AI-Augmented Authenticity: Multimodal Artificial Intelligence and Trust Formation in Cultural Consumer Evaluation

This study examines how artificial intelligence (AI) contributes to contemporary processes of authenticity evaluation by functioning as a multimodal diagnostic cue in consumer decision-making. Drawing on survey data collected from 468 visitors at Terra Madre Salone del Gusto in Turin, Italy, the study tests a structural model comprising five latent constructs: Authenticity Trust, Perceived AI Usefulness and Diagnosticity, Multimodal Value, User Engagement, and Behavioural Intentions. The findings indicate that heritage-based and institutional authenticity cues remain foundational in consumers’ evaluations, but are increasingly associated with interaction with AI-supported information perceived as credible and diagnostically informative. Multimodal inputs—particularly the integration of textual, visual, and auditory narratives—are positively associated with perceived multimodal value and user engagement within AI-supported evaluation. Experiential enjoyment during interaction with the AI system is positively associated with behavioural intentions to adopt AI-supported evaluation tools, while behavioural intentions encompass both adoption readiness and a stated willingness to pay a premium for products perceived as authentic. Although the use of a convenience sample limits generalisability, the results highlight the broader potential of multimodal AI systems to enhance perceived diagnostic clarity and evaluative confidence in complex cultural and consumer environments. Conceptually, the study advances the notion of augmented authenticity, defined as a hybrid evaluative process in which tradition-based trust mechanisms are interpreted in relation to perceived AI diagnosticity and multimodal coherence. By situating AI within culturally embedded processes of meaning-making rather than purely instrumental evaluation, the findings contribute to interdisciplinary debates on technology-supported trust processes, consumer judgement, and the societal implications of AI-supported decision-making.