Retailers with fragmented data face algorithmic invisibility
Brands without machine-readable product data may vanish from results entirely.
The next time a consumer asks an artificial intelligence agent to find and purchase a product, a brand may not be considered if its data is not structured in a way machines can trust.
“AEO, or Agent Engine Optimisation, determines whether AI agents — the new intermediaries between consumers and purchases — will recommend, rank, or act on a brand's behalf at all,” Low Ngai Yuen, managing director at AEON360, told the Retail Asia Summit in Malaysia on 15 April 2026
The shift, she argued, is already underway — and the proof is in a partnership most retailers outside the United States barely noticed.
Earlier this year, Google activated a live AI shopping agent powered by Gemini, exclusively integrated with Walmart — capable of recommending and purchasing products on a consumer's behalf in real time. No other retailer was invited.
“The retailer's product catalogues, customer records, and digital architecture were structured well enough for an AI agent to navigate and act upon confidently,” Yuen said. Most traditional retailers, particularly across Southeast Asia, cannot say the same.
In the SEO era, visibility was shaped by keywords, backlinks, and page authority. AEO, however, operates on an entirely different logic — one that many brands have far less experience managing.
"Relevance, predictability, utility, and trust are what they will look at," the managing director said. "If whatever they have recommended is usually taken up by the consumers, chances are the brand has a high level of relevance as well as trust.”
In practice, AI agents will build continuous, performance-based trust scores for brands, updated based on whether recommendations convert into purchases.
“Brands with clean, consistent, machine-readable data will rise whilst those with fragmented records, inconsistent product descriptions, or poor agent-driven conversion rates will fall — quietly, and possibly permanently,” Yuen warned.
A commercial layer is also emerging on top of organic ranking. "In the future, there will be company-specific services that just run agents, and then they will come to you and tell you are number 54 in my list.”
She said that if a brand wants to go up the ranks, they need to pay. The model mirrors paid search advertising, but in an environment where consumers may never know a commercial arrangement shaped what they were shown.
For regional retailers, the urgency is straightforward: the infrastructure gap between them and AEO-ready players like Walmart is not a technology problem—it is a data discipline problem.
"Are we ready for algorithms to take over? Who is asking this question in your business?" the managing director challenged the audience.
She noted that few are asking it seriously enough. “Product data is inconsistently structured, and customer identities exist in disconnected silos.”
Yuen concluded that transaction histories are rich, but intent data — what consumers considered and rejected before buying — is almost entirely uncaptured.