Research on the impact of AI in higher education has grown significantly in recent years. Scholars from various fields have explored different aspects of AI implementation in higher education, including pedagogical innovations, learning analytics and student support, assessment and grading, educators' professional development, and ethical and social implications. However, there are still gaps in the research, such as the lack of emphasis on higher-order thinking skills, collaboration, communication, and AI skills in higher education studies.

Additionally, there is a need for further investigation into large-scale implementation of learning analytics, ethical considerations in assessment and grading, addressing educators' concerns and training needs, and exploring ethical concerns and societal impacts. Table 1 provides a summary of the existing research focus areas and identified gaps.