AI-powered search is rewriting the rules of product visibility for brands and retailers. Those who master it will dominate the digital shelf, while those who lag risk disappearing from consumer reach altogether.
Online search has been stable for two decades. A handful of search engines set the rules, and retailers mastered SEO to meet them. But that playbook no longer applies. AI is upending the consumer discovery journey. Consumers are shifting from keyword search to conversational queries, often 20 words or more. Rather than delivering a list of links, these queries produce AI-generated answers, complete with product suggestions and context.
This is the first structural change to online search since its invention, and the impacts are already visible in the data. As Bain & Company reports, consumer reliance on zero-click results like AI summaries has translated into a 15–25% drop in organic web traffic. What’s more, 42% of AI users receive shopping recommendations directly from AI platforms. For brands, Large Language Models (LLMs) have become the new gatekeepers of discovery.
AI is redefining search and product discovery
Traditional SEO rewarded keyword placement and link-building. AI-driven search rewards context, depth and relevance. LLMs don’t parse ‘blue handbag’ as a string of words. They parse it as intent: Who is searching, why, and in what context?
This shift has two consequences. First, shallow product descriptions no longer suffice. A one-liner about ‘100% Italian leather’ will likely be ignored. AI engines favour detailed, intent-rich descriptions: how the bag fits, whom it suits, what occasions it works for, and how it compares to alternatives.
Second, discovery no longer ends at the brand’s own site. AI answer engines aggregate unaided opinions, social chatter and independent reviews. Visibility depends on the full digital footprint surrounding a product, not just what the brand controls.
Brands risk invisibility without structured, enriched data
Messy data means missing shelf space in AI results. LLMs rely on structured, machine-readable product information. Fragmented, inconsistent or outdated feeds can lead to products being misrepresented or omitted entirely.
As a first step toward LLM visibility, brands can do a little housekeeping: Fix code that accidentally blocks AI crawlers, outdated schemas or missing product images. This helps ensure sites are both crawlable and enriched for AI discovery.
But that’s only a first step. The next step is to optimise for multimodal search across text, image and video. Google Lens already processes 20 billion visual queries a month, one in four with commercial intent, according to Google. If product images don’t align with descriptions, or if video is absent, AI models will skip over them.
The stakes and the level of difficulty will keep rising. That’s why brands must embrace product data as a critical growth asset, maintained with the same rigour as inventory or pricing.
From SEO to AEO
The response is not more SEO. It’s Answer Engine Optimisation (AEO). Where SEO chased rankings, AEO ensures products surface in conversational answers. That means brands and retailers must:
- Deep, structured content: Move from minimal copy to multi-layered detail, including FAQs, use cases and buyer contexts.
- Multimodal enrichment: Support every listing with high-quality imagery, multiple angles and video demonstrations.
- Technical hygiene: Maintain up-to-date schemas, llms.txt files and AI-ready metadata to keep sites readable by crawlers.
- Consistent brand voice: AI doesn’t just ingest product data. It also ingests reviews, articles and unaided mentions. Retailers must ensure coherence across the digital ecosystem to build trust and defend against misrepresentation.
A call to action: Brands can’t wait
Many brands find themselves at a crossroads. They can either ignore this shift and risk becoming invisible in the places where consumers now make decisions or embrace it and turn AI into an ally for discovery.
This requires new operating models, where marketing, data and tech teams collaborate closely to keep product information fresh, structured and enriched. It also demands investment in content creation beyond traditional copywriting, expanding into video, contextual descriptors and multimodal assets.
But above all, it calls for urgency. Consumers have already adopted AI-powered search, and these platforms are shaping the commerce layer on top. The brands that act decisively now will gain an edge in influencing consumer intent earlier than ever before.
The new battle for visibility
The rules of product visibility have been rewritten. Keywords alone no longer guarantee discovery. AI determines relevance based on context, consistency and richness of product data. Brands that fail to adapt risk being erased from the consumer journey. Those who embrace structured data, multimodal formats and AEO can thrive in this new era of search.
This is the first true upheaval in search since search engines were invented. The question is no longer ‘Can people find us on Google?’ It’s ‘Do we show up in the AI answers that now define discovery?’.
