人工智能驱动嘉兴市先进制造业集群发展：赋能路径、实践探索与政策研究

Artificial Intelligence Driving the Development of Advanced Manufacturing Clusters in Jiaxing: Empowerment Pathways, Practical Explorations, and Policy Research

摘要: 人工智能与制造业的深度融合，正在重塑先进制造业集群的竞争力结构和演化逻辑。本文以浙江省嘉兴市为研究对象，系统考察人工智能驱动先进制造业集群发展的赋能机制、演进路径与政策支撑。研究发现，人工智能对先进制造业集群的驱动遵循“数据驱动–算力赋能–算法增值”的递进逻辑，其赋能路径沿着“点状试点–线状贯通–面状集成–立体协同”的层次递进，形成从企业智能升级到产业链智能协同再到集群整体智能化的纵深演化格局。在行业龙头企业智能化转型的带动下，嘉兴初步形成了以智算基础设施为底座、以“135N”先进制造业集群为主阵地、以“人工智能 + 制造”政策体系为保障的发展格局，但仍面临数据治理滞后、中小企业能力鸿沟、复合型人才短缺等结构性挑战。进一步推动人工智能与先进制造业集群深度融合发展，应在强化算力底座、推进数据要素化、优化人机协同生态、深化区域协同等方面持续发力。

Abstract: The deep integration of artificial intelligence and manufacturing is reshaping the competitive structure and evolutionary logic of advanced manufacturing clusters. Taking Jiaxing City in Zhejiang Province as the subject of this study, this paper systematically examines the empowerment mechanisms, evolutionary pathways, and policy support for AI-driven development of advanced manufacturing clusters. The study finds that the role of AI in driving advanced manufacturing clusters follows a progressive logic of “data-driven—computing power empowerment—algorithm-driven value enhancement”. Its empowerment pathways advance through the hierarchical stages of “point-based piloting—linear integration—area-wide integration—multidimensional collaboration”, forming a deepening evolutionary pattern that progresses from enterprise-level intelligent upgrading to industrial chain-level intelligent collaboration and ultimately to cluster-wide intelligent integration. Driven by the intelligent transformation of leading enterprises in the industry, Jiaxing has preliminarily established a development framework anchored by intelligent computing infrastructure, centered on the “135N” advanced manufacturing clusters, and supported by an “AI + Manufacturing” policy system. However, it still faces structural challenges such as lagging data governance, a capability gap among small and medium-sized enterprises (SMEs), and a shortage of multidisciplinary talent. To further promote the deep integration of artificial intelligence and advanced manufacturing clusters, sustained efforts should be made in strengthening the computing infrastructure foundation, advancing the commoditization of data, optimizing the human-machine collaboration ecosystem, and deepening regional collaboration.