Incorporating intelligent systems into STEAM education, covering science, technology, engineering, arts, and mathematics, has emerged as a promising approach to enhance learning and support personalized learning paths. However, the current understanding of their application in STEAM education is limited. This research addresses this gap by conducting a systemic mapping study to identify research trends, gaps, and challenges. A thorough search of major databases yielded 50 eligible articles, which were analyzed based on their focus on STEAM fields, educational levels, and pedagogical approaches. The findings show that intelligent systems are primarily used in science and technology, with less emphasis on engineering, mathematics, and arts. Most applications target higher education, particularly through online courses and learning management systems, employing approaches like personalized, game-based, and collaborative learning. Despite their potential, there remain certain challenges, such as limited empirical evidence on their effectiveness and a need for more research on integrating the arts. This research offers an overview of current contributions and identifies areas for future research in intelligent systems applications within STEAM education.