As generative AI tools rapidly integrate into higher education—assisting with instruction, content generation, student evaluation, and research—universities face a complex landscape of ethical challenges. Drawing on a detailed review of current scholarship, this study evaluates the integration of generative AI, focusing on ongoing debates surrounding academic integrity, authorship, and the reliability of machine-generated output. Beyond individual misconduct, it addresses broader systemic risks, including algorithmic bias, data privacy vulnerabilities, detector inaccuracies, and the urgent need for clear institutional governance.

Varsha Dilipkumar Thombre, Pratiksha Kamble, "Responsible and Ethical Use of Generative AI in Higher Education" International Journal of Advance Research in Science, Management, Engineering and Technology, V1(4): Page(83-89) September - October 2026. ISSN: 3139-1141. www.ijarsmet.com. Published by Scientific and Academic Research Publishing.