The Dark Side of Generative AI in Marketing: AI-Generated False and Misleading Advertising and Its Consumer Consequences

Generative artificial intelligence (GenAI) is transforming advertising by enabling marketers to create persuasive text, images, and other promotional content rapidly and at lower cost. At the same time, the ability of generative systems to produce highly realistic content creates concerns about deception, misinformation, transparency, and the credibility of consumer-facing information. The present study examines the consumer consequences of AI-generated false and misleading advertising, with particular emphasis on hallucinated product claims. The study focuses on whether AI-generated hallucinated product claims influence perceived deception, AI skepticism, and perceived information reliability, and whether these consumer responses subsequently shape purchase intention. Drawing on the stimulus-organism-response (S-O-R) framework, the study conceptualizes hallucinated product claims as the stimulus, the three consumer evaluations as the organism, and purchase intention as the response. A quantitative, cross-sectional, deductive research design was adopted. Data were collected from 320 business-school students and faculty members through a structured questionnaire using a five-point Likert scale, and the model was assessed using SmartPLS. The reported measurement results show Cronbach's alpha values above 0.70, composite reliability above the stated threshold, and average variance extracted above 0.50 for all constructs, indicating acceptable reliability and convergent validity. The reported discriminant-validity matrix also supports construct distinctiveness. The structural model reports a VIF range of 1.47-2.24 and an R² of 0.421 for purchase intention. Four of the six hypotheses are supported. AI-generated hallucinated product claims significantly increase perceived deception and significantly reduce perceived information reliability. Perceived deception significantly reduces purchase intention, while perceived information reliability significantly increases purchase intention. The paths from hallucinated product claims to AI skepticism and from AI skepticism to purchase intention are not statistically significant. The findings indicate that message-level judgments of deception and information reliability are more consequential for purchase intention in the reported model than generalized skepticism toward AI. The study extends the S-O-R perspective to the dark side of GenAI in advertising and highlights the importance of factual verification, transparency, human oversight, disclosure, and consumer AI literacy.