Science · SOC 19-1023
Field observation and specimen collection are irreplaceable by AI; data analysis and literature review face meaningful automation pressure.
Parts of the job are exposed, but judgment and context still matter.
Timeline: AI image and audio recognition tools are transforming wildlife monitoring, creating demand for biologists who can interpret AI outputs and translate them into conservation action — but field presence remains essential.
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AI job-risk card
Zoologists and Wildlife Biologists is watch on AIFear. Parts of the job are exposed, but judgment and context still matter.
AIFear.com
Our AI Fear Score for Zoologists and Wildlife Biologists is 40/100 (Watch). Parts of the job are exposed, but judgment and context still matter.
40 out of 100, based on an AI-model review of this occupation's O*NET tasks against what current AI can actually do.
Most exposed: Writing scientific papers, reports, and journal articles, Conducting literature reviews for research planning, Analyzing animal characteristics to identify and classify them, Developing population management systems from data. Harder to automate: Field observation of wildlife in natural habitats, Collecting and dissecting animal specimens, Managing zoo staff and public outreach programs, Interpreting ecosystem-level findings for policy.
Lean into Wildlife population modeling, AI-assisted species identification (camera traps, audio), Field ecology and habitat assessment, Conservation policy and stakeholder engagement, Scientific communication. Consider roles such as Conservation Program Director or Wildlife Management Consultant or Environmental Impact Assessment Scientist.
Tasks, skills and AI-exposure for this role were reviewed by an AI model against its O*NET task profile (curated roles use published research anchors). Pay and employment, where shown, are U.S. BLS OEWS (May 2024) figures. This is an estimate, not a prediction about any individual's job. Compare all occupations.