The Effects Of AI-Washing On Consumer’s Trust, Ethics And Purchase Intention

Abstract

As artificial intelligence becomes a dominant signifier of innovation in marketing, the practice of AI washing as the strategic exaggeration or fabrication of AI capabilities in marketing communications has emerged as a critical ethical concern. This article reports study results examining AI washing perception and its consequences for consumer trust, perceived brand ethicality, purchase intention, and word-of-mouth (WOM) intention. Partial Least Squares Structural Equation Modeling (PLS-SEM) is employed with a survey sample of 854 consumers to establish predictive relationships. Drawing on the Trust-Action Model, Ethical Decision-Making Theory, and Consumer Information Processing Theory, the findings shows that AI washing severely and significantly damages all four consumer outcomes. Crucially, a serial mediation pathway Perceived Brand Ethicality-Brand-Trust-Behavioral Intentions was supported in the study, confirming that deception functions primarily as a moral failure before translating into eroded trust and suppressed behavior. Moderation analyses revealed a competence-based susceptibility gradient: technological literacy and prior AI experience amplified these negative effects, whereas age did not. Convergent cross-study effect sizes confirm robust findings with important implications for marketing practice, consumer protection, and AI governance.