<p>One of the central questions raised for management in light of the rise of modern artificial intelligence (AI) is whether to pursue substitution automation strategies or to seek ways to enable/augment human knowledge using AI systems. This question has significant ethical and socio-political consequences that will require intensive theoretical investigation. The management science field will have to address questions about the role of human intelligence and knowledge in organizations. This paper argues that knowledge management (KM) provides a theoretical and practical foundation to address these questions because (a) KM has a human-centric, enabling view of knowledge and technology and (b) KM has incorporated epistemology and epistemic constructs into its theoretical base. The paper supports this thesis by showing that the central epistemic models of KM shed theoretical and practical light on replacement versus automation strategies. Further, it argues that KM’s epistemic models generally support a human enabling/augmenting strategy, while demarcating a place for replacement automation. The paper is organized around two research questions: Research Question 1: How do KM models incorporate epistemic theory and concepts? Research Question 2: How do KM models and their associated epistemic theories conceptualize knowledge in relation to AI-based automation, and in particular, to what extent do they support enablement versus substitution AI and knowledge work? </p>