Clinical readiness of artificial intelligence in urology and andrology: A PubMed-indexed scoping review and evidence map

Background Artificial intelligence is widely reported across urology and andrology, but publication volume does not show which applications are ready for supervised clinical evaluation. Objectives To map the PubMed-indexed clinical literature on artificial intelligence in urology and andrology and identify use cases with evidence sufficient for supervised pathway evaluation. Eligibility Criteria English-language PubMed/MEDLINE records published from January 1, 2020 to April 4, 2026 were eligible if they addressed clinically recognizable urological, andrological, or male sexual and reproductive health artificial-intelligence tasks. Urolithiasis was excluded by design. Sources of Evidence Twenty prespecified PubMed queries were supplemented by hand-searching of reporting frameworks, governance documents, and sentinel implementation studies. Charting Methods Records underwent artificial intelligence (AI)-assisted title and abstract screening with human adjudication, audit sampling, and a rule-assisted final eligibility sensitivity check with author confirmation. We staged priority translational evidence by validation depth, clinician comparison, prospective evaluation, workflow implementation, and outcome or economic evidence. Results After deduplication, prescreen filtering, AI-assisted screening, human adjudication, audit correction, file-level cleanup, and final eligibility verification, 2,892 published journal records were included. Evidence closest to supervised implementation planning clustered in prostate MRI reader assistance, prostate digital pathology, and urinary tract infection (UTI) triage and stewardship support. Bladder cystoscopy and AI-assisted sperm selection for intracytoplasmic sperm injection (ICSI) occupied a credible next tier, while pathway-level decision support and ambient documentation were supported by contextual implementation exemplars only. Clinician-reviewed patient-message response support, prostate-specific membrane antigen positron-emission tomography (PSMA PET) quantification, surgical video analytics, micro-ultrasound, and most andrology models remained earlier in translation; renal radiomics and retrieval-grounded guideline support remained exploratory. Conclusions In urology and andrology, clinical maturity currently tracks standardized inputs, defensible reference standards, bounded workflow roles, external validation, and retained human oversight more closely than publication volume or headline model performance.