The Dual Edge of Generative AI in E-Learning: Supporting Decision-Making Under Uncertainty While Confronting Ethical Challenges in Higher Education

This study examines how recent research explores the impact of generative artificial intelligence on higher education, focusing on its role in decision-making under uncertainty and ethical challenges. A bibliometric analysis was conducted on 641 publications indexed in Scopus (2023–2024) to classify research trends, identify prolific authors, leading institutions, and the most relevant academic sources. The findings indicate a sharp rise in research activity during 2024, with most studies (75%) addressing artificial intelligence-based decision-making in e-learning. Geographically, China leads scientific production, followed by the United States and India. The analysis reveals that most studies highlight the potential of generative artificial intelligence to optimize administrative processes and enhance personalized learning, while also identifying critical concerns, including ethical risks, data privacy issues, and disparities in access to artificial intelligence-driven tools. Additionally, a substantial portion of research on ethical challenges emphasises the necessity of institutional policies to mitigate risks related to academic integrity and algorithmic biases. Despite the rapid expansion of research in this area, significant gaps remain, particularly in regulatory frameworks and teacher training programs for generative artificial intelligence adoption. This study underscores the necessity of well-defined ethical guidelines, tailored professional development for educators, and equitable infrastructure investment. By systematically mapping trends and research gaps, this study provides a foundation for ethical governance and AI-enhanced educational decision-making. Future research should refine regulatory frameworks, promote equitable AI adoption, and assess generative artificial intelligence's long-term cognitive and social impacts in learning environments.