The rapid evolution of wireless communication systems has introduced unprecedented demands for higher data rates, enhanced coverage, lower latency, and improved energy efficiency. Conventional wireless communication networks often experience challenges related to signal attenuation, multipath fading, interference, and coverage limitations, particularly in dense urban environments and indoor scenarios. Intelligent Reflecting Surface (IRS) technology has emerged as a revolutionary solution capable of transforming traditional wireless environments into programmable and adaptive communication ecosystems. An IRS consists of a large number of passive reflecting elements that can dynamically manipulate electromagnetic wave propagation by adjusting signal phase, amplitude, and reflection characteristics. This capability enables significant improvements in signal quality, spectral efficiency, coverage enhancement, and energy utilization. This paper presents a comprehensive study of Intelligent Reflecting Surface technology and its applications in next-generation wireless networks. Furthermore, an AI-Assisted Intelligent Reflecting Surface Framework (AI-IRSF) is proposed to optimize wireless communication performance through adaptive beam steering, intelligent signal reflection, and machine learning-based resource management. Simulation analysis demonstrates substantial improvements in signal strength, network throughput, coverage reliability, and energy efficiency compared with conventional communication architectures. The study concludes that IRS technology will become a fundamental component of future 6G communication infrastructures and smart wireless environments.

Keywords— Intelligent Reflecting Surface, Wireless Networks, 6G Communication, Smart Radio Environment, Artificial Intelligence, Beamforming, Energy Efficiency, Signal Optimization.