Generative A.I. in sport advertising: effects of source-message (in)congruence, model types and A.I. awareness

Purpose The purpose of the study was to investigate the effects of artificial intelligence (A.I.) awareness, advertisement models and source-message incongruence on consumer evaluations of A.I.-generated advertisements. It explores how these factors interact in shaping consumer perceptions and advertising effectiveness. Design/methodology/approach A 2 (source-message (in)congruence: incongruent vs. congruent) x 3 (A.I. awareness: unawareness, pre-advertisement, post-advertisement) x 3 (advertisement model: traditional human, virtual human, digital twin) between-subjects design was employed in this study. Using stratified random sampling, a total of 231 undergraduate students were recruited from course groups and randomly assigned to one of nine experimental treatments, each involving the viewing of a specific A.I.-generated advertisement followed by a survey. Data were analyzed using two-way ANCOVA and regression analyses, controlling for participants' involvement in sports and brand. Findings The results indicated that A.I. awareness timing, advertisement model types and source-message incongruence significantly affected consumer evaluations of advertisements. A.I. awareness generally had a positive impact on evaluations, with the most favorable outcomes when awareness of the A.I.-generated nature occurred after viewing the advertisement. Virtual human models were rated the lowest, while digital twin and traditional human models received similarly positive evaluations. Source-message incongruence negatively influenced evaluations. An interaction effect was observed between A.I. awareness timing and advertisement model types under high source-message incongruence, where virtual human models showed the highest effectiveness when A.I. awareness occurred after viewing. Originality/value Given that sports are characterized by the transcendence of human limitations and the emphasis on physical and emotional challenges – elements that A.I. cannot replicate – it is essential to examine how sports consumers perceive A.I., which, despite offering efficiency and personalization advantages, contrasts with the fundamentally human nature of athletic performance. This research contributes to the literature on A.I.-generated advertising by uniquely investigating the interaction between A.I. awareness timing and advertisement model types within the context of source-message incongruence. It offers critical insights for practitioners and researchers on strategically timing A.I.-generated ad disclosures and selecting appropriate advertisement models to optimize their effectiveness. By addressing these underexplored variables, the study enhances understanding of consumer perceptions and provides a foundation for more effective A.I. integration in advertising practices.