Design of enterprise operation and management mode based on big data + artificial intelligence technology

Abstract

This study addresses the needs of enterprises undergoing intelligent transformation by proposing an enterprise operation and management model that integrates big data and artificial intelligence technologies. It constructs an intelligent operation system centered on data-driven operations, algorithm empowerment, and a closed-loop system. By integrating key technologies such as system architecture decoupling, multi-source heterogeneous data fusion, graph neural network process modeling, and reinforcement learning strategy optimization, it achieves the intelligent restructuring of functional modules including financial forecasting, risk warning, supply chain scheduling, and customer behavior modeling. The results of platform-level integration testing and function effectiveness evaluation show that this model has achieved significant improvements in prediction accuracy, resource allocation efficiency, and decision response timeliness, providing a technical path and empirical support for building a highly resilient and responsive enterprise operation mechanism.