Mapping AI Literacy Frameworks: A Global Document Analysis of Dimensions, Competencies, and Communication Gaps
TL;DR
A global document analysis of 34 AI literacy frameworks published between 2015 and 2025 to examine their disciplinary orientations, theoretical foundations, contextual specificity, and competency structures indicates that existing frameworks cover cognitive, technical, ethical, application-oriented, pedagogical, and affective dimensions, but communication-related competencies remain dispersed and insufficiently consolidated.
Abstract
Artificial intelligence (AI) literacy has emerged as an essential competency in the context of rapid technological transformation, yet existing frameworks have been developed unevenly across disciplines and rarely address the specific needs of communication-related fields. This study conducts a global document analysis of 34 AI literacy frameworks published between 2015 and 2025 to examine their disciplinary orientations, theoretical foundations, contextual specificity, and competency structures. The findings show that most frameworks are concentrated in education-oriented contexts, while communication-specific frameworks remain limited. In addition, 82.4% of the identified frameworks do not specify a national or regional context, and 73.5% do not specify an explicit theoretical or model-based foundation. Through qualitative coding and framework content synthesis, the study identifies a consolidated structure consisting of six overarching dimensions, 69 subdimensions, and 109 competencies. The results further indicate that existing frameworks cover cognitive, technical, ethical, application-oriented, pedagogical, and affective dimensions, but communication-related competencies remain dispersed and insufficiently consolidated. Elements such as communication and collaboration, digital communication and expression, AI-generated content evaluation, information and mis/disinformation, content authenticity, disclosure of AI use, and responsible AI practices appear across selected frameworks, yet they are usually embedded within broader competency structures rather than organized as a coherent communication-sensitive AI literacy framework. By revealing these disciplinary, conceptual, and communication-related gaps, this study provides an evidence-based foundation for future development of AI literacy frameworks for communication-related fields. Future research should further develop and empirically validate communication-sensitive AI literacy frameworks with communication students, educators, and professionals.