AI Architecture for Educational Transformation in Higher Education Institutions (Poornaprajna International Journal of Management, Education & Social Science (PIJMESS), 2025)
Background: The rapid integration of Artificial Intelligence (AI) into Higher Education Institutions (HEIs) is reshaping educational paradigms through AI architecture—structured systems that redefine education stakeholders, behavioural roles, and leverage predictive analytics.Objective: This paper aims to explore the current state, challenges, and transformative potential of AI architecture in HEIs, with a focus on teaching methodologies, student-centric learning paradigms, and administrative efficiency supported by Learning Management Systems (LMS).Methods: A mixed-methods approach was employed, analyzing data from diverse stakeholders across multiple universities and examining different approaches to online syllabus implementation, supplemented by a synthesis of global literature.Results: Findings indicate significant benefits, including the evolution of educational paradigms with AI and supporting technologies. This evolution facilitates transformation towards student-centric learning and operational efficiency, accompanied by shifts in the roles of teachers, students, infrastructure, and syllabi.Conclusion: The study proposes a four-phase transformation framework that highlights the development of AI-driven social learning ecosystems and new AI infrastructure, prioritizing these over traditional physical infrastructure. Sustainable implementation recommendations are also provided.
Keywords: Educational transformation; Methodology; Ecosystem; AI; Syllabi; Higher education institutions