Veterinary Assistants and Laboratory Animal Caretakers
AI is not doing this work today.
This occupation's activities barely register in measured AI usage. Generative AI is not doing this work today. The pressures that matter here are more likely economic or robotic than linguistic.
Where this occupation sits among all 785 measured. Bands are quintiles of the real distribution. Applicability measures task overlap with observed AI usage. It is not a probability of job loss.
What this job involves
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.
Where AI overlaps this work, activity by activity
The occupation's most important work activities (O*NET weights, normalized to this set), each with its measured AI performance across 200,000 real conversations: how often AI is used for it, how well it completes it, and how much of the activity it covers.
| Work activity | Share of role | AI performance |
|---|---|---|
| Assist healthcare practitioners during medical procedures. | 18.9% | Not observed 0.00 |
| Administer basic health care or medical treatments. | 14.6% | Not observed 0.00 |
| Assist individuals with special needs. | 13.3% | Not observed 0.00 |
| Monitor health conditions of humans or animals. | 9.2% | Not observed 0.00 |
| Prepare medical equipment or work areas for use. | 7.4% | Not observed 0.00 |
| Perform administrative or clerical activities. | 7.1% | Moderate 0.58 |
| Clean tools, equipment, facilities, or work areas. | 5.6% | Not observed 0.00 |
| Prescribe medical treatments or devices. | 5.2% | Not observed 0.00 |
| Administer diagnostic tests to assess patient health. | 5.1% | Not observed 0.00 |
| Collect environmental or biological samples. | 4.6% | Not observed 0.00 |
| Evaluate patient or client condition or treatment options. | 4.5% | Not observed 0.00 |
| Schedule appointments. | 4.3% | Not observed 0.00 |
"Not observed" is a measurement, not missing data: that activity does not meaningfully appear in the usage sample. AI performance = completion × scope × coverage (user-goal view), 0–1.
What drives this score: the biggest AI-overlapped activity in this role is perform administrative or clerical activities; the most important activity AI is not observed doing is assist healthcare practitioners during medical procedures. The plan below is built around exactly that split.
Low exposure is an asset. Spend it deliberately.
Next 30 days
- Don't buy the panic. This occupation's activities barely appear in AI usage data. Your near-term exposure is other people's headlines, not your tasks.
- Skim the gains anyway. Even here, an assistant helps with the thin admin layer: Perform administrative or clerical activities is the one place the data shows any overlap.
Next 90 days
- Deepen the human core. Activities like Assist healthcare practitioners during medical procedures are measured as fully outside current AI. Mastery there is compounding, defensible value.
- Mentor the exposed. Colleagues in adjacent office-heavy roles are the ones facing redesign; understanding their tools makes you a better coordinator and leader.
The longer game
- Watch the actual frontier for this work: usually physical automation, demographics or regulation rather than language models. This dataset intentionally measures only generative AI.
- Revisit after major data updates. If this page's vintage changes and your band moves, the plan moves with it.
- AI applicability score and per-activity metrics: Tomlinson, Jaffe, Wang, Counts & Suri, Working with AI: Measuring the Applicability of Generative AI to Occupations, Microsoft Research 2025 (arXiv:2507.07935), data CC BY 4.0.
- Occupation description and activity structure: O*NET 30.0 Database, USDOL/ETA, CC BY 4.0.
- Bands, personalization weights and action plans are JobRiskAI editorial layers; method and limitations on the methodology page.