| Summary: | 5G network slicing supports three major service scenarios including enhanced mobile broadband(eMBB), ultra-reliable low-latency communication(uRLLC), and massive machine-type communication(mMTC). It can share physical resources and ensure the isolation requirements between slices. Network slicing features，such as on-demand customization, real-time deployment, and dynamic guarantee，enable network flexibility, but make network management and operation more complex and challenging. Artificial intelligence(AI) technology is a potential solution to the complexity of network slice management. Therefore, this article will study the integration of AI and network slice management, propose an AI-based intelligent slice management architecture, introduce the intelligent slice management processes in detail, and present some typical application cases.
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