AI赋能制造业数字化转型发展态势

摘要/Abstract

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。

关键词: 制造业, 数字化转型, AI赋能, 态势

Abstract:

Under the backdrop of the profound restructuring of the global manufacturing competitive landscape and the emergence of a new wave of technological revolution, AI-enabled digital transformation in manufacturing has become a Strategic Initiatives for breaking through industrial upgrading bottlenecks and cultivating new quality productive forces. Through systematic literature review and analysis of global trends in AI-driven manufacturing transformation, this study reveals the evolutionary patterns, global competitive dynamics, and future challenges of AI-empowered digital transformation in manufacturing. Key findings include: (1) AI technology penetration exhibits phased leapfrogging characteristics, evolving from single-point applications and partial process optimization to systemic empowerment. This transformation is driven by a three-dimensional mechanism—technology infiltration, process reengineering, and ecosystem reconstruction—that comprehensively accelerates manufacturing digitalization. (2) The global landscape demonstrates five salient features: data elements becoming strategic assets, systemic enhancement of full-chain efficiency, structural transformation of corporate operational logic, accelerated strategic deployment by major economies, and the emergence of AI governance as a global common agenda. China has developed a distinctive pathway leveraging its "technology-market-industry" synergistic advantages. (3) Three-tier challenges persist: technical barriers including data silos and algorithmic black boxes, industrial constraints involving green transition pressures and standardization gaps, and geopolitical tensions over technological dominance and fragmented governance frameworks. The study proposes future research priorities: innovation in AI foundational logic and its impact on reshaping global manufacturing geography, pathways for AI-enabled green-digital synergy in sustainable manufacturing, and strategies to navigate international AI competition toward an open, win-win global community. This research provides a systematic framework for understanding the strategic value, implementation pathways, and global competition patterns of AI-driven manufacturing digitalization, offering policy implications for developing new quality productive forces and advancing China's manufacturing powerhouse construction.

Key words: manufacturing, digital transformation, AI-enabled, trends

中图分类号:

F405
F420

李健旋, 蒋佳浩. AI赋能制造业数字化转型发展态势[J]. 科学学研究, 2026, 44(6): 1169-1177.

LI Jian-xuan, JIANG Jia-hao. Development trends of AI-enabled digital transformation in manufacturing[J]. Studies in Science of Science, 2026, 44(6): 1169-1177.

图/表 1

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