Mapping Two Decades of Evolution of Artificial Intelligence and Machine Learning in Digital Marketing and Digital Promotion to Determine the Current Direction: A Systematic Review Using Bibliometrics [Dataset]

Abstract

The past two decades have seen a significant rise in research exploring the applications of artificial intelligence (AI) and machine learning (ML) in digital marketing. This study conducts a comprehensive bibliometric analysis to map the intellectual evolution of this field, offering a longitudinal perspective across two periods: 2000–2021 and 2022–2024. Using SciMAT, the research identifies motor, transversal, emerging, and specialized themes, highlighting key topics such as recommender systems, anthropomorphism, natural language processing (NLP), and social media marketing. The findings reveal how foundational themes, like technology acceptance and user-generated content, have evolved into advanced applications focused on real-time personalization, consumer interaction, and automated decision-making. This work not only outlines the conceptual structure of AI in digital marketing but also identifies critical gaps and future research opportunities. Practical implications are provided for industry professionals, emphasizing strategies for leveraging AI-driven tools to enhance customer engagement, optimize campaigns, and foster trust. By mapping the progression of research themes, this study offers a roadmap for academics and practitioners aiming to navigate the dynamic landscape of AI in digital marketing.