Allocative Efficiency and Distributive Equity in Healthcare Resource Allocation: A Multiregional Comparative Study of China’s Guangxi Region with AI-Enhanced Insights

Artificial Intelligence (AI) can enhance the allocation of medical resources through demand forecasting, optimization of resource allocation efficiency, and regulation of equity. Based on an analysis of medical resource allocation in Guangxi from 2019 to 2022, this study proposes a new productivity empowerment pathway centered on AI. A dataset covering population, economy, and geography was built. Data Envelopment Analysis and Gini coefficient assessments revealed an overall allocation efficiency of 0.9460, with the Western River Economic Belt showing the highest stability despite declining total factor productivity. In 2022, Beibu Gulf’s medical institution Gini coefficient reached 0.4317, while the 2020 bed and healthcare personnel allocation exceeded the 0.5 warning threshold. Spatial agglomeration analysis identified structural contradictions: “regional surplus–economic shortage” in Beibu Gulf and “regional shortage–economic surplus” in western Guangxi. To address these, a three-level strategy is proposed: policy-level dynamic systems guiding resource redistribution via hierarchical diagnosis and insurance adjustments; talent-level regional training programs; and technology-level development of a three-tier intelligent network connecting tertiary hospitals, county medical communities, and primary healthcare to advance AI-driven collaboration and lesion identification, improving both efficiency and equity.