Double trouble: How AI efficiency is boosting speed but burdening team leaders and bypassing quality

Purpose The article explores the impact of the usage of AI (Artificial Intelligence) in the workplace and the burden it brings to leaders in ensuring quality. It also discusses the growing reliance on AI and its effect on team dynamics, especially how it affects productivity, collaboration, and authenticity. Design/methodology/approach This conceptual article draws insights from both existing literature and professional practice. It discusses human–AI interactions and their implications for leaders in tackling the associated challenges for task fulfillment, quality control, and dealing with AI free-riders. Findings While AI can significantly increase workplace efficiency, it is enhancing the burden on team leaders. The rise of AI free-riders demotivates contributing members and hence creates imbalances in team dynamics. This causes an increased workload for leaders to validate authenticity and ensure quality. The article proposes a 4-step framework to overcome these challenges, including transparency, collaboration, balance, and acceptance. Originality/value The article proposes a nuanced view of the issues posed by AI free-riders in team dynamic settings. It further discusses how team leaders can effectively address such issues by offering a practical framework that can enhance human-AI collaboration.

Authors

Publication Details

Journal
Development in Learning Organizations An International Journal
Published
2025-04-08
DOI
https://doi.org/10.1108/dlo-11-2024-0344
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.28
Controls
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article

Double trouble: How AI efficiency is boosting speed but burdening team leaders and bypassing quality

Ameya Agrawal, Salman Ali
1 citations
Development in Learning Organizations An International Journal
Big Data and Business Intelligence
2.28
article

Double trouble: How AI efficiency is boosting speed but burdening team leaders and bypassing quality

Ameya Agrawal, Salman Ali
article en
1 citations

Abstract

Purpose The article explores the impact of the usage of AI (Artificial Intelligence) in the workplace and the burden it brings to leaders in ensuring quality. It also discusses the growing reliance on AI and its effect on team dynamics, especially how it affects productivity, collaboration, and authenticity. Design/methodology/approach This conceptual article draws insights from both existing literature and professional practice. It discusses human–AI interactions and their implications for leaders in tackling the associated challenges for task fulfillment, quality control, and dealing with AI free-riders. Findings While AI can significantly increase workplace efficiency, it is enhancing the burden on team leaders. The rise of AI free-riders demotivates contributing members and hence creates imbalances in team dynamics. This causes an increased workload for leaders to validate authenticity and ensure quality. The article proposes a 4-step framework to overcome these challenges, including transparency, collaboration, balance, and acceptance. Originality/value The article proposes a nuanced view of the issues posed by AI free-riders in team dynamic settings. It further discusses how team leaders can effectively address such issues by offering a practical framework that can enhance human-AI collaboration.

Development in Learning Organizations An International Journal
Openalex Percentile: Top 13%
Big Data and Business Intelligence
2.28
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Double trouble: How AI efficiency is boosting speed but burdening team leaders and bypassing quality — Ameya Agrawal, Salman Ali · Development in Learning Organizations An International Journal (2025) | TGRS Research Map | TGRS