This article describes the use of artificial intelligence techniques to improve the direction and attitude precision of small aircraft. First, the study focuses into basic AI approaches such as reinforcement learning, PID control, and neural networks. These types of systems provide adjustable and sensitive control mechanisms, allowing small aircraft to accurately react to changing conditions during flight. Furthermore, the MATLAB Simulation model incorporates PID controller-based AI control to simulate small aircraft characteristics under various scenarios. In the end, the research discussed formal risk analysis and safety considerations while installing AI control systems in small aircraft. Failure mode effects analysis and fault tree analysis can be utilized to identify potential hazards and manage risks, ensuring the reliability as well as security of AI-controlled systems. Incorporating an artificial intelligence application with a PID controller to improve aircraft magnetic heading and attitude estimation involves applying AI to continually modify the PID gains in response to the system’s behavior and performance. Using this technique can lead to improved control performance, especially during situations in which system dynamics are unclear or change over time. The purpose of this research is to greatly improve the reliability and accuracy of small aircraft control systems by integrating the recommended AI control, simulation models, and strict safety requirements.