The rapid integration of Artificial Intelligence (AI) in higher education has significantly transformed teaching, learning processes, and institutional service delivery. This study examines the relationship between service quality in Higher Education Institutions (HEIs) and student job readiness, with particular emphasis on the mediating role of AI-driven learning. Drawing upon the SERVQUAL framework and employability theory, the study proposes a conceptual model linking institutional service quality dimensions—tangibility, reliability, responsiveness, assurance, and empathy—to student job readiness outcomes through AI-enabled learning systems. Adopting a quantitative research design, data were collected from undergraduate and postgraduate students across multiple institutions. Structural Equation Modeling (SEM) was employed to test the hypothesized relationships among variables. The findings reveal that service quality has a significant positive effect on student job readiness, while AI-driven learning partially mediates this relationship. This research contributes to the literature by integrating service quality theory with AI-enhanced pedagogy and provides practical implications for academic leaders seeking to strengthen graduate employability in the context of ongoing digital transformation.