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With the integration of power electronics-interfaced devices into power systems, it is becoming more and more challenging to develop comprehensive and precise models for power system monitoring and control. This also poses serious challenges for model-based state estimation process. The situation is even worse in distribution systems, where real-time measurements are always insufficient. As a result, fusing multiple sources of data with different granularity and accuracy is becoming critical. This opens the door for leveraging the powerful data-driven Artificial Intelligent technology for power system state estimation. This panel aims to discuss the roles of AI for state estimation and related challenges for practical applications. Use cases will be discussed as well.