Human-in-the-loop: A faculty-led model for integrating GenAI in executive economics instruction

This article presents a classroom-tested, faculty-led model for integrating Generative AI (GenAI) into executive management education, grounded in adult learning theory and constructivist pedagogy. Implemented in a postgraduate Business Economics course at a business school in Singapore, the intervention embedded ChatGPT across four Executive MBA cohorts (n = 87) using scenario-based prompting, Socratic inquiry, and transcript-annotated reflection. Comparative analysis with four demographically matched traditional cohorts (n = 93) revealed that GenAI-supported instruction significantly improved assignment performance. Ordinary Least Squares (OLS) regression confirmed that AI integration was a robust and statistically significant predictor of higher scores, even after controlling for demographic and professional background variables. Simultaneous quantile regression further showed that lower-performing students experienced the greatest gains, highlighting the intervention's equalizing potential. Beyond these quantitative results, students demonstrated more structured economic reasoning and deeper conceptual application. By emphasizing faculty agency, ethical AI use, and inquiry-based design, this model offers a scalable and replicable approach for integrating GenAI in executive education.