Breakthrough and Path Optimization of the Dilemma of Public Housing Management in Universities from the Perspective of AI Empowerment

Abstract

As a core strategic resource supporting the high-quality development of higher education, the management level of university public housing directly impacts the enhancement of educational governance efficiency. The traditional public housing management model currently faces multiple challenges including the lack of collaborative mechanisms, imbalanced resource allocation, and ambiguous distribution mechanisms, making it difficult to meet the requirements of modern educational governance. The iterative upgrades of artificial intelligence (AI) technology have provided new possibilities for transforming public housing management models. Based on literature review and logical analysis, this paper examines the current status and core challenges of university public housing management. It explores three pathways to optimize AI-powered public housing management: establishing a multi-source data integration and cross-departmental collaboration system, implementing a three-dimensional dynamic allocation model with AI-driven optimization, and developing institutional innovations with transparent allocation supervision systems. The aim is to promote the transformation of public housing management towards data-driven, dynamically regulated, and collaboratively efficient practices, providing theoretical references and practical guidance for enhancing the modernization of university governance.