With the continuous development of the payment market, the data structure characteristics of new business forms such as mobile Internet have changed significantly, and intelligent cloud data center is the general trend of development in the current indus- try. This paper proposes an artificial intelligence method and system design for dynamic scheduling of cloud resources based on busi- ness prediction. The resource availability of daily physical machines has changed over time, and it is necessary to reintegrate the re- sources in order to save energy and meet the requirements of service. In the early stage of large-scale marketing, capacity analysis is combined to make prediction in advance, and intelligent multi-dimensional capacity decision expansion based on artificial intelli- gence and machine self-learning is adopted. The dynamic migration and integration method of virtual machines in cloud data centers with high energy efficiency provides a new solution for improving energy efficiency of cloud computing data centers, ensuring sys- tem reliability and reducing operation and maintenance costs of cloud data centers.