AI-driven knowledge management system reconstruction: the CPOS four-dimensional collaborative framework

Purpose This paper aims to address the limitations of traditional knowledge management (KM) theories in the era of artificial intelligence (AI) and propose a comprehensive framework to redefine KM in the context of AI-driven technological advancements. Design/methodology/approach The study constructs the “Cognition-Process-Organization-Strategy” (CPOS) four-dimensional collaborative theoretical framework. It integrates insights from traditional KM theories, AI technologies and emerging practices to systematically analyze the impact of AI on KM. The framework is developed through a three-stage logic of technology-driven transformation, theoretical adaptation and system reconstruction. Findings The CPOS framework reveals that AI technologies fundamentally reshape KM by enabling cognitive reconstruction, process parallelization, organizational decentralization and strategic paradigm shifts. It highlights the transition from human-centered KM to human–machine collaborative knowledge production, emphasizing dynamic, open and distributed knowledge ecosystems. Originality/value This paper contributes to the field by bridging the gap between traditional KM theories and AI applications. It introduces a novel theoretical framework that redefines KM in the AI era, offering a systematic approach to understanding and implementing AI-driven KM systems. The CPOS framework provides a comprehensive roadmap for organizations to navigate the challenges and opportunities of, AI, KM, CPOS framework, human–machine collaboration.