Towards Effective AI Adoption in Higher Education: A Comprehensive Conceptual Model

Abstract

The adaptation of Artificial Intelligence (AI) in higher learning system is a revolution that has brought about improvement in student learning and administration. Therefore, the purpose of this research is to explore the different factors that would enable the successful integration of AI technologies in higher learning institutions, based on the gaps observed in the literature where most of the studies have emphasized on the technological aspects. Key factors, including digital literacy, cultural acceptance, data availability and quality, funding availability, infrastructure, user readiness, and ethical and privacy concerns, were identified for developing a unified conceptual framework. Lastly, this analysis underscores the mutual dependencies of these elements, giving a systematic understanding that is vital for AI integration. Thus, through the inclusion of multiple perspectives on the integration of AI into education, this study provides comprehensive findings regarding the possibilities and difficulties that arise from AI integration, which will help to create specific AI solutions to improve educational results.