<p>With socioeconomic development, market expectations for agri-food supply chains are increasingly high. Yet, traditional systems remain plagued by low automation, simplistic management, and chronic issues such as product waste, process opacity, and operational inefficiency. This review systematically examines advances in intelligent technologies across three key areas: harvest optimization, postharvest preservation, and stakeholder synergy. We assess the current applications of technologies including machine learning, deep learning, and the Internet of Things, which have improved efficiency in automated harvesting, non-destructive quality inspection, and dynamic cold chain management. Meanwhile, blockchain, digital twins, and smart contracts have significantly enhanced full-chain traceability and decentralized trust. Crucially, by incorporating real-world industrial case studies, this review transcends pure technological evaluation to critically analyze the structural barriers to large-scale commercialization. We highlight prominent challenges, including high capital expenditures, the global North-South digital divide, the “oracle problem,” and the inequality of data sovereignty. Finally, actionable recommendations are proposed for technology developers, core enterprises, and regulatory bodies. Ultimately, this work aims to guide the digital and intelligent transformation of agri-food supply chains toward a more efficient, transparent, and equitable global ecosystem.</p> Graphical Abstract <p></p>