 A Framework for Collaborative Artificial Intelligence in MarketingMing-Hui Huang and Roland T. Rust Journal of Retailing, 2022, vol. 98, issue 2, 209-223 Abstract: We develop a conceptual framework for collaborative artificial intelligence (AI) in marketing, providing systematic guidance for how human marketers and consumers can team up with AI, which has profound implications for retailing, which is the interface between marketers and consumers. Drawing from the multiple intelligences view that AI advances from mechanical, to thinking, to feeling intelligence (based on how difficult for AI to mimic human intelligences), the framework posits that collaboration between AI and HI (human marketers and consumers) can be achieved by 1) recognizing the respective strengths of AI and HI, 2) having lower-level AI augmenting higher-level HI, and 3) moving HI to a higher intelligence level when AI automates the lower level. Implications for marketers, consumers, and researchers are derived. Marketers should optimize the mix and timing of AI-HI marketing team, consumers should understand the complementarity between AI and HI strengths for informed consumption decisions, and researchers can investigate innovative approaches to and boundary conditions of collaborative intelligence. Keywords: Artificial intelligence; Collaborative AI; Collaborative intelligence; Augmentation; Replacement (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:jouret:v:98:y:2022:i:2:p:209-223 DOI: 10.1016/j.jretai.2021.03.001 Access Statistics for this article Journal of Retailing is currently edited by A. Roggeveen More articles in Journal of Retailing from Elsevier |
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