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Culturally Adaptive AI Digital Humans for Cross-Border Service Delivery
Abstract
AI digital humans are increasingly used as intelligent self-service interfaces in global service sectors such as customer support, tourism, and digital government. However, their effectiveness is often limited by poor cultural adaptability, leading to miscommunication and reduced user trust. This study proposes a cross-cultural intelligent adaptation model that integrates context awareness, cultural filtering, and user feedback to enhance service interactions across cultural boundaries. Empirical results from multicultural user tests show significant improvements in communication accuracy and customer satisfaction. The findings offer practical guidance for service organizations deploying culturally sensitive AI agents to improve cross-border customer experience.
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