Artificial intelligence (AI) and machine learning (ML) in marketing: a 25-year bibliometric-TCCM synthesized mapping of trends, gaps and future research agenda

Bashar, Abu; Nyagadza, Brighton; Khan, Irfanullah; Chuchu, Tinashe

Artificial intelligence (AI) and machine learning (ML) in marketing: a 25-year bibliometric-TCCM synthesized mapping of trends, gaps and future research agenda

Bashar, Abu ORCID: https://orcid.org/0000-0003-1415-5591, Nyagadza, Brighton ORCID: https://orcid.org/0000-0001-7226-0635, Khan, Irfanullah and Chuchu, Tinashe ORCID: https://orcid.org/0000-0001-7325-8932 (2026) Artificial intelligence (AI) and machine learning (ML) in marketing: a 25-year bibliometric-TCCM synthesized mapping of trends, gaps and future research agenda. Quality & Quantity.

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Official URL: https://doi.org/10.1007/s11135-026-02696-z

Abstract

The major aim of the study is to review existing literature, conceptualize and map various future research avenues in line with integrating Artificial Intelligence (AI), Machine Learning (ML) and marketing applications. It employs bibliometric analysis, network analysis and theories, contexts, characteristics, and methodologies (TCCM) framework. Similar techniques were applied in social research studies to study and comprehensively report the existing research structure, gaps and probable studies to bridge them up. The sample data in this analysis collected from 2001 to 2025 and consists of 439 publications selected as per the criteria and used for further analysis, demonstrates the recency of research in AI, and ML in marketing applications. The results show an exponential growth in this domain and collaboration among authors throughout the world. It offers important social, practical and theoretical contributions to the evolving literature on AI, and ML in marketing applications. Originally, the study unpacked innovative development of new frameworks, impact assessment, emerging trends, identification of challenges and opportunities, cross disciplinary insights with significant advancement of effective professional practice and impactful theory development in line with AI, and ML in marketing applications.