 Artificial Intelligence and Machine Learning: Exploring drivers, barriers, and future developments in marketing managementGioia Volkmar, Peter M. Fischer and Sven Reinecke Journal of Business Research, 2022, vol. 149, issue C, 599-614 Abstract: Companies neither fully exploit the potential of Artificial Intelligence (AI), nor that of Machine Learning (ML), its most prominent method. This is true in particular of marketing, where its possible use extends beyond mere segmentation, personalization, and decision-making. We explore the drivers of and barriers to AI and ML in marketing by adopting a dual strategic and behavioral focus, which provides both an inward (AI and ML for marketers) and an outward (AI and ML for customers) perspective. From our mixed-method approach (a Delphi study, a survey, and two focus groups), we derive several research propositions that address the challenges facing marketing managers and organizations in three distinct domains: (1) Culture, Strategy, and Implementation; (2) Decision-Making and Ethics; (3) Customer Management. Our findings contribute to better understanding the human factor behind AI and ML, and aim to stimulate interdisciplinary inquiry across marketing, organizational behavior, psychology, and ethics. Keywords: Artificial Intelligence; Machine Learning; Marketing Management; Decision- Making; Delphi Method; Ethics (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:149:y:2022:i:c:p:599-614 DOI: 10.1016/j.jbusres.2022.04.007 Access Statistics for this article Journal of Business Research is currently edited by A. G. Woodside More articles in Journal of Business Research from Elsevier |
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