A Practical Study on the Integration of AIGC into Brand Identity Design Courses

Abstract

Artificial intelligence-generated content (AIGC) is beginning to change how design students search, sketch, compare, and revise. Brand Identity Design is a good place to examine this change because the course is not only about making attractive visuals. Students must read a brand, identify its audience, turn abstract values into visual symbols, and keep a visual system coherent across different media. AIGC tools can assist with reference collection, keyword generation, moodboard exploration, preliminary logo ideas, and application mock-ups. These uses are helpful, but they do not remove the hard part of the course. Brand identity design still depends on brand understanding, semiotic awareness, aesthetic judgment, teacher feedback, and students’ own revision. Recent studies in design education suggest that generative AI works best in early ideation and visual variation, while design quality still needs human selection and refinement. Based on this view, the paper proposes a practice-oriented path for integrating AIGC into Brand Identity Design courses. The path covers pre-class research, in-class ideation, design development, presentation, reflection, and evaluation. It also introduces AI use statements, prompt logs, process portfolios, teacher review, and originality reflection as ways to control risks such as homogenization, copyright uncertainty, over-reliance, and blurred authorship. The goal is not to make AIGC the center of the course. It is to place the tool inside a guided teaching process where students still have to think, decide, and revise.