Adopting Generative AI: The Role of Generation Style in Ads for GenAI in Fostering Sense of Understanding
(A2026-132754)

AUTHORS

Chuang Wei, Central University of Finance and Economics

ABSTRACT

Generative AI (GenAI) is increasingly pervasive in practice. However, existing research has indicated the opacity of AI as a major obstacle to consumers’ adoption and advocated increasing algorithmic transparency, for example, by employing explainable AI. In contrast to the interface design approach, the present research proposes that a stepwise (vs. all-at-once) generation style in ads for GenAI increases consumer usage intentions by enhancing their sense of understanding. Furthermore, we identify cognitive load and prompt complexity as two theoretically derived moderators. Five studies, including one measuring actual behavior, were conducted to provide empirical support for the hypotheses. This research contributes to the literature on consumers’ adoption of GenAI, process-oriented advertising, and sense of understanding and offers practical insights for marketers of GenAI.