From land to data: how artificial intelligence shapes communication in the agri-food sector

Purpose This study explores how artificial intelligence (AI) transforms advertising strategies in the agri-food sector, with a focus on sustainability, personalization, and consumer trust. It investigates how algorithmic content impacts consumer behavior and the perception of product value, particularly in ethical and sustainable consumption contexts. Building on the Technology Acceptance Model (Davis, 1989), the Elaboration Likelihood Model (Petty & Cacioppo, 1986), and Trust Transfer Theory, this work conceptualizes AI not only as a technical tool but as a semantic mediator between brand and consumer. In the agri-food ecosystem—where values such as transparency and origin are key to trust—the study positions AI within a dynamic communication cycle between digital platforms, producers, and consumers. The theoretical integration addresses the specific expectations of trust in food-related decisions, highlighting AI’s potential and its boundaries in shaping sustainable, value-driven behaviors. Design/Methodology/Approach This contribution draws on a multi-theoretical framework that combines established and emerging perspectives to examine the role of AI in sustainable consumer engagement. Specifically, it integrates the Technology Acceptance Model (Davis, 1989), the Elaboration Likelihood Model (Petty & Cacioppo, 1986), and Trust Transfer Theory to explain cognitive and affective responses to AI-driven communication. Additionally, it incorporates AI-Driven Consumer Behavior, Generative AI in Marketing, Algorithmic Nudging, the Intention Economy, and the Word-of-Machine Effect to capture the dynamics of personalization, predictive analytics, and ethical influence. In line with research highlighting the role of open and sustainable innovation in the agri-food system (Pontieri et al., 2021), this framework acknowledges the complexity of food-related decisions and the importance of ethical alignment in algorithmic interactions. Finally, the Value Co-Creation Theory reinforces the idea that AI can act as a facilitator of meaningful, value-based interactions between brands and consumers in the agri-food sector. These questions aim to empirically investigate the mechanisms through which AI-based advertising influences consumer behavior in the agri-food sector: RQ1: Does AI adoption in agri-food advertising campaigns improve conversion rates? RQ2: Does perceived personalization mediate the relationship between AI-driven advertising and purchase behavior? RQ3: Does trust in AI content moderate the effect of perceived personalization on conversion? In line with the research framework, the following hypotheses are proposed to explore the tested dynamics H1:AI adoption is positively associated with advertising conversion. H2: Perceived personalization positively mediates the relationship between AI and conversion. H3: Trust positively moderates the relationship between personalization and conversion, enhancing perceived effectiveness. H4: In the agri-food sector, the adoption of AI-based advertising does not significantly influence consumer conversion in the absence of high trust, due to the specific relational and ethical expectations associated with food products. Methodology A quantitative survey will be administered to 400 consumers exposed to agri-food advertising (social media, e-commerce). Variables include frequency of exposure, personalization perception, trust, and conversion behavior. Data analysis will use factor analysis and Process macro (models 4 and 7) to test mediation and moderation, with multigroup analysis to compare green-oriented and price-oriented consumers. Findings AI is expected to positively affect conversion only when personalization and trust are high. Consumers sensitive to sustainability may respond more to AI content when it transparently integrates value-based elements like origin and traceability. AI's narrative capability plays a central role in driving ethical consumption. Originality/Value The study extends persuasive communication models into the domain of automated AI advertising in the agri-food sector. It positions AI not just as a technical channel but as a cultural actor that co-constructs meaning. For managers, it emphasizes that AI-based marketing must combine ethical design, narrative relevance, and transparency to convert algorithmic efficiency into sustainable value.