Dr. Rebecca Rojansky, Assistant Professor and Co-Director for Pathology Informatics at Stanford University, discussed the evolving role of AI in pathology and how digital transformation is reshaping the field. She provided an overview of pathology’s place in the medical landscape and highlighted how AI can improve diagnostic accuracy, efficiency, and accessibility. Using a case study of a 30-year-old patient with suspected leukemia, Dr. Rojansky demonstrated how AI-powered tools assist in diagnosis, from blood tests to bone marrow biopsy analysis. She explained how digital pathology has streamlined workflows, reduced turnaround times, and helped address the global shortage of pathologists. However, challenges remain, including high data storage costs, lack of standardized formats, and difficulties in validating AI models. Despite these barriers, AI is already enhancing collaboration among pathologists by automating tedious tasks, such as detecting tumor cells and analyzing blood smears, and is opening new possibilities for integrating pathology data with patient records to enable personalized treatment. Looking ahead, Dr. Rojansky emphasized the need for further collaboration to structure pathology data for AI training, improve multimodal models, and develop cost-effective data storage solutions.