AI knowledge capability and innovation: the power of cognitive processing and empowerment

IF 9.5 2区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Journal of Knowledge Management Pub Date : 2026-09-29 DOI:10.1108/jkm-04-2026-0780
Dengkai Wu,Canghong Wang,Abdul Hameed Pitafi,Jehan Saleh Lardhi,Oumaima Haj Ammar
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Abstract

Purpose This study aims to integrate ideas from organizational learning theory with new AI capabilities to investigate how AI-driven knowledge processes may improve innovation performance. Specifically, this study explores the process in which AI-based (AI Ba) knowledge production and integration support advancement of AI knowledge capability and AI psychological empowerment. In addition, this study also investigates the moderating role of Gen-AI cognitive. Design/methodology/approach Data were collected from 301 professionals in the USA working in AI-enabled organizational settings, and structural equation modeling was used for data analysis. Findings The results of this study show that both AI knowledge production Ba and AI knowledge integration Ba is positively associated with AI knowledge capability and AI psychological empowerment. AI knowledge capability is also positively related to AI innovation performance. Similarly, AI psychological empowerment is also significantly related to AI innovation performance. Furthermore, the findings of this study show that Gen-AI cognitive processing positively moderates the association between AI knowledge capability and AI innovation performance, while Gen-AI cognitive processing did not moderate the relationship between AI psychological empowerment and AI innovation performance. Originality/value Overall, this study contributes to the literature by providing an extensive framework for linking AI-enabled knowledge processes to psychological and performance consequences. This study also has practical implications for organizations attempting to use AI capabilities to drive creativity, highlighting the relevance of cognitive and psychological factors in AI adoption.
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人工智能知识能力与创新:认知加工与赋能的力量
本研究旨在将组织学习理论的思想与新的人工智能能力相结合,研究人工智能驱动的知识过程如何提高创新绩效。具体而言,本研究探讨了基于人工智能(AI Ba)的知识生产和整合支持人工智能知识能力提升和人工智能心理赋能的过程。此外,本研究还探讨了Gen-AI认知的调节作用。设计/方法/方法从美国在人工智能支持的组织环境中工作的301名专业人员中收集数据,并使用结构方程建模进行数据分析。研究结果表明,人工智能知识生产Ba和人工智能知识整合Ba与人工智能知识能力和人工智能心理赋能呈正相关。人工智能知识能力也与人工智能创新绩效呈正相关。同样,人工智能心理赋能也与人工智能创新绩效显著相关。此外,本研究发现Gen-AI认知加工正向调节AI知识能力与AI创新绩效之间的关系,而Gen-AI认知加工对AI心理赋能与AI创新绩效之间的关系没有调节作用。总体而言,本研究为将人工智能支持的知识过程与心理和表现后果联系起来提供了一个广泛的框架,从而为文献做出了贡献。这项研究还对试图利用人工智能能力来推动创造力的组织具有实际意义,强调了人工智能采用中认知和心理因素的相关性。
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来源期刊
CiteScore
13.70
自引率
15.70%
发文量
99
期刊介绍: Knowledge Management covers all the key issues in its field including: ■Developing an appropriate culture and communication strategy ■Integrating learning and knowledge infrastructure ■Knowledge management and the learning organization ■Information organization and retrieval technologies for improving the quality of knowledge ■Linking knowledge management to performance initiatives ■Retaining knowledge - human and intellectual capital ■Using information technology to develop knowledge management ■Knowledge management and innovation ■Measuring the value of knowledge already within an organization ■What lies beyond knowledge management?
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