Abstract This study examines how generative artificial intelligence (GenAI) is associated with changes in organizational knowledge governance by introducing AI-generated outputs into knowledge-intensive work. Specifically, it investigates whether greater GenAI epistemic integration is associated with epistemic authority redistribution, whether such redistribution is associated with knowledge governance tension, and how that tension relates to two distinct innovation outcomes: innovation novelty and innovation reliability. The study also examines whether domain knowledge complexity and knowledge governance adaptability shape these relationships. Data were collected through a cross sectional survey of 345 professionals involved in knowledge and innovation activities across multiple industries. The proposed model was tested using partial least squares structural equation modeling (PLS-SEM). The findings show that GenAI epistemic integration is positively associated with epistemic authority redistribution, which is, in turn, positively associated with knowledge governance tension. Knowledge governance tension is positively associated with innovation novelty but negatively associated with innovation reliability. Domain knowledge complexity strengthens the relationship between GenAI epistemic integration and epistemic authority redistribution, while knowledge governance adaptability weakens the relationship between epistemic authority redistribution and knowledge governance tension. The study contributes to research on knowledge governance and GenAI by showing that the organizational consequences of GenAI are not limited to efficiency or idea generation. They also involve shifts in who is treated as a legitimate source of knowledge, how knowledge claims are validated, and how organizations balance creative exploration with dependable innovation outcomes.
Khalid H. Alshammari (Sun,) studied this question.