Bence Varga

AI is rapidly reshaping e-commerce. Product discovery is no longer driven only by human shoppers using search filters—it is increasingly influenced by AI assistants, recommendation engines, and autonomous shopping agents. In this new reality, the quality and structure of product data determine whether a product is even considered by these systems.

This session explores how brands and retailers can transform traditional product catalogs into AI-ready product data ecosystems that power search, recommendations, and emerging agentic commerce scenarios.

Drawing on the experience of Icecat, one of the world’s largest product content syndication platforms, the talk will showcase how structured product content, standardized specifications, and automated enrichment enable scalable e-commerce operations and better digital shelf performance. Icecat currently helps brands manage and distribute structured product content globally, ensuring consistency and discoverability across channels. 

The session will also share insights from recent Icecat initiatives and webinars around AI-driven product content creation and automation, including how generative AI can produce product descriptions, bullet points, translations, and SEO-optimized content at scale. 

Finally, we will look ahead at the impact of AI shopping agents, which increasingly rely on structured product data to select and recommend products. Brands with incomplete or poorly structured product information risk being invisible to these emerging commerce interfaces.