A multicenter consortium validated artificial‑intelligence models for classifying urothelial neoplasms on digital pathology slides, reporting robust performance across institutions. The research team—including J.Y. Park, J. Kim, and Y.J. Kim—benchmarked models against expert pathologists and highlighted potential to standardize diagnostics and triage cases for molecular testing. The study addressed generalizability by testing models on external datasets, a common barrier to clinical deployment. For readers: digital pathology combined with validated AI can accelerate diagnosis and reduce interobserver variability in tumor grading and subtype classification.