Teaching AI-assisted forecasting in economics and finance: a case-based approach to human–AI collaboration
Year: 2026
Type: article
Abstract: 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.
Author: Subhadra Ganguli
Institution: Pennsylvania State University
Language: English
Subfield: Management of Technology and Innovation
Domain: Social Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W7203823032