Artificial intelligence is emerging as a major driver of transformation in higher education, reshaping universities from traditional teaching institutions into complex systems of knowledge production, sharing, and co-creation. This paper adopts a conceptual and analytical review approach to examine the impact of AI on core university functions, including teaching, research, and academic management. The findings show that although AI systems can process large-scale data, generate content, and support decision-making, they still lack ethical judgment, accountability, and contextual understanding of human values. In this framework, the future of higher education is defined through the “human-in-the-loop” paradigm, which emphasizes the central role of humans in problem formulation, evaluation of outcomes, and final decision-making. The study further highlights that the competitive advantage of future universities lies not in replacing human intelligence with machines, but in strengthening human–machine collaboration and developing key competencies such as critical thinking, data literacy, and prompt engineering. Moreover, this transformation requires the establishment of responsible, ethical, and transparent governance frameworks to ensure trustworthy adoption of AI in academic systems. Ultimately, the paper concludes that the competitiveness of universities in the era of artificial intelligence depends on the quality of human–machine interaction and the ability of higher education systems to cultivate responsible, adaptive, and creative decision-makers capable of operating effectively in AI-augmented environments.