Strategic knowledge management in the digital era: boundary crossing, AI and innovation in advanced manufacturing

Purpose The firms struggle to turn technological achievements into productivity gains. Although external knowledge acquisition is important, empirical evidence is limited on how digital boundary crossing drives innovation, particularly via artificial intelligence (AI). This study aims to develops an integrated theoretical framework to examine how digital boundary crossing influences technological innovation in advanced manufacturing and to identify the boundary conditions that strengthen or constrain these effects, thereby extending the knowledge management and technological innovation literature. Design/methodology/approach An empirical test was conducted using panel data on 461 Chinese listed advanced manufacturing companies from 2015 to 2023, using a two-way fixed effects model. The core variable “digital boundary crossing” was operationalized by integrating three dimensions: digital transformation index, knowledge breadth and market position, and a composite indicator was constructed using the criteria importance through intercriteria correlation method. Findings This study shows that digital boundary crossing significantly boosts corporate technological innovation. Knowledge diversity partially mediates this effect, while AI amplifies both the direct impact of digital boundary crossing on innovation and its role in fostering knowledge diversity (KD). These effects are stronger in firms with stronger market positioning, larger scale, higher product competitiveness and in innovation-intensive regions with advanced intellectual property systems and widespread AI adoption. Originality/value This study conceptualizes “digital boundary crossing” as a multidimensional construct and shows how it drives technological innovation through KD. It also guides managers in using digital infrastructure and AI to strengthen cross-boundary knowledge integration and sustain innovation, advancing theory on digital-era boundary crossing and providing empirical evidence of AI’s role in knowledge management.