Student Relationship Management with Adaptive AI - Sangounsak, Kanyamaat; Boonrawd, Saowaluck; Prasertphongkun, Niramol; Pikulhom , Panisa; Phusomnuek , Radanut (International Journal of Educational Communications and Technology, 2025)
The integration of Adaptive Artificial Intelligence (AI) into Student Relationship Management (SRM) has emerged as a transformative strategy for enhancing student engagement, retention, and academic success. By leveraging AI-driven technologies, educational institutions can personalize student interactions, anticipate academic challenges, and optimize decision-making processes. This study examines the role of Adaptive AI in SRM, utilizing a systematic review and bibliometric analysis to synthesize existing research on AI-driven SRM frameworks. A conceptual structure for the integration of Adaptive AI into student management strategies is proposed, highlighting its potential to create a more responsive and student-centric educational environment. The findings emphasize the advantages of data-driven decision-making, predictive analytics, and personalized support mechanisms in improving institutional efficiency and student outcomes. Furthermore, this study explores key challenges associated with the implementation of AI in SRM, including technological constraints, ethical considerations, and data privacy concerns. As AI continues to shape the future of higher education, understanding its implications is critical for educators, policymakers, and institutional leaders. This research contributes to the growing body of knowledge on AI-enhanced SRM and provides valuable insights into best practices for integrating Adaptive AI into student support services. The study underscores the need for a strategic, data-informed approach to SRM, ensuring that AI-driven solutions align with institutional goals and student needs.