Artificial intelligence and marketing education: mapping current research and emerging patterns

Madina ALENOVA, Zhuldyz Rsaly, Monowar Mahmood, Norizan Mohd Kassim

2026

Closed access Metadata (CSL-JSON)
DOI 10.1108/et-11-2025-0936
Data confidence 85 high
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Abstract

Purpose The purpose of this study is to explore how artificial intelligence (AI) is reshaping marketing education and to assess the extent to which marketing education addresses technological transformation within education contexts. Design/methodology/approach This study uses a systematic bibliometric review to examine the intersection of AI and marketing education. In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, 801 records were retrieved from the Web of Science Core Collection database and screened, resulting in the identification of 66 relevant scholarly articles. Visualization and analytical tools such as VOSviewer, Biblioshiny and Research Rabbit were applied to identify key publication outlets, authorship patterns, co-citation networks and thematic clusters. Findings Analysis reveals rapid growth in AI-related research after 2020, with dominant themes including digital pedagogy, ethical considerations, student competencies and the integration of generative AI tools. Despite this expansion, the literature remains fragmented and primarily conceptual, lacking robust empirical evidence on learning outcomes, cross-cultural dimensions and the long-term effects of AI in marketing curricula. Originality/value This research provides a comprehensive synthesis of the literature on AI in marketing education and outlines critical directions for future inquiry. It offers insights for educators and curriculum designers seeking to align marketing programs with emerging AI-driven practices. This review further emphasizes the need for competency-based and student-centred approaches that reflect the evolving global landscape of AI-enhanced learning. However, as the research domain is at an early stage of consolidation, the findings reflect both the promise and the fragmentations at the intersection of AI and marketing education.