Advertising is present all around us. Consumers are constantly exposed to and influenced by ads through towering billboards, social media, and various online platforms. In today’s dynamic advertising landscape, where there is a substantial shift toward online promotion, the challenge involves not only in maintaining customer engagement but also meeting a variety of consumer needs. Conventional ad campaigns primarily focus on broad goals like driving sales or brand awareness with their content that often requires significant time and resources. With the advent of generative AI and its applications that allow content generation in the form of images or videos, businesses can accelerate production of campaigns in shorter time frames. This paper puts forth a novel approach to transform customer engagement by incorporating viewers’ personal interests into curated ad creatives. The proposed approach involves understanding the customer base, achieved through segmentation. This enforces generation of personalized advertisements to individual customer preferences that boosts customer engagement and drives business growth by making advertisements more relevant and impactful. The study also introduces an agentic workflow in which tools are utilized for image generation, including background creation, image inpainting, and refinement. The process incorporates feedback-driven techniques to iteratively enhance the quality of advertisements. The generated advertisements are evaluated based on the quality, visual appeal, and relevance using metrics such as esthetic score and CLIP score, which range from 5.1 to 6.5 and 0.3 to 0.4, respectively.