AI-enabled social media and student recruitment: Examining student engagement and AI

We explore how AI-enabled social media (SM) shapes student recruitment (SR) by identifying the mechanisms through which student engagement (SE) predicts SR. Our findings show that content enjoyment (CE) and content design (CD) are the most important determinants of SE, while information usefulness (IU) has the least impact. Habit of SM usage (HU), SM influencers (IN), content novelty (CN), credibility (CF), and interactivity (IF) enhance SE. SE strongly improves SR, and AI is strongly positively associated with SR, but does not moderate the SE-SR link. We broaden a comprehensive SM-to-recruitment mechanism by integrating SM features, IN, and HU into a single SE-based model. We enrich Stimulus-Organism-Response (SOR) by theorizing AI as a technological stimulus. We enrich Uses and Gratifications theory (UGT) by showing that hedonic satisfaction dominates utilitarian satisfaction in AI-assisted SR in an emerging higher education market.