GENERATIVE ARTIFICIAL INTELLIGENCE IN E-COMMERCE: ECONOMIC VALUE FORMATION AND TRANSFORMATION OF PLATFORM MODELS

Abstract

This article examines the impact of generative artificial intelligence (GenAI) on electronic commerce, focusing on the creation of economic value and the evolution of platform models. The topic's relevance is determined by the rapid diffusion of GenAI tools in digital trade, where they are having an increasingly significant impact on product search, content creation, personalisation, seller support and consumer interaction. This study aims to summarise the theoretical and practical foundations of GenAI implementation in e-commerce, identifying the key mechanisms through which it generates economic value and reshapes platform-based market models. Methodology. The research is based on a methodology that includes theoretical generalisation, systematisation, comparative analysis, case studies and content analysis of academic publications, institutional reports and official corporate materials. This approach enables the micro-level effects of GenAI tools to be connected with broader changes in the architecture of digital commerce. Results. The study shows that generative artificial intelligence in e-commerce should not be viewed as a collection of standalone automation tools. Its economic significance is revealed through several interconnected mechanisms, including reducing information asymmetry, lowering transaction costs, improving the quality and scalability of commercial content, enabling stronger personalisation and giving sellers broader access to advanced digital tools. Drawing on examples from Amazon, Alibaba, Vinted and Shopify, the article illustrates how GenAI is transforming the role of digital platforms from passive intermediaries to active participants in value creation. At a macroeconomic level, the adoption of GenAI is linked to increased productivity, altered competitive dynamics, and new opportunities for small and medium-sized enterprises. However, it also poses growing risks such as market concentration, algorithmic opacity, and unequal access to AI infrastructure. Practical implications. The obtained results may be useful for understanding how generative artificial intelligence changes the economic logic of e-commerce platforms and expands the digital capabilities of sellers, especially small and medium-sized businesses. Value / Originality. The scientific novelty of the article lies in its interpretation of generative artificial intelligence as a factor in the structural transformation of platform commerce, rather than as a mere tool of operational optimisation.