Alignment of GenAI Modalities With Product Types in Generating Ads: The Mediating Roles of Cognitive Load and Perceived Immersion
Suying Huang, Yushi Jiang · Journal of Consumer Behaviour · 2025
ABSTRACT With the continuous reshaping of digital marketing by generative artificial intelligence (GenAI), understanding how AI‐generated advertising can optimize the responses of consumers is critical for businesses. As GenAI evolves from unimodal models to multimodal models that jointly process texts, images, and audios, the literature still lacks a systematic comparison of their advertising effectiveness. This study aimed to address this gap by exploring the types of products to which unimodal and multimodal GenAI are applicable, and the underlying psychological mechanisms, respectively. A study of real‐world data demonstrates that multimodal AI‐generated advertisements are more suitable for experience products. Two online studies show that the perceived immersion of consumers can be enhanced by the integration of multimodal AI‐generated advertisements with experience products, which thereby generate favorable marketing outcomes. Conversely, the cognitive load of consumers can be reduced by combining unimodal AI‐generated content with search products, which thus strengthens their purchase intentions. This research proposes a modality‐product type matching effect and extends the existing research stream on the application of GenAI in advertising. It further provides marketers and advertisers with reliable strategies for leveraging GenAI.