Bytes and bites: Consumer perceptions toward the power of artificial intelligence for foodborne risk mitigation through traceable food

This study investigated consumer attitudes and intentions toward adopting artificial intelligence (AI) in food traceability systems, an emerging technology aimed at enhancing food safety and transparency. Data collected from an online survey of 1013 United States consumers, the study applies structural equation modeling (SEM) to examine the factors influencing consumer acceptance. Results showed that attitudes and perceived behavioral control are positively associated with decisions to accept AI-assisted food traceability, with trust in science, food safety concerns, fear of food technology, and risk information-seeking behavior also important factors. The model explained 80.2 % of the variance in intention and 18.0 % in attitude. Perceived behavioral control had a stronger impact on intention than attitude, suggesting that consumers who feel they have control over their food choices are more likely to support AI-enhanced traceability. Additionally, trust in scientific institutions emerged as a key predictor of acceptance, underscoring the importance of transparent and science-backed communication strategies. The study also highlights how concerns about foodborne illnesses and proactive risk information-seeking behaviors are positively associated with attitudes toward AI-assisted traceability. In contrast, food technology neophobia is negatively associated with acceptance, indicating the need for targeted educational campaigns to reduce skepticism. These findings provide valuable insights for policymakers, food industry stakeholders, and science communicators in designing effective strategies to enhance consumer confidence in AI-driven food safety initiatives. By addressing consumer concerns and fostering trust, AI-assisted traceability can be more successfully integrated into food systems, ultimately reducing foodborne illness risks and improving public health.