دور الذكاء الاصطناعي في العلاقات الأكاديمية الدولية وتدويل مؤسسات التعليم العالي

The Role of Artificial Intelligence in International Academic Relations and the Internationalization of Higher Education Institutions

An Empirical Analysis from an Emerging Comprehensive University

The internationalization of higher education has become a defining marker of institutional legitimacy, yet the administrative infrastructure supporting it remains remarkably underdeveloped. International offices across the Global North and Global South continue to manage complex multi-institutional relationships through email, spreadsheets, and manual approval chains, generating what this paper conceptualizes as the Internationalization Management Gap (IMG): the structural disjuncture between an institution's stated internationalization ambitions and its capacity to realize them. Drawing on qualitative data from two structured focus groups and fifteen to twenty semi-structured interviews with faculty members and international office professionals, this paper examines three questions: what barriers prevent faculty from engaging in international academic activities; what tools would meaningfully enhance that engagement; and what AI-driven institutional solutions could address these barriers systemically. The paper introduces a dual-equation framework comprising the IMG, a composite index measuring the severity of the gap across three dimensions (Information Asymmetry, Workflow Fragmentation, and Digital Infrastructure Deficit), with empirically justified equal weighting, and the Internationalization Potential Index (IPI), which measures institutional readiness to close that gap through leadership commitment and faculty readiness. There is an obvious need for automated internationalization management infrastructure within higher education institutions that is not regionally specific: it is a structural condition of twenty-first century higher education globally. The paper highlights the fact that AI-powered internationalization management systems represent the most viable structural response to IMG, and evaluates the conditions under which such systems are most likely to produce meaningful and equitable outcomes.