This study aims to investigate how artificial intelligence–driven knowledge management (AI-driven KM) relates to institutional agility in higher education through the mediating role of digital competence and the development of intellectual capital components, namely, human capital and structural capital.
A quantitative approach was adopted using survey data from 525 academic and administrative staff across multiple higher education institutions. Partial least squares structural equation modelling was used to test the hypothesised relationships, including mediation and moderation effects.
AI-driven KM shows significant direct and indirect relationships with institutional agility. Digital competence mediates the relationship between AI-driven KM and agility and is associated with higher human capital and structural capital, which in turn relate positively to agility. Leadership support strengthens the relationship between AI-driven KM and institutional agility, indicating that managerial commitment enhances the agility benefits of AI-enabled knowledge practices.
This study has several limitations. Firstly, the cross-sectional design limits causal inference between AI-driven KM, digital competence and institutional agility. Secondly, the use of self-reported survey data and convenience sampling may introduce common method bias and limit generalisability beyond the higher education context studied. Thirdly, the focus on institutions in a developing-country setting may restrict applicability to other regions. Future research should use longitudinal and comparative designs, incorporate objective performance indicators and examine additional contextual factors such as organisational culture and AI governance.
Institutional agility depends not only on AI-enabled systems but also on staff digital competence and supportive leadership. Higher education institutions should combine investments in AI-driven KM with role-specific capability development, strengthened knowledge infrastructures and leadership practices that support implementation and use.
By clarifying how AI-driven KM relates to institutional agility, this study highlights pathways through which higher education institutions can respond more effectively to societal change. Strengthening digital competence and knowledge-based capabilities supports universities in delivering more adaptive teaching, research and administrative services. In developing-country contexts, these capabilities can help reduce digital inequality by improving institutional responsiveness and access to knowledge. Supportive leadership and responsible AI use further contribute to trust, transparency and sustainable digital transformation, enhancing the social role of universities as inclusive and resilient knowledge institutions.
Given the maturity of RBV and dynamic capabilities research, this study positions its contribution as contextual and mechanism-focused. It offers empirical evidence from higher education in a developing-country context and clarifies how AI-driven KM relates to agility through digital competence and intellectual capital components, with leadership support as a boundary condition.
