AI-Driven Innovation and Optimization of Packaging Design

This study proposes a four-in-one AI-assisted model for packaging design and empirically evaluates it using 120 comparative projects. Traditional design models based on experience, templates, functionality, or imitation produce homogenized designs, long development cycles, high costs, and limited ability to meet contemporary demands for personalization, sustainability, and e-commerce. Compatibility analysis mapped AI capabilities to design needs, resulting in a model integrating data-informed generation, human–AI optimization, scalable tools, and blockchain governance. Stratified sampling and regression analyses showed that AI reduced development cycle times by up to 68.3%, doubled creative concepts, increased satisfaction by 1–1.5 points, improved adoption by 12–15 points, halved revisions, reduced costs by 36.9%, and increased ROI by 88%, with SMEs benefiting the most. The findings demonstrate AI's scalable value in packaging design through human collaboration, particularly for smaller firms, highlighting the need for improved cultural modeling, sustainability tools, and IP frameworks to support industry transformation.