Does AI-Assisted Design Undermine Market Value? The Influence of Design Source, Style, and Campaign Duration

Abstract

Against the backdrop of the rapid advancement of artificial intelligence technologies, traditional design value assessment systems based on creative input are facing new challenges. This study aims to examine the effects of design source (human-designed design vs. AI-assisted design), design style (commercial style vs. AI-native style), and campaign duration on the value assessment of design works in the AI era. Drawing on a real e-commerce platform context, the study conducts empirical analyses through two multifactor experiments. Experiment 1 adopts a 2 × 5 mixed experimental design to compare the value assessment performance of human-designed and AI-assisted design works across different campaign durations. Experiment 2 further introduces the variable of design style and employs a 2 × 2 × 5 three-factor experimental design to investigate the interaction effects among design source, design style, and campaign duration. The findings indicate that AI-assisted design demonstrates significant efficiency advantages in terms of time and cost. However, regarding value assessment indicators such as number of clicks, click-through rate (CTR), conversion rate (CVR), and sales performance, AI-assisted design performs comparably to human-designed design overall. Different design styles exhibit stage-specific differences: commercial style is more effective in attracting user attention and promoting conversion during the early stage of campaigns, whereas AI-native style gradually demonstrates higher conversion efficiency and cost advantages in the middle and later stages. In addition, the value assessment of design works exhibits significant temporal dynamics, with advertising performance reaching a relatively optimal level during the middle stage of campaign deployment. The study finds that AI significantly reduces creative input without weakening the market performance of design works, providing new evidence for understanding the input–outcome relationship in design value. The study also offers practical insights for enterprises seeking to optimize collaborative creation strategies between AI and human designers. The study finds that AI significantly reduces creative input without weakening the market performance of design works, providing new evidence for understanding the input–outcome relationship in design value. The study also offers practical insights for enterprises seeking to optimize collaborative creation strategies between AI and human designers.