With the development of software-defined network (SDN), there will be a large number of devices to access network, which may cause an incalculable burden to the communication network. In addition, due to the high bandwidth in the fifth-generation (5G) era, innovation will occur in different fields. There are not only strict requirements on the communication capability of SDN for these application scenarios but also a lot of computing resources. For massive access devices, it is difficult for the traditional service resource scheduling and the allocation system to meet user demand growth. To address the above-stated problems, an artificial intelligence agent (AI Agent) system is put forth in this article. AI Agents can be deployed in different layers of the SDN, thus realizing functions like network service prediction and resource scheduling. A brand new AI Agent framework is designed, and an AI algorithm is adopted to replace the traditional service prediction and resource scheduling strategies. In the meantime, a relevant agent deployment scheme is put forward. Finally, an AI Agent-based simulation experiment for resource scheduling is designed, and the accuracy in network service prediction and rationality in resource allocation based on this framework are tested. The experimental result showed that the operation efficiency of the SDN can be effectively improved, and the resource hit ratio and user service quality may be improved with AI-agent-based traffic prediction and resource allocation model.