EXPLORING THE AI EDGE: CONCEPTUAL FRAMEWORKS IN THE EVOLUTION OF E-COMMERCE STRATEGIES AND DIGITAL MARKETING
TL;DR
It is shown that passive data accumulation does not directly contribute to brand recall unless it is combined with active ML processing and interactive consumer platforms, and a conceptual framework of the AI edge in e-commerce and digital marketing is synthesised.
Abstract
Artificial intelligence (AI) is changing modern e-commerce and digital marketing as organisations move from simple automation to data-driven strategic execution. Following PRISMA guidelines, this paper systematically reviews peer-reviewed studies published between 2024 and 2026 to examine the operational and brand-equity impacts of machine learning (ML), generative AI and big data analysis across different retail business models. The review shows that passive data accumulation does not directly contribute to brand recall unless it is combined with active ML processing and interactive consumer platforms. High-volume retailers use AI to forecast demand and increase supply chain velocity, while luxury and lifestyle brands use it for visual search, security architecture and hyper-personalised customer experiences. Generative AI further creates a multi-agent co-creation ecosystem involving employees, customers and autonomous systems. Despite these performance improvements, organisational deployment remains constrained by algorithmic bias, content fabrication, data privacy concerns and edge–cloud deployment costs. The paper synthesises these findings into a conceptual framework of the AI edge in e-commerce and digital marketing.