Demystifying the impact of artificial intelligence word-of-mouth (AI-WOM) and knowledge management on social media engagement: comparing Vietnam and China

Purpose This study aims to investigate the impact of artificial intelligence word-of-mouth (AI WOM) on consumer social media engagement (CSME), with a particular focus on the role of AI knowledge management (KM) processes (knowledge acquisition, knowledge sharing and knowledge application), while using the algorithmic persuasion framework (APF) to explore how consumers’ perceptions of AI chatbots (perceived animacy, perceived intelligence, perceived anthropomorphism, perceived algorithm interpretability, perceived unbiasedness and perceived AI expertise) shape AI WOM. Design/methodology/approach A cross-country quantitative design was used using an online survey. Data were collected from 761 online responses in Vietnam and China. The survey was distributed through social media platforms and university networks, with initial seeds selected to ensure diversity in age and education. The hypothesized model was tested using a partial least squares structural equation modeling approach with SmartPLS4 software. Findings The findings reveal that AI WOM significantly influences CSME, with stronger effects in China, while consumers’ perceptions of AI chatbots substantially impact AI WOM, except for perceived intelligence. AI WOM also enhances KM factors, though knowledge sharing impact on engagement differs between Vietnam and China. Originality/value This is the first study to advance AI engagement literature by conceptualizing AI WOM as a distinct form of digital persuasion and contributes to KM research by positioning AI as an active enabler of knowledge dissemination and utilization. Theoretical and practical implications are discussed, providing valuable guidance for businesses leveraging AI-driven communication strategies to foster better consumer engagement across social media platforms.