AI-Driven Innovation Upgrade in The Automotive Manufacturing Industry: A Comprehensive Empirical Study

Zhesen Chen

doi:10.54097/vjggcv79

Authors

Zhesen Chen

DOI:

https://doi.org/10.54097/vjggcv79

Keywords:

Artificial Intelligence, Automotive Manufacturing, Process Innovation, Industry Collaboration, Innovation Performance

Abstract

The rapid maturation of artificial intelligence (AI) technologies has created unprecedented opportunities for industrial transformation, particularly within the automotive manufacturing sector. While prior research has often focused on AI applications in product development, autonomous driving, or supply-chain logistics, comparatively fewer studies have examined the systematic influence of AI on core manufacturing processes and the collaborative dynamics of the automotive industry value chain. This paper investigates whether and how AI can empower innovation upgrades in automotive manufacturing by developing a conceptual framework that links AI-enabled capabilities to organizational coordination and innovation performance. Key findings indicate that AI adoption in production planning, quality control, and predictive maintenance significantly enhances incremental and breakthrough innovation within firms. Moreover, AI-fueled data integration platforms facilitate cross-organizational knowledge sharing, thereby amplifying coordinated innovation across upstream and downstream partners. By elucidating the mechanisms through which AI drives manufacturing innovation, this study contributes to academic theory on digital transformation and offers actionable insights for practitioners pursuing intelligent manufacturing.

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