This systematic review, titled “The Future of Higher Education: University Systems, Artificial Intelligence and University Competitiveness in the Global Space,” was carried out with three primary objectives. The study aimed to analyze the impact of university systems on the global competitiveness of universities. This study aimed to evaluate the moderating effect of AI on the relationship between university systems and the global competitiveness of universities. Third, it aims to determine the combined impact of university systems, artificial intelligence, and the global competitiveness of universities. The review data were obtained via a systematic search of prominent academic databases, such as Scopus, Web of Science, ERIC, and Google Scholar. The search strategy comprised a specific set of keywords and Boolean combinations, including “artificial intelligence,” “university systems,” “higher education,” and “global competitiveness.” Studies published from 2019 to 2025 were analysed. The inclusion criteria emphasised peer-reviewed studies examining the relationship between AI, institutional systems, and competitiveness within higher education. Following the application of the selection criteria and screening process, a total of twenty empirical studies were incorporated into the final analysis. The analysis of data employed a thematic synthesis approach. Data regarding study context, methodology, AI applications, outcomes, and theoretical frameworks was systematically extracted, coded, and organized into thematic categories. The findings indicate that AI is integrated into multiple areas of university operations, such as administrative processes, student support services, research management, and curriculum development. Institutions that strategically adopted AI exhibited improved efficiency, increased innovation capacity, and greater global engagement. The review identified AI as a moderating factor that enhances the positive impact of institutional systems on global competitiveness when properly aligned with strategic objectives. The research findings indicate that AI integration in higher education is transforming university operations and competition internationally. It also identified limitations in the existing literature, such as the lack of unified theoretical frameworks, insufficient longitudinal studies, and inadequate attention to regional diversity and equity implications. The review suggested that subsequent research should utilize more comprehensive and integrative models that incorporate systems theory, digital transformation frameworks, and strategic innovation perspectives. It recommended that policymakers and institutional leaders create environments that facilitate ethical, inclusive, and context-sensitive integration of AI. The conclusions and recommendations aim to guide research, policy, and institutional strategies in responding to the changing challenges and opportunities posed by artificial intelligence within the global higher education context. Higher education, university systems, artificial intelligence, and university competitiveness are critical areas of study that warrant further exploration and analysis.