Artificial Intelligence (AI) is revolutionising zoological research by enabling predictive, data-driven, and ethically informed approaches to the study of biodiversity. Advanced machine learning algorithms, image recognition systems, and predictive modelling now allow automated species identification, real-time behavioural monitoring, and analysis of complex ecological and evolutionary patterns that were previously challenging to quantify. These technologies enhance non-invasive research, reduce observational bias, and improve the efficiency and accuracy of wildlife conservation, ethology, and habitat assessment. This review critically evaluates the transformative applications of AI in zoology while addressing key challenges, including algorithmic bias, data quality, and the imperative for interdisciplinary collaboration among zoologists, data scientists, and ethicists. By integrating AI with traditional methodologies, researchers can adopt more predictive and holistic approaches to understanding ecosystems, informing sustainable conservation strategies, and safeguarding biodiversity. Responsible and transparent implementation of AI ensures that technological innovation aligns with ethical research standards, positioning AI as a pivotal tool for advancing zoological science in the 21st century.
Kumar et al. (Fri,) studied this question.