Аңдатпа
This study reconceptualizes AI Governance Readiness (AIGR) as a form of institutional capital, representing an institution's capacity to establish, coordinate, and operationalize responsible AI governance arrangements in ways associated with student retention intentions through capability orchestration rather than technology adoption alone. Grounded in the Resource-Based View and Dynamic Capabilities Theory, the study develops and tests a structural model linking AIGR with Administrative Efficiency through AI (AEAI) and AI Fluency Orientation (AIFO), while examining Equity Perception (EPS) as a moderator. A quantitative cross-sectional survey of 897 respondents from public and private higher education institutions in Kazakhstan was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with 5,000 bootstrap resamples. The results substantiate six of the seven proposed relationships. AI Governance Readiness is positively associated with Administrative Efficiency through AI ( β = 0.591, p < 0.001) and AI Fluency Orientation ( β = 0.699, p < 0.001). AI Fluency Orientation ( β = 0.367, p < 0.001) and Administrative Efficiency through AI ( β = 0.404, p < 0.001) are positively associated with Student Retention Intentions. AI Fluency Orientation and Administrative Efficiency through AI significantly mediate the association between AI Governance Readiness and Student Retention Intentions, with indirect effects of β = 0.433 and β = 0.375, respectively. Equity Perception does not significantly moderate the Administrative Efficiency through AI–Student Retention Intentions relationship ( β = −0.011, p = 0.444). The findings position AI Governance Readiness as an institutional capability that coordinates governance arrangements, human competencies, and administrative processes to support student-centered outcomes while reinforcing fairness, transparency, accountability, and responsible AI use. The cross-sectional, geographically concentrated sample limits causal inference and generalizability, highlighting the need for longitudinal and comparative research.