Institutional structures, digital inequality, and AI integration in higher education

The global diffusion of artificial intelligence (AI) in higher education raises questions about institutional equity, as adoption patterns shaped by structural factors risk reproducing existing inequalities. This study provides one of the first systematic comparative assessments of AI integration across Nigerian university types, examining how governance structures, resources, and inter-organizational networks shape technology adoption in developing country higher education. This study conducted a comparative content analysis of 45 Nigerian universities (15 Federal, 15 State, 15 Private), assessing AI integration across six dimensions: infrastructure, curriculum, research, industry partnerships, international collaborations, and policy frameworks using structured coding scales with anchored descriptors. Drawing on an integrated framework combining institutional theory, resource-based view, and network theory, data were analyzed using one-way ANOVA, Pearson correlation analysis, and multiple regression. Results reveal moderate overall AI integration (M = 4.79, SD = 1.71) with meaningful variation across dimensions and institution types. Federal universities demonstrated the highest integration (M = 5.25), private universities recorded their strongest performance in curriculum integration (M = 5.87), and state universities showed emerging strength in policy frameworks. Institution age (beta = 0.43, p = 0.016) and geographic location (beta = 0.31, p = 0.029) significantly predicted integration levels, while institution type was not significant when controlling for other factors. The strong correlation between international collaborations and industry partnerships (r = 0.74, p < 0.001) suggests network positions create compounding advantages for well-connected institutions. These findings challenge assumptions that governance structure determines integration capacity and reveal how historical and geographic inequalities perpetuate through technology adoption, with implications for equitable AI deployment and international partnership design in developing country higher education.