Research on the Pathways of Empowering New-type Industrialization with Artificial Intelligence

Authors

  • Xiuwen Jiang

DOI:

https://doi.org/10.62051/ijgem.v8n2.16

Keywords:

Artificial intelligence, Manufacturing industry, New-type industrialization, And deep integration

Abstract

As the core driving force behind the new round of technological revolution and industrial transformation, artificial intelligence (AI) is profoundly empowering the process of new-type industrialization, propelling the manufacturing sector towards intelligent, high-end, and green transformation. Based on the techno-economic paradigm theory, this paper systematically analyzes the internal mechanisms, practical progress, and challenges associated with AI-enabled new-type industrialization. Research indicates that China has achieved notable application outcomes in core industrial processes such as intelligent production scheduling, predictive maintenance, and visual inspection. However, structural bottlenecks persist, including constraints on key core technologies, difficulties in implementing AI in industrial scenarios, a shortage of high-end interdisciplinary talent, and a lack of standardized norms and legal safeguards. To address these issues, this paper proposes strengthening foundational research and breakthroughs in core technologies, expanding typical industrial application scenarios, constructing a multi-tiered talent cultivation system for AI, and accelerating the development of standards and specialized legislation. These measures aim to systematically advance the deep integration of AI with new-type industrialization, providing theoretical foundations and pathway references for building a modern industrial system and realizing the strategy of making China a manufacturing powerhouse.

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References

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Published

27-09-2025

Issue

Section

Articles

How to Cite

Jiang, X. (2025). Research on the Pathways of Empowering New-type Industrialization with Artificial Intelligence. International Journal of Global Economics and Management, 8(2), 134-141. https://doi.org/10.62051/ijgem.v8n2.16