EXPOSED
A large slice of the job — literature reviews, ration formulation runs, statistical analysis of trial data, grant and journal writing, extension bulletins — is exactly the text-and-tabular work AI now does at usable quality. What holds is the physical half: designing and running feeding, breeding, and reproduction trials in barns and feedlots, collecting samples, handling animals, and owning the call on whether a genetics or nutrition program goes to producers. No license protects the title, so the moat is embodiment and accountability for real herds, not regulation.
Headcount grew steadily across the period.
Median pay $60,300 → $68,940 -8.5% 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
+5.8% 2,800 → 2,900 on the projections basis
Growing, and only partly exposed
The BLS expects +5.8% more of these jobs by 2034, and at 46/100 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.
~200 openings a year on average, including replacing people who leave.
ScientistBehavioristSericulturistBacteriologistDairy ScientistAnimal AnatomistAnimal BiologistAnimal ScientistSwine SpecialistAnimal GeneticistNutrition PartnerPoultry ScientistAnimal BehavioristResearch ScientistSwine NutritionistAnimal NutritionistDairy BacteriologistNutrition SpecialistBeef Cattle SpecialistBeef Cattle NutritionistSwine Genetics ResearcherDairy Nutrition ConsultantDairy Nutrition SpecialistAnimal Nutrition Consultant
Holding it up: embodiment . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier Ration balancing against NRC requirement tables, ANOVA/mixed-model runs on trial data, and drafting extension bulletins are already handled well by software plus an LLM, but designing a 90-day feeding trial with valid pen replication, walking the barn to spot a lame heifer skewing intake data, and collecting blood, semen, or rumen fluid still require a person on site — hence mid-band 11 rather than the 14+ of work that cannot be moved to a screen.
Some physical or field component You are in feedlots, farrowing houses, and research dairies with restraint chutes, AI guns, ultrasound wands, and manure underfoot, but the sample then goes to a controlled lab bench and much of the year is spent on analysis and writing — a split that lands at 12, above a screen-only analyst and below the veterinarian or herdsman whose whole day is hands on live animals.
No licence, no signature requirement There is no license to practice animal science: a PhD and ARPAS or ANSI board certification are resume assets, not statutory gates, and when a nutrition program goes to producers it is the feed company, the veterinarian of record, or the IACUC that carries the legal exposure — 3 reflects that IACUC protocol authorship is the only place your name binds anything.
Meaningful discretion Deciding that a genomic selection index or a transition-cow diet is ready to release to commercial herds — where a wrong call costs thousands of animals and a client's season — is a genuinely ambiguous high-stakes judgment, but much of it is bounded by NRC requirement tables, established statistical protocols, and IACUC review, which caps this at 12 rather than the 15+ of someone with no external checkpoint.
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 (11/20 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 (8/20) is whether buyers specifically pay for a person. Judgment and accountability (12/20) 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 23 of this occupation's 46 points (50%).
Embodiment (12/20) 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.
Dietitians and Nutritionists EXPOSED
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 66/100, still EXPOSED.
Routine tier (lit review, stats runs, ration solver, extension copy) automates away, leaving trial design under confounded field conditions, gene-editing and genomic-selection program calls, and diagnosing why a herd trial failed — a genuine two-tier occupation where the residual is the judgment tier
FDA CVM guidance or AAFCO model feed regulation requiring a named, credentialed animal nutritionist (e.g., ACAN/ARPAS-certified) to sign off on commercial ration formulations and feed additive claims — analogous to the PE stamp — with personal attestation that AI-generated formulations were reviewed; also USDA/IACUC rules naming a responsible animal scientist for AI-designed trial protocols
Growth of on-farm precision-livestock and gene-editing validation work requiring in-barn sample collection, surgical/reproductive procedures, and phenotyping that sensor rigs cannot yet substitute; unpredictable animal handling keeps this floor high
Antibiotic-free, welfare-audit (GAP, FARM program) and gene-edited-animal approval regimes naming an individual scientist as accountable for herd-level program decisions and audit defense
Breed associations and large integrators contracting named scientists for genetic-evaluation credibility, where producers pay for a person who will stand behind an EPD or sire recommendation
State veterinary practice act amendments (several boards have contested nutrition/reproduction consulting scope) explicitly carving nutrition and embryo-transfer program design to licensed vets or registered animal scientists, creating a signature requirement where none exists
The limit. Tiny occupation (3,100) heavily embedded in land-grant universities and feed companies; if extension and ag-research budgets shrink, headcount falls regardless of dimension scores. No licensure protects the title today, so the liability lever is the only large one and it depends on a feed-regulation change that has no active bill.
| Madison, WI | 220 | $84,310 +22% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 160 | $82,810 +20% |
| Lincoln, NE | 100 | $79,410 +15% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 60 | $77,880 +13% |
| Baltimore-Columbia-Towson, MD | 40 | $63,740 -8% |
| Fayetteville-Springdale-Rogers, AR | 40 | $240,370 +249% |
| Minneapolis-St. Paul-Bloomington, MN-WI | 40 | $76,530 +11% |
| Omaha, NE-IA | 40 | $73,740 +7% |
| Fayetteville-Springdale-Rogers, AR | 40 | $240,370 +249% |
| Madison, WI | 220 | $84,310 +22% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 160 | $82,810 +20% |
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 46. 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.