What Is AI Shopping? Definition and Example

AI shopping is product discovery, comparison and buying done with AI assistants. Instead of searching and opening many tabs, a buyer describes a need, such as "running shoes for wide feet under €120", and the assistant suggests products, explains trade-offs and may link to or complete a purchase. Product data, reviews and trusted sources shape what it recommends.

Where does it happen?

What data shapes the recommendations?

• Product feeds: Google uses Merchant Center data; OpenAI documents product feeds for ChatGPT.
• Merchant sites: product pages, specs and policies.
• Reviews and UGC: what customers say.
• Editorial sources: reviews, comparisons and listicles.

What should merchants do?

• [ ] Keep product feeds complete and accurate (attributes, price, availability)
• [ ] Write product pages that state key facts in plain text
• [ ] Use Product structured data where appropriate
• [ ] Encourage genuine reviews
• [ ] Monitor which products AI suggests for your category prompts

How is it different from agentic commerce?

AI shopping covers AI-assisted discovery and comparison. Agentic commerce is the part where an AI agent also completes the purchase. Both depend on the same product data.

What are the risks?

• Missing attributes: if your feed lacks a key detail, such as size or compatibility, AI may skip your product.
• Conflicting data: different prices on your site and in a feed reduce trust.
• Attribution gaps: AI-influenced purchases may look like direct traffic.

Example

Illustrative. A coffee-equipment shop notices AI answers for "best grinder for espresso under €300" never mention its own-brand grinder. Its feed lacks grind-setting and burr-type attributes that competitors include. It adds them and monitors the prompts monthly.

Related

• AI agent
• Agentic commerce