AI in Analyzing Audience Responses to Contemporary Graphic Design

The purpose of this study is to investigate the potential utilization of artificial intelligence (AI) in relation to the analysis of audience responses to current graphic design. Using AI tools such as eye-tracking technology, sentiment analysis, and machine learning algorithms, the paper investigates how different visual elements, including color schemes, layouts, typography, and interactivity affect visitor engagement and emotional reactions. A mixed-method, evidence-based approach incorporating a range of designs and a FER+ (Facial Expression Recognition Plus) model that aggregated and mapped emotional and behavioral data was used. In summary the results effectively demonstrate how designers can enhance the effectiveness of their designs in real-time based on insights into user engagement with visual aspects, which was enabled by FER +. This study notes a possibility of a change in the perception of graphic design and the practice of graphic design may change because of AI, in a methodical and data driven way, with a practical guide to the fundamentals of visual communication.