We examine the potential feasibility of using GPT-4V, a multimodal AI, to predict an individual's likelihood of clicking on an ad image based on a detailed psychological profile ("persona") rather than just historical behavior. The analysis breaks down how GPT-4V could process ad images and extensive persona text to infer connections, noting the complexity of matching visual elements and abstract psychological traits. While recognizing GPT-4V's relevant capabilities, the discussion highlights significant challenges like reasoning opacity, potential biases, and data privacy concerns. The author concludes that while theoretically plausible, achieving reliable, scalable, and ethical predictions is currently uncertain, suggesting future research directions focusing on prompt engineering, explainability, and hybrid models.