Purpose/Significance To systematically review the research status of artificial intelligence (AI) literacy assessment tools domestically and internationally, providing evidence-based support for tool optimization and practical application. Method/Process The databases including CNKI, Wanfang, VIP, PubMed, Embase, and Web of Science are systematically searched to identify original development studies of AI literacy scales. Data on development features, dimensional framework, and measurement properties are extracted. Basic features and dimensional evolution are summarized, and methodological quality as well as measurement properties quality are evaluated based on the consensus-based standards for the selection of health measurement instruments (COSMIN) guidelines, followed by grading recommendations. Result/Conclusion A total of 27 assessment tools are included. Content analysis reveals that the dimensional frameworks and connotations of the scales evolves over time and technological advancements, shifting from skill-oriented to comprehensive literacy-oriented approaches. Quality assessment indicates that some scales lack comprehensive validation of properties or sufficient evidence for content validity. Future efforts should focus on cross-cultural adaptation, longitudinal tracking studies, and dynamic dimensional optimization to advance the comprehensive development of AI literacy assessment tools, better serve medical AI literacy education, and enable precise evaluation.