Research on the Reconstruction of Tech-Economic Management Modes Driven by Artificial Intelligence and Big Data

Against the backdrop of the in-depth integration of the digital economy and intelligent technologies, traditional techno-economic management is confronted with challenges such as decision-making lag and information silos. Meanwhile, enterprises are plagued by issues including rigid management systems, lagging technological applications, insufficient model innovation, and weak talent support. Based on relevant theories, this paper analyses the enabling mechanisms of artificial intelligence and big data, and constructs a four-dimensional reconstruction framework of "Concepts-Systems-Technologies-Talents". With collaborative linkage, this framework can promote the transformation of techno-economic management from experience-driven to data-intelligence-driven, enhance the scientificity of enterprise decision-making, operational efficiency, and value creation capacity, and provide paths for the modernization and sustainable development of enterprise management.