A Study on the Reinterpretation and Expansion of Creative Expression Formats in AI Video Advertising

다국어 초록 (Multilingual Abstract)

The rapid advancement of generative artificial intelligence (AI) has reshaped video advertising by shifting creative production from manual craftsmanship to algorithmic collaboration. Early AI-generated advertisements were limited to sequential image generation with minimal narrative coherence, but recent developments in multimodal systems have enabled cinematic continuity, emotional expression, and character stability. This study examines how advertising expression formats have evolved in this context by comparing 20 traditional and 20 AI-generated video advertisements.
A mixed-method analysis—combining qualitative content evaluation and quantitative frequency comparison—was conducted to classify six expressive formats: storytelling, character-based, reversal, metaphorical, exaggerated, and emotional types. The results show that AI-generated advertisements increasingly emphasize storytelling and emotional engagement, while metaphor and exaggeration appear less frequently. These shifts suggest that generative AI strengthens narrative coherence and affective immersion but continues to face limitations in producing abstract or humor-based expressions. Qualitative analysis further identifies three adaptive creative types—Inherited, Transformed, and Fusion—that illustrate how AI reinterprets or hybridizes traditional expressive structures.
The findings indicate that generative AI expands rather than replaces human creativity, giving rise to a hybrid model of authorship in which human intention and algorithmic generation operate jointly. This study contributes a conceptual framework for understanding the expressive transformation of video advertising in the AI era and highlights the growing importance of AI literacy, prompt engineering, and ethical considerations for future creative practice.