Curricular evaluation demonstrates a case-based framework for generative AI-assisted demand forecasting in economics students, highlighting the value of domain knowledge in human–AI collaboration.
This article presents a case-based instructional approach for teaching artificial intelligence (AI)-assisted forecasting in economics and finance courses. Forecasting is a core skill in business education, yet students often encounter forecasting as a technical procedure. The article uses a historical business demand forecasting case during 1980s to design a classroom exercise in which students compare a static forecasting approach with a generative AI-supported forecasting process. The exercise asks students to use prompt engineering and reflect on the role of domain knowledge in generative AI-assisted analysis. The article contributes to business education by offering a structured teaching framework, sample prompts, learning objectives for integrating human–AI collaboration into forecasting instruction.
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Subhadra Ganguli (2026) studied this question.
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