Based on artificial intelligence and big data analysis technology, this article explores how to build a more comprehensive and accurate enterprise risk prediction and management system. Traditional risk management methods have problems such as limited data sources, low prediction accuracy, cumbersome risk management processes, and a lack of real-time monitoring and early warning. This article improves the accuracy and precision of risk prediction by comprehensively utilizing internal and external data, real-time data, and advanced prediction models; It utilizes logistic regression in artificial intelligence technology to achieve automation and intelligence of risk management decisions, improving the efficiency and timeliness of risk management; A risk monitoring system can be established by combining big data analysis technology to achieve real-time monitoring and early warning of risks. Through research and practice, this article aims to improve the level and capability of enterprise risk management. The results show that the throughput of the risk prediction management system based on logistic regression has reached over 980 tps. This provides more effective risk management solutions for enterprises to achieve long-term stable development.