Audience Interpretation of AI-Driven Product Visualization and Virtual Influencers in Culinary Marketing: S–O–R and Parasocial Approaches

Abstract

Background: Artificial intelligence has transformed how culinary products are visualized and communicated in digital marketing. Objective: This study develops a model of audience interpretation of AI-driven product visualization and virtual influencers in culinary digital marketing by integrating the Stimulus–Organism–Response (S–O–R) framework and Parasocial Interaction Theory. Methods: An interpretive qualitative approach with a phenomenological design was applied. Data were obtained from 12 informants: 10 audience members aged 18–35 who had encountered AI-driven culinary content on Instagram or TikTok, one digital marketing practitioner, and one AI expert. In-depth interviews, digital observations, and documentation were analyzed using NVivo 15 through open, axial, and selective coding, thematic categorization, and triangulation. Results: The findings show that AI-driven product visualization and virtual influencers function as stimuli that attract initial attention through aesthetic, modern, and realistic visuals. Audiences process these stimuli through cognitive, affective, and conative evaluations, including assessments of visual realism, message credibility, AI transparency, emotional appeal, uncertainty, and content authenticity. Audience responses appear in the form of engagement, information seeking, intention to try, and purchase intention, but depend on the consistency between promotional visuals and the actual products. Conclusion: This study recommends a human–AI hybrid strategy combining AI-generated visual appeal, transparency, authentic evidence, and human involvement.