Cracking the code: how can AI-generated advertising be effective? Empirical evidence on the antecedents and consequences of advertising value

Abstract

Purpose As an extension to Ducoffe’s model on advertising value (1995, 1996), this study aims to examine the roles of factors such as informativeness, entertainment, irritation, credibility and perceived creativity as antecedents of artificial intelligence (AI)-generated advertising value, while also investigating the moderating effect of AI exposure. Design/methodology/approach The hypotheses were tested through a quantitative methodology using an online survey. Collected data were analyzed using partial least squares structural equation modeling. Findings The results indicate that creativity, entertainment and irritation significantly enhance the perceived value of AI-generated advertising, which positively affects attitude and purchase intention. Furthermore, AI exposure moderates the relationship between advertising value and attitude. Practical implications The findings provide insights into AI-generated advertising, offering practical recommendations for marketers seeking to optimize AI-generated content in their advertisements. Originality/value This study extends the reference model of advertising value to the context of AI-generated advertising and introduces the moderating role of AI exposure to a more comprehensive understanding of how consumers perceive AI-generated content.

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