The knowledge collaboration framework: a review of artificial intelligence in organisational learning and knowledge management

This semi-systematic review examines how artificial intelligence (AI) reshapes organisational learning (OL) and knowledge management (KM), synthesising insights from 149 peer-reviewed articles (1993–2025) from Scopus and Web of Science into a nomological network, linking key concepts and processes. The author synthesised a Knowledge Collaboration Matrix crossing knowledge type (tacit/explicit) with human-AI collaboration mode (automation/augmentation) to explain enhancer-hindrance dynamics of AI across KM steps and OL levels. Explicit knowledge automation is associated with efficiency and scalability, but might risk bias, opacity, and deskilling. Tacit knowledge automation offers limited benefits due to context loss. Explicit knowledge augmentation supports pattern discovery and adaptive learning contingent on infrastructure, data quality and training. Tacit knowledge augmentation promises resilience yet can erode trust and critical thinking if over-mediated. The review proposes key governance mechanisms for effective AI integration and highlights a relative evidence gap on AI in OL compared to KM, informing future research.