Designing game-based learning experiences in Artificial Intelligence Education (AIE) offers several important advantages and contributes to a more effective and engaging educational process. It lies in its ability to enhance engagement, foster active learning, and prepare students for the challenges of the dynamic field of artificial intelligence. This research utilizes a systematic review approach to investigate the landscape of designing game-based learning within Artificial Intelligence Education (AIE). A comprehensive search strategy is implemented, adhering to the PRISMA guidelines for systematic reviews and meta-analyses. After the initial identification of 39 records, a meticulous process of assessment was undertaken, resulting in the removal of 1 duplicate record. The remaining 38 records underwent a stringent screening process, leading to the exclusion of 9 studies based on predetermined criteria. This comprehensive screening and evaluation method focused on the relevance and alignment of 29 records with the researchs core focus. The final tally of records selected for the study amounts to 19, ensuring a comprehensive and highly relevant analysis that concentrates on higher education and the student perspective within the realm of game-based learning in Artificial Intelligence (AIE). The comprehensive SWOT analysis encapsulates the strengths in demonstrating enhanced learning outcomes and diverse methodologies, while highlighting limitations in generalizability and methodological constraints. It is recommended that while the current studies present encouraging advancements in game-based AI education, the continuous pursuit of in-depth research, diverse methodologies, and broader case studies remains imperative to solidify the efficacy, ethical implications, and applicability of these innovative educational strategies.