Artificial Intelligence Competencies and Marketing: A Bibliometric Approach

This paper employs statistical evaluation to investigate how AI competencies interact with marketing. The goal is to identify modern research, highlight flaws, and summarize implications for further research, which means improving one’s understanding of transitional subjects. Explanatory methods and the application of big data principles are used to analyze a data collection of 2,180 daybooks acquired by a network of knowledge and an automated database. Moreover, the fact-finding procedure is aimed towards twofold: first, graphic investigation using R Studio focuses on identifying productive periods, authors, countries, and journals; second, correlation-based keyword analysis using VOSviewer helps identify thematic clusters along with prominent keywords. A few of the notable findings include the title of the nation, journals, and well-known authors, in addition to the emerging educational pathways. This examination refines upcoming trends and research themes through network analysis, recognizing five distinctive groups: i) "AI-based value co-creation and marketing," ii)"AI and supply chain," iii) "Artificial intelligence and digital culture," iv) "AI and strategic thinking," and v)"AI-powered data intelligence and analysis." By clarifying the association between AI competencies, innovation, and marketing, this study contributes to the field's growth and theoretical advancements. This understanding is important for policymakers.