Human–AI Collaboration as a New Governance Paradigm? Unpacking China’s Land Policy Responses to Environmental Pressures and Digital Transformation

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Artificial intelligence (AI) is increasingly embedded in land governance, reshaping how environmental pressures and sustainability goals are addressed. Yet the institutional processes through which human–AI collaboration takes shape remain largely unexplored. This study examines whether human–AI collaboration is emerging as a new governance paradigm in China’s land sector, and if so, through what institutional pathways and practical forms it is being articulated and implemented. Drawing on a systematic analysis of 352 policy documents and case studies from coastal regions, the study develops and applies the CTI framework—an analytical lens that integrates Contextual conditions, Technological capabilities, and Institutional arrangements. The findings reveal three interrelated developments: (1) policy discourse constructs a coherent narrative in which environmental pressures and digital transformation jointly create an imperative for change; (2) a systematic division of labor between AI and human officials emerges in policy and is reflected in practice, with AI handling data processing and preliminary screening while humans retain final decision-making, value judgment, and accountability; and (3) this division is being institutionalized through a staged process of policy guidance, pilot mechanisms, and institutional adaptation. These developments suggest that human–AI collaboration may be taking shape as an emerging governance paradigm in land governance, one that is beginning to be codified and tested in policy and practice. The study contributes an integrative analytical framework, specifies the logic of human–machine division of labor, and extends collaborative governance theory beyond its traditional human-centric assumptions. The findings also carry implications for governance contexts where human–AI collaboration is reshaping land governance and other policy domains.