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

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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Publication Details

Journal
Frontiers in Business Economics and Management
Published
2025-09-09
DOI
https://doi.org/10.54097/vjggcv79
Primary Topic
Firm Innovation and Growth
Type
article
Field-Weighted Citation Impact
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article

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

Zhesen Chen
1 links
Frontiers in Business Economics and Management
Firm Innovation and Growth
article

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

Zhesen Chen
article en

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.

Frontiers in Business Economics and ManagementVol. 20(3)
Nanjing University of Finance and Economics (CN)
Openalex Percentile: Top 67%
Firm Innovation and Growth
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AI-Driven Innovation Upgrade in The Automotive Manufacturing Industry: A Comprehensive Empirical Study — Zhesen Chen · Frontiers in Business Economics and Management (2025) | TGRS Research Map | TGRS