Analysis of Emerging Industry Chains Based on AI and Big Data

This paper addresses the urgent demand and immense value of analyzing emerging industry chains, proposing an innovative approach powered by big data and artificial intelligence (AI). It systematically examines the challenges of analyzing emerging industry chains, the data service system architecture required, key technical methods for industry chain construction, and practical applications through visualization. Key technologies include the management and optimization of industry chain graphs, product/service labeling, and the construction of comprehensive industry chain databases using knowledge graphs. Furthermore, advanced tools such as Product Labeling Algorithm (PLA) technology and graph database construction enable detailed mapping of upstream and downstream relationships, while risk management and visualization enhance decision-making and early warning systems. Supported by the Data-as-a-Service (DaaS) team, this method provides actionable insights for industry chain analysis, risk monitoring, and enterprise research. By focusing on the development of new quality productive forces, it offers strategic solutions for enhancing distributed collaboration, upgrading industry chains, and driving high-quality industrial development. These capabilities have been successfully applied in real-world projects, enabling institutions to handle complex industry chain analyses at unprecedented scales. The demonstrated results underline the potential of this approach to transform industrial research and policy-making, bridging the gap between datadriven insights and actionable outcomes.