AI-powered teamwork in higher education: a comprehensive systematic review of effectiveness and challenges

Akinul Islam Jony, Sultanul Arifeen Hamim and Enric Serradell-López

Chapter 5 in Multidisciplinary Movements in AI and Generative AI, 2025, pp 65-97 from Edward Elgar Publishing

Abstract: Artificial intelligence (AI) holds significant promise as a potential path for improving and progressing working teams. In an evolving world, AI-powered teamwork can be an indispensable asset, driving success and innovation in higher education. Nevertheless, AI in team settings is presently in its nascent phase and needs to be improved, hindering its extensive implementation for enhancing team productivity. With the growing adoption of team-oriented structures in higher education, there is a notable trend to subject these organizational teams to closer scrutiny. Therefore, this study conducts a comprehensive and methodical examination of the existing body of literature to evaluate previous research highlighting the importance of AI in different teams. It aims to arrange the existing corpus of research systematically and provide a summary of recent focal areas on the involvement of AI in heterogeneous teams. The objective is to organize the current body of research, identify prevailing patterns, and present a synopsis of recent focal points and subjects concerning AI's role in diverse teams. Through an extensive search of the well-known databases, 35 pertinent studies are selected systematically. The findings outline the applications of AI within teams, the challenges of integrating AI in teams, corresponding AI solutions or models to deal with these difficulties, and a list of key factors for transforming team dynamics and team improvement using AI. A matrix has been derived at the end to align AI challenges with the corresponding AI model to overcome the difficulties of achieving AI-powered teamwork in higher education.

Keywords: Artificial intelligence; AI; Teams; Teamwork; Higher education; Groupwork; Systematic review (search for similar items in EconPapers)
Date: 2025
ISBN: 9781035358656
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