The present study aimed to model the impact of AI-based advertising personalization on customer loyalty in Iranian digital brands. Given the expansion of data-driven technologies and the increasing use of intelligent algorithms in analyzing consumer behavior, this study examined the role of data-drivenness, personalization algorithms, intelligent content design, user experience, and perceived value in the formation of customer loyalty. The research was applied and conducted using a mixed exploratory method. In the qualitative part, the initial framework of the model was conducted through semi-structured interviews and data analysis using MaxQDA software. The results of the interview analysis led to the identification of 9 main categories and 26 subcategories, which formed the initial framework of the research model. In the quantitative part, the conceptual model was tested with data from 348 customers of digital brands and with the help of SmartPLS software. The results showed that all the path coefficients between the components were positive and significant, and the chain of influence from data-centricity to customer loyalty was continuous and reinforcing. Also, the overall fit index of the model (GOF=0.62) indicated the favorable fit of the proposed model. The findings indicate that AI-based advertising personalization enhances customer loyalty by improving user experience and increasing perceived value and the role of trust and data transparency in the effectiveness of this process is of particular importance. From a management perspective, investing in data-driven infrastructure, developing more accurate personalization algorithms, and designing adaptive content can help increase advertising efficiency and enhance customer loyalty.