ARTIFICIAL INTELLIGENCE USE AND INTELLECTUAL CAPITAL FORMATION: AN EMPIRICAL STRUCTURAL EQUATION MODELING APPROACH

Abstract

This study examines the determinants of artificial intelligence (AI) use and its role in the formation of intellectual capital through the empirical testing of a structural equation model. The research adopts a quantitative, explanatory, and cross-sectional design based on data collected from university students and academic staff exposed to AI-based educational and knowledge management systems. The proposed model integrates institutional and individual determinants—governance quality, institutional support, digital skills, trust in AI, and user satisfaction—and analyzes their effects on AI use as a mediating variable influencing intellectual capital formation. The results demonstrate that AI use plays a central mediating role, translating favorable governance structures, user competencies, and experiential conditions into enhanced human and structural capital. Digital skills and user satisfaction emerge as the strongest predictors of AI use, while governance and institutional support provide essential enabling conditions. Overall, the findings highlight that the contribution of AI to intellectual capital is not automatic but contingent upon coherent socio-technical and governance arrangements. The study provides empirical evidence to support strategic decision-making in educational and organizational contexts seeking to leverage AI for sustainable knowledge development.