agentic ai in marketing education: toward autonomous workflow orchestration

Aria Teimourzadeh, Samantha Kakavand () and Benjamin Kakavand
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Aria Teimourzadeh: UWO - Western University [Ontario], CRIISEA - Centre de Recherche sur les Institutions, l'Industrie et les Systèmes Économiques d'Amiens - UR UPJV 3908 - UPJV - Université de Picardie Jules Verne
Samantha Kakavand: CRIISEA - Centre de Recherche sur les Institutions, l'Industrie et les Systèmes Économiques d'Amiens - UR UPJV 3908 - UPJV - Université de Picardie Jules Verne, CERM ESC Amiens
Benjamin Kakavand: CRIISEA - Centre de Recherche sur les Institutions, l'Industrie et les Systèmes Économiques d'Amiens - UR UPJV 3908 - UPJV - Université de Picardie Jules Verne, School of Business [Kitchener, Ont.] - Conestoga College [Kitchener, Ont.]

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Abstract: Artificial intelligence (AI) is reshaping marketing practice and consequently marketing education. While prior pedagogical research has examined traditional AI tasks and more recently generative AI (GenAI) in marketing education, limited attention has been devoted to the emerging paradigm of agentic AI. This requires instructors and students to move from content creation toward system design, process orchestration and execution of marketing tasks using autonomous AI agents. This paper introduces a novel workflow automation assignment that integrates agentic AI into marketing education. We conceptualize agentic AI for marketing education, distinguish it from traditional and generative AI and develop hypotheses regarding its impact on student satisfaction, perceived learning, and engagement in marketing process automation. In this research, a survey was conducted to measure the teaching effectiveness and overall satisfaction of graduate level marketing students (n = 71) in a French university. The evidence suggests that the proposed assignment using n8n platform has positive outcomes in students' learning experience and engagement.

Date: 2026-04-22
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Published in Marketing Education Review, 2026, pp.1-18. ⟨10.1080/10528008.2026.2659869⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05610520

DOI: 10.1080/10528008.2026.2659869

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