Digital transformation and artificial intelligence in organic supply chains: A systematic review with insights from South Tamil Nadu

Abstract

Organic agriculture is growing rapidly in India, yet organic supply chains remain structurally fragmented, particularly in smallholder-dominated regions such as South Tamil Nadu. Digital transformation and artificial intelligence (AI) offer promising solutions to persistent challenges, including inadequate cold-chain infrastructure, limited traceability, intermediary-dependent marketing and certification workflow inefficiencies. This systematic review draws on evidence from 30 peer-reviewed and institutional publications. These sources were identified through a PRISMA-compliant search of Scopus, Elsevier, Taylor & Francis, Web of Science, IEEE, MDPI, Wiley, FAO, and government databases. The findings indicate that AI-enabled precision farming, machine learning-based demand forecasting, Internet of Things-enabled cold-chain monitoring, and blockchain-supported traceability improve production efficiency, market access and organic supply chain transparency. However, widespread adoption is constrained by inadequate rural connectivity, limited digital literacy, incompatibility between digital platforms and Participatory Guarantee System certification workflows, and weak first-mile infrastructure. This review proposes the Digital Transformation and AI Readiness Framework for Organic Supply Chains (DARF-OSC). DARF-OSC is a five-stage conceptual model that integrates Diffusion of Innovations theory with the Resource-Based View. Also, this review identifies five key research gaps and tiered policy recommendations for South Tamil Nadu.