Recent research has emphasized the growing use of artificial intelligence (AI) in public health communication. However, the effectiveness of AI in developing and implementing culturally sensitive health communication strategies is poorly understood. The complexity of cultural diversity in public health communication prompted a scoping review to systematically examine existing research on the use of AI in developing and implementing culturally sensitive health communication strategies that promote cultural responsiveness and enhance public health. The present study employed a scoping review methodology in line with the Arksey and O’Malley framework and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews. Data were collected from published studies from MEDLINE (PubMed), Scopus, and Google Scholar in the last five years. From the 933 studies initially identified, screening yielded 15 relevant articles spanning 2019 to 2024, assessing AI’s impact of AI across diverse geographical contexts, such as the USA, UK, and China. These studies affirm AI’s efficacy of AI in crafting public health messages that incorporate cultural nuances and ensure anonymity, thus addressing the specific needs of racially minoritized communities. However, varying levels of acceptance are often influenced by ethical concerns, resulting in low trust and patient acceptance of AI for culturally responsive communication in public health care. This scoping review underscores a significant uptick in AI-driven approaches to culturally sensitive public health communication. Despite notable advancements, the body of empirical evidence is limited and primarily focuses on AI systems with minimal decision-making autonomy. Persistent challenges in user acceptance, especially within culturally sensitive settings, indicate that cultural sensitivity and trust-building are pivotal for the successful integration of AI in public health messaging. These findings necessitate further research to deepen the understanding and enhance the effective deployment of AI in diverse cultural contexts.
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