The rise of artificial intelligence (AI) has ushered in a new era where many business functions are increasingly shaped by algorithmic decision-making, automation, and data-driven insights. Artificial superintelligence holds great promise to transform marketing practices. This study was designed to identify key performance indicators, analyze their interactions, and examine citation content. Due to the rapid growth of AI and its expanding influence on buyer behavior, the current literature in this field is fragmented and multidisciplinary. It also lacks a cohesive overview. Therefore, it is crucial to identify knowledge gaps to clearly define the scope and contribution of this research in addressing these issues. The pragmatic approach enabled the researcher to systematically gather citation data from the Scopus database. The data were processed following the PRISMA standard protocol. Ultimately, 1,350 studies were included in the bibliometric analysis and examined using RStudio and VOSviewer software. In terms of performance, the final results highlighted the most influential documents, authors, journals, organizations, and countries. Additionally, analyzing interaction patterns among these elements and reviewing the data provided valuable insights into AI’s role in shaping buyer behavior and the future of artificial superintelligence. It is also important to note that the literature in this area mainly focuses on six major themes: e-commerce platforms and digital purchasing behavior; AI-based models for predicting purchase intent and guiding consumer actions; digital trust and consumer experience with intelligent agents; deep learning and neural networks for modeling and managing consumer behavior; neuromarketing and cognitive analysis using neurobehavioral signals; and buyer attitudes, satisfaction, and demographic factors in the age of AI.