Fteimi, NoraNoraFteimiHopf, KonstantinKonstantinHopf0000-0002-5452-06722022-05-102022-05-102021978-1-7336325-6-0https://fis.uni-bamberg.de/handle/uniba/53987Artificial intelligence (AI) and its rapid technological advancement will considerably affect the future of work and the way organizations manage their knowledge management (KM) processes. Typical KM initiatives include the development, transfer, storage, and evaluation of a firm’s knowledge throughout the knowledge lifecycle, but often neglect ongoing advances in the AI area. Thus, organizations struggle to integrate AI into working environments to leverage outcome efficiency. Starting with a descriptive literature review, we draw on two KM strategies–personalization and codification–and introduce an adaptive, AI-specific approach for organizational KM implementation. Our approach supports KM strategy and research, as it outlines how AI affects current working processes. This enables to understand which role AI can take in the human-AI interaction. Knowledge managers are provided with a tool to align organizational KM with the business strategy and current technological progress in AI context. We also outline future research to validate the construct.engKnowledge ManagementArtificial IntelligencePersonalization StrategyCodification StrategyAdaptive Knowledge Management004330conferenceobject