Determinants of Purchase Intention in AI-Driven E-Commerce: Evidence from Indonesian Digital Consumers

Abstract— In this study, 'AI' refers to the AI-driven personalization features implemented in e-commerce platforms. We focus on the user's perception of how these algorithms tailor product recommendations, dynamic layouts, and offers to fit their individual profiles. The study examines how this perceived personalization acts as a bridge to build trust and provides the contextual relevance that drives purchase intention. This study investigates the determinants of purchase intention in AI-driven e-commerce among Indonesian digital consumers. Specifically, it examines the roles of AI-based personalization, trust, and relevance. A quantitative approach was employed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with 241 respondents. The empirical findings reveal that among the examined structural antecedents, only Perceived Relevance serves as a statistically significant direct catalyst (β = 0.162, p = 0.022) that actively enhances consumer purchase intention. Conversely, AI-driven personalization does not exert a significant direct effect on purchase intention (β = 0.114, p = 0.289). Within the foundational structural layers, AI-driven personalization significantly strengthens Perceived Trust (β = 0.389, p = 0.019). Crucially, the structural model demonstrates that Perceived Trust (β = 0.228, p = 0.115) fails to significantly dictate final purchase intention. Ultimately, this study offers dual contributions: theoretically, it re-evaluates the privacy paradox under an algorithmic framework, and practically, it provides actionable insights for digital retailers to calibrate their AI deployment in strict alignment with the Indonesian Personal Data Protection Act (UU PDP).

Keywords: AI, E-commerce, Personalization, Trust, Privacy Concern, Purchase Intention, AI-driven e-commerce , Hyper-personalization , Algorithmic Recommendation Systems , Perceived Relevance , Privacy Paradox , Algorithmic Trust , Consumer Pragmatism , Purchase Intention , Data Ethics , Emerging Markets