From search to prompt: how generative artificial intelligence is replacing traditional product discovery in e-commerce

Анотація

The rapid integration of generative artificial intelligence technologies into digital markets makes it relevant to examine the transformation of product search mechanisms in e-commerce driven by query-oriented interaction models. The purpose of the article is to analyze the theoretical and practical aspects of replacing traditional product search systems with generative artificial intelligence technologies in e-commerce and to determine the economic prospects, advantages and limitations of AI-based search mechanisms in the digital commercial environment. The study uses a systematic literature review methodology in accordance with the PRISMA recommendations. To ensure analytical consistency and methodological validity, the study uses the AI-Commerce Integration Assessment Framework, developed by the author as an original methodological framework for assessing generative integration of artificial intelligence in e-commerce environments. The framework combines systematic literature review procedures with comparative analytical assessment tools focused on consumer interaction models, personalization mechanisms, AI readiness indicators, and digital adaptability at the platform level.

Functional limitations of traditional search systems are identified, in particular, their limited ability to adapt to context, dependence on exact keyword matching, and insufficient personalization of recommendations. It is shown that generative artificial intelligence significantly changes the logic of interaction between consumers and e-commerce platforms, transforming product search into a dialogic process based on prompts and contextual interpretation of consumer queries. It is noted that prompt-based search reduces cognitive effort, increases personalization and improves the efficiency of the digital customer experience through adaptive recommendation mechanisms that can interpret complex consumer intentions. The article considers the main areas of integration of generative artificial intelligence into e-commerce platforms, in particular, dialogic assistants, intelligent recommendation systems, predictive analytics and multimodal search technologies. A comparative analysis of the characteristics of traditional search engines and product search based on artificial intelligence revealed fundamental differences in the principles of information processing, personalization, flexibility of recommendations and models of interaction with consumers.

The implementation of AI-based search technologies has been found to create significant economic benefits for businesses, including increased conversion rates, optimized operating costs, improved customer retention, and improved data-driven decision-making. It is predicted that future e-commerce development will increasingly depend on enterprises’ ability to combine intelligent automation, ethical AI governance, and consumer trust within personalized digital ecosystems.