Beyond digitalization: how AI-driven knowledge management addresses collaboration challenges among manufacturing supply chain enterprises

Purpose This study aims to examine how artificial intelligence (AI)-driven knowledge management addresses interfirm collaboration dilemmas in manufacturing supply chains that digitalization alone cannot resolve. It focuses on cross-organizational knowledge understanding, trust governance and tacit knowledge transfer. Design/methodology/approach Based on three typical Chinese cases, this study analyzes how AI-driven knowledge management responds to inconsistent data understanding, lack of relational trust and barriers to knowledge absorption in manufacturing supply chains. Findings The study identifies three knowledge-based collaboration dilemmas in digitalized manufacturing supply chains: interpretive misalignment, trust deficits and absorptive barriers. These appear as shared data without shared understanding, formal contracts without relational trust and tacit knowledge transfer without internalization. AI-driven knowledge management addresses these dilemmas through three mutually reinforcing mechanisms. Semantic alignment transforms dispersed data into shared meanings, causal relationships and negotiable decision rationales. Evidence-based trust governance converts collaborative behaviors into verifiable and jointly interpretable process evidence. Digital apprenticeship embeds AI-enabled guidance, feedback and contextualized learning into workflows, enabling tacit knowledge absorption and capability codevelopment. Research limitations/implications This study emphasizes mechanism identification and case-based insight. The generalizability, causal effects and boundary conditions of the three mechanisms require further empirical examination. Practical implications Manufacturing supply chain firms should move beyond data interface integration and information visualization by using AI to enhance semantic alignment, build evidence-based cogovernance and transform individual tacit experience into reusable cross-organizational capabilities. Originality/value This study reframes digitalized manufacturing supply chain collaboration as a knowledge management problem. It advances research from data visualization to meaning construction, from contractual or relational governance to evidence-based trust governance and from tacit knowledge transmission to workflow-embedded digital apprenticeship.