Artificial intelligence recommendations are sometimes erroneous and biased. AI-based systems are known to produce inadequate reactions that can generate or have the potential to cause losses or issues for clients, employees, or organizations. In this chapter, we will examine the knowledge risks created due to different features of artificial and human knowledge. Based on examples from the literature related to the limitations and biases of artificially created knowledge, we present a taxonomy of knowledge risks generated in organizations by the dynamic interaction between human and artificial knowledge. The suggested taxonomy follows a prior developed taxonomy of knowledge risks found in the existing literature and contains seven clusters of knowledge risks, each related to the following knowledge processes: knowledge creation, knowledge acquisition, knowledge loss, knowledge sharing, knowledge use, emotional knowledge dynamics, and spiritual knowledge dynamics. Our approach is theoretical; its novelty lies in outlining the knowledge risks arising from the biases of artificial knowledge in their dynamic interaction with human knowledge. Our study contributes to understanding the effects of the dynamic interaction between human and artificial knowledge in organizations, as well as shaping future research on these new phenomena, and defining the AI-supported knowledge management systems.