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Advances in technology are continuously reshaping its diagnosis, treatment selection, and prognosis assessment. In recent years, artificial intelligence (AI) has demonstrated marked potential in transforming bladder cancer care. By integrating and analyzing multi-source data, AI enhances the precision and efficiency of disease management. This review comprehensively examines the current applications of AI across various domains, including radiographic imaging analysis, pathological diagnosis, cystoscopic image processing, molecular subtyping, drug development, organoid research, prognostic modeling, and medical device innovation. It highlights the advantages of AI over conventional methods, outlines model development strategies, and summarizes commonly employed algorithms. Furthermore, we discuss the key challenges in translating AI tools into real-world clinical practice. This narrative review aims to inform the future development of AI-driven digital health systems, ultimately contributing to the realization of precision medicine and personalized management for bladder cancer patients.<\/jats:p>","DOI":"10.34133\/csbj.0197","type":"journal-article","created":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T19:37:07Z","timestamp":1784662627000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark_01","source":"Crossref","is-referenced-by-count":0,"title":["The Current Status and Evaluation of Artificial Intelligence in Bladder Cancer: Clinical Applications and Research"],"prefix":"10.34133","volume":"35","author":[{"given":"Zhuo","family":"Yin","sequence":"first","affiliation":[{"name":"School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, \rThe University of Hong Kong, Hong Kong SAR, China."},{"name":"Department of Urology, \rThe Second Xiangya Hospital of Central South University, Hunan, China."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2331-7011","authenticated-orcid":true,"given":"Joshua W. 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