From analytics to empathy and creativity: Charting the AI revolution in marketing practice and education

Giulia Pavone (), Lars Meyer-Waarden () and Andreas Munzel
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Giulia Pavone: Kedge BS - Kedge Business School
Lars Meyer-Waarden: TSM - Toulouse School of Management Research - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - CNRS - Centre National de la Recherche Scientifique - TSM - Toulouse School of Management - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse
Andreas Munzel: Vlerick Business School [Leuven]

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Abstract: The rapid advancement of artificial intelligence (AI) increasingly demands an understanding of its impact on marketing practice and education. Our hybrid literature review synthesizes 312 peer-reviewed articles on AI in marketing and consumer behavior, using scientometrics and the TCCM (Theory, Context, Characteristics, Methodology) framework. We identify five research areas: human–AI interaction in services, natural language processing (NLP) and computer vision for consumer insights, AI for e-commerce and decision support, marketing automation and creativity, and AI ethics. AI's evolution is marked by a transition from analytical to empathetic and intuitive technologies like affective computing and generative AI. We highlight the changing dynamics between humans and AI, AI integration in marketing practices and education, and the transformed AI-enhanced marketing workplace. We underscore the significance of ethical considerations, the well-being of users, and the integration of generative AI tools. This review provides a comprehensive guide for forthcoming research, practical applications, and educational advancements in AI-enhanced marketing.

Keywords: marketing; hybrid literature review; ethics; consumer behaviors; artificial intelligence (search for similar items in EconPapers)
Date: 2025-01
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Published in Recherche et Applications en Marketing (English Edition), 2025, vol. 40 (n° 1), pp.92-120. ⟨10.1177/20515707241283311⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05579362

DOI: 10.1177/20515707241283311

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