随着人工智能技术在高等教育领域的深入应用，高校教育评价正在经历由“管理”向“治理”的深层转变。AI为过程性评价、增值性评价和多元主体协同提供了新的技术基础，但在制度、主体、技术与价值层面仍面临多种制约。制度层面的路径依赖和数据权属模糊，使评价体系难以适应智能化场景；主体之间的权责不清、信任不足削弱了AI评价的参与基础；数据孤岛、算法偏见和可解释性不足等技术难题，进一步加剧了评价结果的不确定性；同时，技术效率导向与教育人文价值之间也存在内在张力。针对上述问题，本文提出构建弹性制度框架、重塑协同治理机制、完善敏捷技术治理体系以及培育信任文化氛围等策略，以期为高校教育评价改革提供可行路径。研究认为，只有在制度、技术与价值协同推进的前提下，AI赋能才能真正促进教育评价的公平性与发展性，实现对高校治理现代化的支撑。

With the profound application of artificial intelligence in higher education, university evaluation systems are undergoing a significant paradigm shift from a “management-oriented” model toward a “governance-oriented” approach. AI provides new technological foundations for process-based evaluation, value-added assessment, and multi stakeholder collaboration, yet its adoption still faces constraints from institutional, organizational, technical, and value related dimensions. Institutional inertia and unclear data ownership hinder the adaptation of existing evaluation systems to intelligent environments; ambiguous responsibilities and limited trust among stakeholders weaken participation in AI-based evaluation; persistent issues such as data fragmentation, algorithmic bias, and poor model interpretability further heighten uncertainties in evaluation outcomes. Meanwhile, tensions between technological efficiency and the humanistic values of education remain unresolved. In response, this study proposes strategies including constructing a flexible institutional framework, reshaping collaborative governance mechanisms, strengthening agile technical governance system, and fostering a culture of trust, aiming to offer feasible pathways for reforming university evaluation systems. The study argues that only through the coordinated advancement of institutional, technical, and value dimensions can AI truly empower educational evaluation to be more fair and developmental, to contribute to the modernization of higher education governance.