Artificial intelligence in sales research: Identifying emergent themes and looking forward

Viktor Jarotschkin, Mostofa Wahid Soykoth and Nawar N. Chaker

Journal of Business Research, 2025, vol. 198, issue C

Abstract: The rapid advancement of artificial intelligence (AI) in sales lends promising grounds for sales practice and academic research. Using a two-study, multi-method approach to examining the literature, this study provides a detailed overview of the current position of AI in sales research. We consider how AI is studied as a substantive topic and how it is used as an analytical tool to study sales phenomena. Study 1 uses bibliometric analysis to provide a “horizontal” view of the literature by uncovering the network characteristics and structure. Study 2 uses topic modeling based on Latent Dirichlet Allocation (LDA)—a machine learning (ML) approach—to offer a “vertical” view of the literature by plunging into the contents of each article to reveal five important themes that characterize the state of the literature. We also offer a future research agenda to guide more studies that integrate AI and sales.

Keywords: Artificial intelligence; Sales; Machine learning; Topic modeling; Bibliometric analysis; Literature review (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:198:y:2025:i:c:s0148296325002061

DOI: 10.1016/j.jbusres.2025.115383

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