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Smart cities have a complex structure and generate a large amount of data. This is precisely why the presence of artificial intelligence is necessary to effectively detect and neutralize any malware. Artificial intelligence enables not only detection but also an attack, but also to improve the entire smart city protection system. Combining available protection solutions with constant improvements and reacting at the right time are of most importance. This paper serves as a survey and tutorial on the application of artificial intelligence for malware detection in smart cities. The focus is placed on smart city domains such as the Internet of Things, Operational Technology, traffic management, utilities, and public safety systems. Areas outside the smart city context, such as personal cybersecurity or general IT infrastructure, are not covered in this study. The main contributions of this paper include: providing a comprehensive overview of how Artificial intelligence supports malware detection and prevention through advanced technologies and analytical methods, identifying key challenges and limitations in applying Artificial intelligence to urban cybersecurity, and outlining future directions for improving system resilience and adaptive protection. Artificial intelligence has a large number of algorithms and methods, which are helping to monitor and analyze the system behavior. In addition to identifying threats, it is possible to adapt to new forms of malicious software. There are certain challenges in implementing artificial intelligence for malicious software detection, as well as strategies for improving protection.