Evaluating the Role of Artificial Intelligence in Wildlife Identification

The identification of wildlife species is increasingly hindered by the “taxonomic impediment”—a global shortage of human experts and the labor-intensive nature of manual identification. While Artificial Intelligence (AI) offers a transformative solution, its professional adoption depends on scientific trust and technical accessibility. This study evaluated these dynamics through a cross-sectional survey of 130 participants, predominantly undergraduate students (77.7%) aged 18–25 (85.4%). Results indicated a moderate level of AI awareness (58.5%), though usage remains dominated by general-purpose tools like Google Lens (86.9%) rather than specialized scientific platforms. Although participants generally viewed AI as useful (M = 3.45), a 40% “trust gap” persists, where respondents require expert verification before relying on AI results. Inferential analysis using Spearman’s Rank Correlation confirmed a significant positive relationship between a respondent’s wildlife knowledge and their perceived usefulness of AI (rs = 0.22, p = 0.010), suggesting that domain expertise actually enhances technological valuation. Primary hurdles to field adoption include internet dependency (44.6%), animal disturbance (40.8%) and misidentification risks (32.3%). Consequently, the findings advocate integrating AI as a “human-in-the-loop” assistant rather than replacing field biologists. The study recommends developing region-specific, offline-capable models and embedding AI-based conservation projects into college biology curricula to bridge the gap between casual and professional use.