Human–AI Collaboration and Organizational Innovation: The Mediating Role of AI-Enabled Knowledge Sharing and the Moderating Role of Employee AI Literacy

Abstract

Artificial intelligence (AI) is increasingly embedded in organizational work, but the availability of AI technology alone does not explain whether organizations become more innovative. This study develops an empirical framework that positions Human–AI Collaboration (HAIC) as an organizationally relevant capability and examines how collaboration with AI may be converted into Organizational Innovation (OI) through AI-Enabled Knowledge Sharing (AIKS). Employee AI Literacy (EAIL) is proposed as a boundary condition that may strengthen the conversion of human–AI interaction into useful knowledge-sharing practices. Drawing on Dynamic Capabilities Theory and Organizational Knowledge Creation Theory, the study argues that employees create value when they combine human judgment, domain expertise and AI-supported information processing, subsequently validating and sharing the resulting knowledge within the organization. The proposed model responds to an emerging research need to move beyond simple AI-adoption measures toward the organizational processes that connect human–AI interaction with innovation. A quantitative cross-sectional survey design is suggested, and the data will be gathered from workers and managers who need to employ AI based working technologies. Structural Equation Modeling with partial least squares (PLS-SEM) is suggested to evaluate the measurement and structural modeling including mediation, and moderation. The study provides a process-oriented approach where knowledge sharing is mediated by AI as the knowledge-conversion mechanism and employee AI literacy as a boundary condition. The manuscript is a valid starting point for empirical testing, scale refinement and eventual submission to a journal.