<![CDATA[Wearable artificial intelligence (AI) technologies are rapidly transforming how human communication is sensed, interpreted, and augmented across multiple social contexts. Despite increasing research interest, comprehensive synthesis of empirical studies examining wearable AI in communication remains limited. This study presents a systematic literature review following the PRISMA 2020 guidelines to map the development of wearable AI communication research published between 2015 and 2025. Searches were conducted across five major databases—Scopus, Web of Science, PubMed, IEEE Xplore, and ACM Digital Library—yielding 93 eligible studies, of which 58 were included in a quantitative meta-analysis. The findings identify five dominant research clusters: health communication, interpersonal and social communication, occupational communication, educational communication, and accessibility communication. Smartwatches, EEG headbands, and biosensor-based wearables emerged as the most frequently used technological platforms, while deep learning architectures dominated analytical approaches. Results indicate that wearable AI systems can effectively infer communicative states such as emotional arousal, cognitive workload, and behavioral intention, with pooled accuracy exceeding 80% across several domains. However, significant challenges remain regarding methodological heterogeneity, limited demographic diversity, algorithmic bias, and underdeveloped ethical governance. The study concludes that wearable AI is reshaping the communicative landscape by integrating physiological sensing with algorithmic interpretation, while emphasizing the need for interdisciplinary research, inclusive datasets, and robust ethical frameworks to ensure equitable and responsible deployment.]]>
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