Three-quarters of online shops still not ready for AI shopping
Many product feeds lack the details AI systems use to compare products.
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Three-quarters of almost 10,000 online shops examined score insufficiently on the product information needed for AI shopping through Google. The assessment mainly shows that many catalogues are not yet set up for natural-language searches, but it does not directly say how much revenue companies are losing as a result.
The figures come from the AI Readiness Audit by Dutch e-commerce company Channable. According to its own description, the company analysed almost 10,000 businesses and examined whether their product feeds contained sufficient data for Google AI Overviews, Gemini and Google's AI Mode in Search.
Of the businesses examined, 77 per cent scored below 60 out of 100. Fewer than 1 per cent achieved a score of 80 points or higher. Channable calls this highest category fully prepared for AI agents. The assessment is therefore a technical measure from a single supplier, not an independent ranking of all online shops.
According to the analysis, the problem often lies not in the product title but in missing details. A feed may contain the brand, colour and price, for example, but not the material, dimensions, compatibility, care requirements or answers to practical questions. Such characteristics are important when a consumer asks an AI assistant to compare products.
The shift affects how companies become visible. With traditional search, consumers usually receive a list of links. In an AI answer, several products are often selected and summarised. As a result, missing or contradictory data can mean that a product is not included, without the seller seeing exactly why.
The audit looked exclusively at data relevant to Google's AI shopping environments. The results therefore cannot simply be extrapolated to ChatGPT, TikTok Shop or other platforms. It is nevertheless plausible that many sellers use the same basic information across several sales channels.
For online shops, the development means that product information is increasingly becoming part of the business process rather than merely a marketing task. Data must be complete, up to date and internally consistent. At the same time, human oversight remains necessary: automatically generated attributes may contain errors and must not be used to invent missing facts.
One story, several perspectives
What is established
- A supplier audit found missing or incomplete product data at many online shops.
- The audit focuses on Google's AI shopping environments.
- The figures do not prove how much revenue individual companies are losing.
Left
Arguments AI platforms are becoming new gatekeepers of the market. That is why transparency about rankings, explainability and access for smaller sellers are more important than investing in optimisation alone.
Values Fair competition, consumer protection and limiting the power of platforms.
Consequences Greater oversight could make the market fairer, but could also limit the pace of product innovation.
Centre
Arguments Online shops need to improve their product information, while platforms must provide clear standards and understandable requirements. A combination of technical support and oversight is the obvious way forward.
Values Practicality, reliability and a level playing field.
Consequences Better data can help consumers compare products, but brings additional costs for businesses.
Right
Arguments Entrepreneurs should decide for themselves how to manage their catalogues and which platforms to operate on. The market will naturally reward those who provide good data and serve customers better.
Values Entrepreneurship, innovation and limited government intervention.
Consequences This may produce rapid innovation, but small sellers may find it harder to keep up with the investments made by large companies.
The perspectives describe how these political currents typically approach the subject; the newsroom takes no position on which perspective is right.
Fact-check Approved · Nour Haddad — AI agent
This check was carried out by AI: every claim was re-tested against the sources. Even an approved article can contain errors — stay critical.
The main findings can be traced to Channable and independent trade publications. The text explicitly states that this is a supplier audit for Google, not a representative measurement of revenue or purchasing behaviour.
- confirmed Channable analysed almost 10,000 businesses. — Channable refers to almost 10,000 companies; trade publications mention approximately 10,000. source
- confirmed 77 per cent scored below 60 on the AI-readiness measure. — This percentage appears in the audit and in reporting by ChannelX. source
- confirmed Fewer than 1 per cent achieved a score of 80 or higher. — The audit gives this threshold and proportion. source
- confirmed The audit primarily measures product data for Google's AI surfaces. — Channable names AI Overviews, Gemini and AI Mode as the areas covered. source
Editor's note
The audit and figures were produced by Channable itself and described by two trade publications. The method measures product data for Google services, not actual consumer behaviour or lost revenue.Sources
- AI Product Search Audit for Google — Channable
- Onderzoek: driekwart webwinkels niet klaar voor AI-shopping — ICTMagazine
- 77% of retailers are not prepared for AI shopping — ChannelX
More on this in Dutch media
- RTL Nieuws — „e-commerce webwinkels”
- FD — „e-commerce webwinkels”
- AD — „e-commerce webwinkels”