The swift progress of Artificial Intelligence (AI) is altering the higher education landscape by changing how knowledge is produced, shared, and assessed. This study examines the transformative influence of AI on improving teaching efficacy, individualising student learning, and expediting academic research in universities. AI-powered tools like adaptive learning platforms, intelligent tutoring systems, plagiarism detectors, and predictive analytics are making teaching more efficient and getting students more involved. AI also helps teachers create inclusive, data-driven curricula that meet the needs of different types of students. This study employs a mixed-method research design, integrating quantitative data from surveys conducted with 300 faculty members and students in higher education institutions alongside qualitative interviews with 20 academic experts and AI practitioners. Quantitative data will assess perceptions, effectiveness, and acceptance levels of AI-based tools in education and research, whereas qualitative findings will investigate challenges, ethical considerations, and institutional preparedness. The results are expected to show that AI improves personalised learning outcomes, makes administrative work easier, and helps research and instruction make decisions based on evidence. But worries about data privacy, algorithmic bias, and being too reliant on technology are also important problems. The results will help teachers, policymakers, and leaders of institutions create guidelines for responsible and fair use of AI, which will encourage new ideas, openness, and academic success in the digital age.
Iqbal et al. (2025) studied this question.