14881: Foster Knowledge-Based Dynamic Capabilities Through Tacit Knowledge from Employee-AI Collaboration (session 25937)

Sunday, July 27, 2025

08:30 - 10:00 CEST (GMT+2)

Location: Bella Center: Hall C- C1-m2

Session Type: Paper Session
Orientation: Practice,Research
Shareable link: https://cdmcd.co/bRaAdv

Author(s)

HT

Hongkun Tang

Renmin University of China, China
BL

Ben Nanfeng Luo

Renmin University of China, China
JY

Jean Fan Yang

-, China
DL

Duoran Liu

Renmin University of China, China
ZM

Zhiou Ma

Renmin University of China, China
SW

Simeng Wang

Renmin University of China, China

As organizations integrate artificial intelligence (AI) into daily operations constantly, prevalent Employee-AI collaboration drives a demand for more effective knowledge acquisition. This study aims to examine how organizations can leverage the tacit knowledge from Employee-AI collaboration to enhance knowledge-based dynamic capabilities (KBDCs). Adopting a qualitative research design based on 29 semi-structured interviews of employees from different levels who collaborate with AI in their daily work, we identify a dynamic and iterative knowledge management mechanism in organizations that can transfer tacit knowledge from Employee-AI collaboration into strategic organizational assets, contributing to KBDCs building. We revealed that employees’ adaptive experiences with AI offer a dynamic knowledge base, supporting organizational learning and adaptability. This study contributes theoretically by highlighting mechanisms through which employees’ tacit knowledge from AI collaboration fosters KBDCs, enriching the knowledge-based view of dynamic capability and supplementing knowledge management mechanisms in organizations. Practical implications are also discussed.

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