EXPOSED
Nearly all of this work is physical: restraining a frightened cat for a blood draw, cleaning kennels and cages, feeding and watering animals, prepping surgical suites, holding animals during radiographs. Language AI can't do any of that, and today's robotics can't handle an unpredictable 80-pound dog. The exposure is administrative and structural, not robotic — the record-keeping, intake paperwork, appointment and inventory tasks get absorbed, wages stay low, and the role carries no license or sign-off authority to anchor it.
Headcount grew steadily across the period.
Median pay $28,590 → $38,150 +6.8% in real terms
This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.
So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.
BLS projection, 2024–2034
+8.7% 117,800 → 128,100 on the projections basis
Growing, and only partly exposed
The BLS expects +8.7% more of these jobs by 2034, and at 54/100 the work is only partly exposed — some tasks are automatable, the core of the job is not. Nothing here is in tension.
Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.
~22,200 openings a year on average, including replacing people who leave.
Avian KeeperAnimal CaregiverAnimal CaretakerAnimal Care ProviderVeterinary AttendantAnimal Care SpecialistSmall Animal CaretakerAnimal Health TechnicianResearch Animal AttendantAnimal Care Service WorkerLaboratory Animal CaretakerLaboratory Animal TechnicianCertified Veterinary AssistantEmergency Veterinary AssistantInpatient Technician AssistantVeterinarian Helper (Vet Helper)Veterinarian Assistant (Vet Assistant)Veterinary Receptionist (Vet Receptionist)Kennel Vet Assistant (Kennel Veterinary Assistant)Veterinary Kennel Assistant (Vet Kennel Assistant)
Holding it up: embodiment . Weakest point: liability shield .
Tasks largely resist digitisation Restraining a struggling animal, scrubbing runs, monitoring post-anesthesia recovery, and hauling feed are tasks no software touches — the only genuinely automatable slice is intake forms, vaccine reminders, and inventory logs, which is why this sits at 17 rather than a clean 20.
Hands-on in uncontrolled environments You are on your feet in kennels and treatment rooms with unpredictable animals, urine, bleach, autoclaves, and bite and scratch risk — an environment nobody controls, which is why this is a 19 and only sub-20 because the setting is at least indoors and familiar rather than a roadside or a rooftop.
No licence, no signature requirement No state licence gates this work; credentialing (AVA, ALAT) is voluntary and the DVM or licensed vet tech signs the treatment record, dispenses the drugs, and absorbs the malpractice claim, so the 3 reflects only that IACUC and USDA animal-welfare training is documented in your name.
Executes defined procedures on defined inputs Feeding schedules, cage-change frequency, and restraint holds are protocol-driven, and the calls that matter — dose changes, when to intervene clinically — go to the veterinarian; your discretion is escalation judgment, noticing an animal is off-feed or in distress and reporting it, which is real but bounded, hence 6.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (17/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (3/20) is whether the law requires a licensed human to sign. Trust premium (9/20) is whether buyers specifically pay for a person. Judgment and accountability (6/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 18 of this occupation's 54 points (33%).
Embodiment (19/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
Dental Assistants SAFE
The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 71/100 — SAFE.
In the research-animal segment, tighter enforcement of the Animal Welfare Act / PHS Policy requirement that specific named, trained personnel document daily health observations, plus AAALAC accreditation reviewers treating AI-generated cage-side monitoring logs as insufficient without a named human observer's attestation.
Task-mix shift as intake paperwork, scheduling, inventory and record-keeping are absorbed by practice-management AI, leaving a day that is almost entirely handling, restraint, sanitation and surgical prep — the residual is the part no current system does. Note this raises the score of the remaining work while reducing headcount per clinic.
State practice acts expanding the list of tasks reserved to credentialed technicians (anesthesia monitoring, dental scaling, catheter placement, controlled-drug handling), combined with the AVMA/NAVTA 'Registered Veterinary Nurse' title-protection push — this would create a licensed rung that some assistants move into and that carries personal accountability. Watch for state veterinary board rule packages of the kind Ohio and Colorado have debated.
If automated cage monitoring (Vium/Tecniplast-style sensor systems) becomes standard, the caretaker's role shifts from logging to adjudicating flagged animals — deciding what is a reportable adverse event, when to escalate to the attending veterinarian, when to pull an animal from a protocol. The named-observer duty under IACUC protocols would sit on a human making that call.
Fear Free and low-stress-handling certification becoming something clinics advertise and clients select on, so that gentle human restraint is a named, priced service rather than invisible labor. Already visible in Fear Free's ~90k certified professionals, but it has not yet moved assistant wages.
The limit. task_resistance and embodiment are already near maximum; there is essentially no headroom there and no route to a large trust premium for a role clients rarely see by name. Realistic ceiling is roughly the mid-60s, and it comes almost entirely from credentialing — which means it accrues to assistants who cross into a licensed technician tier, not to the title as it exists. Wage floor pressure is not addressed by any of these levers.
| New York-Newark-Jersey City, NY-NJ | 5,560 | $46,160 +21% |
| Los Angeles-Long Beach-Anaheim, CA | 4,830 | $46,070 +21% |
| Atlanta-Sandy Springs-Roswell, GA | 2,880 | $36,110 -5% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 2,740 | $45,320 +19% |
| Seattle-Tacoma-Bellevue, WA | 2,400 | $45,640 +20% |
| Phoenix-Mesa-Chandler, AZ | 2,390 | $38,710 +1% |
| Dallas-Fort Worth-Arlington, TX | 2,350 | $36,040 -6% |
| Chicago-Naperville-Elgin, IL-IN | 2,190 | $39,280 +3% |
| San Francisco-Oakland-Fremont, CA | 2,150 | $49,400 +29% |
| San Jose-Sunnyvale-Santa Clara, CA | 620 | $49,210 +29% |
| Kahului-Wailuku, HI | 60 | $49,200 +29% |
We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.
That is worth saying out loud next to a score of 54. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.