UTTAR PRADESH JOURNAL OF ZOOLOGY

Artificial intelligence (AI) is increasingly used in zoological sciences to support the analysis of large, complex and heterogeneous biological and environmental datasets. This review synthesises the applications, advances, challenges and future perspectives of AI in zoology, ecology, aquaculture, toxicology and biodiversity conservation. The manuscript highlights the contribution of machine learning, deep learning, computer vision, bioacoustics, remote sensing, Internet of Things technologies and explainable AI to species identification, taxonomic research, animal behaviour analysis, wildlife monitoring, population estimation, disease surveillance and zoo management. In ecology and conservation, AI-assisted tools improve biodiversity assessment, habitat mapping, species distribution modelling, ecological forecasting, climate-change assessment and conservation planning. In aquaculture and fisheries, AI supports smart production systems through water-quality monitoring, precision feeding, biomass estimation, growth prediction, disease detection, mortality assessment, stock evaluation and sustainable resource management. In toxicology and ecotoxicology, AI contributes to predictive toxicity modelling, environmental risk assessment, biomarker discovery and alternative approaches that may reduce dependence on animal experimentation. The review also identifies major constraints affecting AI implementation, including data quality, taxonomic and geographical bias, limited interpretability, computational demands, cybersecurity risks, ethical concerns, regulatory requirements and unequal access to technology. Particular attention is given to the need for robust validation, interdisciplinary expertise and context-specific interpretation when AI outputs are used for biological or management decisions. Future progress is expected to depend on responsible integration of explainable AI, multimodal models, digital twins, environmental DNA analytics, omics technologies and autonomous monitoring systems. Overall, AI provides important opportunities to strengthen evidence-based zoological research and environmental management, provided that its use remains scientifically validated, ethically governed and complementary to field expertise.