Comprehension | 3.4 | |
| Oral Expression | 3.4 | |
| Written Expression | 3.3 | |
| Problem Sensitivity | 3.3 | |
| Information Ordering | 3.3 | |
| Deductive Reasoning | 3.1 | |
| Manual Dexterity | 3.1 | |
| Near Vision | 3.1 | |
| Written Comprehension | 3.0 | |
| Inductive Reasoning | 3.0 | |
| Flexibility of Closure | 3.0 | |
| Selective Attention | 3.0 | |
| Arm-Hand Steadiness | 3.0 | |
| Finger Dexterity | 3.0 | |
| Multilimb Coordination | 3.0 | |
| Trunk Strength | 3.0 | |
| Extent Flexibility | 3.0 | |
| Speech Recognition | 3.0 | |
| Speech Clarity | 3.0 | |
| Category Flexibility | 2.9 |
| Service Orientation | 3.1 | |
| Social Perceptiveness | 3.0 | |
| Coordination | 3.0 | |
| Time Management | 3.0 | |
| Instructing | 2.9 | |
| Complex Problem Solving | 2.9 | |
| Judgment and Decision Making | 2.9 |
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
| Example | Category | |
|---|---|---|
| Microsoft Access | Data base user interface and query software | Hot technology |
| Microsoft Excel | Spreadsheet software | Hot technology |
| Microsoft Office software | Office suite software | Hot technology |
| Microsoft Outlook | Electronic mail software | Hot technology |
| Microsoft PowerPoint | Presentation software | Hot technology |
| Microsoft Word | Word processing software | Hot technology |
| IDEXX Laboratories IDEXX Cornerstone | Medical software | |
| Labeling software | Label making software | |
| McAllister Software Systems AVImark | Medical software | |
| Practice management software PMS | Medical software | |
| Scheduling software | Calendar and scheduling software |
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
What to study: Agriculture, Agriculture Operations, and Related Sciences . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Share of people in this occupation at each level of education.
| High School Diploma | 78.2% | |
| Post-Secondary Certificate | 10.9% | |
| Less than a High School Diploma | 6.4% | |
| Some College Courses | 3.7% | |
| Post-Baccalaureate Certificate | 0.5% | |
| Associate's Degree (or other 2-year degree) | 0.3% |
The interests and personal qualities O*NET associates with people who do this work.
| Realistic | 6.3 | |
| Investigative | 4.3 | |
| Conventional | 4.0 | |
| Social | 3.5 |
| Animal Service | 6.3 | |
| Health Care Service | 5.0 | |
| Life Science | 4.0 | |
| Physical/Manual Labor | 3.9 | |
| Medical Science | 3.5 | |
| Personal Service | 2.4 | |
| Office Work | 2.0 |
| Dependability | 5.0 | |
| Attention to Detail | 4.0 | |
| Integrity | 3.0 | |
| Cooperation | 2.3 | |
| Self-Control | 2.0 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $29,160 |
| 25th percentile | $34,320 |
| Median (50th) | $37,320 |
| 75th percentile | $44,550 |
| 90th percentile | $48,150 |
| People employed | 114,190 |
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Professional, Scientific, and Technical Services · Sector | 103,290 | $37,110 |
| Veterinary Services · National industry | 101,800 | $37,070 |
| Educational Services · Sector | 5,090 | $47,670 |
| Other Services (except Public Administration) · Sector | 2,820 | $36,760 |
| Retail Trade · Sector | 1,740 | $41,490 |
| Health Care and Social Assistance · Sector | 330 | $48,350 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 320 | $47,810 |
| Manufacturing · Sector | 70 | $47,420 |
| Arts, Entertainment, and Recreation · Sector | 70 | $42,960 |
| Temporary Help Services · National industry | — | $47,810 |
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Veterinary Services · National industry | 296.38× | 101,800 |
| Professional, Scientific, and Technical Services · Sector | 12.95× | 103,290 |
| Other Services (except Public Administration) · Sector | 0.86× | 2,820 |
| Educational Services · Sector | 0.5× | 5,090 |
| Retail Trade · Sector | 0.15× | 1,740 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 0.05× | 320 |
| Health Care and Social Assistance · Sector | 0.02× | 330 |
Part of the Agriculture and Healthcare & Human Services career clusters.
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
Options the data surfaces for Veterinary Assistants and Laboratory Animal Caretakers — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Capabilities this work builds that are used across many other occupations.
Occupations O*NET rates as related — the nearby moves on the map.
How people typically prepare for this work.
On the global GenAI exposure gradient this work sits around the 15th percentile of 427 international occupations.
Veterinary Assistants and Laboratory Animal Caretakers show 20th-percentile AI task overlap — and about 22,200 annual U.S. openings
Veterinary Assistants and Laboratory Animal Caretakers show 20th-percentile AI task overlap — and about 22,200 annual U.S. openings • Veterinary Assistants and Laboratory Animal Caretakers rank in the 20th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • The occupation is projected to see about 22,200 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be growing fast (+8.7%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $37,320, across about 114,190 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 54% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census. (2026-01-15-v4-plus-2025-03-27-v2) Source: Singulariki — "Veterinary Assistants and Laboratory Animal Caretakers". https://singulariki.com/roles/role-31-9096-00 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom
Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
Data compiled June 2, 2026. Figures are estimates, not advice.
Singulariki. "Veterinary Assistants and Laboratory Animal Caretakers." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-31-9096-00
Singulariki. (2026). Veterinary Assistants and Laboratory Animal Caretakers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-31-9096-00
@misc{singulariki-role-31-9096-00,
title = {Veterinary Assistants and Laboratory Animal Caretakers},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-31-9096-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.