In the era of Generative AI (Gen AI), addressing the governance of AI-generated misinformation is a significant challenge faced by information systems. The emergence of large language models (LLMs) holds great potential to reshape the landscape of combating misinformation. Inspired by this, this study explores whether Gen AI can accurately detect AI-generated misinformation, based on the governance concept of “leveraging technology to regulate technology”. By crawling 1302 mixed-labeled pieces of claims from Snopes during Aug. 2023 to Nov. 2024, including True, False, and Fake (i.e., AI-generated), this research proposes a Fine-Tuned GPT (FT-GPT) model for the detection for AI-generated misinformation. Through comparison with existing mainstream deep learning algorithms, the study demonstrates the superior performance of the FT-GPT model in detecting AI-generated misinformation. The contribution of this research lies in introducing the task of detecting AI-generated misinformation, distinct from traditional binary classification tasks, and proposing the FT-GPT model for the misinformation research.