Is knowledge management dead or dying? How is it changing? In order to address these questions, this chapter presents historical and emerging technology views of knowledge management (KM). In so doing, we primarily investigate the impact of large language models (LLMs) and generative AI on KM’s continued evolution. As part of that investigation, we examine several different issues in knowledge management, starting with a historical review of knowledge management and the related concept of executive information systems. We discuss the emerging notion of large language models as the basis of knowledge management and then analyze some of the challenges and opportunities associated with that model. For example, the Dunning–Kruger effect leads to concerns about both overuse and overconfidence of such systems. We analyze recent research that indicates what kinds of problems work best with LLMs and further examine the impact of LLMs on characteristics of critical thinking, and the need for “verification thinking.” We also examine the ability of users to perform “knowledge shifting” to capture the effect on novice knowledge management workers. In addition, we develop the notion of knowledge management exhaust. We conclude with proposals and implications for future research.