TECHNOLOGICAL FACTORS INFLUENCING GENERATIVE ARTIFICIAL INTELLIGENCE ADOPTION IN RESEARCH WITHIN KENYAN UNIVERSITIES

Abstract

The deployment of Generative Artificial Intelligence (Gen AI) offers transformative possibilities for academic scholarship, introducing rapid methods for data parsing, programmatic coding, and literature synthesis. However, within developing academic ecosystems like Kenya, systemic environmental and technical gaps affect how seamlessly these innovations are absorbed. This paper isolates and examines the first objective of a broader doctoral inquiry: to determine the extent to which Technological Factors significantly influence the adoption of Gen AI in research in universities in Kenya. Utilizing a robust mixed-methods research design under a post-positivist philosophical paradigm, quantitative field data from 267 active academic researchers across universities was evaluated alongside qualitative institutional triangulation. Bivariate Spearman’s rank correlation (rho) and Hierarchical multiple regressions confirmed that technological factors act as a primary determinant of adoption velocity β= 0.392, t = 9.333, p < .001). Specifically, Data Quality & Availability demonstrated the highest coupled impact on advanced analytical deployment (rho = 0.55), while baseline Infrastructure Readiness directly dictates the reliability of task automation (rho = 0.53). The paper concludes with structural recommendations for university IT directorates to counteract the current state of "digital decoupling" through local proxy optimizations, dedicated campus bandwidth rings, and API interoperability integrations.