Abstract: In an era of rapid technological change, universities must continually adapt their curricula to prepare students for evolving careers. Yet systematic analysis and benchmarking of university course offerings across institutions remain labor-intensive and slow, limiting timely, data-informed curriculum decisions. This paper presents a GenAI-enabled tool for curriculum analysis that automates the extraction, retrieval, and categorization of course information from university course catalogs, enabling scalable and reusable analysis across topics and institutions. The tool integrates search with generative AI to identify relevant courses and classify them along user-defined dimensions (e.g., topic, use case, discipline), substantially reducing the manual effort required for cross-institutional curriculum comparison. We demonstrate the tool’s capabilities through a case study of extended reality (XR) offerings in AACSB-accredited business schools, showing that it can replicate and extend prior manual curriculum studies with high accuracy while operating at significantly greater scale and speed. Designed for IS and computing education stakeholders, the tool supports curriculum design, academic benchmarking, and alignment with emerging industry skill demands. By transforming distributed and unstructured course catalog descriptions into structured, comparable insights, this work provides a practical, generalizable solution to help universities keep pace with technological change through evidence-based curriculum analysis.

Keywords: Generative AI, IS curriculum, Workforce development, Curriculum design & development, Industry-relevant skills, Program assessment & design

Download This Article: JISE2026v37n4pp625-638.pdf

Recommended Citation: SaCouto, L., Gürpinar, T., Jia, S., & Quadri, S. (2026). Supporting Universities in Keeping Up With Technological Change: A GenAI Tool for Curriculum Analysis. Journal of Information Systems Education, 37(4), 625-638. https://doi.org/10.62273/RATM2670