Somewhat Resilient
Last Update: 6/19/2026
AI Resilience Score for Zoologist/Wildlife Biologist:
50.0%
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Med
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Low
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
Med
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
There are a reasonable number of sources for this result, but there is some disagreement between them.
Contributing sources
AI Resilience Report forZoologists and Wildlife Biologists
$72,860 median salary•1,400 annual openings•SOC Code: 19-1023.00
Zoologists and Wildlife Biologists are somewhat less resilient to AI impacts than most occupations, according to our analysis of 7 sources.
Zoologist and wildlife biologist work is labeled "Somewhat Resilient" because AI is genuinely changing a big chunk of the day-to-day workflow, especially the time-consuming task of sorting through thousands of camera-trap photos, which used to take months but now takes days with tools like SpeciesNet. That shift means the job itself is evolving, and biologists who do not pick up some basic machine-learning skills may find themselves falling behind as these tools become standard across conservation organizations.
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Zoologist and wildlife biologist work is labeled "Somewhat Resilient" because AI is genuinely changing a big chunk of the day-to-day workflow, especially the time-consuming task of sorting through thousands of camera-trap photos, which used to take months but now takes days with tools like SpeciesNet. That shift means the job itself is evolving, and biologists who do not pick up some basic machine-learning skills may find themselves falling behind as these tools become standard across conservation organizations.
Read full analysisAnalysis of Current AI Resilience
Zoologist/Wildlife Biologist
Updated Quarterly
How is AI changing Zoologist/Wildlife Biologist jobs?
Right now, AI is mostly augmenting zoologists and wildlife biologists rather than replacing them — it's like giving researchers a super-powered assistant. The biggest changes are in counting and identifying animals, which used to take huge amounts of time. In a new study, AI can dramatically speed up the painstaking work of tracking wildlife with remote cameras, cutting analysis time from months or even a year to just days while producing nearly the same scientific conclusions as humans.
Researchers at WSU and Google tested a tool called SpeciesNet on camera-trap photos and found that for most species, models built from AI-identified images closely matched those produced by human experts. The lead scientist was clear: "We're not trying to replace people" [1] — the goal is faster decisions for conservation.
Beyond camera traps, ecologists are learning to use AI for drone, acoustic, and satellite data. The Smithsonian Conservation Biology Institute now runs a course because computer vision is rarely taught in ecology programs [2], helping biologists pick and evaluate models for their own research. AI is also creating new problems biologists must handle: fake videos can spread misinformation, and therefore, they can decrease the public awareness about biodiversity, making the implementation of some conservation actions more difficult, according to a recent Wildlife Society Q&A on AI-generated wildlife content [3].
Sources
How fast is AI adoption growing for Zoologist/Wildlife Biologist?
Adoption is moving fast for data-heavy tasks because the tools are free or low-cost and the time savings are huge — early AI tools offered some relief by filtering out blank images, often 60–70% of the total, and newer models like SpeciesNet can run a full pipeline in days. That's especially valuable for smaller or underfunded conservation groups [4] who can't afford armies of student reviewers.
But adoption is slower for the human parts of the job — fieldwork, stakeholder consultation, public outreach, and policy recommendations. Mongabay reports that more data does not automatically produce better understanding, and conservation still needs people to figure out why species are declining and what to do about it. There are also social and ethical concerns: a Conservation Frontlines analysis [5] from February 2026 warns about AI-generated wildlife imagery distorting public perception, and the Wildlife Society notes that AI-generated videos may have the potential to influence attitudes, policy debates, and funding priorities.
The encouraging takeaway: AI is taking over the tedious sorting work so biologists can spend more time on the things humans do best — designing studies, interpreting findings, working with communities, and protecting wild places. If you're drawn to this career, learning some basic machine-learning skills alongside your biology training will make you really valuable.
Sources
Will AI replace Zoologist/Wildlife Biologist?
Not entirely. We think AI will take over some tasks, but not the whole job.
Our AI Resilience Score for this career sits at 50.0%, which reflects a real tension: AI is genuinely changing how wildlife biologists work, but it is not close to replacing what makes them valuable. Right now, tools like SpeciesNet can cut months of camera-trap analysis down to days while producing results that closely match human expert conclusions [1]. Early AI tools also helped by filtering out blank images, which can make up 60 to 70 percent of camera-trap footage, freeing up researchers for more meaningful work [4].
What stays human is the harder, more important stuff. Designing studies, interpreting why species are declining, working with local communities, and making conservation policy recommendations all require judgment and relationships that AI cannot replicate. The Smithsonian Conservation Biology Institute is even training biologists to evaluate AI models themselves [2], which shows the field wants people who can work alongside these tools, not be replaced by them.
The job market outlook through 2034 is modest, so this is not a career with explosive hiring ahead. But the adaptive capacity of this role is genuinely high. Biologists who build some machine-learning literacy alongside their field skills will be especially well positioned as conservation work grows more data-driven.
Sources
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Latest AI news for Zoologist/Wildlife Biologist
These articles highlight how AI is transforming the careers of zoologists and wildlife biologists. For instance, AI tools are enhancing wildlife conservation by analyzing data faster, enabling better tracking of species. In a case study, AI-generated heat maps showed how meerkats utilize their enclosure space, improving animal welfare in zoos. However, there are concerns about AI creating misleading representations of wildlife. Understanding these technologies fosters resilience and adaptability in the field, ensuring students are well-prepared for the evolving landscape of wildlife conservation.
Q&A: Should wildlife biologists embrace AI?
wildlife.org • 6/20/2026
Jun 11, 2026 — Machine learning trains computer systems to pick up on patterns in data, like identifying wildlife in camera trap imagery, and gets better over ... Read more
Can AI help conservation? | WWF
www.worldwildlife.org • 6/20/2026
Mar 3, 2025 — AI helps us accelerate conservation by processing data that would take years for humans to analyze alone. ... AI helps us detect and track species ... Read more
AI videos of animals could be dangerous. Here’s how to spot them.
www.popsci.com • 11/8/2025
Researchers warn that they can distort our connection to wildlife.
Artificial Intelligence's Potential in Zoo Animal Welfare
onlinelibrary.wiley.com • 7/14/2025
Heat map visualization of enclosure space use by meerkats, generated by the artificial intelligence model described in the case study.
Artificial Intelligence Is Watching Wildlife
www.nwf.org • 3/28/2024
Artificial intelligence is assisting wildlife conservation efforts in species from trout to whales while raising some watchdog eyebrows.
More Career Info
Career: Zoologists and Wildlife Biologists
They study animals and their habitats to understand their behavior and help protect wildlife and the environment.
Parent Careers
Employment & Wage Data
Median Wage
$72,860
Jobs (2024)
18,200
Growth (2024-34)
+1.6%
Annual Openings
1,400
Education
Bachelor's degree
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Collect and dissect animal specimens and examine specimens under microscope.
2
Inform and respond to public regarding wildlife and conservation issues, such as plant identification, hunting ordinances, and nuisance wildlife.
3
Coordinate preventive programs to control the outbreak of wildlife diseases.
4
Oversee the care and distribution of zoo animals, working with curators and zoo directors to determine the best way to contain animals, maintain their habitats and manage facilities.
5
Make recommendations on management systems and planning for wildlife populations and habitat, consulting with stakeholders and the public at large to explore options.
6
Study animals in their natural habitats, assessing effects of environment and industry on animals, interpreting findings and recommending alternative operating conditions for industry.
7
Prepare collections of preserved specimens or microscopic slides for species identification and study of development or disease.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.
