Artificial Intelligence as a Catalyst for Institutional Transformation in Higher Education

Abstract

Introduction: Artificial intelligence (AI) has evolved from a technological innovation into a strategic catalyst for institutional transformation in higher education. This study explores how AI supports the modernization of academic structures, pedagogical practices, and decision-making processes, moving beyond traditional models of technology adoption toward systemic educational innovation.

Objectives: This work aims to examine how AI contributes to the modernization of higher education by identifying key factors influencing its adoption. It also seeks to develop a strategic framework that aligns technological integration with institutional objectives, leadership practices, and organizational culture to foster sustainable academic transformation.

Methods: A mixed-methods approach was applied, combining quantitative and qualitative techniques. Guided by the Unified Theory of Acceptance and Use of Technology (UTAUT) and Sociotechnical Systems Theory, the study used Likert-scale surveys and focus group discussions with faculty and administrators to analyze individual and organizational perspectives on AI implementation.

Results: Findings reveal that successful AI integration depends not only on user training and technological proficiency but also on leadership engagement, institutional culture, and alignment with educational goals. Interdisciplinary collaboration and ethical awareness emerged as essential components for achieving meaningful and sustainable innovation through AI in higher education.

Conclusions: AI adoption in higher education represents a shift from isolated technological use to systemic innovation. A strategic framework is proposed emphasizing continuous professional development, ethical governance, and collaborative engagement to ensure that AI enhances quality, inclusiveness, and sustainability across institutional and pedagogical dimensions.