Artificial intelligence in marketing research and future research directions: Science mapping and research clustering using bibliometric analysis

Abstract The marketing environment has experienced significant advancements due to the transformative influence of technologies such as artificial intelligence, data analytics, decision sciences, and robotics. These innovations have entirely reshaped the fundamental marketing principles as we know them. This study uses bibliometric analysis to conduct a systematic literature review of research on Artificial Intelligence (AI) in marketing and provides future research directions. It also aims to identify the most influential and productive contributors and progression of research on AI in marketing. The bibliographic data of 317 documents on artificial intelligence in marketing research was extracted from the Scopus database. The bibliometric analysis is performed to comprehensively understand the most influential and productive articles, authors, sources, and the top contributing countries and institutions towards the discipline of AI in marketing research. The results and the publication trend show exponential growth yearly in AI in marketing research. Furthermore, it discovered four main thematic clusters: Data mining and deep learning in decision support systems, big data and generative AI in marketing, AI‐enabled commerce, and chatbots and marketing Tech that represent the recent research being carried out under AI in marketing. The trending topics recognized are marketing algorithms for decision‐making, AI‐enabled marketing, the Internet of Things (IoT) and marketing, natural language processing and customer service, robotic services, and chatbots. This study also emphasizes potential future research areas, building upon the established thematic clusters.