The wireless sensor networks focus on traditional, machine learning-based, and advanced AI-driven methods. A comparison of speed, overhead, and energy consumption yields significant findings. While the traditional methods exhibit small trade-offs between energy use and network latency, the machine learning technique exhibits considerable flexibility and enhanced security. In addition to revealing enhanced performance metrics, such as lower overhead, maximum energy efficiency, and faster speed, this study introduces a groundbreaking AI-driven encryption architecture. The results show how AI can revolutionize WSN security by offering a dependable and adaptable solution. The use of graphics enhances the findings' readability and provides a more nuanced perspective on performance variations. By integrating AI, this study sets a baseline for existing procedures and paves the way for future advancements in WSN security. Internet of Everything (IoE) advanced wireless networks are crucial. © 2025 Elsevier B.V., All rights reserved.