From Data-Driven to Augmented Management: Artificial Intelligence in E-Commerce Customer Journey Modeling in Morocco

This narrative review examines the transformation of management practices in Moroccan e-commerce through artificial intelligence integration for customer journey modeling. Drawing on systematic analysis of seventy-twoscientific publications from 2019 to 2024, this study explores the paradigmatic transition from data-driven to augmented management. The analysis reveals three principal dimensions: technological evolution of customer journey modeling transitioning from traditional statistical methods to advanced machine learning algorithms; contextual specificities of the Moroccan market characterized by accelerated post-COVID digitalization and hybrid purchasing behaviors; managerial implications including reconfiguration of decision-making competencies and emergence of hybrid data-manager roles. Results identify critical challenges including organizational resistance observed in sixty-seven percent of studied cases, ethical concerns, and inadequacy of international frameworks. Comparative analysis with South Africa, Egypt, and Brazil reveals shared challenges but distinctive implementation pathways. This research proposes an integrative conceptual framework for augmented management adapted to emerging economies and presents a five-stage maturity model for digital transformation. Keywords: Artificial intelligence; Customer journey; E-commerce; Augmented management; Digital transformation; Morocco