Companies are increasingly losing sight of how consumers discover and choose products because AI answer engines often deliver zero-click recommendations that determine purchase decisions before consumers reach brand-owned channels. This is a structural shift rather than a transient trend, and most current analytics architectures are not designed to detect the losses that result.
What has changed?
- According to Salesforce research, 82% of digital commerce started on a brand’s website in 2014; by 2024 that share fell to 38%. The journey that once began at a brand’s front door now often starts on other platforms, increasingly with AI.
- Consumers ask AI where to shop, what to buy, and which product suits them; the AI-provided answer frequently establishes the shortlist that guides their decision.
- Bain research indicates that four in five consumers rely on zero-click results at least 40% of the time. Adobe Analytics recorded over 800% year-over-year growth in AI-driven traffic to retail sites, signaling how rapidly AI platforms are inserting themselves between brands and customers.
The measurement gap
Current analytics measure the path from landing page to purchase well, but they offer almost no instrumentation for the layer between consumer intent and brand discovery — the layer where AI now operates. Consequences include:
- There is no event in session logs that flags "AI excluded you." If an AI assistant recommends a competitor, that absence typically leaves no trace in brand analytics.
- There is no abandoned-cart entry for a shopper who never reached the brand site because an AI gave a direct recommendation.
- Semrush’s 2025 zero-click study found that 60% of searches end without a click; for AI-mediated discovery the share is structurally higher because the answer itself is the destination.
If a brand is not present in the AI answer, it is not in the consumer’s consideration set — and conventional dashboards will not surface that loss.
The metric that’s missing
Brands that want to understand their competitive position in an AI-mediated market must ask different questions: How does my brand appear when consumers ask AI for recommendations in my category? What language does AI use to describe my products? Where am I present, where am I absent, and where is the AI describing me in ways that do not match my positioning?
These are infrastructure questions rather than traditional marketing questions, and answering them requires audits and tools beyond current commerce and marketing toolkits.
Empirical findings
Rezolve Ai commissioned research of 1,500 U.S. consumers in January 2025 and found that a majority of shoppers who use AI for product research make purchase decisions directly from those AI-generated recommendations, without returning to a search engine or a brand site to verify. The implication is that by the time consumers reach brand-owned properties, the decision may already have been made elsewhere.
What brands should do next
Brands that retain commercial relevance as AI mediates more of discovery will be those that develop visibility into that layer, not merely presence on owned platforms. Practically, this means:
- Treat AI discoverability as a measurable discipline rather than an assumption;
- Build the infrastructure to track, measure, and influence how AI systems represent them to consumers;
- Conduct audits that reveal where a brand appears or is omitted from AI recommendations and how the AI describes its products.
Tools to support these activities are starting to appear, while measurement frameworks remain unstandardized. Brands that begin building visibility now gain a structural advantage as the market shifts, because every day without visibility lets AI-formed preferences solidify without the brand’s input.
Note on the article
This article is sponsored content produced with support from Rezolve Ai. Sponsored posts on VentureBeat are clearly marked. For more information: sales@venturebeat.com.
