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Consumers are validating information across more platforms before making decisions. New findings show where AI systems look for authority. #
Trust in AI search is declining, consumers are validating information across more platforms, and AI visibility is increasingly tied to brand authority rather than traditional SEO metrics.
Those are among the key findings from new research by Fractl and Search Engine Land, presented by Fractl cofounder Kelsey Libert at SMX Advanced. The study offers a detailed look at how consumers evaluate AI-generated answers, which signals influence AI recommendations, and where brands are falling short on governance and disclosure.
After the conference, I spoke with Libert to dig deeper into the data. Our conversation covered the growing trust gap in AI search, the role of earned media and entity authority in AI visibility, and why many organizations are still unprepared for the operational challenges AI introduces.
The honeymoon is over #
The headline finding from Libert’s research is hard to ignore. In 2025, 82% of consumers found AI search more helpful than traditional search results. By 2026, that figure had dropped to 54%, a decline of 28 percentage points in a single year. The skeptic camp grew sixfold over the same period.
I asked Libert what she thinks is driving that erosion.
- “Hallucinations. Initially, AI was a frictionless instant-answer machine that felt superior to Google’s crowded SERPs. As people lost trust in AI answers and had to put in more effort to validate them, that instant gratification disappeared, and the helpfulness score dropped dramatically,” Libert said.
She isn’t entirely pessimistic about where things are headed, though.
- “AI is on an exponential improvement scale, so I expect this number to restabilize over the next year as people learn how to refine their prompts and engineers improve the technology,” Libert said.
That restabilization may come sooner than expected. Libert pointed to a June 5 CNN report covering Anthropic’s warnings that AI may soon be capable of improving itself without human intervention. Whether that accelerates the recovery of consumer trust or deepens concern about AI reliability remains to be seen.
In the meantime, consumers are hedging. The research found that buyers now check an average of 2.4 platforms before validating a purchase, a pattern consistent across Gen Z, millennials, and boomers.
Google still leads AI tools three to one for trusted product recommendations, commanding 39% of consumer trust versus 14% for AI tools. Reddit, at 15%, sits between them.
Organic visibility is diversifying #
For SEOs worried about the erosion of organic traffic, Libert’s framing offers a more nuanced picture than the typical doom narrative. About 50% of marketers report traffic declines since AI Overviews launched, and 61% directly blame AI tools. At the same time, 57% see traffic growth from social platforms, including TikTok, Reddit, and YouTube, and 40% see growth from AI assistants such as ChatGPT and Perplexity.
The channel map Libert presented at SMX is worth understanding.
- Google remains dominant at 84.8 billion visits, serving primarily as an intent-capture engine.
- YouTube and Instagram/TikTok together handle brand discovery.
- ChatGPT and Gemini are used primarily for research and learning.
- Facebook and Reddit serve human-validation functions.
Search isn’t disappearing. It’s fragmenting, and brands that optimize for only one of these channels are leaving significant visibility on the table.
The GEO hierarchy: Table stakes, high risk, and the moat #
Libert’s research categorized generative engine optimization tactics into three tiers, and the distinctions matter for how marketers should allocate effort.
The most commonly used tactic is FAQ optimization, employed by 49% of marketers. Libert calls this high risk, and the reason is straightforward.
- “The high-risk category is based on how easily AI can replicate that content, and general industry FAQs are typically pretty easy for AI and your competitors to produce.”
FAQ strategies can be strengthened by layering in proprietary data, subject matter expertise, and unique insights, but on their own, they offer little defensibility.
Table-stakes tactics include building brand mentions (43%), establishing topical authority (36%), and implementing structured data (30%). These are necessary but not sufficient.
The moat, as Libert describes it, consists of original data and proprietary studies (35%) and digital PR (24%). These are harder for AI to replicate, which is precisely what makes them valuable.
- “LLMs and Google need fresh content to pull into timely and common RAG queries. Beyond that, data journalism and digital PR efforts help increase your brand’s entity authority by helping you earn brand mentions across influential sources across the web,” Libert explained.
The signal strength behind this approach is backed by Ahrefs research analyzing roughly 75,000 brands across ChatGPT, AI Mode, and AI Overviews.
Branded web mentions and YouTube impressions showed the strongest correlations with AI visibility, ranging from 0.50 to 0.74 on the Spearman scale.
Backlink count and ad spend fell in the weakest tier, below 0.30. The practical implication, as Libert put it, is that “AI systems reward brand presence and mentions more than traditional SEO scale metrics.”
I asked Libert what she would do first if building brand mentions from scratch. Her answer was tactical and specific:
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Use Semrush or Ahrefs to identify high-authority, niche-relevant publishers that have covered competitors, build relationships with those journalists, and pitch concepts that fill gaps in their coverage using proprietary data or subject matter expertise.
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Use SparkToro to identify the publishers, YouTube channels, and podcasts a target audience actually consumes, then prioritize earned placements in those venues.
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Use Reddit to study what performs well in relevant subreddits and contribute substantive commentary or content, not promotional noise.
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“Earned media always comes back to one principle. Focus on creating fresh, educational, actionable, valuable, and newsworthy industry insights, and repurpose that content across the channels of influence for your target market,” LIbert said.
The trust gap brands are ignoring #
One of the most striking data points in Libert’s presentation involves the gap between what consumers expect and what brands actually do.
Between 84% and 91% of consumers say they want AI labeling across all content formats, including text, video, audio, and images. Only 20% of organizations say they always disclose their AI use. One-third never disclose at all.
Libert doesn’t think consumers are simply opposed to AI in marketing. The concern is more specific.
- “Consumers aren’t wary about AI use in marketing. They’re concerned when brands use it for their entire marketing workflow with zero checks and balances.”
She cited the research finding that nearly half of marketers admit to not fact-checking their AI-produced content and that 48% say AI makes their work faster but more average.
Dove came up as one of the few brands actively positioning against what Libert calls “AI-dominant marketing slop,” though she acknowledges the field is still mostly treating disclosure as a compliance checkbox rather than a brand signal.
There is also a deeper question about where AI assistance ends and human creativity begins, one the industry hasn’t settled.
- “There’s some debate on when it needs to be disclosed, since plenty of people use it more as an assistant in the creative process vs. having it do everything end-to-end,” Libert said. “In that case, who truly owns the creativity, and what level of disclosure is required? That’s still up for debate.”
The inverted pyramid problem #
The slide that drew the most reaction in the SMX room showed how marketers are allocating their human review time for AI-generated content. Editorial review claimed 72% of attention. Voice and tone review claimed 62%. Fact-checking fell to 54%, plagiarism and legal review to 42% each, and bias evaluation to just 27%.
Libert called this an “all of the above” problem, spanning training gaps, workflow fragmentation, and leadership priorities.
- “When employees can’t keep up with the basic learning process to execute their workflow effectively with AI, how can you expect them to also focus on the checks and balances of AI’s output without the proper support from leadership to take time to develop and refine entirely new workflows?” she said.
- “We’re focusing on the surface-level review of AI’s output because that’s all people have the capacity and proper support for. That data point is a huge leadership SOS.”
Her core argument here aligns with the most pointed line in her presentation: fix the infrastructure before you scale the output. AI won’t kill credibility. Untrained oversight will.
What smaller brands can actually do #
The closing argument of Libert’s SMX talk, that AI rewards brand equity rather than creating it, raises a fair concern for newer entrants who lack years of accumulated authority. I pushed her on this.
Her answer was more optimistic than the headline suggests. AI Overviews aren’t simply surfacing the top search results. They are surfacing brands that have built genuine authority around niche topics.
- “Younger brands can still compete by focusing on building out their entity authority around the long tail, where most conversions actually live,” she said.
She also sees an opening created by the same corporate inertia that slows large-brand adaptation.
- “Plenty of larger brands are stuck in more corporate bureaucracy and are slower to adapt to the changes and opportunities of using AI to scale insightful data analysis and thought leadership content. There’s actually plenty of room for smaller brands to compete, now more than ever.”
The caveat?
- “It’s a matter of slowing down and learning how to use AI effectively, not scaling AI slop.”
The playbook for AI visibility #
The 2026 AI search playbook that Libert presented at SMX distills to four imperatives:
- Monitor brand representation across all influential platforms.
- Build entity authority through original research and subject matter expertise.
- Triangulate visibility across search, video, social proof, and trusted media.
- Govern AI use with formal disclosure and review processes rather than ad hoc workarounds.
None of this is particularly complicated in concept. The difficulty is organizational.
The brands that treat credibility as infrastructure rather than aesthetics are most likely to be cited, recommended, and trusted as AI search continues to mature.
Topics on this page
[Generative Engine Optimization](https://searchengineland.com/topic/generative-engine-optimization/)
[Artificial intelligence](https://searchengineland.com/topic/artificial-intelligence/)
[Brightfractal Inc.](https://searchengineland.com/topic/brightfractal-inc/)
[Kelsey Libert](https://searchengineland.com/topic/kelsey-libert/)
[Ahrefs](https://searchengineland.com/topic/ahrefs/)
[AI Overviews](https://searchengineland.com/topic/ai-overviews/)
[Anthropic](https://searchengineland.com/topic/anthropic/)
[Cable News Network, Inc.](https://searchengineland.com/topic/cable-news-network-inc/)
[ChatGPT](https://searchengineland.com/topic/chatgpt/)
[Consumer Trust](https://searchengineland.com/topic/consumer-trust/)
[Digital marketing](https://searchengineland.com/topic/digital-marketing/)
[Gemini](https://searchengineland.com/topic/bard/)
[Generation Z](https://searchengineland.com/topic/generation-z/)
[Large language model](https://searchengineland.com/topic/large-language-model/)
[Retrieval-augmented generation](https://searchengineland.com/topic/retrieval-augmented-generation/)
[Search engine](https://searchengineland.com/topic/search-engine-2/)
[Search Engine Land](https://searchengineland.com/topic/search-engine-land/)
[Search engine optimization](https://searchengineland.com/topic/search-engine-optimization/)
[Search engine results page](https://searchengineland.com/topic/search-engine-results-page/)
[Semrush](https://searchengineland.com/topic/semrush/)
[SMX Advanced Europe](https://searchengineland.com/topic/smx-advanced-europe/)
[SparkToro](https://searchengineland.com/topic/sparktoro/)
[TikTok](https://searchengineland.com/topic/tiktok/)
[YouTube](https://searchengineland.com/topic/youtube/)
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