Artificial Intelligence and the Transformation of the Automotive Sectoral Innovation System
Abstract
Background
This study examines the impact of artificial intelligence (AI) on the South Korean automotive innovation system. It analyses the transformation of production-based innovation across system elements and the broader system in which they are embedded, both increasingly shaped by AI.
Objectives
The study addresses the lack of systematic analyses of AI’s impact on the automotive business system and aims to generate strategic, policy, and theoretical insights.
Methods/Approach
The research applies an augmented sectoral system of innovation and production (SSIP) framework, combined with Delphi analysis, expert interviews, and document analysis.
Results
The findings indicate accelerating transformations across SSIP components in both the present and the near future. Automakers, parts suppliers, and technology suppliers, together with their AI networks, emerge as leading actors, while research institutes, universities, government agencies, institutions, and consumers lag. Intensifying interactions among SSIP constituents, AI systems, and AI-based production activities and innovations further reinforce these transformations.
Conclusions
A holistic analysis of the AI-driven automotive SSIP shows how leading actors interactively shape system dynamics. The findings provide a basis for designing policy instruments to support slower-transforming actors and facilitate overall system transformation.
© 2026 Kritsada Patluang, published by IRENET - Society for Advancing Innovation and Research in Economy
This work is licensed under the Creative Commons Attribution 4.0 License.