This study presents three levels of intelligent communication development: highly specialized, general, and superintelligent. It analyzes the specific characteristics and potential applications of each level in the communication context, focusing on the contributions of machine learning, deep learning, and neural networks. The study explores how advances in AI are enabling the creation of increasingly intuitive and personalized interactions between humans and machines. For the highly specialized level, it is learned that its characteristic is the execution of defined tasks to automate routine communication and increase efficiency. The hypothetical general level is characterized by human-level cognitive flexibility, with potential applications including meaningful conversations and adapting communication to diverse contexts. Finally, the theoretical superintelligent level is characterized by surpassing human limits in all metrics, with predicted applications like predicting global communication trends and integrating facial recognition into a full understanding of human identity. In addition, significant applications of intelligent communication in various fields are presented.