数字经济加速区域产业智能化转型。江西数字产业设计环节长期存在知识分散、资源割裂、协同低效等问题。本文以江西数字产业设计知识体系为研究对象，构建AI赋能设计知识图谱技术框架，完成多模态知识采集、本体建模、混合存储与动态更新等全流程实施。语义推理、产业适配、知识更新与生态协同层面的效能瓶颈被逐一剖析。图神经网络优化、轻量化工具适配、知识安全保障、增量迭代机制与生态协同策略系统化提出。一条适配江西区域特色的设计知识智能组织与效能提升路径由此形成，为数字产业设计智能化升级提供了可行方案。

Digital economy accelerates the intelligent transformation of regional industries. The design sector of Jiangxi’s digital industries has long been plagued by problems such as scattered knowledge, fragmented resources and inefficient collaboration. Taking the design knowledge system of Jiangxi’s digital industries as the research object, this paper constructs a technical framework of AI-enabled design knowledge graph, and implements the whole process including multimodal knowledge collection, ontology modeling, hybrid storage and dynamic update. The efficiency bottlenecks in semantic reasoning, industrial adaptation, knowledge updating and ecological collaboration are analyzed one by one. Systematic strategies are proposed, including graph neural network optimization, lightweight tool adaptation, knowledge security guarantee, incremental iteration mechanism and ecological collaboration. A path of intelligent organization and efficiency improvement of design knowledge suitable for Jiangxi’s regional characteristics is formed, which provides a feasible scheme for the intelligent upgrading of design in digital industries.