Transforming Agriculture through AI, IoT, and Blockchain: Opportunities and Barriers in the Shift to Agriculture 4.0

Abstract

Agriculture faces mounting pressure to increase productivity while reducing its environmental footprint, coping with climate variability and meeting the food demands of a growing global population. Digital transformation, commonly framed under the banner of Agriculture 4.0, offers a pathway through which artificial intelligence, the Internet of Things and blockchain technology converge to reshape farming systems, from field-level decision-making to end-to-end supply chain governance. This review critically synthesises the peer-reviewed literature on the application, integration and diffusion of these three technology families across crop production, livestock management and agri-food supply chains. It examines how machine learning and deep learning models support yield forecasting and pest and disease diagnostics, how sensor networks, unmanned aerial vehicles and wireless communication architectures underpin precision agriculture and precision livestock farming, and how blockchain-enabled traceability and smart contracts are reshaping trust and transparency in supply chains. The review further considers the structural, economic, infrastructural and social barriers that constrain adoption, with particular attention to smallholder and low- and middle-income contexts, data governance and privacy concerns, and gender and digital-literacy gaps. Evidence indicates that although individual technologies have matured considerably, their convergence into interoperable, farmer-centred systems remains uneven and is shaped as much by institutional and economic conditions as by technical readiness. The review concludes by outlining priority research directions and policy considerations for equitable and sustainable technology-enabled agricultural transformation.