In recent years, brain-computer interfaces (BCIs) have made significant strides in helping individuals with paralysis regain control over their movements and communication. A groundbreaking approach now integrates artificial intelligence (AI) copilots into BCI systems, enhancing their performance and usability. This shared autonomy model allows AI to collaborate with users, leading to remarkable improvements in task execution, such as cursor control and robotic arm manipulation. The innovative hybrid adaptive decoding method, which combines convolutional neural networks with advanced filtering techniques, has shown promising results.