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Game changers: A generative AI prompt protocol to enhance human-AI knowledge co-construction
Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering. University of Cape Town, South Africa.ORCID iD: 0000-0002-3486-8292
Graduate School of Business, University of Cape Town, Cape Town, South Africa.ORCID iD: 0000-0001-9575-6676
UC Business School, University of Canterbury, Christchurch, New Zealand.ORCID iD: 0000-0002-9546-1285
University of Stellenbosch Business School, Cape Town, South Africa.ORCID iD: 0000-0002-7452-2974
2024 (English)In: Business Horizons, ISSN 0007-6813, E-ISSN 1873-6068, Vol. 67, no 5, p. 499-510Article in journal (Refereed) Published
Abstract [en]

The democratization of powerful artificial intelligence (AI) tools, including ChatGPT, has sparked the interest of business practitioners given their ability to fundamentally change the way we work. While AI tools are positioned to augment human capabilities, their effective implementation requires the skill to understand where, when and how to best utilize them efficiently. Furthermore, meaningful engagement with the content produced by generative AI (GenAI) necessitates the intricacy of appropriate prompt engineering to optimize the learning process. As the field of GenAI continues to advance, the art of developing impactful prompts has become a necessary skill for harnessing its full potential. This research develops an AI prompting protocol through a constructivist theory lens. Based on the principles of constructivism, where individuals assimilate new knowledge by bridging it with their existing understanding, this research suggests an active engagement process in the human-AI co-construction of knowledge through GenAI. The goal is to empower business managers and their teams to construct effective AI prompts and validate responses, thereby enhancing user interaction, optimizing workflows, and maximizing the potential outcomes of AI chatbots.

Place, publisher, year, edition, pages
Elsevier, 2024. Vol. 67, no 5, p. 499-510
Keywords [en]
ChatGPT, Constructivism, Generative AI, Large language models, Prompt engineering
National Category
Information Systems
Research subject
Industrial Marketing
Identifiers
URN: urn:nbn:se:ltu:diva-105470DOI: 10.1016/j.bushor.2024.04.008ISI: 001301369500001Scopus ID: 2-s2.0-85191961665OAI: oai:DiVA.org:ltu-105470DiVA, id: diva2:1858159
Note

Validerad;2024;Nivå 2;2024-09-20 (hanlid);

Full text license: CC BY

Available from: 2024-05-15 Created: 2024-05-15 Last updated: 2025-10-21Bibliographically approved

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Robertson, JeandriFerreira, CaitlinBotha, Elsamari

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