Analysis of AIGC and Visual Communication Design Fusion Strategies

Abstract

This article conducts an in-depth exploration of the integration of AIGC (Artificial Intelligence Generated Content) and visual communication design. Firstly, it provides a detailed analysis of the technical characteristics of AIGC, including the core technical frameworks represented by the Generative Adversarial Network (GAN) and diffusion models, as well as its powerful creative generation ability demonstrated by the closed-loop mechanism based on "learning - genera-tion - iteration". At the same time, it points out the pain points existing in visual communication design in terms of labor costs, style innovation, design efficiency, etc., and expounds on the complementarity between the two. Then, it delves into the necessity of the integration of the two. AIGC can not only significantly shorten the design cycle and improve design efficiency through automated processes, but also stimulate designers' innovative thinking and realize an innovative mode of "human-machine collaboration". Moreover, it performs excellently in meeting users' personalized needs, and can generate personalized design content according to user portraits and usage scenarios. Finally, through practical cases, the remarkable advantages of AIGC in practical scenarios such as the intelligent construction of brand visual systems and the design of dynamic and immersive media are demonstrated.