This systematic review maps the empirical landscape of AI literacy by examining its correlations with a diverse array of affective, behavioral, cognitive and contextual variables. Building on the review of AI literacy scales by Lintner (2024), we analyzed 31 empirical studies that applied six of those AI literacy scales, covering 14 countries and a range of participant groups. Our findings reveal robust correlations of AI literacy with AI self-efficacy, positive AI attitudes, motivation, and digital competencies, and negative correlations with AI anxiety and negative AI attitudes. Personal factors such as age appear largely uncorrelated with AI literacy. The review reveals measurement challenges regarding AI literacy: discrepancies between self-assessment scales and performance-based tests suggest that metacognitive biases like the Dunning Kruger effect may inflate certain correlations with self-assessment AI literacy scales. Despite these challenges, the robust findings provide a solid foundation for future research.
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