“Made with AI” but why? How consumers interpret beneficiary-framed AI disclosures in advertising

Abstract

Abstract As generative AI becomes more prevalent in advertising, firms increasingly face requirements to disclose AI involvement. Although prior research shows that such disclosures may generate negative consumer responses, it remains unclear whether explanatory disclosures can mitigate these effects. This research examines beneficiary-framed AI disclosures, explanations communicating why AI was used and who benefits, across three studies. In a controlled text-based experiment (Study 1), more specific explanations improve evaluations relative to minimal and less specific AI labels. However, beneficiary framing effects are not systematic, and practically negligible. Moreover, these benefits do not generalize to more realistic advertising contexts. Across two Instagram-style ad studies (Studies 2A and 2B), explanatory disclosures fail to improve consumer responses and, in some cases, lead to more negative evaluations with effects that are either statistically equivalent to zero or significantly negative. Across studies, AI aversion emerges as a robust predictor of negative responses, suggesting that disclosure effects are driven more by consumers’ prior beliefs than by the specific framing of explanations. The findings suggest caution in adding explanatory disclosures, as default inferences of firm-serving motives are difficult to override.