A Generative AI-Integrated Framework for Teaching Operations Management: Case-Based Projects

As generative artificial intelligence (GAI) reshapes business education, instructors must simultaneously safeguard academic integrity and develop students’ AI literacy for an increasingly AI-driven workplace. This study developed the GAI Learning Framework (GLF), a replicable, step-by-step experiential learning approach for case-based projects in undergraduate business courses, illustrated through an operations management (OM) application. Rather than enabling passive cognitive offloading, the GLF promotes active learning by requiring students to craft context-rich prompts grounded in course materials, systematically compare outputs across multiple GAI platforms (e.g., ChatGPT, Claude, and Gemini), and critically evaluate discrepancies against independently verified sources. The framework was implemented across two sections of an undergraduate OM course and evaluated using a student survey that combined Likert-scale items with open-ended reflections (n = 50). All three constructs exceeded the scale midpoint, with pooled means ranging from 3.93 (Constructive Alignment) to 4.08 (Cognitive Load/Scaffolding). Qualitative student reflections further indicated that students perceived the framework as fostering active learning, AI platform literacy, and professional communication skills. This study offers educators a practical, classroom-tested framework for integrating GAI tools into case-based projects in business courses while preserving analytical rigor and promoting experiential learning. Supplemental Material: The online appendices are available at https://doi.org/10.1287/ited.2026.0224 .