Unleashing Innovation: How Fit Between Organizational Generative AI Adoption and Employee AI Literacy Drives Creative Performance

Abstract
Purpose — Prior research has largely treated organizational generative artificial intelligence (GenAI) adoption and AI literacy as separate drivers of innovation, paying limited attention to whether GenAI-related job demands match employees’ AI abilities. Drawing on person-organization (P-O) fit theory, we conceptualize organizational GenAI adoption as a contextual demand and employees’ AI literacy as a key individual ability, and examine how their alignment affects creative performance, as well as the role of work motivation in this process.
Design/methodology/approach — We collected multi-wave dyadic data from 324 supervisor-subordinate pairs and tested the hypotheses using polynomial regression and response surface methodology.
Findings — We find that the fit between organizational GenAI adoption and employees’ AI literacy is positively associated with employee creative performance and that high-high fit yields higher creative performance than low-low fit. Among misfit configurations, overqualification is more conducive to creative performance than underqualification. Furthermore, autonomous motivation and controlled motivation jointly mediate the relationship between fit and creative performance, revealing dual motivational pathways that link GenAI-related demands-abilities fit to creativity.
Originality/value —From a P-O fit perspective, this study enhances our understanding of the complexities surrounding the adoption of GenAI and its impact on employee outcomes, thereby contributing to the literature on GenAI-enabled innovation.