Recently, reconfigurable intelligent surface (RIS) has been suggested as a remarkable enabler for sixth generation (6G) wireless communication with a wide range of applications ranging from just extending the coverage of sub 6 GHz communications to route around blockages in directional communications, eg, using millimeter wave (mmWave) and terahertz (THz) bands. However, RIS has numerous technical challenges to withstand its practical realizations, including network configuration, cascaded massive/passive channel estimations, and antenna phase shifts (PSs) adjustment. Besides, it opens the door for new practical optimization challenges when aided by different wireless communication systems, eg, RIS relay selection in wireless RIS relaying, user/RIS association in multiple base station (BS) multiple RIS systems, network planning, and path trajectory optimization in RIS mounted unmanned aerial vehicles (UAVs), etc. Artificial intelligence (AI) has a lot of tools that can address most of these challenges with high efficiency and low complexity. Thus, this paper aims to provide a comprehensive presentation about the state-of-the-art AI-enabled RIS-aided wireless communications, in-