  Reconfigurable intelligent surface (RIS) is an emerging meta-surface that can
provide additional communications links through reflecting the signals, and has
been recognized as a strong candidate of 6G mobile communications systems.
Meanwhile, it has been recently admitted that implementing artificial
intelligence (AI) into RIS communications will extensively benefit the
reconfiguration capacity and enhance the robustness to complicated transmission
environments. Besides the conventional model-driven approaches, AI can also
deal with the existing signal processing problems in a data-driven manner via
digging the inherent characteristic from the real data. Hence, AI is
particularly suitable for the signal processing problems over RIS networks
under unideal scenarios like modeling mismatching, insufficient resource,
hardware impairment, as well as dynamical transmissions. As one of the earliest
survey papers, we will introduce the merging of AI and RIS, called AIRIS, over
various signal processing topics, including environmental sensing, channel
acquisition, beamforming design, and resource scheduling, etc. We will also
discuss the challenges of AIRIS and present some interesting future directions.
