Intelligent cocoa: a systematic review of artificial intelligence applications in the cocoa supply chain

Purpose This study aims to provide a systematic and interdisciplinary review of the current applications of artificial intelligence (AI) across the cocoa supply chain, with a specific focus on the integration of technological and social dimensions. Design/methodology/approach The analysis is based on a structured literature review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Sources were retrieved from the Scopus database using targeted queries and selected through clearly defined inclusion and exclusion criteria. The contributions were thematically coded according to a functional classification of cocoa supply chain phases, allowing for the identification of both technological use cases and their social implications. Findings The results show that AI applications in the cocoa sector are rapidly evolving, especially in crop monitoring, disease detection, smart irrigation, post-harvest quality control, and traceability. The adoption of lightweight, interpretable AI models on low-cost devices is enabling the inclusion of smallholder farmers. Moreover, AI acts as both a decision-support tool and a driver of organizational transformation, fostering data-driven practices and ethical transparency within agri-food networks. Research limitations/implications The emergent and heterogeneous nature of the literature limits the comparability of results and the assessment of real-world impact. Future research should explore the longitudinal effectiveness and scalability of AI in operational environments, with greater attention to contextual barriers such as infrastructure, skills, and governance. Originality/value This is the first review to systemically map AI applications across all phases of the cocoa supply chain while also integrating socio-technical considerations. The study offers practical insights for technology developers, policymakers, and agri-food stakeholders aiming to promote ethical and sustainable digital transformation in global food systems.