<![CDATA[The increasing adoption of artificial intelligence (AI) in social commerce has intensified the need to understand how algorithmic personalization and advertising relevance shape consumer behavior. Drawing on engagement theory and digital marketing perspectives, this study examines the effects of AI-driven personalization and perceived advertising relevance on online purchase intention, with customer engagement positioned as a mediating construct. A quantitative survey was conducted among 304 active social commerce users (response rate: 98.7%), and the data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS). The measurement model demonstrates strong reliability and validity, while the structural model reveals substantial explanatory power (R² = 0.599 for customer engagement; R² = 0.748 for purchase intention). The results indicate that AI-driven personalization and advertising relevance significantly enhance customer engagement, which in turn strongly predicts online purchase intention. Mediation analysis confirms that engagement partially mediates these relationships, highlighting its central role in translating technological precision and perceptual congruence into behavioral intention. The findings extend existing literature by integrating AI-enabled marketing mechanisms within an engagement-driven framework, emphasizing that personalization effectiveness depends not only on algorithmic accuracy but also on its capacity to generate meaningful user involvement in social commerce environments.]]>
