Generative and predictive artificial intelligence systems have moved from the edges of education to the heart of teaching, learning, research and administration in just a few academic years. In this article I offer a literature review of the chances and dangers that artificial intelligence, especially generative AI brings to universities. I focus on integrity the way teachers are changing how students learn and think critically digital equity, digital divide and institutional governance. I rely on peer‑reviewed studies, systematic reviews, meta‑analyses and international policy guidance that were mostly published from 2022 to 2026. The review pulls together evidence on tutoring systems and personalized learning on how reliable and fair AI detection tools are, on how often and how artificial intelligence causes academic misconduct and on how assessment redesign is occurring in learning environments full of artificial intelligence. The review shows that data on learning outcomes is very mixed. Long research on tutoring systems shows steady moderate gains in achievement. But recent studies on AI are split: some say students become more engaged others say exam scores drop students rely too much on artificial intelligence and independent thinking weakens. Likewise artificial intelligence‑detection technologies that aim to protect integrity are not reliable and they show bias against non‑native English writers highlighting algorithmic bias and due‑process concerns that current institutional policy has not fixed. The review points out a gap between fast technology roll‑out and slow high‑quality, long‑term research that covers many institutions. It argues that careful use of intelligence in higher education demands changes in teaching design, fairness of access, data governance, AI governance and keeping human academic judgement. The article ends with recommendations that are based on evidence for universities, teachers, students, researchers, policymakers and technology makers. It also suggests a framework that links artificial intelligence adoption to learning results via the middle steps of institutional governance and responsible implementation.
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- Anonymous (Author), 2026, The future of Education with AI. How AI affects Higher Education, Munich, GRIN Verlag, https://www.grin.com/document/1763890
