Redefining Digital Influence: AI Chatbots vs. Social Media Influencers in Driving Customer Engagement and Online Shopping Intention

This study examines how specific antecedents of social media influencers (SMIs) and artificial intelligence (AI) chatbots bolster customer engagement, which subsequently shapes online shopping intention within emerging digital retail environments. This study adopts a quantitative method, and data were collected via an online survey with a final sample of 540 Lebanese users of AI and social media. The results confirmed the strong impact of AI chatbots’ antecedents on customer engagement. AI personalization had the strongest effect, followed by perceived usefulness, responsiveness, and trustworthiness. These dimensions significantly upend engagement with AI chatbots, which in turn positively predicted online shopping intention. Conversely, only SMIs’ expertise and communication quality influenced engagement with SMIs, while credibility and trustworthiness were nonsignificant. Customer engagement with SMIs had an insignificant impact on shopping intention, whereas engagement with AI chatbots significantly converted into online shopping intention, highlighting the rising impact of AI over influencer marketing in digital commerce. This study introduces a dual-theory framework by integrating the stimulus–organism–response model and customer engagement theory to explore how AI chatbots and SMIs’ antecedents sway online shopping intention via customer engagement. The study contributes by comparatively examining how established AI-related stimuli operate relative to SMI cues within a unified engagement framework. Unlike prior studies, this research reveals that SMIs may no longer serve as credible or trustworthy stimuli, challenging traditional influencer marketing assumptions. Practically, the findings underscore AI’s rising dominance in digital commerce, offering marketers actionable insights into designing responsive, personalized, and trustworthy AI interfaces.