As artificial intelligence (AI) continues to transform higher education, understanding both the opportunities and risks associated with its integration is essential for responsible decision-making. Building on a comprehensive review of 56 recent studies, this article applies a structured risk impact matrix to evaluate key AI applications in education — such as personalized learning, AI-driven assessments, generative content creation, and learning analytics — by balancing their potential benefits with inherent risks. This matrix categorizes and highlights major challenges, including ethical issues, data privacy concerns, scalability limitations, infrastructure needs, and adoption resistance. The framework provides educational institutions, policymakers, and educators with actionable insights and practical recommendations for guiding the effective, ethical, and scalable deployment of AI in higher education. By addressing these critical areas, this study supports the development of informed AI policies and promotes an environment where AI can enhance educational outcomes while safeguarding student privacy and institutional integrity.

Keywords: Benefits and Risks of AI in Education, AI Integration Challenges, Literature-Based Risk Analysis.