AI-enabled knowledge renewal: the role of leaders’ AI attitudes and unlearning in enhancing employees’ creative performance

Purpose This study aims to examine how artificial intelligence (AI) usage influences employees’ unlearning processes and subsequent creative performance, emphasizing the moderating role of leaders’ attitudes toward AI. While AI adoption is reshaping work dynamics, the role of leadership in employees’ adaptation and learning remains underexplored. Design/methodology/approach A two-wave survey was conducted with 314 employees and their 117 direct supervisors from knowledge-intensive organizations in China, spanning sectors including IT, advanced manufacturing and R&D. Hypotheses were tested using covariance-based structural equation modeling. Findings The results indicate that AI usage positively affects employees’ unlearning of outdated knowledge and enhances their creative performance. Furthermore, leaders’ positive attitudes toward AI significantly strengthen these effects, suggesting that leaders’ attitudes are critical in facilitating employees’ adaptation and creative outcomes in AI-integrated work environments. Practical implications Organizations should actively foster leadership support for AI adoption to enhance employees’ learning agility and creative problem-solving. Originality/value This study contributes to the knowledge management literature by integrating AI-driven unlearning with leadership perspectives. It highlights the critical role of leaders in shaping employees’ learning behaviors and creativity, offering new insights into how organizations can optimize AI implementation through effective leadership.

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Publication Details

Journal
Journal of Knowledge Management
Published
2025-09-09
DOI
https://doi.org/10.1108/jkm-02-2025-0209
Citations
4
Primary Topic
Job Satisfaction and Organizational Behavior
Type
article
Field-Weighted Citation Impact
11.05
Controls
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article

AI-enabled knowledge renewal: the role of leaders’ AI attitudes and unlearning in enhancing employees’ creative performance

Yin Jun, Khan Dam Hoang
4 citations
Journal of Knowledge Management
Job Satisfaction and Organizational Behavior
11.05
article

AI-enabled knowledge renewal: the role of leaders’ AI attitudes and unlearning in enhancing employees’ creative performance

Yin Jun, Khan Dam Hoang
article en
4 citations

Abstract

Purpose This study aims to examine how artificial intelligence (AI) usage influences employees’ unlearning processes and subsequent creative performance, emphasizing the moderating role of leaders’ attitudes toward AI. While AI adoption is reshaping work dynamics, the role of leadership in employees’ adaptation and learning remains underexplored. Design/methodology/approach A two-wave survey was conducted with 314 employees and their 117 direct supervisors from knowledge-intensive organizations in China, spanning sectors including IT, advanced manufacturing and R&D. Hypotheses were tested using covariance-based structural equation modeling. Findings The results indicate that AI usage positively affects employees’ unlearning of outdated knowledge and enhances their creative performance. Furthermore, leaders’ positive attitudes toward AI significantly strengthen these effects, suggesting that leaders’ attitudes are critical in facilitating employees’ adaptation and creative outcomes in AI-integrated work environments. Practical implications Organizations should actively foster leadership support for AI adoption to enhance employees’ learning agility and creative problem-solving. Originality/value This study contributes to the knowledge management literature by integrating AI-driven unlearning with leadership perspectives. It highlights the critical role of leaders in shaping employees’ learning behaviors and creativity, offering new insights into how organizations can optimize AI implementation through effective leadership.

Journal of Knowledge ManagementVol. 30(1)
Shenzhen University (CN)
Openalex Percentile: Top 2%
Job Satisfaction and Organizational Behavior
11.05
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