AI-Driven Flexibility in Next-Generation Communication Systems A Review of Models, Confrontation, and Tomorrow’s Directions

Artificial Intelligence (AI) is changing how next-generation communication systems, such as 5G, 6G, and beyond, are designed and run. Modern networks are facing bigger challenges like handling more users, managing varying traffic, using spectrum efficiently, dealing with different types of devices, and maintaining good service quality. Traditional fixed designs are not keeping up with these changes. This paper gives a detailed look at how AI makes communication systems more flexible in several areas like network structure, spectrum use, device compatibility, service delivery, protocol setup, security, and real-time choices. By using techniques like machine learning, deep learning, and reinforcement learning, communication systems can automatically adjust, predict usage, manage resources on the fly, and react to issues quickly. The paper covers AI approaches used in Networking defined by software’s, Network Function Virtualization (NFV), cognitive radio, or intelligent edge computing. It also shares examples where AI has greatly improved performance, reliability, and efficiency in actual networks. Important challenges such as privacy, understanding AI decisions, extra computing needs, and setting standards are discussed. Finally, the paper suggests future research areas to create fully autonomous and flexible communication systems. This review helps researchers and professionals build smarter, more adaptable, and sustainable networks for the future digital world. [2,4,5,6,12,16].