  Semantic communication (SemCom) is expected to be a core paradigm in future
communication networks, yielding significant benefits in terms of spectrum
resource saving and information interaction efficiency. However, the existing
SemCom structure is limited by the lack of context-reasoning ability and
background knowledge provisioning, which, therefore, motivates us to seek the
potential of incorporating generative artificial intelligence (GAI)
technologies with SemCom. Recognizing GAI's powerful capability in automating
and creating valuable, diverse, and personalized multimodal content, this
article first highlights the principal characteristics of the combination of
GAI and SemCom along with their pertinent benefits and challenges. To tackle
these challenges, we further propose a novel GAI-integrated SemCom network
(GAI-SCN) framework in a cloud-edge-mobile design. Specifically, by employing
global and local GAI models, our GAI-SCN enables multimodal semantic content
provisioning, semantic-level joint-source-channel coding, and AIGC acquisition
to maximize the efficiency and reliability of semantic reasoning and resource
utilization. Afterward, we present a detailed implementation workflow of
GAI-SCN, followed by corresponding initial simulations for performance
evaluation in comparison with two benchmarks. Finally, we discuss several open
issues and offer feasible solutions to unlock the full potential of GAI-SCN.
