Given the growing demands in computer science (CS) education and the rapid progress of artificial intelligence (AI) technologies, this article presents a comprehensive review of selected empirical studies on AI in CS education, published from 2003 to 2023. The data for this review were sourced from the Web of Science, ACM Digital Library, IEEE Xplore database, and specialized AI in Education journals. Based on a set of predetermined criteria, 20 eligible studies were critically reviewed using multiple methods, including selected bibliometrics, content analysis, and categorical meta-trends analysis. This review generates an up-to-date synopsis of the current landscape of AI in CS education research. It highlights the specific AI technologies and their applications, assesses their confirmed and potential educational benefits, and establishes the connections between AI technological innovations and their practical implementations in CS education. The article also presents concrete examples and inspirational insights for AI technology experts as well as CS educators, who are at the forefront of incorporating AI advancements into CS education. Furthermore, it engages in extensive discussions regarding practical implications and outlines future research directions from a multitude of perspectives. The progression of AI needs initiatives aimed at addressing diversity, equity, and inclusion (DEI) concerns in CS education. Future research requires collaborative, interdisciplinary, and transdisciplinary efforts on a large scale, with a focus on long-term research and development endeavors.