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Purpose The purpose of this paper is to provide an in-depth analysis of the challenges associated with using artificial intelligence (AI) in academic research and suggest various preventive measures that can be taken to address these issues and transform them into opportunities. Design/methodology/approach To develop measurement items and constructs, the authors collected 248 responses through an online survey. These responses were then used to establish the structural model and determine discriminant validity through the use of structural equation modeling with SmartPLS 4.0.9.9. Additionally, the authors used SPSS (Version 29) to create graphs and visual representations of the challenges faced and the most commonly used AI tools. These techniques allowed them to explore data and draw meaningful conclusions for future research. Findings This research shows that AI has a positive impact on higher education, improving learning outcomes and data security. However, issues such as plagiarism and academic integrity can destroy students. The study highlights AI’s potential in education while emphasizing the need to address challenges. Practical implications This paper emphasizes the preventive measures to tackle academic challenges and suggests enhancing academic work. Originality/value This study examines how AI can be used to personalize learning and overcome challenges in this area. It emphasizes the importance of academic institutions in promoting academic integrity and transparency to prevent plagiarism. Additionally, the study stresses the need for technology advancement and exploration of new approaches to further improve personalized learning with AI.
Tamanna et al. (Sat,) studied this question.