• 中国科学学与科技政策研究会
  • 中国科学院科技战略咨询研究院
  • 清华大学科学技术与社会研究中心
ISSN 1003-2053 CN 11-1805/G3

科学学研究 ›› 2026, Vol. 44 ›› Issue (6): 1169-1177.

• 热点议题 • 上一篇    下一篇

AI 赋能制造业数字化转型发展态势

李健旋,蒋佳浩   

  1. 河海大学
  • 收稿日期:2025-05-20 修回日期:2025-09-01 出版日期:2026-06-15 发布日期:2026-06-15
  • 通讯作者: 李健旋
  • 基金资助:
    中国制造业数字化与绿色化关联耦合机理及测度研究

Development Trends of AI-Enabled Digital Transformation in Manufacturing: A Literature Review

  • Received:2025-05-20 Revised:2025-09-01 Online:2026-06-15 Published:2026-06-15

摘要: 在全球制造业竞争格局深度重构与新一轮科技革命交汇的背景下,AI赋能制造业数字化转型已成为突破产业升级瓶颈、培育新质生产力的战略举措。本文通过系统性梳理国内外文献,结合AI赋能制造业转型的全球动态进行解析,揭示AI赋能制造业数字化转型的演进规律、全球竞争态势与未来挑战。研究发现:(1)AI技术渗透呈现阶段性跃迁特征,已从单点技术应用、局部流程优化演进至系统性赋能阶段,通过技术渗透-流程再造-生态重构的三维作用机制,全面驱动制造业数字化转型。(2)AI赋能制造业数字化的全球态势:数据要素上升为战略资产、全链效能系统性跃升、企业底层逻辑结构性变革、主要经济体加速战略布局、AI治理成为全球共性议题,中国依托"技术+市场+产业"组合优势形成独特发展路径。(3)AI赋能制造业数字化转型存在三重挑战:技术层面存在数据孤岛与算法黑箱,产业层面存在绿色约束与标准壁垒,国际层面存在技术主导权争夺与治理体系分化。研究提出应进一步关注的研究热点:AI底层逻辑创新及重组全球制造业版图的态势、AI赋能制造业数字化与绿色化耦合重塑全球青山绿水的路径、AI赋能制造业国际博弈焦点及走向开放共赢全球命运共同体的时代趋势。本文为理解AI驱动制造业数字化转型的战略价值、实践路径及全球竞争格局提供了系统性框架,对中国发展新质生产力和建设制造强国具有决策参考价值。

Abstract: In the context of the deep restructuring of the global manufacturing competition pattern and the convergence of a new round of scientific and technological revolution, AI-enabled digital transformation of the manufacturing industry has become a strategic initiative to break through the bottleneck of industrial upgrading and cultivate new quality productivity. This paper analyzes the global dynamics of AI-enabled manufacturing transformation by systematically combing domestic and international literature to reveal the evolution law, global competition situation and future challenges of AI-enabled manufacturing digital transformation. The study found that: (1) AI technology penetration presents a staged leap characteristic, has evolved from a single point of technology application, local process optimization to the systematic empowerment stage, through the technology penetration - process re-engineering - ecological restructuring of the three-dimensional role of the mechanism, to comprehensively drive the digital transformation of the manufacturing industry. (2) The global situation of AI-enabled manufacturing digitization: the data element has risen to be a strategic asset, the whole chain efficiency has systematically jumped up, the underlying logic of the enterprise has structurally changed, major economies have accelerated the strategic layout, and AI governance has become a global common issue, and China has formed a unique development path relying on the combination of advantages of “technology+market+industry”. (3) There are three challenges in AI-enabled digital transformation of manufacturing industry: data silos and algorithmic black boxes at the technical level, green constraints and standard barriers at the industrial level, and competition for technological dominance and differentiation of governance systems at the international level. The study proposes the research hotspots that should be further focused on: AI underlying logic innovation and restructuring of the global manufacturing landscape, AI-enabled manufacturing digitization and greening coupled to reshape the global path of green mountains and green water, AI-enabled manufacturing international game focus and the trend toward an open and win-win global community of destiny. This paper provides a systematic framework for understanding the strategic value, practical path and global competition pattern of AI-driven digital transformation of manufacturing industry, which is of decision-making reference value for China's development of new-quality productive forces and the construction of a manufacturing powerhouse.