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AI Automation Index
Will AI Replace Animal Scientists?
Task-level automation exposure for Animal Scientists: 9 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
57%
weighted task index
9 of 9 tasks scored
Median Salary
$68,940 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Low
3,100 people hold this job — size, not growth
Projected 2025–35
+5.8%
employment change
200 openings a year · BLS line item
Pay by state
BLS OEWS publishes 13 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$47,930 – $132,830
Highest medians
Texas $132,830
Minnesota $88,640
Wisconsin $84,310
Washington $83,160
Kansas $80,090
Lowest medians
Illinois $47,930
Nebraska $55,300
Michigan $60,010
North Dakota $72,100
Iowa $75,290
State figures come from the 19-1011 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 57%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 0%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 19%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 12%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 9/100
Low
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
9 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 75%
6 tasks
Medium exposure (≥ 35%) 19%
2 tasks
Low exposure (below 35%) 6%
1 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Constituent Tasks
#5415 · Core · 62% automatable
Study nutritional requirements of animals and nutritive values of animal feed materials.
information retrieval — Literature research strong; farm observation human
Research livestock management methods.
#20865 · Core · 72% automatable
Write up or orally communicate research findings to the scientific community, producers, and the public.
text generation — Reports drafted; presentations need human delivery
Prepare scientific or technical reports or presentations.
#5417 · Core · 45% automatable
Develop improved practices in feeding, housing, sanitation, or parasite and disease control of animals.
decision support — AI proposes agricultural methods; field validation required
Develop agricultural methods.
#5414 · Core · 65% automatable
Advise producers about improved products and techniques that could enhance their animal production efforts.
decision support — Generates improvement options; human tailors and owns
Advise others on business or operational matters. Advise others on ways to improve processes or products.
#5413 · Core · 62% automatable
Conduct research concerning animal nutrition, breeding, or management to improve products or processes.
information retrieval — Literature research strong; farm observation human
Research livestock management methods.
#5416 · Core · 62% automatable
Study effects of management practices, processing methods, feed, or environmental conditions on quality and quantity of animal products, such as eggs and milk.
information retrieval — Literature research strong; farm observation human
Research livestock management methods.
#5418 · Core · 62% automatable
Research and control animal selection and breeding practices to increase production efficiency and improve animal quality.
information retrieval — Literature research strong; farm observation human
Research livestock management methods.
#5419 · Supplemental · 45% automatable
Determine genetic composition of animal populations and heritability of traits, using principles of genetics.
data analysis — Bioinformatics aided; wet-lab work human
Research genetic characteristics or expression.
#5420 · Supplemental · 3% automatable
Crossbreed animals with existing strains or cross strains to obtain new combinations of desirable characteristics.
physical manipulation — Animal breeding is skilled physical procedure
Perform animal breeding procedures.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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