The Future of Higher Education: University Systems, Artificial Intelligence and University Competitiveness in the Global Space Systematic Literature Review

Abstract

This systematic review, entitled “The Future of Higher Education: University Systems, Artificial Intelligence and University Competitiveness in the Global Space,” was conducted with three main objectives. First, it aimed to examine the influence of university systems on the global competitiveness of universities. Second, it sought to assess the moderating role of AI on the relationship between university systems and global competitiveness of universities. Third, it intends to establish the joint effect on university systems, AI, and global competitiveness of universities. Data for the review were collected through a systematic search of major academic databases, including Scopus, Web of Science, ERIC, and Google Scholar. The search strategy included a defined set of keywords and Boolean combinations such as “artificial intelligence,” “university systems,” “higher education,” and “global competitiveness.” Empirical studies published between 2019 and 2025 were considered. Inclusion criteria focused on peer-reviewed studies that explored the intersection of AI, institutional systems, and competitiveness in higher education. After applying the selection criteria and screening process, twenty empirical studies were included in the final analysis. Data were analyzed using a thematic synthesis approach. Information on study context, methodology, AI applications, outcomes, and theoretical frameworks was extracted, coded, and grouped into thematic categories. The findings revealed that AI is being integrated into various domains of university operations, including administrative processes, student support services, research management, and curriculum development. Institutions that adopted AI strategically demonstrated enhanced efficiency, innovation capacity, and global engagement. The review also found that AI served as a moderating factor, amplifying the positive effects of institutional systems on global competitiveness when effectively aligned with strategic goals. The study concluded that the integration of AI in higher education is reshaping how universities operate and compete on a global scale. However, it also identified limitations in the current literature, including the absence of unified theoretical frameworks, limited longitudinal studies, and a lack of focus on regional diversity and equity implications. As a result, the review recommended that future research adopt more comprehensive and integrative models that combine systems theory, digital transformation frameworks, and strategic innovation perspectives. It further suggested that policymakers and institutional leaders develop enabling environments that support ethical, inclusive, and context-sensitive AI integration. These conclusions and recommendations are intended to inform research, policy, and institutional strategies in addressing the evolving challenges and opportunities presented by artificial intelligence in the global higher education landscape.