(untitled) (Research, Society and Development, 2026)
Artificial Intelligence (AI) has progressively expanded from experimental applications to clinically relevant performance across multiple medical domains. This integrative review analyzes current applications of AI in Brazilian medical practice, with emphasis on clinical integration, governance challenges, and strategic perspectives. A structured search of PubMed, SciELO, and Google Scholar was conducted covering publications from 2018 to 2025. A total of 127 studies were included in the qualitative synthesis, and 20 high-impact studies were selected for in-depth thematic analysis. Results indicate consolidated diagnostic performance in imaging-based specialties and predictive modeling, while highlighting persistent gaps in external validation, real-world implementation, and equitable deployment. Recent developments in generative AI introduce additional regulatory and safety complexities, particularly regarding dynamic validation and post-deployment monitoring. In Brazil, AI integration occurs within a universal healthcare system marked by infrastructural heterogeneity and evolving regulatory frameworks, including the General Data Protection Law and the National Digital Health Strategy. The findings suggest that sustainable AI integration depends not solely on algorithmic sophistication but on governance maturity, institutional readiness, and equitable health system strengthening.