Artificial Intelligence has been progressively integrated into healthcare services, especially after the Covid-19 pandemic, which has boosted its adoption. Despite the potential to improve diagnoses and optimize workflows, there are still gaps in the understanding of the use of Artificial Intelligence by healthcare professionals. Challenges such as professional training, system reliability and technological infrastructure limit its equitable implementation. Identify evidence on the use of Artificial Intelligence by health professionals, highlighting applications, benefits and challenges. This study aimed to identify evidence on the use of Artificial Intelligence by health professionals, highlighting applications, benefits and challenges, through a rapid scoping review with qualitative synthesis using the webQDA® software. A rapid review was carried out of original empirical studies, including descriptive, cross-sectional, observational and retrospective designs, published between July and December 2024 in Portuguese, English and Spanish, retrieved from the Web of Science, PubMed, Cochrane Library, Scopus and BVS databases with descriptors related to Artificial Intelligence and health, using inclusion and exclusion criteria. For the qualitative analysis of the data, the combination of the RAYYAN® and webQDA® tools was used. Artificial Intelligence has been applied in diagnosis and predictive medicine, regarding the accuracy of tests and speeding up clinical decision-making. However, challenges such as the lack of digital literacy among professionals, the need to validate algorithms and limited infrastructure have been pointed out as barriers to the adoption of these technologies. Artificial Intelligence can optimize clinical practice through greater diagnostic accuracy and operational efficiency. However, its implementation requires investment in professional training, continuous validation of systems and improvements in technological infrastructure.