When you're told it's AI: Disclosure Effects on Purchase Intent across Advertising Contexts : An Experimental Study on the Roles of Perceived Authenticity and Offering Type Congruence

Artificial-intelligence-generated content is increasingly used in advertising, creating new questions about how consumers respond when AI involvement is disclosed. Although prior research often associates AI disclosure with negative consumer responses, existing findings remain mixed, and less is known about the mechanisms and conditions that determine when disclosure becomes consequential. The thesis responds to this gap by examining how AI disclosure affects purchase intent, and whether this relationship is mediated by perceived authenticity and conditioned by offering type congruence. A quantitative scenario-based between-subjects experiment was conducted among 205 university students from Denmark and Germany. The experiment manipulated AI disclosure (label vs. non-label) and offering type (real-reality vs. fake-reality) to assess their effects on perceived authenticity and purchase intent. The findings show that AI disclosure did not have a significant direct effect on purchase intent across the full sample. However, disclosure reduced perceived authenticity only in the real-reality condition, where the advertised offering relied more strongly on perceived realism and connection to actual experience. In this condition, lower perceived authenticity subsequently reduced purchase intent. No significant disclosure effect emerged in the fake-reality condition. The thesis contributes to emerging literature on AI-mediated advertising by demonstrating that perceived authenticity functions as a mediating mechanism, while offering type congruence determines when disclosure becomes consequential. Practically, the findings suggest that managers should consider the fit between AI use and the offering context when designing and disclosing AI-generated advertising.