With the growing integration of artificial intelligence into live streaming commerce, understanding how algorithmic features shape consumer acceptance becomes critical. This study investigates the influence of AI algorithm transparency on consumer trust within China’s live streaming ecommerce context, and examines the mediating role of perceived risk. Grounded in the Technology Acceptance Model (TAM), a quantitative survey was administered to 323 live streaming commerce users from Guangzhou and Hangzhou, with data analyzed via structural equation modelling. Results indicate that AI algorithm transparency significantly enhances consumer trust (?= 0.42, p < 0.001) and significantly reduces risk perception (?= 0.51, p < 0.001), while risk perception negatively affects trust (?= 0.38, p < 0.001). Furthermore, risk perception partially mediates the transparency–trust relationship (indirect effect = 0.19, 95% CI [0.12, 0.27]). These findings extend TAM to AI-driven retail settings, offering empirical evidence that transparent algorithms foster trust both directly and indirectly by alleviating consumer concerns. Practical implications for platform designers and marketers are discussed, alongside study limitations and directions for future research.
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