People with high-level cervical spinal cord injury can have significant impairments in their ability to control their environment, including challenges operating a smartphone or navigating a power wheelchair. The use of eye-tracking technology has been crucial in improving communication and control for individuals with tetraplegia. However, traditional eye-tracking systems often have limitations in terms of accuracy, calibration time, and practicality. To overcome these limitations, researchers have explored the use of Convolutional Neural Networks (CNNs) in AI-enhanced eye-tracking technology. CNNs are a type of deep learning algorithm that can learn complex patterns in image data, allowing for more accurate and reliable eye-tracking. AI-enhanced eye tracking using three times eye blinking is a novel approach that has shown great potential in improving the accuracy and efficiency of eye tracking technology. By using advanced machine learning algorithms, this approach can detect and track eye movements based on the number of blinks, providing a more reliable and efficient way to interact with digital devices. This technology has the potential to revolutionize the way we interact with digital devices, making them more accessible and user-friendly for people with disabilities or impairments. The results and discussions related to AI-enhanced eye tracking using three times eye blinking have shown that it can be a viable alternative to traditional eye tracking technology, which can be costly, time-consuming, and difficult to use. Furthermore, this approach is highly customizable and can be adapted to meet the specific needs and preferences of individual users. As such, it has the potential to significantly enhance the quality of life for individuals with motor impairments, visual impairments, or other disabilities that affect their ability to use traditional eye tracking technology. AI-enhanced eye tracking using three times eye blinking is a promising technology that has the potential to create a more inclusive and accessible digital world. With continued research and development, we can expect to see even more innovative solutions and applications for this technology in the future.