Ctrl+F for Compliance: AI and Enrollment Reporting

Join Cornell University’s Division of Enrollment as they share how the institution is leveraging artificial intelligence to increase efficiency and accuracy in enrollment reporting processes and in distilling large quantities of regulatory content across enrollment functions. The team sought to use AI to identify existing error patterns across student enrollment records, to discover previously unknown data trends and anomalies in reporting, and to quickly parse complex regulatory requirements and institutional policies. Key takeaways include lessons learned, strategies for scalable implementation, and reflections on the evolving role of AI in higher education.

Committee Group: Group VI: Information Technology

First Learning Outcome: Understand the foundational principles and human-centered design strategies that guide ethical and effective AI implementation in enrollment compliance. 

Second Learning Outcome: Identify practical applications of AI in federal enrollment reporting and withdrawal processing, and translate technical concepts into accessible language for diverse institutional contexts.

Third Learning Outcome: Evaluate lessons learned and explore scalable approaches to AI adoption, including environmental considerations and future directions for innovation in higher education administration.

Core Competency: Technological Knowledge

Proficiency: Records & Academic Services Proficiencies

Presenter(s): 

Rhonda Kitch Cornell University

Gena Boling Cornell University