Admissions in the Age of AI: Best Practices and a Virginia Tech Case Study

The rapid rise of AI has introduced both promise and uncertainty into college admissions. Institutions are seeking guidance on ethical best practices while also experimenting with innovative models. This session will provide an overview of how AI is being used in admissions nationally, including best practices emerging around transparency, ethics, and equity. A detailed case study will be provided with Virginia Tech’s “human+machine” model, which pairs human and AI essay review. The model ensures consistency and fairness while preserving human judgment. Lessons from building this system internally, collaborating with faculty, and communicating transparently with stakeholders will be shared.

Committee Group: Group I: Admissions and Enrollment Management

First Learning Outcome: Understand emerging uses of AI in admissions and best practices for ethical adoption. 

Second Learning Outcome: Analyze a real-world case study of AI + human collaboration in admissions at scale.

Third Learning Outcome: Apply a framework (transparency, human oversight, mission alignment) to evaluate AI use at their own institutions.

Core Competency: Technological Knowledge

Proficiency: Enrollment Management Proficiencies

Presenter(s): 

Juan Espinoza Virginia Polytechnic Institute and State University

Emily Pacheco Case Western Reserve University