AI-Driven Resilience: Unpacking China's Industrial Chain Transformation

The Evolution of China's Industrial Chain Resilience

China's manufacturing sector has undergone significant transformation over the past four decades, evolving from a factor endowment-driven, extensive division of labor to a networked system characterized by economies of scale and synergistic effects. The diffusion of AI is driving structural changes in production functions, optimizing resource allocation, and enhancing industrial chain resilience.

The Role of AI in Building Resilience

AI-powered algorithms and machine learning have become crucial components in strengthening the robustness of the supply chain and reducing external threats. By embedding AI into the mechanisms of building supply chain resilience, China's industrial sector can achieve a new level of efficiency and competitiveness.

The Dual-Path Mechanism of AI's Empowerment

This study proposes a dual-path mechanism of ‘technological innovation effect’ and ‘digital empowerment effect’ to explore how AI affects industrial chain resilience. The former emphasizes how AI enhances the supply chain’s ability to cope with shocks by optimizing the R&D process and fostering new technologies, while the latter focuses on how AI-driven data integration and intelligent decision-making enhance the supply chain’s dynamic adaptability.

Heterogeneous Patterns of AI's Impact

The effect of AI on resilience varies across different supply chain resilience dimensions, internal supply chain segments, and industries with different export dependence. This study dissects supply chain segments and industry types to uncover the heterogeneous patterns of AI’s impact.

The Bottom Line

AI-driven resilience is crucial for China's industrial sector to maintain global competitiveness. By understanding the mechanisms behind AI's empowerment of resilience, policymakers and business leaders can make informed decisions to leverage AI's potential and drive sustainable growth.