Artificial intelligence (AI) and machine learning technologies are increasingly gaining importance for accurately analyzing consumer behavior and delivering customized advertising content within digital marketing strategies. A rapid increase has been observed in the recent research concerning machine learning and artificial intelligence in the digital marketing literature. This research aims to strategically and thematically present a scientific map of publications using digital marketing, machine learning, and artificial intelligence. For this purpose, the bibliometric analysis method, one of the quantitative research methods, has been used in the study. The data used in this study were obtained from the Scopus database, covering 2007-2023. The gathered data were analyzed and visualized using the Bibliometrix analysis program with its web interface provider, Biblioshiny. A total of 171 publications were reached in the research. There has been an increase in publications since the year 2017. The journal with the most publications is Communications in Computer and Information Science. The most frequently used words are artificial intelligence, marketing, machine learning, commerce, digital marketing, learning systems, machine learning, decision-making, e-learning, and deep learning. Moreover, a co-occurrence network exists between machine learning, marketing, artificial intelligence, digital marketing, and commerce. The highest level of publication collaboration has occurred between the United States of America (USA) and India. The involvement of numerous authors from diverse journals suggests that the topic attracts attention from multiple fields. This study offers an extensive bibliometric analysis to visualize the academic publication landscape of digital marketing, machine learning, and artificial intelligence. Subsequent research is expected to emphasize the real-world applications of these technologies in various industries. The visualization of the data obtained from the analyses in this research holds significance for guiding future studies in this area.