Leveraging AI for Individualized Outreach in Enrollment Marketing: A Study on Boosting University Application Intentions

Abstract

Background: With the rise of Artificial Intelligence (AI) in higher education marketing, universities can reach prospective students in a more personalized manner. Nevertheless, only a few studies in the prevailing literature examine the dependence of students' enrollment decisions on trust and privacy perceptions regarding an institution's admission ability due to its AI-driven marketing, especially in an Indonesian setting.

Objective: This study investigates the impact of AI marketing strategies on university application intentions of prospective students. Through the Stimulus-Organism-Response framework, it examines how AI content recommendation and interaction quality affect perceived trust and privacy risks, and subsequently, enrollment behavior.

Method: This quantitative research employed purposive sampling, collecting data from 350 prospective students. The conceptual model was examined using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4. Privacy calculus was included as a moderator to examine trade-offs between personalization advantages and data privacy risks.

Results: All seven hypotheses received support, as both AI content recommendations and interaction quality have direct and indirect influences on university application intentions. Perceived trust had a strong mediation effect on content quality, while privacy risk had a strong mediation effect on AI interaction. Privacy calculus moderated the effect of privacy risk on application intention, indicating that high AI service utility can alleviate data-related concerns.

Conclusion:This study extends higher education marketing literature by presenting a holistic perspective on the Privacy-Personalization Paradox. It identifies institutional trust and privacy calculus as critical psychological determinants of digital recruitment systems, and offers strategies for universities leveraging AI-based engagement tools.