Surveillance, Suggestion, and Sabotage: Understanding Consumer Pushback Against <scp>AI</scp> in E‐Commerce and Q‐Commerce

ABSTRACT This research explored the psychological and behavioral resistance of consumers toward AI‐enabled personalization in the contexts of e‐commerce and quick commerce (Q‐commerce). Though advanced AI technologies offer benefits such as efficiency and convenience, consumers report concerns about emotional manipulation, information overload, and diminished consumer autonomy. Using the Technology Threat Avoidance Theory (TTAT) and the Stimulus–Organism–Behavior–Consequence (SOBC) model, we have explained how AI‐related stimuli may evoke consumer resistance. We used a mixed‐methods approach. In Study 1, we conducted in‐depth interviews with 18 Indian consumers to identify the dominant factors of resistance, and in Study 2, we surveyed 487 consumers. We validated and tested the proposed framework using Confirmatory Factor Analysis (CFA) and structural equation modelling (SEM). Findings show that emotional manipulation and information overload increase consumers' threat perception of AI and psychological reactance. These, in turn, lead to resistance intentions, platform avoidance, and brand distrust. However, brands' CSR initiatives and human oversight throughout the process can weaken the relationship between resistance behaviors and brand distrust. In short, our findings suggest that consumer resistance to AI is a patterned response to emotional and ethical concerns‐ not a direct rejection of AI. This study provides helpful insights for managers, designers, and policymakers to develop more transparent and responsible AI systems in the context of e‐commerce and Q‐commerce.