Machines think, but do we? Embracing AI in flat organizations: Challenges of technological change in women-owned manufacturing firms

Drawing on the combined strengths of Conservation of Resources (COR) theory and Information Processing Theory (IPT), we explored the relationship between technological turbulence and knowledge hiding, with employees’ awareness of AI as a key mediating factor. We also examined the dual moderating effects of hierarchical flatness in an organization and change leadership to test the theoretical synergy of COR and IPT. Data were collected from 315 women-owned manufacturing firms and analyzed through PLS-SEM. The findings reveal that employees’ AI awareness mediates the link between technological turbulence and knowledge-hiding behaviors. A flatter organizational structure aids in spreading AI awareness among employees, while effective change leadership serves as a crucial moderator, reducing knowledge hiding by influencing employee behavior. The survey highlights that increased AI awareness can lead to fears about AI's impact on job security, driving knowledge hiding. However, skilled leadership can mitigate this by promoting innovation and encouraging collaboration with external partners. This study provides original insights by developing and empirically validating a model of knowledge hiding in response to technological turbulence in women-owned manufacturing sectors in Punjab, Pakistan. It deepens the understanding of knowledge management by examining the interplay between organizational flatness and AI integration, areas often overlooked in existing literature.