Artificial intelligence technology has become a key technology for improving the efficiency and reliability of aircraft engine maintenance in the field of engine fault diagnosis. AI-based fault diagnosis technology uses advanced algorithms such as machine learning, deep learning, and transfer learning algorithms to analyze the large amount of data generated by aircraft engines during operation to achieve early identification and accurate prediction of potential engine faults. This technology can learn fault patterns from complex data to improve the accuracy and speed of diagnosis. By real-time monitoring of an engine’s operating status, this technology can not only remind maintenance personnel in a timely manner to intervene to prevent faults but also optimize maintenance plans and reduce unnecessary maintenance costs and downtime. In addition, with the continuous optimization of algorithms and the enhancement of data processing capabilities, AI-based fault diagnosis technology will become more precise and efficient, which is highly important for improving the operational safety and economy of aircraft engines.