Logforum | 2026
Authors: Aboumejd F.; El Oualidi M.A.; Ahlaqqach M.
DOI: 10.17270/J.LOG.001317
Journal: Logforum
Year: 2026
Publisher: Poznan School of Logistics
Document Type: Article
Open Access: All Open Access; Gold Open Access
Cited by: 0
Background: The COVID-19 pandemic triggered a sharp increase in demand for online shopping, as traditional distribution channels increasingly gave way to digital platforms in response to changing consumer behavior. This shift created a highly competitive environment for businesses seeking to enter or expand within the online market. Consequently, e-commerce logistics and postal logistics providers were compelled to adapt rapidly to meet evolving e-customers' requirements. Traditional logistics models proved inadequate, prompting scholars and practitioners to explore how emerging technologies—particularly artificial intelligence (AI)—could be integrated into existing processes to enable more adaptive and efficient approaches to urban logistics. The aim of this paper is to synthesize existing literature on AI applications in e-commerce logistics, focusing on four operational clusters: pickup and delivery, parcel sorting, address verification, and reverse logistics. Accordingly, this study provides a comprehensive state-of-the-art review of AI applications, a critical gap analysis, and actionable insights for future AI-driven innovations in e-commerce logistics. Methods: This review adopts a narrative approach, drawing on a targeted selection of relevant and recent literature published between 2019 and 2025. Key insights were identified through academic databases and analyzed to classify AI methods across selected e-commerce logistics operations. The objective is to summarize current trends, identify research gaps, and inform future research directions. Results: The review reveals that many AI methods remain underexplored or unused across several e-commerce logistics operations. In addition, multiple critical operational and performance parameters are insufficiently addressed in the existing literature. Conclusions: This study highlights significant underexplored opportunities for applying artificial intelligence in e-commerce logistics. The findings underscore the need for deeper investigation and novel AI-driven solutions to enhance the efficiency, resilience, and sustainability of e-commerce logistics systems. © 2026, Poznan School of Logistics. All rights reserved.
address verification; Artificial intelligence; e-commerce; parcel sorting; pickup and delivery; reverse logistics