In this article, we propose artificial intelligence (AI) enabled unmanned aerial vehicle (UAV) aided wireless networks (UAWN) for overcoming the challenges imposed by the random fluctuation of wireless channels, blocking and user mobility effects. In UAWN, multiple UAVs are employed as aerial base stations, which are capable of promptly adapting to the randomly fluctuating environment by collecting information about the users' position and tele-traffic demands, learning from the environment and acting upon the satisfaction level feedback received from the users. Moreover, AI enables the interaction among a swarm of UAVs for cooperative optimization of the system. As a benefit of the AI framework, several challenges of conventional UAWN may be circumvented, leading to enhanced network performance, improved reliability and agile adaptivity. As a further benefit, dynamic trajectory design and resource allocation are demonstrated. Finally, potential research challenges and opportunities are discussed.