Harnessing Artificial Intelligence to Enhance Necropsy Workflows in Diagnostic Veterinary Pathology: A Narrative Review

Necropsy remains a key part of diagnostic veterinary pathology, providing valuable information on causes of death, herd health status and emerging animal diseases. Traditional necropsy practice, however, often faces limitations such as time pressure, subjective judgment, inadequate record keeping and weak use of accumulated data. Artificial intelligence offers a practical way to reduce these problems and improve postmortem examinations in veterinary medicine. This review examines how specific AI-based tools can support necropsy workflows by improving consistency, efficiency and data integration. Validated applications include computer vision-based lesion detection and natural language processing systems that structure necropsy reports for surveillance and retrospective analysis. Emerging uses involve multimodal data integration and decision-support systems that assist with differential diagnosis and targeted ancillary testing. While early evidence supports improved standardization and analytical capacity, many applications remain dependent on dataset quality, species-specific validation, and professional oversight. Artificial intelligence is therefore best viewed as a decision-support technology that complements, rather than replaces, veterinary pathologist expertise.