How AI is redefining product discovery
This resource outlines how AI is changing shopper behavior, and how brands must adapt.
About the guide
Today’s shopping journey doesn’t always begin with a search bar—it starts with a conversation.
With tools like ChatGPT and Perplexity emerging as digital shopping assistants, ecommerce brands are facing a new challenge: making sure their product data is not only visible, but understandable to AI. This shift from traditional SEO to generative engine optimization (GEO) means your product listings need to do more than rank—they need to speak the language of intelligent agents.
This guide breaks down what’s happening, what’s coming next, and how your business can stay visible as AI transforms the buyer journey. This resource provides the learnings you need to stay competitive:
- How shopper-to-merchant discovery is evolving into agent-to-agent commerce
- Why structured, enriched product data is the new storefront in an AI-first world
- What brands must do today to stay visible as AI tools replace traditional search
- The critical role of product content in AI-driven checkout and recommendation flows
- How to assess whether your catalog is AI-ready
Download our guide, “How AI is redefining product discovery,” and start preparing your business for the next era of ecommerce.
Frequently asked questions
What is AI product discovery?
AI product discovery refers to using artificial intelligence — often including machine learning, natural-language processing, and data analytics — to help businesses recommend, surface, and offer products to customers. Rather than relying solely on manual categorization, search, and human curation, AI product discovery enables personalized, intent-driven, data-backed product suggestions and search results.
How is AI changing the traditional product discovery process for ecommerce brands?
With AI, product discovery becomes faster, more scalable, and continuously evolving. AI can process huge volumes of structured and unstructured data (like customer behavior, reviews, search queries) to detect trends, anticipate customer needs, and deliver personalized product recommendations — dramatically speeding up research, reducing reliance on manual tagging, and helping retailers stay competitive in an AI-driven retail landscape.
What benefits does AI-powered product discovery bring for businesses and customers?
For businesses, AI product discovery can reduce time-to-market, improve product–market fit, and enable more efficient ideation and catalog management. For customers, it delivers more relevant, personalized shopping experiences — making it easier to find products that match their needs and preferences without sifting through irrelevant search results.
What should companies do to prepare their catalogs for AI-driven product discovery?
To make a catalog “AI-ready,” companies should ensure their product data is structured, enriched, and contains clear, standardized metadata. Because AI tools rely on quality data to interpret customer intent and deliver accurate recommendations, well-organized product descriptions, categories, attributes, and contextual info will improve visibility and performance under AI-powered discovery systems.