earticle

영어

AI platforms have been widely introduced in East Asian rural revitalization to enhance agricultural efficiency and promote smart governance. However, many of these platforms encounter "build-but-not-use" failures at the grassroots level. Drawing on comparative insights from Korea and Japan, as well as 13 semi-structured interviews conducted in Fujian, China, this study identifies three core institutional obstacles: information disconnection, feedback deficiency, and responsibility mismatch.To systematically analyze these challenges, a four-level nested framework— encompassing macro, meso, micro, and technical levels— is developed, alongside three mechanism chains: information, feedback, and responsibility. By integrating policy analysis, digital governance theory, and qualitative field research, the study constructs a structural diagnostic framework to reveal misalignments between institutional configurations and platform performance.Findings demonstrate that technical inefficiencies are deeply rooted in institutional coordination gaps rather than technological limitations alone. The research further validates three disconnection mechanisms— information gaps, feedback disruption, and responsibility ambiguity— across diverse East Asian contexts. This transdisciplinary approach bridges public administration and information systems, offering a novel pathway for institutional adaptation. The study offers transferable insights for optimizing rural digital governance and highlights the importance of cross-level coordination in the sustainable implementation of AI platforms.