Generative AI and Meaning-Making in Media and Communication: A Systematic Review of Semiotic Perspectives (2021–2026)

Generative artificial intelligence (GenAI) is reshaping media and communication, yet research on its semiotic role in meaning-making remains theoretically and methodologically fragmented. This systematic review examines semiotic frameworks, technological modalities, communication contexts, and human–AI agency in research published from 2021 to 26 August 2026. Scopus and Web of Science searches identified 376 records; the final included corpus comprises 128 studies. The synthesis distinguishes between modality-specific concerns: studies of large language models primarily examine interaction and dialogue, whereas text-to-image studies emphasize representation and synthetic imagery. The RAW agency data contained four cases coded as predominantly AI-led, but these classifications changed following a documented text-consistency review, showing that the agency pattern is sensitive to coding decisions. We derive four provisional configurations: instrumental human anchoring, mediated distributed semiosis, co-creative/agentive participation, and contested or unresolved computational semiosis. The studies also reveal interconnected methodological, conceptual, cultural, technological, and governance gaps. These findings suggest that participation in sign production and mediation should be distinguished from claims of autonomous intentional agency; they do not establish whether generative systems possess intentional understanding.