This study explores the ethical integration of generative AI in higher education (HE) through a scientometric and content analysis. It identifies key research areas, including ethical frameworks, academic integrity, and student interaction with AI. The study highlights the dual role of AI in HE: its potential to enhance educational practices and its challenges in maintaining academic integrity and ethical standards. The findings reveal a growing interest in AI applications in HE, with significant citation bursts in areas such as machine learning, artificial intelligence, and higher education. The study also identifies three main thematic clusters: ethical frameworks and policy development, academic integrity and content creation, and student interaction with AI. The research underscores the need for ethical guidelines, AI literacy, and human-centered AI tools to ensure responsible AI use in HE. The conceptual model proposed in the study provides a framework for integrating AI in HE while balancing innovation with integrity. The study concludes that while AI offers substantial benefits for educational advancement, it also presents challenges that require vigilant governance to uphold academic integrity and ethical standards. The implications of the study extend to policymakers, educators, and AI developers, emphasizing the importance of ethical considerations in AI applications within HE.This study explores the ethical integration of generative AI in higher education (HE) through a scientometric and content analysis. It identifies key research areas, including ethical frameworks, academic integrity, and student interaction with AI. The study highlights the dual role of AI in HE: its potential to enhance educational practices and its challenges in maintaining academic integrity and ethical standards. The findings reveal a growing interest in AI applications in HE, with significant citation bursts in areas such as machine learning, artificial intelligence, and higher education. The study also identifies three main thematic clusters: ethical frameworks and policy development, academic integrity and content creation, and student interaction with AI. The research underscores the need for ethical guidelines, AI literacy, and human-centered AI tools to ensure responsible AI use in HE. The conceptual model proposed in the study provides a framework for integrating AI in HE while balancing innovation with integrity. The study concludes that while AI offers substantial benefits for educational advancement, it also presents challenges that require vigilant governance to uphold academic integrity and ethical standards. The implications of the study extend to policymakers, educators, and AI developers, emphasizing the importance of ethical considerations in AI applications within HE.