HomeAbstract of 11th-icrbmeHow Ai-driven Hrm Shapes Innovative Work Behavior and Ai Knowledge Sharing? a Social Cognitive Perspective

How Ai-driven Hrm Shapes Innovative Work Behavior and Ai Knowledge Sharing? a Social Cognitive Perspective

  • Jun 22, 2026
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Abstract Book of the 11th International Conference on Research in Business, Management and Economics

Year: 2026

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How Ai-driven Hrm Shapes Innovative Work Behavior and Ai Knowledge Sharing? a Social Cognitive Perspective

Dr. Imran Hameed

ABSTRACT:

AI-driven human resource management (AI-driven HRM) is increasingly reshaping how organizations design HR practices, support employees, and manage human-machine collaboration. Despite growing scholarly attention to AI in HRM, limited research has examined how AI-driven HRM influences positive employee behaviors through individual psychological mechanisms. Using the lense of social cognitive theory, this study proposes AI self-efficacy as a mediating variable between AI-driven HRM and employees’ innovative work behavior and AI knowledge-sharing. We also explore digital leadership as a boundary condition that can enhance the linkage between AI-driven HRM and AI self-efficacy. The data were collected using a dyadic research design, with 354 supervisor-employee dyads analyzed. AMOS was used for testing the proposed model. The results indicated that AI-driven HRM results in enhancing the individual’s AI-self-efficacy. The results also showed that AI self-efficacy in turn increase employee innovative work behavior and AI knowledge sharing. The findings also confirmed the mediation effect of AI self-efficacy, suggesting that increasing employees’ confidence in working with AI tools and technologies through the use of AI-driven HRM facilitates innovative work behavior and AI knowledge sharing. The moderating effect of digital leadership on AI-driven HRM and AI self-efficacy was not confirmed, however. By adopting a social cognitive approach to examine the relationship between AI-driven HRM, AI self-efficacy, and innovative work behaviors and the link between AI self-efficacy and AI knowledge sharing, this study advances the behavioral approach to AI-driven HRM. While the potential of AI in HR systems to enhance employee innovation and knowledge sharing is promising, the theoretical and empirical validation of its expected amplifying effect of digital leadership is needed.

Keywords: AI-Driven HRM, AI Self-Efficacy, Innovative Work Behavior, AI Knowledge Sharing, Digital Leadership