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Artificial Intelligence Generated Content in Visual Design: Technologies, Applications, Challenges, and Future Directions

Mengxue Li¹, Siyuan Liu², Junhua Zhou³

Research on Art Design / 2026,2(1): 22−32 / 2026-04-22 21 11

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• Information:

  1. University of Shanghai for Science and Technology, Shanghai;
  2. The Hong Kong University of Science and Technology (Guangzhou), Guangzhou;
  3. Higher Education Press, Beijing

• Keywords:
  AIGC; Visual design; Generative AI; Human-AI collaboration
• Abstract: AIGC, which stands for artificial intelligence-generated content, has become a significant driver of modern visual aesthetics. Beyond image synthesis, it transforms how artists conceptualize, envision, restructure, and manage their creative process. AIGC studies changes in our lives through the means and aesthetics grounded in technicality. It first examines the current technical framework used by most generative models, such as GANs, diffusion models, text-to-image mapping, style transfer, and controllable output. The next step is discussing the main uses of AIGC in branding, advertising, UI/UX, illustration, and conceptual art. It is clear then that AIGC logic has sped up the process of thinking, turned vague notions into concrete images, and changed how words and pictures work together. It also addresses issues such as intellectual property disputes, style imitation, representational bias, and aesthetic homogenization, while reorganizing the notion of creativity. From the author’s point of view, AIGC cannot replace us entirely, but it will reconfigure our cooperation with digital tools. It all depends on how much effort is put into practicing, teaching, and administering systems concerning ethics in regard to generative technology within visual communication.
• DOI: 10.35534/rad.0201003 (registering DOI)
• Cite: Li, M. X., Liu, S. Y., & Zhou, J. H. (2026). Artificial Intelligence Generated Content in Visual Design: Technologies, Applications, Challenges, and Future Directions. Research on Art Design, 2(1), 22−32.