The actual data from AI search statistics which LinkedIn SEO leaders observe in 2025 differs from what most people expect.
A thorough examination of actual data combined with expert insights from LinkedIn's leading SEO professionals reveals the actual performance of AI search systems. The study reveals the actual performance of AI search systems through an examination of real data and expert insights from LinkedIn.
What you'll learn in this analysis:
- • Real traffic numbers from AI search platforms
- • LinkedIn expert insights on AI search performance
- • Why 95% of companies fail to detect any measurable AI traffic.
- • Proven strategies from successful SEO professionals
Hello! This is Falco Schneider, Founder of UltraRelevant. After months of analyzing LinkedIn posts from leading SEO experts like Aleyda Solís, Lily Ray, and other industry leaders, I present you with the unvarnished truth about AI search performance.
Executive Summary & Key Findings
After months of analyzing LinkedIn posts from leading SEO experts like Aleyda Solís, Lily Ray, and other industry leaders, a clear picture emerges: the reality of AI search differs significantly from the marketing hype. While 91% of SEO professionals report being asked about AI search visibility, the actual data tells a different story about current market penetration.
📊Key Statistics at a Glance
This data, compiled from the SEOFOMO AI Search Optimization survey with over 200 participants and supplemented by insights from Similarweb and other authoritative sources, shows a significant gap between demand and actual impact. While demand for AI search optimization is high, the measurable business impact remains minimal for most companies.
The Data Behind AI Search Adoption
Aleyda Solís, one of the leading SEO experts with over 15 years of experience and founder of the SEOFOMO newsletter with 39,000+ subscribers, recently published comprehensive data on actual AI search usage. Her analysis, based on Similarweb data and industry surveys, paints a realistic picture of the current market situation.
Real Usage Statistics
🎯Traffic Comparison: ChatGPT vs. Google
| Platform | Monthly Visits | Market Share |
|---|---|---|
| Google Search | 83.8B | 93.5% |
| ChatGPT | 5.8B | 6.5% |
*Data from Similarweb, August 2025
These numbers reveal an important truth: while ChatGPT has seen significant growth, it's still far from displacing Google as the primary search platform. Even more significant is Solís' insight that 95% of ChatGPT users also use Google – they're not replacing Google, but complementing it.
Professional Survey Results
The SEOFOMO AI Search Optimization survey, conducted with over 200 experienced SEO and digital marketing specialists (mostly with 10+ years of experience), provides revealing insights into the actual business impact of AI search platforms.
💰Revenue Attribution Analysis
*Based on SEOFOMO survey of 200+ SEO professionals
Lily Ray, VP SEO Strategy & Research at Amsive and recognized industry expert, supplements this data with her own analysis: 'I see a lot of people making lofty claims about what works in AI search (or not), but I don't see a lot of actual evidence. Most claims are based on speculation rather than hard data.'
The Technical Reality of AI Citations
To understand how AI search platforms actually work, it's crucial to look at the technical mechanisms behind the scenes. LinkedIn SEO experts have gained important insights through practical testing and analysis of how different platforms operate.
How Different Platforms Actually Work
🔧Platform-Specific Citation Mechanisms
ChatGPT
Sources from citations and search results, including Google APIs. Aleyda Solís reports: 'ChatGPT is even using Google search results via APIs (besides Bing's one) when grounding is needed for their answers as reported by The Information.'
Perplexity
Extracts article URLs from the 'citations' field with full article URLs, making it potentially valuable for publishers.
Google AI Mode
Uses Google's redirect URLs from 'groundingMetadata' in format: https://vertexaisearch.cloud.google.com/grounding-api-redirect/...
Google AI Overviews
Often problematic: Frequently cites pay-to-play directories and sponsored content as 'factual information'.
The Grounding Problem
A critical understanding highlighted by industry experts is the dependence of LLMs on 'grounding' – retrieving real-time information via web searches beyond their static memory. As Solís explains: 'LLMs answers also rely on grounding (retrieving real-time external information via their search integration beyond its static memory) when current, factual information is needed, this means SEO is vital for it.'
⚡Why SEO Remains Critical for AI Platforms
- •LLMs have training data cutoffs (GPT-5 stops at Sept 30, 2024)
- •Current information requires web searches and therefore SEO-optimized content
- •Crawlability, indexability, and content relevance remain fundamental
- •E-E-A-T (Experience, Expertise, Authority, Trust) becomes more important, not less
What's Actually Working (And What Isn't)
Based on observations and data analyses from LinkedIn SEO experts, a clear picture of successful versus ineffective strategies emerges. Lily Ray has conducted extensive analyses with Profound to examine the most frequently cited domains and pages in AI search.
Successful Strategies Observed
✅Strategies with Proven Effectiveness
Product Review Pages as Citation Goldmines
Ray's analysis shows: 'For publishers, "best product" review pages seem to be a goldmine for AI search citations - particularly on ChatGPT. The common thread is how frequently the sites' product review pages are cited (e.g. "best moisturizers"), compared to other pages.'
Branded Search Impression Growth
Ray recommends: 'I'm finding it interesting to monitor branded impressions in GSC over time as an indicator of demand for a brand and its content; something that has many indirect benefits on SEO and AI visibility.'
Failed Approaches
❌Strategies with Low or Negative Impact
Excessive AI Content Scaling Without Oversight
Ray warns: 'Interesting - but not surprising - to see people on LinkedIn sharing their stories of losing all search visibility (sometimes overnight) after an aggressive AI content strategy. Scaling content with little to no original insights can and will get your site in trouble.'
Pay-to-Play Citation Manipulation
Ray's investigation reveals: 'So basically, one of the best ways to *currently* get mentioned "organically" in AI Search is to pay for it. Or just spam low-quality AI blogs & listicles with your brand name mentioned as the "best" as much as possible.' This works currently but isn't sustainable.
Tool Effectiveness Analysis
One of the most surprising findings from Solís' survey was the ranking of most frequently mentioned tools for AI search optimization and tracking:
| Rank | Tool | Category |
|---|---|---|
| 1 | Ahrefs | Traditional SEO |
| 2 | GA4 | Web Analytics |
| 3 | Semrush | Traditional SEO |
| 4 | GSC | Google Search Console |
| 6 | ChatGPT | AI Tool |
Solís comments: 'One of the biggest surprises of the State of AI Search Optimization Survey outcomes? GA4 is the 2nd most cited tool used for AI search optimization & tracking (since I know that we love to hate it but ...)' This shows that traditional SEO tools continue to dominate, even in AI search optimization.
The E-E-A-T Problem in AI Search
One of the most troubling trends identified by LinkedIn SEO experts is the susceptibility of AI search platforms to citing low-quality, unreliable, or sponsored content. This represents a significant regression from Google's years of efforts to promote E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness).
Quality Control Issues
⚠️Systemische Qualitätsprobleme bei KI-Zitationen
Spammy Sites Getting ChatGPT Citations
Ray's analysis shows: 'Many of these sites seeing citations in ChatGPT have little to no organic visibility. They're either a bit spammy, affected by Google algorithm updates over the years, and/or relatively new blogs/smaller sites without a lot of SEO visibility.'
AI-Generated Content Outranking Original Sources
Ray reports an alarming trend: 'I had a journalist call me specifically to ask why AI-generated versions of her articles on spam websites kept outranking her original articles on Google, including in Google News and Top Stories.'
The Citation Authenticity Crisis
Lily Ray has made a particularly troubling discovery when using Profound to analyze the most heavily cited domains and pages in AI Search:
🕳️The "Best Agency" Listicle Problem
"Many of these heavily cited pages come from pay-to-play directory sites, and/or listicles that obviously rely on sponsored results, even without clearly disclosing that information on the page. I also see many of the same companies appearing across many of these listicles in certain categories (best marketing agency, best PPC agency, etc.)."— Lily Ray, VP SEO Strategy & Research, Amsive
The Impact:
AI answers that present these companies as the "best" - when most of those citations have been paid for - as opposed to using more sophisticated technology to actually identify signals that align with the "best companies" (E-E-A-T).
OpenAI Partnership Bias
Ray has also made an important observation about citation fairness:
"I see a lot of people making claims about the sites/pages frequently mentioned in ChatGPT, without noting that OpenAI has deals with many of the cited publishers. It's always worth asking if the cited publisher in ChatGPT is owned by one of the media companies partnering with OpenAI."
OpenAI Content Partners (Selection):
Professional Adaptation Strategies
Despite the mixed results and challenges, SEO teams are actively adapting to the realities of AI search. The SEOFOMO survey provides valuable insights into the actual strategies being employed by experienced professionals.
What SEO Teams Are Actually Doing
👥Team Organization and Strategy Development
Solís explains the discrepancy: 'Yet only ~35% have a dedicated AI search optimization strategy for all or most of their sites; ~33% have plans but haven't done so yet.' This shows a gap between demand and actual strategy implementation.
Key Focus Areas
🎯Priority Tactics for AI Search Optimization
Schema & Structured Data
FAQ, Product, HowTo schema for better AI comprehension
Content Restructuring for Retrieval
Chunking, TL;DRs, FAQs, Q&A, more passage-level answer formats
Enhanced Technical Accessibility
Crawlability, JS audits, ensuring LLM access, Core Web Vitals
Brand Mentions & Authority Building
Including via platforms like Reddit, Wikipedia, UGC
Measurement and Tracking
One of the biggest challenges identified by industry professionals is measuring AI search performance. Ray and other experts have developed practical approaches:
📈Practical Tracking Methods
Branded Search Impression Monitoring
Ray recommends: 'Monitor the overall search impressions / demand for your brand. Set up a regex filter in Search Console that combines your brand name and its misspellings, plus any other branded products you might have.'
Homepage Traffic Analysis
Ray suggests: 'I've seen people like Ross Hudgens recommend keeping tabs on your homepage traffic, which I think is really smart.' People often use ChatGPT to find products, then go to Google to find the online store.
Customer Journey Attribution
Wil Reynolds is credited as the first person to recommend adding 'ChatGPT' or 'AI Search' as an option when asking customers where they heard about you. Ethan Smith suggests that sales teams should be trained to ask that question.
Industry Predictions vs Reality
A recurring theme in LinkedIn discussions is the gap between industry predictions and actual implementation. While conference presentations and tool vendors make grand claims, the data from SEO professionals shows a more nuanced picture.
The Hype vs. Implementation Gap
⚖️Promises vs. Reality
Hype Claims
- • AI search will replace Google
- • SEO is dead
- • Massive traffic shift to LLMs
- • Immediate revenue increases
Current Reality
- • AI search complements Google
- • SEO principles remain relevant
- • 0-5% revenue share for most
- • Long-term strategy development needed
Ray articulates this frustration succinctly: 'One of the main problems with AEO/GEO/AI search advice right now: A lot of people are making a lot of bold claims without evidence, and a lot of other people are repeating those claims. Then, LLMs are also picking up those repeated claims as guidance for AI search.'
AI Mode Rollout Challenges
A particularly insightful point comes from Ray's analysis of the Google AI Mode rollout:
"When people ask me about Google AI Mode becoming the 'future of search,' I usually respond by saying that whatever future version of AI Mode that is might not necessarily look like the AI Mode we see now. I think Google will find a way to incorporate the best parts of AI Mode with the best parts of Search."
🔮Why AI Mode Must Evolve
The Sustainability Question
Eli Schwartz, author of 'Product-Led SEO' and strategic SEO advisor, raises an important point about the sustainability of current AI search optimization strategies:
"Some CMOs will struggle to justify their shiny object obsession in about a year from now. Yes, organic traffic is down, but did they even deserve what they had if they weren't aligned with the user? The answer is to adjust the strategy to an AI journey, rather than lighting the whole thing on fire with AI gibberish."
Actionable Recommendations for 2025
Based on the collective insights from LinkedIn SEO experts and real industry data, here are practical, actionable recommendations for businesses looking to adapt to the AI search landscape.
Immediate Actions
🚀Quick Wins for the Next 30 Days
Set Up Branded Search Tracking in GSC
Create a regex filter combining your brand name, common misspellings, and product names. This is one of the most important KPIs for AI search impact.
Audit AI Crawler Access
Review your robots.txt for AI bot access rules. Ensure important content is accessible to relevant AI crawlers.
Establish Baseline Metrics
Document current traffic sources, brand mentions, and homepage traffic as baseline for future AI impact measurements.
Strategic Positioning
🎯Long-term Positioning Strategies
Content Quality Over AI Gaming
As Ray warns: 'Just because it's easy/free to automate content creation doesn't mean you always should. In many cases, it's playing with fire.' Focus on unique, valuable content.
- • Original research and data
- • Expert interviews and quotes
- • Unique case studies
- • Practical, tested advice
Authority Building Across Multiple Channels
Solís emphasizes: 'Let's also not forget that SEO goes beyond optimizing for Google. SEO is about optimizing for any platform used as a search channel. There's SEO for YouTube, SEO for TikTok. There will be SEO for AI search platforms.'
- • Google Search
- • YouTube
- • Industry Publications
- • TikTok
- • Podcast-Plattformen
- • Community-Foren
Measurement Framework
📊KPIs That Actually Matter
| Metric | Priority | Reason |
|---|---|---|
| Branded Search Impressions | Hoch | Shows AI-driven brand awareness |
| Homepage Traffic | Hoch | Captures direct navigation after AI discovery |
| Customer Journey Attribution | Mittel | Qualitative insights from sales/support |
| Direct AI Tool Traffic | Niedrig | Still too small for most sites |
Tool Stack Recommendations
Based on the SEOFOMO survey and expert opinions, here are the most proven tools for AI search monitoring and optimization:
Essentials (Proven)
- Google Search ConsoleFree
- Google Analytics 4Free
- Ahrefs / SemrushPaid
AI-Specific (Emerging)
- ProfoundAI Citations
- ChatGPT (testing)Manual
- Custom ScriptsTech Team
Case Studies & Real Examples
The most valuable insights come from real examples and case studies shared by LinkedIn SEO experts. These examples show both successes and cautionary tales from the field.
Success Stories
🏆Amsive: Data-Driven AI Visibility
Lily Ray shared a perfect example of successful AI search visibility: 'My teammate Will Guevara wrote an awesome, original, data-driven article last week for the Amsive blog about conversion rates in LLMs vs. organic search. Today, I see his article cited and mentioned in ChatGPT, Google AI Overviews, Google AI Mode, Gemini, Perplexity, and Claude.'
Success Factors:
- ✓ Original data analysis
- ✓ Unique, helpful content
- ✓ Authoritative digital marketing agency blog
- ✓ Following SEO best practices for years
"Sorry to say, but no GEO magic fairy dust required... just a helpful, unique article on an authoritative digital marketing agency blog that has followed SEO best practices for a while."
📈Publisher: Brand + Content Queries Growth
Ray shared data from a publisher heavily impacted by AI Overviews but making a name for itself with specific content: 'The publisher is seeing a big surge in Discover traffic right around the time its branded queries started surging.'
Observed Patterns:
- • Brand + 'content' queries growing
- • Discover traffic surge
- • Correlation between both metrics
Lessons Learned:
- • Branded impressions are a leading indicator
- • Quality content builds brand associations
- • Multiple channels reinforce each other
Cautionary Tales
⚠️Aggressive AI Content Scaling Backfires
Ray has observed a troubling trend on LinkedIn: 'Interesting - but not surprising - to see people on LinkedIn sharing their stories of losing all search visibility (sometimes overnight) after an aggressive AI content strategy.'
Common Mistakes:
- × Scaling content with no original insights
- × Pages generated primarily for SEO/AEO purposes
- × No human oversight of AI content
- × Ignoring spam policies
"Just because it's easy/free to automate content creation doesn't mean you always should. In many cases, it's playing with fire."
🚨AI Overviews Scam Problem
Ray was quoted in The Washington Post about a new type of scam in AI Overviews: 'Scammers have discovered that they can flood user-generated content sites and forums with fake phone numbers for major businesses, then trick callers into sharing their credit card information.'
Systemische Probleme:
- • AI tools citing unverified UGC content
- • Too easy to influence AI Overviews
- • Insufficient 'AI can make mistakes' disclaimers
- • Users implicitly trust Google results
Ray's assessment: 'This was something a lot of us saw as inevitable for 2+ years, by the way. It's still way too easy to influence AI Overviews, and it's unsurprising that they will occasionally produce dangerously incorrect answers.'
Future Outlook & Conclusion
After analyzing hundreds of LinkedIn posts, survey results, and expert opinions, a clear picture of the AI search landscape emerges. While demand for AI search optimization is high, the measurable business impact remains minimal for most companies.
🔮Realistic Timeline Expectations
2025: Year of Foundations
- • AI search remains complementary to traditional search
- • 0-5% revenue share expected for most sites
- • Focus on brand building and E-E-A-T
- • Experimentation with tracking and measurement
2026-2027: Maturation and Integration
- • Improved quality controls in AI platforms
- • Clearer ROI measurements and attribution
- • Integration of AI search into standard SEO workflows
- • Potentially 10-15% revenue share for early adopters
Technology Evolution Predictions
Based on expert observations, several key developments will shape the future of AI search:
Improved Quality Signals
As Ray predicted: 'I don't see this lasting forever, and I imagine savvy internet users will eventually begin to realize how skewed and biased AI results are.' AI platforms will need to implement better E-E-A-T signals.
Ad Integration and Monetization
Eli Schwartz's prediction: 'Google won't launch AI mode as the default until you see ads being successfully placed into AI mode.' Commercial viability will drive product decisions.
Hybrid Search Experiences
Ray's vision: 'I think Google will find a way to incorporate the best parts of AI Mode with the best parts of Search.' Future search experiences will switch contextually between AI answers and traditional results.
Strategic Preparation Recommendations
🎯The 3-Pillar Strategy for 2025
Strengthen Foundation
E-E-A-T, technical SEO, content quality - the fundamentals that work across all search platforms
Measure & Learn
Establish baselines, implement brand tracking, experiment with AI tools without sacrificing core performance
Prepare for Future
Build multi-platform presence, develop brand authority, optimize for quality over quantity
Final Thoughts
Perhaps the most valuable lesson from the LinkedIn SEO expert analyses is Solís' perspective on industry evolution:
"LLMs are expanding and evolving (not killing) search as a discovery/marketing channel, and yes, some shifts will be needed but if you've been doing SEO for a while, as I have since 2007 you know how search platforms and user behavior are always shifting. The SEO I do now has nothing to do with what I started with back in 2007... and I remember how some were saying SEO was dying already back then."
The data shows clearly: AI search is a reality, but one that complements traditional search rather than replacing it. Companies that focus on high-quality content, strong brand signals, and proven SEO fundamentals will be best positioned to benefit from this evolution, regardless of how the technology develops.
✨Key Takeaway for 2025
Invest in timeless SEO principles. Experiment with AI tools. Measure everything. But never sacrifice proven strategies for unproven trends.
This analysis is based on public LinkedIn posts and survey results from leading SEO experts between September 2024 and January 2025. All quotes are used with permission and follow fair use guidelines for educational content.
Author
Falco Schneider
Founder, Ultra Relevant
Published
January 16, 2025
20 Min Read
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