Generative AI and the Transformation of Modern Commerce

Abstract

Generative Artificial Intelligence (Generative AI or GenAI) has emerged as one of the most consequential technological developments shaping contemporary commerce. Unlike earlier forms of automation that primarily executed predefined rules, generative AI systems can produce text, images, audio, video, software code, product descriptions, recommendations, and other forms of content. Their integration into commercial activities is consequently transforming how firms communicate with customers, develop products, conduct marketing, manage operations, analyse information, and make strategic decisions. This research paper examines the role of generative AI in transforming modern commerce from theoretical, conceptual, and empirical perspectives. It focuses particularly on e-commerce, consumer behaviour, digital marketing, customer service, sales, supply-chain management, accounting, finance, and strategic management.
The paper argues that generative AI is changing commerce at three interconnected levels: operational efficiency, customer interaction, and business-model transformation. At the operational level, generative AI can automate content production, customer support, documentation, coding, knowledge management, and routine analytical tasks. At the customer level, AI-powered shopping assistants can provide personalized recommendations, conversational product discovery, comparison, and decision support. At the strategic level, generative AI is contributing to the emergence of new forms of digital commerce in which AI systems may increasingly mediate product discovery and, potentially, purchasing decisions.
The transformation is accompanied by significant challenges. Generative AI can produce inaccurate or fabricated information, reproduce biases, create intellectual-property concerns, expose confidential data, and increase cybersecurity and privacy risks. Its use may also alter competitive dynamics by lowering some barriers to entry while simultaneously increasing the importance of proprietary data, computing infrastructure, distribution channels, and technological capabilities. Recent OECD analysis suggests that the competitive consequences of AI are highly context-dependent and influenced by firms' size, capabilities, access to data and other enabling inputs.