How Artificial Intelligence Influences Consumer Reflection in Decision‐Making: The Role of AI Anthropomorphism and Reinforcement

ABSTRACT Consumer reflexivity describes how individuals evaluate consumption in relation to their historical, social, and ideal selves. As AI‐driven recommendations become increasingly personalized, understanding how AI design features shape these reflexive processes is essential. This research examines the roles of anthropomorphism and reinforcement in influencing consumer reflexivity. Study 1 validates a self‐reflexivity model, showing that reflections on historical, social, and ideal selves sequentially drive self‐evaluation, emotional responses, and behavioral intentions. Study 2 employs a 2 × 2 experiment to assess structural stability and across anthropomorphism and reinforcement contexts. The core reflexivity pathway remains largely structurally stable across conditions, and cross‐condition tests of systematic path‐strengthening differences are not supported. Importantly, evidence from measurement invariance testing implies a shift in the meaning and composition of the ideal‐self construct, indicating a construct‐level, meaning‐shifting mechanism rather than a simple amplification of downstream relationships. The findings advance consumer identity research by distinguishing structurally stable self‐foundations from context‐sensitive aspirational representations in AI‐mediated interactions, and by offering guidance for designing human‐centered recommender agents that support reflective decision‐making and consumer well‐being.