  Generative artificial intelligence (GAI) has emerged as a rapidly burgeoning
field demonstrating significant potential in creating diverse contents
intelligently and automatically. To support such artificial
intelligence-generated content (AIGC) services, future communication systems
should fulfill much more stringent requirements (including data rate,
throughput, latency, etc.) with limited yet precious spectrum resources. To
tackle this challenge, semantic communication (SemCom), dramatically reducing
resource consumption via extracting and transmitting semantics, has been deemed
as a revolutionary communication scheme. The advanced GAI algorithms facilitate
SemCom on sophisticated intelligence for model training, knowledge base
construction and channel adaption. Furthermore, GAI algorithms also play an
important role in the management of SemCom networks. In this survey, we first
overview the basics of GAI and SemCom as well as the synergies of the two
technologies. Especially, the GAI-driven SemCom framework is presented, where
many GAI models for information creation, SemCom-enabled information
transmission and information effectiveness for AIGC are discussed separately.
We then delve into the GAI-driven SemCom network management involving with
novel management layers, knowledge management, and resource allocation.
Finally, we envision several promising use cases, i.e., autonomous driving,
smart city, and the Metaverse for a more comprehensive exploration.
