Abstract
This article explores the intersection of artificial intelligence (AI) and marketing technologies (MarTech) by conducting a comprehensive bibliometric analysis. The aim is to identify dominant research themes, key contributors, and major gaps in the existing literature. MarTech is conceptualised as a system of digital tools that enables marketing transformation. Scopus and Web of Science were used to collect records. Following a preliminary comparison, the final analytical corpus of peer-reviewed scientific publications (n=492) was drawn solely from Scopus. The study is based on a dataset from 1987 to 2025. Using Biblioshiny, the analysis examined publication dynamics, citation patterns, co-authorship networks, and thematic clusters. The results indicate consistent growth in scholarly attention, with an annual publication increase of 7.39 % across the full period and 36.53 % between 2015 and 2025. Five primary thematic clusters were identified: (1) AI-Marketing Core and Innovation, this cluster acts as a motor theme, integrating innovation, AI applications, and marketing outcomes, and providing conceptual and methodological scaffolding for the field; (2) Technology Adoption, functioning as a basic theme, it connects sources of innovation with market outcomes; (3) Market Applications and Digital Commerce, this cluster reflects the operationalisation of value in commerce and digital marketing, exhibiting high centrality and moving towards motor-theme status; (4) Perception and Human-Centred Factors, representing a niche but strategically important human perspective; it moderates the relationship between adoption and outcomes. (5) Generative Artificial Intelligence (e.g., ChatGPT), this is the most emerging stream, acting as an accelerator for innovation, adoption, and applications, while simultaneously elevating the importance of quality, safety, and ethics. The United States, India, and China lead in publication volume, while the United Kingdom, France, and Australia demonstrate the highest citation impact. Despite the growing literature base, theoretical fragmentation persists, and limited studies address the ethical, social, and emotional implications of AI in marketing.