Artificial Intelligence and Educational Governance A New Model for Learning Universities

The main purpose of this study is to develop a conceptual governance model that integrates Artificial Intelligence (AI) into higher education systems to promote universities’ transformation into learning organizations. As universities face increasingly complex social and technological challenges, there is a need for adaptive, data-driven, and ethical governance frameworks that balance innovation with accountability. To achieve this goal, the research employed a qualitative meta-synthesis approach, systematically reviewing and synthesizing relevant studies published between ۲۰۱۵ and ۲۰۲۵ in databases such as Scopus, Web of Science, and ERIC. From an initial pool of ۲۲۰ articles, ۴۵ studies were selected based on their conceptual and empirical contributions to AI applications in educational governance. Data analysis was conducted through thematic coding and synthesis, leading to the identification of five major domains in which AI supports governance and organizational learning: (۱) data-informed leadership, (۲) predictive analytics for institutional planning, (۳) automated feedback and quality assurance systems, (۴) digital ethics and accountability, and (۵) personalized learning management. The main findings indicate that AI-driven governance enables evidence-based decision-making, strengthens collaboration across institutional levels, and fosters a culture of continuous learning. The proposed model underscores the dynamic interaction between technology, human agency, and organizational culture. This study provides theoretical and practical insights for policymakers and university leaders seeking to integrate AI responsibly into educational governance to build intelligent, adaptive, and learning-centered universities.

کلیدواژه ها:

Artificial Intelligence ، Educational Governance ، Learning Organization ، Higher Education ، Data-Driven Decision Making