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Artificial intelligence as a transformation catalyst: Modeling and optimizing digital customer experience in Moroccan e-commerce
[L'intelligence artificielle comme catalyseur de transformation : Modélisation et optimisation de l'expérience client digital dans le e-commerce Marocain]

Author

Listed:
  • Mohamed Salim Thamir

    (LEG - Laboratoire d'économie et de gestion (LEG), Faculté pluridisciplinaire de Khouribga (FPK), Université Sultan Moulay Slimane (USMS), Maroc)

  • Ibtissam Lakhlili

    (LEG - Laboratoire d'économie et de gestion (LEG), Faculté pluridisciplinaire de Khouribga (FPK), Université Sultan Moulay Slimane (USMS), Maroc)

  • Aya Sehmani

    (UH2C - Université Hassan II de Casablanca = University of Hassan II Casablanca = جامعة الحسن الثاني (ar))

Abstract

Digital transformation is reshaping the e-commerce landscape in Morocco, forcing companies to strategically rethink customer experience. This study presents a critical narrative review of recent literature (2018–2025) exploring the transformative contributions of artificial intelligence (AI) in modeling online customer journeys. Our approach was based on a systematic analysis of key scientific publications, including reference articles, meta-analyses, and existing systematic reviews on this emerging field. The analytical framework developed deconstructs the relationship between AI and customer experience along several interrelated dimensions. The study first maps the theoretical applications of AI in customer experience optimization and evaluates the proposed conceptual framework to measure its impact on platform performance. It then reveals how the theoretical cultural characteristics of Moroccan consumers interact with intelligent interfaces, presenting unique design and adaptation challenges. Finally, the theoretical implementation model is tested using critical success factors documented in the emerging market literature. The results of this critical synthesis show that strategically adopting AI in the customer journey can generate dual conceptual added value: operational through process optimization and transformational through the creation of hyper-personalized contextual experiences. This study makes a significant contribution to the theoretical corpus of digital transformation in emerging market companies and offers a comprehensive conceptual framework. Its academic significance opens new perspectives for the development of cultural adaptation models for the integration of artificial intelligence technologies in the Moroccan digital environment. Keywords: Artificial intelligence, Customer experience, e-commerce, Customer journey, Digital transformation. Classification JEL: M39 Paper type: Theoretical Researc

Suggested Citation

  • Mohamed Salim Thamir & Ibtissam Lakhlili & Aya Sehmani, 2025. "Artificial intelligence as a transformation catalyst: Modeling and optimizing digital customer experience in Moroccan e-commerce [L'intelligence artificielle comme catalyseur de transformation : Modélisation et optimisation de l'expérience client ," Post-Print hal-05405390, HAL.
    • Handle: RePEc:hal:journl:hal-05405390
    DOI: 10.5281/zenodo.17821133
    Note: View the original document on HAL open archive server: https://hal.science/hal-05405390v1
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    JEL classification:

    • M39 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Other

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