AI ADOPTION IN E-COMMERCE: A LITERATURE & BIBLIOMETRIC REVIEW

Artificial Intelligence (AI) has revolutionized e-commerce by enhancing customer experience, operational efficiency, and data-driven decision-making. As AI adoption continues to expand, understanding its research landscape, key trends, and challenges is crucial. However, existing studies primarily focus on specific AI applications, such as recommendation systems and chatbots, while a comprehensive bibliometric analysis of AI adoption trends remains limited. Additionally, research gaps exist in understanding regional adoption disparities, ethical concerns, and regulatory challenges in AI-driven e-commerce. This study aims to analyse AI adoption trends in e-commerce using bibliometric techniques, identify key research themes, and propose future research directions. A systematic bibliometric review was conducted on Scopus-indexed research articles (2004–2024) using the PRISMA framework for systematic screening. Biblioshiny (R-based tool) and VOSviewer were utilized to analyse citation networks, keyword co-occurrence, and thematic clusters. The findings indicate a significant rise in AI research in e-commerce since 2018, with China, India, and the U.S. leading in publications. Four key research themes emerged: customer experience and personalization, operational efficiency and supply chain, fraud detection and cybersecurity, and ethical AI and regulatory challenges. While AI adoption continues to advance, challenges such as data privacy concerns, algorithmic bias, and regulatory gaps remain critical. This study provides a structured bibliometric review of AI adoption trends in e-commerce and highlights key research gaps and emerging areas, such as Generative AI, sustainable e-commerce, and ethical AI governance. The findings offer valuable insights for researchers, policymakers, and businesses, guiding the strategic implementation of AI in global e-commerce.