Jun 2026· Jurnal Komunikasi Malaysian Journal of Communication· 0 citations
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.
The findings indicate that AI literacy integration is at its infancy stage, with integration patterns continuing to evolve, and is constrained by numerous challenges, including limited access to licensed AI tools, outdated infrastructure, lack of staff training, insufficient institutional support, ethical and data privacy concerns, and the absence of standardized pedagogical frameworks.
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