AI visibility is changing how brands are discovered, recommended, and later searched for.
As part of our Total Search Summit, we explored how brands appear across AI answers, organic results, influential sources, media coverage and demand signals. The ambition was simple: move beyond surface-level AI-search conversations and understand where visibility, recommendation and demand are starting to diverge.
What the research combined
We brought together proprietary LLM prompt testing across multiple commercial categories, organic visibility analysis, brand citation review, source ecosystem mapping, media coverage analysis and retail demand-shape insight.
10 findings from our research
- AI answers are turning category prompts into brand shortlists
- Ranking is no longer the same as being recommended
- Demand is changing shape, not simply disappearing
- Generic search is losing some of its discovery role
- The recommendation ecosystem is heavily affiliate-led
- Freshness, scale and source momentum may influence the AI shortlist
- Not all media coverage is equal
- Best-of lists over-index as AI-ready evidence
- Brand websites still matter, but as source assets
- Social platforms play a different role in Search
FINDING 1: AI answers are turning category prompts into brand shortlists
Across categories, LLM responses consistently move from broad guidance to named brand recommendations. That makes AI visibility commercially meaningful, even when direct referral traffic is difficult to track.
Evidence
- 86% of LLM responses included at least one brand recommendation (ChatGPT/Gemini prompt testing)
- Only 14% provided no brand recommendations
What we found
AI answers behave less like a results page and more like a recommendation layer. A broad question quickly narrows into a shortlist of brands, products or providers.
This shifts the focus from “do we rank?” to “are we recommended, and how often?”
What this means for you
AI visibility is now part of category visibility. Brands need to understand whether they appear, how they are framed, and who they appear alongside.
Actionable takeaway
Measure and manage AI recommendation visibility. An LLM Visibility Audit can help you understand inclusion, positioning and competitive context.
FINDING 2: Ranking is no longer the same as being recommended
Strong organic performance does not guarantee inclusion in AI recommendations.
Evidence
- 40% of Google-ranking brands did not appear in AI shortlists.
- 68% of AI-recommended brands had no direct Google top 20 ranking.
- 26% of the top 3 Google-ranking brands were not AI-recommended.
What we found
While there is overlap, AI visibility and organic visibility are not the same system. Third-party sources, publisher ecosystems and recommendation environments play a significant role.
What this means for you
SEO remains essential, but it’s no longer enough. Brands must understand the wider ecosystem influencing AI recommendations.
Actionable takeaway
Use LLM visibility and citation analysis to identify which publishers, reviews and sources shape AI shortlists, and build presence within them.
FINDING 3: Demand is changing shape, not simply disappearing
Retail data suggests that demand is evolving into more specific, lower-funnel behaviours rather than declining outright.
Evidence
- +3% overall brand impressions
- -7% pure/navigation brand demand
- +13% brand + product demand
What we found
Broader brand queries declined, while more specific, intent-rich searches increased across products, collections and services.
What this means for you
Reduced top-level demand should not be viewed in isolation. Discovery may be happening earlier across AI, social and publisher environments, while Search becomes more precise.
Actionable takeaway
Expand measurement beyond traditional search volume. Look for how AI-driven discovery influences branded and product-led demand.
FINDING 4: Generic search is losing some of its discovery role
Generic Search still matters, but it appears to be capturing less of early-stage discovery.
Evidence
- -19% decline in priority generic search volume
- CTR fell from 2.5% to 1.8% despite stable positions
- 61% of the decline came from queries where rankings held or improved
What we found
Generic rankings are no longer a complete proxy for category demand. Discovery is happening more widely across the ecosystem.
What this means for you
Visibility is no longer defined by owned sites alone. Affiliates, publishers and review platforms increasingly shape discoverability.
Actionable takeaway
Audit visibility across the full ecosystem, including AI, to understand where discovery happens before lower-funnel search.
FINDING 5: The recommendation ecosystem is heavily affiliate-led
The environments influencing recommendations are often commercially structured.
Evidence
- 81% of influential sources included affiliate or monetisation mechanics
What we found
Recommendation content, especially reviews, comparisons and “best of” articles, is frequently monetised. This shapes how brands are presented and prioritised.
What this means for you
Recommendation visibility is built across a network of publishers, affiliates and platforms, not just owned channels.
Actionable takeaway
Map your recommendation ecosystem to identify the sources most likely to influence both AI outputs and consumer choice.
FINDING 6: Freshness, scale and source momentum may influence the AI shortlist
Presence across current, high-coverage environments appears to matter.
Evidence
- 39% of influential sources were recently updated
- 70% of the top LLM-recommended brands were listed companies
What we found
Fresh content, scale and repeated presence across sources may influence inclusion in AI recommendations.
What this means for you
AI visibility is not achieved through a one-off activity. It requires consistent presence across relevant and current sources.
Actionable takeaway
Develop an ongoing AI visibility programme that tracks citation growth, source momentum and recommendation trends.
FINDING 7: Not all media coverage is equal
The effectiveness of coverage depends on how useful it is for recommendations, not just how much is generated.
Evidence
- 14 vs 83 media mentions (Brand A vs Brand B)
- 64% vs 23% high AI-ready rate
- 66% vs 30% LLM response coverage
What we found
More concentrated, recommendation-led coverage outperformed broader PR volume.
What this means for you
Coverage should be assessed on its ability to support recommendations, not just reach.
Actionable takeaway
Prioritise media placements that are structured for recommendation – specific, relevant and easily interpretable.
FINDING 8: Best-of lists over-index as AI-ready evidence
Certain formats are inherently more usable for AI systems.
Evidence
- 13% of content signals were “best-of” lists
- 67% of strong AI-ready evidence came from these formats
What we found
Ranked lists and “best for X” articles are already structured like answers, making them easier for AI to use as recommendation evidence.
What this means for you
Format matters as much as presence. Not all coverage contributes equally to visibility.
Actionable takeaway
Prioritise content formats that clearly structure recommendations – rankings, buying guides and use-case-led lists.
FINDING 9: Brand websites still matter, but as source assets
Owned sites remain critical, but increasingly as part of the evidence layer.
Evidence
- Homepages support brand validation
- PLP/PDP pages provide product and category evidence
- Articles and blogs support advice and use-case relevance
What we found
Different page types serve different roles across discovery, validation and action.
What this means for you
Websites should be designed not only for users, but as clear, structured sources of truth.
Actionable takeaway
Conduct an AI readiness audit to ensure your site is accessible, coherent and supports both human and machine understanding.
FINDING 10: Social platforms play a different role in Search
Social contributes to search behaviour, but not primarily through direct citation.
Evidence
- 1.8% of Google’s top 20 results were social platforms
- 0.2% of AI citations came from social
- 34% of keyword families included at least one social result
What we found
Social platforms appear occasionally in Search but rarely as cited sources in AI responses.
What this means for you
Social is less about direct recommendation and more about inspiration, validation and demand creation.
Actionable takeaway
Align social, SEO and AI strategies so that social builds demand, while owned and earned content provides the signals that influence recommendations.
Final perspective
AI visibility is not replacing Search – it’s reshaping how people move through it.
For brands, the challenge is no longer just to be found, but to be understood, trusted and recommended across a more complex ecosystem. The opportunity lies in designing visibility around people: how they discover, evaluate and decide.
Those who do this well will not just appear in Search, but shape it.
Statistics are correct as of July 2026. These findings are for general informational purposes and not guaranteed outcomes.
