Decentralized Market Access for Farmers Using Blockchain-AI Tools

Abstract

Smallholder farmers face persistent barriers to fair market access: fragmented and opaque value chains, information asymmetries in pricing, delayed payments, weak bargaining power, and costly intermediation. Digital public infrastructure and recent advances in distributed ledgers and artificial intelligence (AI) offer a path to redesign market linkages around the farmer. This paper proposes and analyzes an integrated Blockchain-AI market access framework that (i) anchors farmer and farm identities to authoritative registries, (ii) tokenizes produce lots with verifiable quality, origin, and compliance metadata, (iii) uses smart contracts for listing, bidding, escrow, logistics, and automated settlement, and (iv) deploys AI for price nowcasting, quality grading, demand matching, and risk scoring for input credit and insurance. We situate the framework within current policy and infrastructure developments (e.g., India’s AgriStack DPI and e-NAM), and align data governance with the Digital Personal Data Protection (DPDP) Act, 2023. Evidence from the agri-food literature on digital market platforms and blockchain traceability (e.g., IBM Food Trust, Walmart pilots, OpenSC) suggests traceability and faster recalls, while mobile connectivity trends indicate a feasible last-mile channel for farmer-facing apps. Methodologically, we outline a multi-site, FPO-centered pilot with pre/post evaluation comparing realized farmgate prices, payment time, rejection rates, and spoilage against baseline channels. Illustrative pilot results show the potential for higher realized prices through improved price discovery, faster payments via escrow smart contracts, and reduced post-harvest losses through timed logistics triggers—subject to connectivity, digital literacy, and governance constraints. We conclude with a roadmap for phased rollout and discuss scope and limitations, including interoperability, standardization, and regulatory compliance.