  Artificial Intelligence Generated Content (AIGC) Services have significant
potential in digital content creation. The distinctive abilities of AIGC, such
as content generation based on minimal input, hold huge potential, especially
when integrating with semantic communication (SemCom). In this paper, a novel
comprehensive conceptual model for the integration of AIGC and SemCom is
developed. Particularly, a content generation level is introduced on top of the
semantic level that provides a clear outline of how AIGC and SemCom interact
with each other to produce meaningful and effective content. Moreover, a novel
framework that employs AIGC technology is proposed as an encoder and decoder
for semantic information, considering the joint optimization of semantic
extraction and evaluation metrics tailored to AIGC services. The framework can
adapt to different types of content generated, the required quality, and the
semantic information utilized. By employing a Deep Q Network (DQN), a case
study is presented that provides useful insights into the feasibility of the
optimization problem and its convergence characteristics.
