The transformative potential of Artificial Intelligence (AI) in higher education is widely acknowledged, yet its adoption remains limited in emerging economies due to infrastructural, pedagogical and institutional constraints. This study investigates the determinants of AI adoption and its influence on educational effectiveness within the context of Pakistani higher education institutions. Grounded in the Technology Acceptance Model (TAM), Task-technology Fit (TTF) and Institutional Theory, the research offers an integrated framework to understand how individual perceptions, task alignment and institutional support collectively shape AI integration. A cross-sectional survey was conducted among 750 academic stakeholders, including students, faculty and administrators across diverse public and private universities. Using Partial Least Squares Structural Equation Modelling (PLS-SEM), the study tested a moderated mediation model involving perceived usefulness, perceived ease of use, TTF, digital literacy, institutional support and AI adoption. Results show that AI adoption significantly mediates the relationship between key antecedents and educational effectiveness. Notably, digital literacy and institutional support enhance this relationship, serving as critical enablers. Theoretically, this study extends existing technology adoption models by embedding contextual institutional factors, offering a nuanced understanding relevant to resource-constrained settings. Practically, it underscores the need for targeted investments in digital infrastructure, literacy programs and supportive governance to maximise AI’s pedagogical value. By addressing a critical research gap in an underrepresented context, this study provides actionable insights for policymakers, university leaders and educators aiming to foster inclusive and effective AI integration in higher education.
Haq et al. (Fri,) studied this question.