This paper presents how the Advanced Encryption Standard (AES) is utilized in the current Information Technology world. AES encrypts private information, giving security when transferring this information to prevent its access by unauthorized parties using very different mediums, like online transactions or data storage devices. The success of security provided in AES lies in the KSA—Key Scheduling Algorithm which generates the keys which used in encrypting the data. Our research embarks on a deep learning approach-based investigation into AES KSA. More specifically, neural network models will be utilized to probe the operational dynamic and characteristics that the AES KSA exhibits. The purpose of the study is to unveil not just the robustness and possible weaknesses of AES KSA but also to utilize patterns which could be identified for such weaknesses. By the training of our neural network with keys datasets, we strive to identify any visible patterns or weaknesses in AES that can be exploited by individuals for malicious purposes. This paper also significantly enhances the value of literature through debate surrounding different countermeasures, much of which enhance the security architecture corresponding to AES.