Often handed to AI
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
- Analyze characteristics of animals to identify and classify them. · 2.5%
Occupation · SOC 19-1023.00
Study the origins, behavior, diseases, genetics, and life processes of animals and wildlife. May specialize in wildlife research and management. May collect and analyze biological data to determine the environmental effects of present and potential use of land and water habitats.
Also called: Conservation Biologist · Fish and Wildlife Biologist · Fisheries Biologist · Wildlife Biologist · Aquatic Biologist · Fisheries and Wildlife Biological Scientist · Forest Wildlife Biologist · Habitat Biologist · Wildlife Refuge Specialist · Zoologist · Animal Behaviorist · Animal Biologist
Job family: Life, Physical, and Social Science Occupations
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-19-1023-00/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.
64th-percentile task overlap — yet about 1,400 openings a year (+1.6% projected, BLS), and observed AI use leans 5570% 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.) Moderate | 57th | 0.3 | |
| LLM task exposure, γ (OpenAI / Eloundou) Moderate | 66th | 0.8 | |
| AI assistant applicability (Microsoft) High | 72nd | 0.2 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.5), and including AI-powered software (γ 0.8). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
Most of this job's tasks can be done remotely (Dingel–Neiman), which tends to track with higher digital and AI exposure.
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 0.3 · 39th percentile among occupations · Moderate
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.
| Analyze characteristics of animals to identify and classify them. | 3.2% | |
| Disseminate information by writing reports and scientific papers or journal articles, and by making presentations and giving talks for schools, clubs, interest groups and park interpretive programs. | 0.5% | |
| Inform and respond to public regarding wildlife and conservation issues, such as plant identification, hunting ordinances, and nuisance wildlife. | 0.3% | |
| Prepare collections of preserved specimens or microscopic slides for species identification and study of development or disease. | 0.2% |
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | About average · +1.6% by 2034 |
| Projected annual openings | 1,400 |
| Employment 2024 → 2034 | 18,200 → 18,500 |
“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 occupation 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 |
|---|---|---|
| Biologists, Botanists, Zoologists and Related Professionals · 2131 | 40% | Gradient 2 |
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 | 55.7% working with AI · 41.6% handed to AI |
| Most common way people use AI here | Learning · you ask AI to explain or teach |
| Typical AI autonomy | 4.0 / 5 · higher = AI acts more independently |
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 |
|---|---|---|
| Analyze characteristics of animals to identify and classify them. | Directive | 2.5% |
| Study characteristics of animals, such as origin, interrelationships, classification, life histories and diseases, development, genetics, and distribution. | Learning | 0.5% |
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Study characteristics of animals, such as origin, interrelationships, classification, life histories and diseases, development, genetics, and distribution. | 97.9% | |
| Analyze characteristics of animals to identify and classify them. | 92.4% |
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 analyze characteristics of animals to identify and classify them. From: Analyze characteristics of animals to identify and classify them. · 2.5% of measured AI use · directive
Help me study characteristics of animals, such as origin, interrelationships, classification, life histories and diseases, development, genetics, and distribution. From: Study characteristics of animals, such as origin, interrelationships, classification, life histories and diseases, development, genetics, and distribution. · 0.5% of measured AI use · learning
All 14 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
Newer responsibilities O*NET has flagged as growing for this occupation.
O*NET importance rating, from 1 (not important) to 5 (extremely important).
| Biology | 4.8 | |
| English Language | 3.8 | |
| Customer and Personal Service | 3.7 | |
| Mathematics | 3.4 | |
| Geography | 3.4 | |
| Law and Government | 3.3 | |
| Administration and Management | 3.3 |
| Reading Comprehension | 4.0 | |
| Active Listening | 4.0 | |
| Speaking | 4.0 | |
| Critical Thinking | 4.0 | |
| Writing | 3.9 | |
| Science | 3.9 | |
| Active Learning | 3.6 | |
| Monitoring | 3.4 | |
| Mathematics | 3.0 |
| Complex Problem Solving | 4.0 | |
| Judgment and Decision Making | 4.0 | |
| Coordination | 3.8 | |
| Time Management | 3.4 | |
| Social Perceptiveness | 3.3 | |
| Systems Analysis | 3.3 | |
| Persuasion | 3.1 | |
| Negotiation | 3.1 |
| Oral Comprehension | 4.0 | |
| Written Comprehension | 4.0 | |
| Oral Expression | 4.0 | |
| Written Expression | 4.0 | |
| Deductive Reasoning | 4.0 | |
| Inductive Reasoning | 4.0 | |
| Problem Sensitivity | 3.8 | |
| Information Ordering | 3.8 | |
| Speech Clarity | 3.8 | |
| Speech Recognition | 3.6 | |
| Category Flexibility | 3.5 | |
| Near Vision | 3.5 | |
| Fluency of Ideas | 3.4 | |
| Originality | 3.3 | |
| Selective Attention | 3.3 | |
| Flexibility of Closure | 3.1 |
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Showing the top 40 of 41.
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: Biological and Biomedical Sciences , Multi/Interdisciplinary Studies , Natural Resources and Conservation . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Share of people in this occupation at each level of education.
| Bachelor's Degree | 57.2% | |
| Master's Degree | 40.0% | |
| Post-Doctoral Training | 2.8% |
The interests and personal qualities O*NET associates with people who do this work.
| Investigative | 7.0 | |
| Realistic | 5.4 | |
| Conventional | 3.7 |
| Life Science | 6.8 | |
| Nature/Outdoors | 6.5 | |
| Mathematics/Statistics | 4.0 | |
| Animal Service | 3.5 | |
| Public Speaking | 3.2 | |
| Agriculture | 3.2 | |
| Medical Science | 2.9 | |
| Management/Administration | 2.7 | |
| Physical/Manual Labor | 2.6 |
| Dependability | 5.0 | |
| Attention to Detail | 4.0 | |
| Integrity | 3.0 | |
| Intellectual Curiosity | 2.6 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $48,240 |
| 25th percentile | $58,360 |
| Median (50th) | $72,860 |
| 75th percentile | $90,590 |
| 90th percentile | $113,350 |
| People employed | 16,920 |
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 | 2,550 | $74,270 |
| Other Services (except Public Administration) · Sector | 1,250 | $58,720 |
| Educational Services · Sector | 610 | $67,040 |
| Arts, Entertainment, and Recreation · Sector | 460 | $48,310 |
| Engineering Services · National industry | 320 | $86,270 |
| Administrative and Support and Waste Management and Remediation Services · Sector | — | $66,680 |
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 |
|---|---|---|
| Other Services (except Public Administration) · Sector | 2.57× | 1,250 |
| Engineering Services · National industry | 2.52× | 320 |
| Professional, Scientific, and Technical Services · Sector | 2.16× | 2,550 |
| Arts, Entertainment, and Recreation · Sector | 1.59× | 460 |
| Educational Services · Sector | 0.41× | 610 |
Part of the Energy & Natural Resources career cluster.
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 Zoologists and Wildlife Biologists — 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 77th percentile of 427 international occupations.
Zoologists and Wildlife Biologists show 64th-percentile AI task overlap — and about 1,400 annual U.S. openings
Zoologists and Wildlife Biologists show 64th-percentile AI task overlap — and about 1,400 annual U.S. openings • Zoologists and Wildlife Biologists rank in the 64th percentile (Moderate 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 1,400 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 about average (+1.6%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $72,860, across about 16,920 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 56% 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 — "Zoologists and Wildlife Biologists". https://singulariki.com/roles/role-19-1023-00 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. "Zoologists and Wildlife Biologists." 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-19-1023-00
Singulariki. (2026). Zoologists and Wildlife Biologists. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-19-1023-00
@misc{singulariki-role-19-1023-00,
title = {Zoologists and Wildlife Biologists},
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-19-1023-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.