Capital–Technology Structural Coupling and Evolutionary Resilience in China’s AI Industry

This study examines the evolving structural relationship between capital networks and technological trajectories in China’s artificial intelligence (AI) industry from 2018 to 2023. Using a network-based analytical framework, we integrate venture capital co-investment data with patent-text semantic similarity measures to assess the structural association between financial connectivity and technological distribution patterns. Technological diversity is quantified using text-embedding techniques and Shannon entropy, while Quadratic Assignment Procedure (QAP) models are employed to evaluate inter-network alignment between capital ties and technological similarity. The results indicate a progressively strengthened capital–technology coupling accompanied by increasing technological convergence within the industrial network. Robustness checks across multiple similarity thresholds confirm the stability of these structural associations. Quadrant-based analysis identifies a persistent asymmetry between technologically distinctive but financially peripheral firms and highly central yet technologically homogeneous actors. Robustness analysis further suggests a “robust yet fragile” network configuration characterized by resilience to random disturbances but vulnerability to hub-targeted shocks. Collectively, the findings illuminate the structural implications of capital–technology interdependence for industrial sustainability. From a sustainability perspective, maintaining structural diversity alongside capital coordination is essential for preserving adaptive capacity in rapidly evolving innovation ecosystems. Excessive alignment between financial networks and dominant technological paradigms may enhance short-term efficiency but constrain long-term evolutionary flexibility.