The incorporation of AI into academia changes academic structures. From research methodologies to pedagogies and publishing, AI challenges conventional practices in knowledge acquisition, academic evaluation and production. While the applications of AI support enhanced accessibility, innovation and efficiency, there are also increasing issues and concerns regarding the ethics, values, and misuse of AI, including AI bias and regulatory gaps within academic institutions. Further exploration may reveal new strategies to successfully implement AI in education without issues of overreliance. Overdependence on AI in Academia explores the opportunities and consequences of AI integration in higher education. It examines concerns of academic freedom, equity, institutional responsibility, and the need for a human-centered approach to AI governance. This book covers topics such as curriculum development, digital literacy, and higher education, and is a useful resource for educators, computer engineers, sociologists, academicians, researchers, and scientists.