Retailers and brands investing in structured product data need to prepare their catalogues to participate in the next generation of commerce, where algorithms increasingly determine commercial opportunity before customers even engage, says Justin Thomas, VP Sales Northern Europe at Akeneo
The retail shelf has always been where products compete for attention. Whether that shelf exists in a supermarket aisle, a marketplace, a retailer’s website or a social commerce platform, the principle has remained the same – if customers cannot find your product, they cannot buy it.
Increasingly however, AI agents will do the evaluating. As agentic AI becomes embedded into commerce, digital assistants will search, compare, filter and recommend products on behalf of consumers. Rather than browsing dozens of options themselves, shoppers will increasingly ask an AI to find the best cordless vacuum under £300, the healthiest breakfast cereal for children or the most sustainable trainers available tomorrow. The AI will perform the research before presenting only a handful of recommendations.
This fundamentally changes product visibility because brands and retailers will no longer compete solely for human attention but for the confidence of the machine. This will require brands and retailers to change from optimising for search engines and retail algorithms, and this will mean massively expanding the product information pool. Rich product descriptions, compelling imagery and carefully chosen keywords remain important but agentic AI as the new decision maker will not just rank products based on popularity or advertising spend; its recommendations will increasingly depend on structured evidence, comparing specifications, availability, pricing, customer ratings, sustainability credentials, compatibility, delivery promises and countless other data points before deciding which products deserve consideration.
If product information is incomplete, inconsistent or unreliable, AI agents have every reason to exclude it from consideration altogether. Retailers and brands will be playing for high stakes as the first sale may be won long before a consumer sees the product. This depends on structured attributes, standardised specifications, trusted descriptions, complete technical information and accurate categorisation as the evidence that AI uses to understand what a product is, who it is suitable for and whether it fulfils a customer’s request.
Product content is only the beginning. Availability, pricing, promotions, regional restrictions, delivery options, warranty information, certifications and customer reviews all become signals that influence an AI’s confidence. AI agents will want to know more than whether a product exists in stock, they will increasingly ask whether they can trust it.
Generative AI has arguably made trust one of the most valuable assets in commerce. Consumers may never know why an AI recommended one product over another, but the AI itself will increasingly require confidence that the information it uses is accurate, current and verifiable. Conflicting specifications across channels, outdated pricing, missing attributes or inconsistent descriptions all reduce that confidence.
The next challenge is rethinking product experiences because they must become machine-readable, whereas to date they have been built primarily for human readers. AI agents consume structured information far more effectively than beautifully written marketing copy alone. Rich taxonomies, consistent attribute models, governed product relationships and standardised metadata all improve an AI’s ability to interpret products accurately.
The result is that visibility will become algorithmic which means organisations must provide complete, consistent and trusted product information that machines can interpret with confidence. Product data quality thus becomes directly linked to discoverability, recommendation frequency and ultimately commercial performance.
This is an important opportunity for brands because the invisible shelf will not reward the loudest companies but the ones that are clearest. As AI agents increasingly mediate purchasing decisions, brands will need to optimise not only for human experience but also for machine understanding. Product information thus becomes critical infrastructure rather than just marketing content.
The question every brand and retailer should now be asking themselves is not simply whether customers can find their products, but whether the AI ever considers them in the first place.
