Developing judgement for business: an AI-based model of independent management learning

Johnson, Mark, Maitland, Elizabeth ORCID: 0000-0003-1551-4787 and Sofka, Wolfgang ORCID: 0000-0003-1598-6127 (2026) Developing judgement for business: an AI-based model of independent management learning Journal of Business Research, 204. p. 115842. ISSN 0148-2963, 1873-7978

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Abstract

The rapid acceleration in the sophistication, visibility and accessibility of machine learning and artificial intelligence (AI) technologies presents opportunities and challenges for management learning and education. We focus on two key elements: (i) weaknesses in current AI approaches in management learning and education; and (ii) the challenges of providing timely, personalized and reliable feedback that is particularly central to experiential learning designs. We propose a novel, ranking-based explainable AI approach that uses Adaptive Comparative Judgment (ACJ) theory and Gaussian statistical distributions that can be tailored to deliver structured self-directed and formal learning. We show how combining generative AI, our comparative judgment AI and dynamic simulations creates learning designs based on frequent, tailored, reliable and dialogue driven individualized feedback on management decisions, that builds deep skills in self-reflection and judgment.

Item Type:	Article
Uncontrolled Keywords:	Machine learning, Artificial intelligence, Management judgment, Independent learning
Divisions:	Faculty of Humanities & Social Sciences Faculty of Humanities & Social Sciences > School of Management Faculty of Humanities & Social Sciences > Faculty of Humanities & Social Sci (All T&R Staff) Faculty of Humanities & Social Sciences > School of Management > Strategy, IB and Entrepreneurship (SIBE) Faculty of Humanities & Social Sciences > School of Management > School of Management (T&R Staff)
Depositing User:	Symplectic Admin
Date Deposited:	04 Dec 2025 10:18
Last Modified:	28 Feb 2026 07:31
DOI:	10.1016/j.jbusres.2025.115842
Open Access URL:	https://doi.org/10.1016/j.jbusres.2025.115842
Related Websites:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3195826
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