The rapid growth of wireless communication systems, cloud computing infrastructures, Internet of Things (IoT) devices, and mobile broadband services has significantly increased global energy consumption. Modern communication networks contribute substantially to carbon emissions due to the continuous operation of base stations, data centers, communication equipment, and networking devices. As the demand for high-speed connectivity continues to rise, the development of environmentally sustainable communication systems has become a critical research priority. Green Communication Technologies (GCT) have emerged as an innovative approach for reducing energy consumption, minimizing carbon footprints, and improving the overall sustainability of communication infrastructures. These technologies incorporate energy-efficient network architectures, intelligent resource management, renewable energy integration, artificial intelligence-driven optimization, and green hardware design. This paper presents a comprehensive study of Green Communication Technologies and proposes an Artificial Intelligence-Based Green Communication Framework (AI-GCF) that integrates machine learning, energy-aware networking, dynamic resource allocation, and renewable energy management. Performance evaluation demonstrates significant improvements in energy efficiency, network sustainability, operational cost reduction, and carbon emission mitigation compared with conventional communication systems. The findings suggest that Green Communication Technologies will play a crucial role in achieving sustainable digital transformation and supporting future 6G communication ecosystems.