Reflections on Building an Artificial Intelligence Bot to Prepare Students to Engage in Strategic Conversations During Foresight Fieldwork

Rui Pedro Gonçalves, Matthew J. Spaniol, Nicholas J. Rowland and Niels Gorm Malý Rytter

Futures & Foresight Science, 2025, vol. 7, issue 1

Abstract: This paper is primarily based on experientially derived insights about building a bot with artificial intelligence (AI)–in this case, chat generative pre‐trained transformer (ChatGPT)–to prepare students to engage in strategic conversations during foresight fieldwork. The motivation of the exploratory process outlined in this paper is the pedagogical concern of sending students into the field sufficiently prepared to meet the expectations of external stakeholders. The authors explore a in‐class prompt engineering exercise to create a “chief operating bot” (COB) to simulate a C‐suite executive. The student‐faculty team input hand‐selected, industry‐specific, company‐generated documentation, and, after asking ChatGPT to “roleplay” the COO, the student queries this COB in an exploratory fashion embedded in a contained, consequence‐free learning environment. The audience for this paper is faculty responsible for overseeing student engagement experiences like fieldwork, as well as department heads and school deans looking to promote new tools and advance novel applications of AI in their units. The authors explore ways to enhance student readiness for scenario fieldwork based on an exercise drawn from van der Heijden's clairvoyant question, which we refer to colloquially as the “crystal ball thought experiment.” The authors, upon reflection, conclude that the COB can valuably supplement–but not fully replace–face‐to‐face interactions with a COO. Broadly, leveraging AI to create interactive tools like COBs has the potential to transform business education by bridging academic preparation with real‐world demands, enhancing student readiness, advancing AI‐assisted curricula, and contributing to strategic planning and regional development.

Date: 2025
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https://doi.org/10.1002/ffo2.202

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Persistent link: https://EconPapers.repec.org/RePEc:wly:fufsci:v:7:y:2025:i:1:n:e202

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