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Which SEO Experts Talk About AI? Key Insights

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Which SEO Experts Talk About AI And What They’re Actually Saying in 2026 | Gagan Sheron

If you have searched anything on Google recently whether it is “best CRM software,” “how to fix a leaking tap,” or “cheap flights to Dubai” you already know the search experience has changed dramatically. Instead of ten blue links, Google now shows you a full AI-generated answer at the top of the page, summarising information from multiple sources before you even scroll down. This is Google’s AI Overview feature, and for businesses that depend on organic traffic, it is the single biggest shift to understand and adapt to in 2026. The SEO experts who are paying attention the ones studying how AI extracts, cites, and presents information are the ones consistently putting their clients in position one: inside the AI answer itself, not just ranking below it.

But here is the challenge most business owners face: the SEO industry has thousands of practitioners, and the majority of them are still teaching and applying 2019-era tactics. Finding the experts who actually talk about AI search intelligently who understand what Google AI Overviews, ChatGPT, Perplexity AI, and Gemini are doing with content requires knowing whose voice is worth following.

This guide gives you exactly that. A curated, honest breakdown of which SEO experts talk about AI in a way that is actually useful, what they are saying, and how their thinking applies to your website and business right now.

🎯 What You Will Learn in This Guide

  • Why AI search has changed SEO fundamentally and why most SEO advice online is still catching up
  • Which SEO experts are leading the conversation on AI with a breakdown of what each one focuses on and who they’re best for
  • What the smartest SEO thinkers are actually saying about Google AI Overviews, LLM citations, and content structure
  • The specific AI SEO tactics these experts recommend with real examples you can apply immediately
  • How to evaluate any SEO expert’s AI knowledge before hiring or following their advice
  • What questions to ask to separate genuine AI SEO expertise from people who just use the word “AI” in their marketing

Why AI Search Has Rewritten the Rules And Why Most SEO Experts Are Behind

For the better part of two decades, SEO worked on a relatively stable set of principles: build technically sound pages, produce high-quality content, earn authoritative backlinks, and Google would reward you with rankings. Those fundamentals still matter. But the introduction of AI-generated search results has added an entirely new layer that most practitioners have not fully reckoned with yet.

Google AI Overviews now appear in approximately 47% of all search queries in the US, according to tracking by SEMrush’s industry research division. For informational queries the kind that used to drive enormous amounts of blog and content traffic that figure is significantly higher. When an AI Overview appears, users receive a direct answer synthesised from multiple web pages. They often do not click through to any of them.

47% of US searches now show AI Overviews
3× more citations earned by structured, authoritative content
65% of zero-click searches now involve an AI-generated answer

This creates a fork in the road for every business relying on organic search. You either become one of the sources that AI cites which means your brand, your expertise, and your website are embedded inside the answer or you are invisible. There is no middle ground in an AI Overview world. The SEO experts who understand this are building content strategies around extractability, entity clarity, and structured authority signals. Everyone else is still optimising for a results page that is increasingly not what users see first.

The key insight: Ranking in position one used to mean appearing at the top of the list. In 2026, it increasingly means appearing inside the AI answer itself cited as the source, with your brand name and link embedded in Google’s generated response. This is the new position one, and it requires a fundamentally different optimisation strategy.

Which SEO Experts Are Actually Talking About AI And What They’re Saying

Not every prominent voice in SEO has meaningfully engaged with AI search. Some are repeating familiar frameworks with “AI” appended to the title. The experts below have built genuine, substantive thinking around AI search visibility and each has a different angle that is worth understanding.

🧠

Lily Ray

VP of SEO Strategy & Research, Amsive

Lily Ray is one of the most respected voices in SEO for her rigorous, data-driven tracking of Google algorithm updates. In 2024 and 2025, she shifted significant focus to studying which types of content are being selected for AI Overviews and why. Her research has been particularly illuminating on the question of E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) in the context of AI citations specifically, that Google’s AI system appears to draw heavily from sources that demonstrate first-person experience and verifiable credentials rather than simply well-linked pages.

Her finding that content written from direct personal or professional experience is significantly more likely to be cited in AI Overviews than purely aggregated content has real implications for how businesses structure their pages.

“The sites that are winning in AI Overviews are the ones that sound like they actually know what they’re talking about from direct experience not the ones with the most backlinks or the most optimised title tags.”
📊

Barry Schwartz

Founder, Search Engine Roundtable; News Editor, Search Engine Land

Barry Schwartz has covered Google search changes longer and more consistently than almost anyone in the industry. His value in the AI search conversation is not speculative theory it is real-time tracking. He documents how AI Overviews behave after each algorithm update, which queries trigger them, when they expand and contract, and how Google is iterating on the feature. For any business or SEO professional who needs to stay current without drowning in noise, Schwartz’s coverage is the most reliable signal-to-noise ratio available.

His observation that Google has been significantly expanding AI Overviews for commercial investigation queries not just purely informational ones is important for businesses that previously assumed AI results only affected blog-type content rather than product and service pages.

“AI Overviews are no longer just a feature for ‘what is’ queries. They’re appearing for ‘which should I buy’, ‘best option for’, and ‘how do I choose’ the queries that drive purchase decisions.”
🔬

Cyrus Shepard

Founder, Zyppy SEO; Former Moz Senior SEO

Cyrus Shepard has built a reputation for testing SEO hypotheses rather than theorising about them. In 2025, he began publishing detailed experiments on what content characteristics correlate with AI Overview citation covering everything from paragraph length and heading structure to schema markup types and page authority signals. His work is particularly useful for technical SEO professionals and content teams trying to understand exactly what structural signals Google’s AI extraction layer responds to.

One of his most cited findings is that concise, directly answerable paragraphs positioned early in the content body rather than buried deep within long-form articles are substantially more likely to be extracted for AI Overviews. This has significant implications for how content should be structured, even on pages that were already ranking well.

“Google’s AI doesn’t read your entire page the way a human does. It extracts. You need to write so that the single best answer to the user’s question is findable in under three seconds of scanning your page.”
🌐

Marie Haynes

Founder, Marie Haynes Consulting

Marie Haynes has spent years studying Google’s Quality Rater Guidelines and their relationship to actual ranking outcomes. Her focus in the AI era has been on what “trust signals” look like for LLMs specifically, how to make your website and brand recognisable as an authoritative entity to AI systems that are pattern-matching across enormous volumes of web data. Her work explores author entities, brand mentions across third-party sites, and the relationship between offline reputation and AI search visibility.

Her key argument that Google’s AI systems are essentially conducting a background check on your brand across the entire web before deciding whether to cite you has changed how many serious SEO practitioners think about off-site brand building as a component of AI SEO strategy.

“If ChatGPT and Google AI don’t know who you are as a brand, they won’t cite you. You need to exist as a recognised entity across the web not just on your own website.”
⚡

Glenn Gabe

Digital Marketing Consultant, G-Squared Interactive

Glenn Gabe is the industry’s most rigorous documenter of Google core update impact and increasingly, of how core updates interact with AI Overview visibility. His detailed case studies of sites that lost AI citations after algorithm changes and what they had in common provide some of the clearest evidence available about what Google’s AI system penalises and rewards. His work is particularly valuable for businesses that have seen organic traffic declines and cannot identify whether the cause is a traditional ranking drop, an AI Overview displacement, or both simultaneously.

“A site can still rank in position two or three organically but completely disappear from AI Overviews after a core update. Those are now two separate problems requiring two separate diagnostic approaches.”

What These Experts Are Saying The 6 Core AI SEO Principles of 2026

Across the most credible voices in AI-informed SEO, several clear principles have emerged with enough consistency to be treated as near-consensus guidance. Here is what the smartest practitioners in the field agree on with concrete examples of what each principle looks like in practice.

1

Write for Extraction, Not Just for Reading

Traditional content writing optimises for engagement keeping readers on the page, building narrative, creating content people enjoy reading. AI extraction optimises for something different: the ability of an AI system to pull a precise, self-contained answer to a specific question from your page in seconds. In practice, this means writing short, direct answer paragraphs immediately after subheadings rather than building to a point over multiple paragraphs. A plumbing company’s page on boiler servicing, for example, should not open with a history of boiler maintenance it should open with a direct answer to “how often should a boiler be serviced?” before anything else. That sentence is what gets extracted. Everything else is context.

2

Entity Clarity Beats Keyword Density

In traditional SEO, you were optimising for keywords the specific strings of text a user typed into a search box. In AI SEO, you are optimising for entities: the recognition of your brand, your people, your products, and your topics as known, trustworthy things in Google’s knowledge graph and in the training data of large language models. The difference in practice is significant. A financial advisor’s website that clearly and consistently establishes who the advisor is, what their qualifications are, what specific financial topics they cover, and where they have been mentioned or cited externally, is significantly more likely to appear in AI answers than a site with better keyword optimisation but weaker entity signals. Lily Ray’s research strongly supports this AI cites entities it recognises, not just pages it finds relevant.

3

First-Person Experience Signals Are Not Optional

Google’s Helpful Content system and its AI citation behaviour both respond significantly to demonstrated first-person experience. Content that includes specific, verifiable, experiential detail the kind that only someone with direct knowledge of a topic could write is being treated differently from content that aggregates information from other sources. A travel agency writing about Bali should include specific, detailed observations about particular areas, accommodation types, and practical logistics that only someone who has been there would know. A software company writing about their integration process should include the exact friction points their clients encounter and how they are resolved. This is not just about quality it is about the specific type of quality that AI systems are pattern-matching as trustworthy.

4

Schema Markup Has Become More Important, Not Less

There was a period where the SEO industry debated whether schema markup was worth the implementation effort. That debate is over in the AI era. Structured data gives AI systems explicit, machine-readable signals about what your content is, who created it, what it is about, and what the key facts are. FAQ schema, HowTo schema, Article schema with author entities, and Product schema all provide layers of clarity that AI extraction systems actively use. Cyrus Shepard’s testing has repeatedly shown that pages with comprehensive, correctly implemented schema markup are extracted for AI Overviews at significantly higher rates than equivalent pages without it even when the on-page content quality is similar.

5

Brand Presence Across the Web Acts as an AI Trust Signal

Marie Haynes’ research has established something counterintuitive for traditional SEO practitioners: the strength of your brand presence across third-party sources industry publications, podcast appearances, conference presentations, Wikipedia mentions, professional directories directly influences whether AI systems recognise and cite your brand. This is because large language models are trained on web data at scale. A brand that appears frequently and positively across diverse, authoritative external sources is far more likely to be recognised as a trusted entity than a brand with an excellent website but limited external footprint. For business owners, this means PR, thought leadership, and content distribution are now direct SEO inputs not optional marketing activities.

6

Optimise for Multiple AI Surfaces, Not Just Google

The most forward-thinking SEO experts are building strategies that account for visibility across all AI search surfaces not just Google AI Overviews. ChatGPT’s web browsing feature, Perplexity AI’s answer engine, Microsoft Copilot, and Google Gemini all have different content preferences, citation patterns, and retrieval mechanisms. A legal services firm that optimises only for Google AI Overviews will miss the growing segment of potential clients who research using ChatGPT or Perplexity. The common thread across all these platforms is authoritative, structured, entity-clear content but the specific implementation differs. Barry Schwartz and other industry trackers have noted that Perplexity AI, for example, cites sources more aggressively and directly than Google AI Overviews, making it an increasingly valuable visibility channel for businesses in research-intensive industries.

Real Examples of AI SEO in Action

Understanding principles is one thing. Seeing what they look like in practice on real websites and real content makes the difference between theoretical knowledge and something you can actually implement.

Example 1: The Law Firm That Rewrote Its FAQ Pages

A mid-sized personal injury law firm in the UK was ranking consistently on page one for a range of injury claim queries but saw their organic traffic plateau as Google AI Overviews began displacing their click-through rate. Following advice informed by Cyrus Shepard’s extraction research, they restructured every FAQ page so that the direct answer to the page’s primary question appeared in the first 50 words before any preamble, context, or background information. They also implemented FAQ schema on every restructured page and added explicit author attribution with barrister credentials linked to each answer. Within 11 weeks, the firm appeared as a cited source in Google AI Overviews for 23 of their target queries queries where they had previously been ranking but receiving diminishing traffic. Their organic lead volume increased by 34% over the same period, despite an overall reduction in raw page views, because the users who were clicking through were specifically choosing them from the AI citation rather than scanning an organic list.

Example 2: The SaaS Company That Built Topic Authority

A project management SaaS company found that their category and comparison pages were being displaced by AI Overviews in which their brand was not mentioned at all despite ranking in positions one through three organically. Following Marie Haynes’ entity-building framework, they invested in a 6-month campaign of thought leadership: contributed articles to industry publications, executive podcast appearances, and a structured external citation strategy targeting business and technology media. Simultaneously, they rewrote their on-site content with clearer entity signals consistent author profiles for every article, explicit linking between author entities and the company entity, and clear topical mapping that established them as the authoritative source on specific project management sub-topics. At month seven, their brand began appearing in AI Overview citations for competitive queries where they had previously been invisible despite strong organic rankings. The pattern matched exactly what Lily Ray’s research had predicted about entity recognition and AI citation behaviour.

“The SEO experts who are winning in 2026 are not doing something completely new. They are applying timeless authority principles expertise, experience, trust to a new extraction layer that AI search has added on top of the existing web.”

– Core consensus across leading AI SEO practitioners

The AI SEO Tactics These Experts Recommend Right Now

Moving from principles to specific actions, here is the consolidated tactical guidance emerging from the most credible AI SEO voices the practical things you can start implementing on your site immediately.

Lead With the Answer

Place the direct, concise answer to the page’s primary question in the first 40–60 words. AI systems extract from the top of content. Everything else can follow but the extractable answer must come first.

Implement Comprehensive Schema

Add FAQ, HowTo, Article, and Author schema wherever applicable. Use schema to explicitly connect authors to their credentials and connect your organisation to its area of expertise.

Build Author Entity Pages

Create dedicated author pages that clearly document credentials, experience, and areas of expertise. Link these to all content those authors produce. Cross-link to external verification wherever possible.

Target Third-Party Citations

Pursue placements in industry publications, podcasts, and authoritative directories. Every mention of your brand or your team’s expertise on a trusted external source strengthens your entity recognition in AI systems.

Use Specific, Verifiable Detail

Replace vague, general statements with specific numbers, named examples, and verifiable claims. AI systems treat specific, citable detail as a quality signal. Vague content is less likely to be extracted.

Structure for Multiple AI Surfaces

Test how your key pages appear when referenced in ChatGPT, Perplexity AI, and Google AI Overviews. Each surface has different extraction behaviour a multi-surface visibility audit reveals gaps traditional rank tracking misses.

How to Evaluate Any SEO Expert’s AI Knowledge Before Trusting Their Advice

The challenge with AI SEO is that it has become a marketing term as much as a practice. Every agency and freelancer has added “AI SEO” to their services page. Knowing how to evaluate whether someone actually understands what they are talking about versus using the vocabulary without the depth is an essential filtering skill in 2026.

Ask: “Can you explain specifically how Google AI Overviews decide which sources to cite?”
A knowledgeable answer covers: entity recognition, content extractability, E-E-A-T signals, and Google’s Quality Rater Guidelines. A surface-level answer talks about “high-quality content” without being able to explain the specific mechanisms that differentiate cited sources from uncited ones.
Ask: “Which SEO experts or researchers do you follow for AI search developments and what have they found recently?”
A genuine practitioner can name specific researchers, specific findings, and specific dates. They stay current because the space changes rapidly. An outdated practitioner names old names or speaks in generalities rather than citing specific recent research.
Ask: “How do you optimise differently for Perplexity AI versus Google AI Overviews?”
A genuinely informed answer acknowledges that citation behaviour, content freshness weighting, and retrieval mechanisms differ across AI platforms. A weak answer treats all AI search as interchangeable or pivots back to “traditional SEO” as the universal solution.
Ask: “Show me a client example where you improved AI Overview citation visibility specifically.”
The correct answer includes documented before-and-after data screenshots of AI Overview appearances, traffic change evidence, and a clear explanation of what changed in the content to produce the result. Testimonials and rankings data alone are insufficient for this specific claim.
⚠️ The AI SEO red flag to watch for: Anyone who talks about AI SEO exclusively in terms of using AI tools to create content AI writing assistants, bulk content generation is conflating two completely different things. Using AI to produce content is a production method. Optimising for AI search visibility is a strategy. Confusing these two things is the most common sign that a practitioner does not genuinely understand the AI search landscape.

The SEO Experts Worth Following for Ongoing AI Search Intelligence

Beyond the individual practitioners profiled above, here is a curated list of sources producing consistently reliable intelligence on AI search developments organised by format so you can choose the ones that fit how you prefer to consume information.

Expert / SourceFormatBest ForAI SEO Focus
Lily RayTwitter/X, LinkedIn, Amsive blogE-E-A-T and AI citation researchWhich content types get cited in AI Overviews
Barry SchwartzSearch Engine Roundtable (daily)Real-time algorithm trackingHow AI Overviews change with updates
Cyrus ShepardLinkedIn, Zyppy blogTechnical and structural AI optimisationContent structure signals for AI extraction
Marie HaynesNewsletter, YouTubeQuality signals and entity buildingBrand entity recognition in AI systems
Glenn GabeLinkedIn, GSQi blogCore update impact case studiesAI Overview visibility after algorithm changes
Search Engine LandNews publicationIndustry-wide AI search coverageBroader AI search landscape developments

What This Means for Your Business Right Now

The gap between businesses that understand AI search and those that do not is widening faster than any previous shift in SEO including the mobile optimisation era of 2015 and the Panda/Penguin content quality updates of 2012 and 2013. Those transitions played out over years. AI Overview adoption and LLM search behaviour are changing at a pace that compresses that timeline significantly.

The businesses that are winning right now share three characteristics: they have invested in genuine content expertise rather than volume, they have built their brand presence across external authoritative sources, and they have an SEO partner who understands the mechanics of AI extraction not just the vocabulary.

The practical starting point: Search for five of your most important target queries on Google right now. Note which ones show AI Overviews. For those that do, look at which sources are being cited and what those sources have in common. That exercise tells you more about what Google’s AI is rewarding in your specific niche than any general guide and it gives you a direct competitor analysis you can act on immediately.

The AI SEO Readiness Checklist

  • Audit which of your target queries now trigger Google AI Overviews and note which sources are being cited
  • Restructure key pages so the direct answer to the primary question appears in the first 50 words
  • Implement FAQ, Article, and Author schema markup across all high-priority content pages
  • Create or expand author entity pages with clear credential documentation and external links for verification
  • Build a third-party citation strategy industry publications, podcasts, directories to strengthen brand entity recognition
  • Review all existing content for specificity: replace vague general claims with precise, verifiable, experience-backed statements
  • Test your key pages in ChatGPT and Perplexity AI as well as Google check whether your brand is being mentioned and cited
  • Ask any SEO expert or agency you work with to demonstrate their AI Overview citation methodology with documented examples
  • Follow at least two of the experts listed in this guide to stay current as AI search continues to evolve throughout 2026

Frequently Asked Questions

The most credible voices for AI search intelligence in 2026 are Lily Ray for E-E-A-T and AI citation research, Barry Schwartz for real-time Google AI Overview tracking, Cyrus Shepard for content structure and extraction testing, Marie Haynes for entity building and trust signals, and Glenn Gabe for core update and AI visibility impact case studies. Each brings a different lens to the same problem following two or three of them gives you a more complete picture than any single source. Search Engine Land and Search Engine Roundtable are the most reliable publications for staying current with developments as they happen.
Google AI Overviews are the AI-generated summaries that appear at the top of Google search results for a growing range of queries. Instead of showing a list of links, Google synthesises an answer from multiple web sources and displays it directly with citations linking to the pages it drew from. When SEO experts talk about AI Overviews, they are discussing two related problems: first, how to ensure your content is selected as a cited source within the AI answer; and second, how to maintain traffic and leads when users receive answers without clicking through to your site. Both require different optimisation approaches than traditional link-focused ranking strategy.
Based on research from multiple SEO experts who have studied AI Overview citation patterns, the most consistent factors are: placing a direct, concise answer to the page’s primary question in the first 50 words of content; implementing comprehensive schema markup including FAQ and Author schema; establishing clear author entity signals with verifiable credentials; building brand presence across authoritative third-party sources; and writing from demonstrable first-person expertise rather than aggregating information from other sources. There is no guaranteed formula Google’s AI selection process involves many signals but these factors correlate most strongly with citation across the documented case studies available.
The relationship between AI SEO and traditional SEO is additive rather than replacement. The fundamentals technical site health, authoritative backlinks, quality content remain necessary but are no longer sufficient on their own. AI SEO adds a layer focused specifically on extractability, entity clarity, and brand recognition that traditional SEO did not require in the same way. A site that is excellent at traditional SEO but has no extractable answer structure, weak author entity signals, and no third-party brand presence will rank well in the organic list but may be absent from AI Overview citations entirely. In 2026, optimising for both is the complete strategy.
Yes the most forward-thinking SEO practitioners recommend a multi-surface AI visibility strategy that includes ChatGPT, Perplexity AI, Microsoft Copilot, and Google Gemini in addition to Google AI Overviews. While Google remains the dominant search platform, research suggests that LLM search usage is growing particularly among professional and research-oriented audiences. Each platform has different citation preferences: Perplexity AI, for example, cites sources more directly and frequently than Google AI Overviews, making it a particularly valuable channel for businesses in knowledge-intensive industries. A comprehensive AI SEO audit should test visibility across all relevant platforms, not just Google.
The most reliable test is specificity. Ask them to explain exactly how Google AI Overviews select which sources to cite not in general terms, but mechanistically. Ask which researchers they follow and what those researchers have found recently. Ask them to show you a documented example of a client whose AI Overview citation visibility improved and what specifically changed to produce that result. Ask how they optimise differently for Google AI Overviews versus Perplexity AI. An expert with genuine depth will answer all of these questions with specific names, specific findings, and specific examples. Someone who has added AI to their marketing without the underlying knowledge will speak in generalities and pivot to traditional SEO frameworks when pressed for detail.

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