Main Article Content
Abstract
Artificial intelligence has become an increasingly important topic in digital marketing research, particularly due to the rapid development of machine learning, big data analytics, personalization, chatbots, generative AI, and digital commerce. This study aims to map the scientific development of research on artificial intelligence and digital marketing using bibliometric analysis. Bibliographic data were collected from the Scopus database using the search string TITLE-ABS-KEY (“artificial intelligence” AND “digital marketing”). After applying filters for publication year, document type, language, and publication stage, 148 journal articles published between 2020 and 2024 were included in the final dataset. The data were analyzed using Biblioshiny, the web-based interface of the bibliometrix package in RStudio. The findings show that research on artificial intelligence and digital marketing has grown rapidly, with an annual growth rate of 56.51%. The number of publications increased from 12 articles in 2020 to 72 articles in 2024. The most productive source was the Journal of Digital and Social Media Marketing, while the most globally cited document was Dwivedi et al. (2021), with 1,744 citations. Keyword analysis shows that artificial intelligence, digital marketing, machine learning, commerce, social media, big data, and deep learning are dominant themes. The thematic map and co-occurrence network indicate that artificial intelligence and digital marketing form the core conceptual structure of the field, while ChatGPT, SEO, deep learning, and digital transformation represent specialized or emerging themes. This study contributes to the literature by providing a comprehensive bibliometric overview of AI and digital marketing research and identifying future directions related to generative AI, personalization, consumer trust, privacy, and AI-driven marketing performance.
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