Which external content sources are preferred by AI?

An academic paper updated last year (“From Generation to Judgment: Opportunities and Challenges of LLM- as-a-Judge”) surveyed the emerging field of ‘LLM judges’ (that is, AI systems built to evaluate, score, and ‘judge’ inputs — or their own outputs). One thing is clear from the research: AI systems are getting increasingly good at content evaluation.

Understanding how LLMs are currently used for evaluation across various use cases — and what criteria they excel (or fail) at assessing — can give us some insights into how AI platforms may evaluate and select citations from external content (like yours!).

AI researchers (see sources under ‘Further Reading’ below) have found that LLMs prefer content that is:

• Relevant to the questions users are asking 
• Coherent, well-evidenced, and logically structured 
• Validated by others (ie, highly cited or frequently mentioned by others) 
• Includes credible citations to others, substantiating its claims and trustworthiness
• “Helpful, honest, and harmless” (See notes on Claude’s ‘Constitution’, below)
• Complete in its topical coverage
• Recent 
• Easily extractable

“We need to understand how AI interprets our content and generates answers so we can adapt our strategies and ensure our content appears in results.”

— Ana Perez, SEO Manager

Why content quality matters more than ever in the age of AI search

Your content quality matters in AI search because generative systems rely heavily on retrieval signals, source reputation, and structured knowledge to decide which content to incorporate into their answers. Modern AI-powered search experiences do not generate responses from thin air — they draw from indexed web content, ranked sources, and retrieval-augmented pipelines. 

When determining which external sources to cite, summarize, or rely on, AI systems draw on many of the same credibility signals that underpin traditional ranking systems: domain authority, consistent authorship, factual alignment, and corroboration across trusted sources. 

In practice, high E-E-A-T (experience, expertise, authority, and trustworthiness) content is more likely to be retrieved, retained in context, and considered safe to reuse in AI-generated answers.

SEO professionals will already be very familiar with the concept of E-E-A-T. The idea stems from Google’s internal Search Quality Rater Guidelines, the massive manual used by thousands of human testers to grade Google’s search algorithm.

First popularized as a benchmark for “Your Money or Your Life” (YMYL) topics, E-E-A-T has evolved from a niche set of quality guidelines into a foundational pillar of how search algorithms identify and reward the most credible voices in any given field. 

E-E-A-T can also serve as a strong content framework for GEO/AEO, as AI search systems have an incentive to prioritize factually accurate, credible, trustworthy content in order avoid the reputational damage caused by LLM hallucinations (we’ve all seen plenty of examples of this in the press over the past few years!).

On content quality in the age of AI search:

“Content quality is always going to be a trending topic, but even more so in 2026. Brands that rely too heavily on AI to write copy will struggle to demonstrate genuine E-E-A-T. Google and OpenAI’s models are already learning to evaluate who is behind the content, why it exists, and what value it adds, so I would say content quality should be on everyone’s radar! “

—Chloe Steele, SEO Account Manager at Verde Digital

(Hear more from Chloe in our Lumar webinar session: “SEO & GEO Trends for 2026”) 

AI’s grading rubric: how LLMs can evaluate content quality today

To understand why some content is cited and others ignored, we must look at how AI evaluates quality. 

The LLM-as-Judge paper we mentioned before outlines the primary benchmarks that today’s AI systems can use to “judge” external inputs as well as their own outputs. For a piece of content to survive the AI’s internal filtering process, it should score high across six critical areas:

• Helpfulness 
• Harmlessness
• Relevance 
• Reliability 
• Feasibility, and
• Overall Quality

These aren’t just abstract concepts; they are specific metrics an AI “judge” might use to decide if your content is authoritative enough to present to a user.

But are these AI-powered evaluations actually being implemented by public-facing AI platforms today? Yes, it seems so.

Anthropic’s Claude 2 Model Card, for example, discusses their work to train Claude on the three H’s; they have explicitly stated that they are training their LLM to be Helpful, Honest, and Harmless.

Per the Claude 2 Model Card document:

“Our core research focus has been training Claude models to be helpful, honest, and harmless. Currently, we do this by giving models a Constitution – a set of ethical and behavioral principles that the model uses to guide its outputs.”

“You can read about Claude 2’s principles in a blog post we published in May 2023 [See: Claude’s Constitution]. . . . We use the constitution in two places during the training process. During the first phase, the model is trained to critique and revise its own responses using the set of principles and a few examples of the process. During the second phase, a model is trained via reinforcement learning, but rather than using human feedback, it uses AI-generated feedback based on the set of principles to choose the more harmless output.”

Industry analysis of Google’s documentation suggests that its AI Overviews are not a fully separate silo; they are powered in part by some of the same core ranking systems as traditional search, including the “Helpful Content System.” If content is deemed “helpful” and demonstrates strong E-E-A-T according to Google’s search evaluation criteria, chances are, it’s also more likely to be considered a valuable source for AI summarization.

When it comes to other companies’ AI search tools, like those embedded in Microsoft Bing, we also have clues that these AI systems are being developed to prioritize trustworthy content. In Microsoft’s “Responsible AI” document, it underscores Microsoft’s commitment to “Fairness,” “Reliability & Safety,” and “Transparency” in its AI systems. For Bing’s Copilot to be reliable, safe, and transparent, the sources it uses for information should be demonstrably accurate and trustworthy.

Likewise, in Perplexity’s help articles, it states that: “When you ask Perplexity a question, it uses advanced AI to search the internet in real-time, gathering insights from top-tier sources.” — Again, content quality and E-E-A-T signals are at work here.

“SEO best practices remain essential even as AI search grows. Focus on building brand visibility across multiple channels, creating AI-friendly content with structured headings and quotable insights, researching real user questions, and incorporating first-party data and unique perspectives. Above all, make your content genuinely helpful.”

— Ana Perez, SEO Manager

How to improve EEAT for GEO

As AI-generated content floods the web, human expertise is becoming a differentiating factor rather than a baseline expectation. LLMs are increasingly trained to recognize who produced content, why it exists, and what real-world experience backs it up. Surface-level content is increasingly filtered out in favor of genuinely authoritative sources.

As Jon Clark, Managing Partner at Moving Traffic Media, puts it:

On taking E-E-A-T to the next level:

“With all this AI-generated content spilling out onto the web, human expertise is about to become a major differentiator. Again. It’s the un-apologetic authors, the credentials that stand up to scrutiny and the real hands-on experience that sets the regurgitated reviews and surface-level tat apart from genuine authority.

[In] 2026, both Google and the AI systems they’re building will be looking for the all-important trust credentials – where did that insight come from, and who put their name on it.”

• (Note: You can hear more from Jon in his Lumar GEO/AEO webinar session, “The New Metrics of AI Search – GEO/AEO KPIs You Should Track Now.” )

Content Quality Checklist for GEO / AEO

Practically, creating high-quality, strong E-E-A-T content for generative engine optimization means incorporating the following into your content production workflows:

□   Named authorship with verifiable credentials — Content attributed to real experts with demonstrable experience signals trust to both human readers and AI systems evaluating source quality.

□  First-party data and original research — Proprietary statistics, surveys, and case studies give AI systems unique, citable material that they cannot source elsewhere.

□  Factual accuracy and consistency — Contradictions between pages on your own site, or between your content and established facts can erode AI trust in your brand as a reliable source.

□   Transparent sourcing — Citing reputable external references, studies, and named experts reinforces the factual grounding of your content.

New Lumar tools for GEO content optimization

Explore Lumar’s powerful platform features for GEO content optimization:

• GEO Content Evaluation Tools
• AI Visibility Tracking Tools
• The Full Lumar GEO / AEO Platform

Get Lumar’s FULL guide to GEO / AEO

Ready to dive deeper into how to build a strong GEO / AEO strategy for AI search? Get our full, free “AI Search Optimization Playbook” now.

The Ultimate Guide to GEO

Get the full GEO/AEO playbook

This post is an excerpt to our 80-page guide to GEO / AEO – Get the FULL AI Search Playbook for free here.

About Lumar’s GEO / AEO explainer series

In this Lumar series, we’re exploring strategies for generative engine optimization (GEO), also known as answer engine optimization (AEO) — that is, how to boost your brand’s AI visibility and likelihood of earning mentions or citations from LLMs and AI-powered platforms like ChatGPT, Claude, Gemini, Perplexity, or Google’s AI Overviews and AI Mode.

The post LLM-as-a-Judge: How to Become a Preferred Content Source for AI Answers appeared first on Lumar.

An introduction to Content GEO

Content GEO is about ensuring your content is built for both human understanding and AI retrieval, assessment, selection, and inclusion. It requires focus on publishing factually accurate, well-structured, semantically relevant, and comprehensive content that AI systems can extract, summarize, and cite confidently. 

For human readers, your content still needs to be clear, useful, accurate, persuasive, and easy to navigate. 

For AI systems, your content also needs to be structured in a way that makes its meaning, relevance, evidence, and expertise easy for machines to identify.

That means Content GEO is not about writing robotic copy or chasing GEO/ AEO “hacks.” It is about making your best expertise easier for machines to understand without making it less useful for people.

A good Content GEO strategy should address questions like:

• Is this content clearly about the topic it claims to cover?
• Does it answer the user’s question directly?
• Does it contain accurate, specific, and useful information?
• Does it show why the brand is qualified to speak on this topic?
• Can an AI system extract a useful answer from this page without misrepresenting it?
• Does the content strengthen the brand’s association with the topics it wants to own?

If Technical GEO determines whether your content is accessible to AI bots, Content GEO determines whether it is deemed useful, trustworthy, and likely to be chosen. It ensures that once an AI system can access your content, recognize your brand, and trust your authority (see also: Entity GEO and Brand Authority GEO), it has the right material to use when generating its responses for users.

Why It Matters Now: As AI-generated “slop” floods the web, LLMs are being trained to prioritize “helpful, honest, and harmless” content (the 3 Hs!). To survive the AI’s internal filtering process, your content must score high in helpfulness, reliability, and overall quality.

The Ultimate Guide to GEO

Get the full GEO/AEO playbook

This post is a companion piece to our 80-page guide to GEO / AEO – Get the FULL AI Search Playbook for free here.

Differences between SEO content and GEO content

Where traditional SEO content aimed to align with keyword queries, Content GEO focuses on satisfying AI reasoning — ensuring your brand’s insights, explanations, and expertise become the material LLMs rely on when generating answers.

In an AI-driven search landscape, your content adds yet another dimension to its role in your broader marketing toolkit; it becomes training material for the models shaping the future of online search.

“We need to understand how AI interprets our content and generates answers so we can adapt our strategies and ensure our content appears in results.”

— Ana Perez, SEO Manager

Traditional SEO content has often been built around ranking for a keyword and earning the click. Content GEO expands that goal.

In AI search, visibility may happen before, after, or without a website visit. Your content might influence an AI-generated answer even when the user does not click. Your brand might be cited directly, mentioned without a link, summarized as part of a recommendation, or omitted entirely.

That means content teams need to think beyond traffic alone. Content can now shape:

• AI understanding: Whether AI systems correctly understand what your brand knows, offers, and stands for.
• AI inclusion: Whether your content is selected as part of an AI-generated response.
• AI citation preference: Whether your content is chosen over a competitor’s when multiple sources could answer the same question.
• Brand-topic association: Whether AI systems consistently connect your brand with the topics that matter to your category.
• Answer accuracy: Whether AI systems describe your brand, products, services, and expertise correctly.

This does not make traditional SEO obsolete. Strong SEO fundamentals still matter. Many AI search experiences rely on traditional search indexes, established content signals, and web-wide authority signals. But Content GEO asks content teams to build pages that are not only optimized for ranking and reading, but also for retrieval and reuse.

Content SEO and Content GEO overlap, but they are not identical.

Traditional content-focused SEO tactics often start with a search query, keyword opportunity, ranking gap, or traffic goal. The main question is: How do we create the best page to rank and earn the click?

Content GEO starts with a slightly different question: How do we create the best source for an AI system to understand, trust, and use when generating an answer?

That shift changes the content brief.

A traditional SEO-focused content brief might emphasize target keywords, search volume, H1s, title tags, internal links, and SERP competitors. A GEO content brief still includes those considerations, but it also asks for clearer answers, more explicit definitions, stronger evidence, better topical alignment, visible expertise, and page sections (or ‘chunks’) that make sense when interpreted outside of the full page context.

The best Content GEO work does not abandon SEO. It raises the quality bar.

Where Content GEO fits in the AI visibility funnel

Content GEO sits primarily in the AI Understanding and AI Inclusion stages of the AI visibility funnel.

At the discovery stage, technical factors determine whether AI bots and search crawlers can access your content. That is the domain of Technical GEO.

But once your content can be accessed, the next questions are different:

• Can AI systems understand what this content is about?
• Can they connect it to the right topics and entities?
• Can they identify a useful answer?
• Can they evaluate the content as accurate, helpful, and trustworthy?
• Can they confidently include it in a generated response?

Those are Content GEO questions.

This is why Content GEO cannot operate in isolation. It works best when the other GEO pillars are already in motion. If AI cannot crawl your page, the content may not be discovered. If AI cannot recognize your brand as an entity, the brand may not be properly associated with the content. If AI does not see enough authority signals around your brand, even strong content may lose out to a more trusted source.

Content GEO is the layer that turns access and authority into usable answers.

“In 2026, GEO/AEO will be essential for visibility, requiring content to be highly structured, fact-based, and semantically rich to be considered authoritative enough for AI to reference.

Rather than chasing rankings alone, SEOs must now optimise for inclusion in zero-click, conversational responses — ensuring that brand-owned content is answer-ready and aligned with user intent at a granular level.”

— Rejoice Ojiaku, Senior Content Specialist at Wise

(Check out Rejoice’s Lumar webinar session: “SEO in the Age of AI: A Conversation on GEO, AEO & the Future of Search.”) 

How Content GEO influences AI search visibility

A strong Content GEO strategy can improve four key aspects of AI search visibility.

1. Extractability

Extractability is how easily an AI system can pull a clear, factual answer from your page.

Content that buries the answer under long intros, vague claims, or disconnected paragraphs is harder to reuse. Content that states the answer clearly, defines key terms, and explains the surrounding context is more likely to support AI-generated responses.

2. Citation preference

Citation preference is whether an AI system chooses your content instead of another source.

For competitive topics, AI systems often have multiple possible sources to draw from. Your content needs to give them a reason to prefer yours: clearer explanations, stronger evidence, better specificity, fresher information, original insights, or more complete coverage.

3. Topical association

Topical association is how consistently AI systems connect your brand with a specific subject area.

One optimized article rarely builds durable AI visibility on its own. Content GEO works best when individual pages support a broader topical footprint. Over time, your content should help AI systems understand what your brand is known for.

4. Completeness

Completeness is whether your content covers enough of the topic to satisfy the user’s real question and likely follow-up questions.

AI search experiences are conversational. A single prompt may imply several related needs. Content that only answers the narrowest version of a query may be less useful than content that anticipates the user’s next question, defines scope, addresses nuance, and points toward the right next step.

What Content GEO is not

Content GEO is not keyword stuffing for AI. It is not adding an FAQ block to every page and calling the job done. It is not generating thousands of generic articles to “feed” LLMs.

In fact, generic AI-written content can make the problem worse. If every brand publishes the same surface-level explanations, AI systems have little reason to choose one source over another.

Content GEO is about making your content more distinctive, more useful, more structured, and more grounded in real expertise.

That can include original research, expert commentary, unique customer insights, product knowledge, practical examples, data, comparisons, and clearly sourced claims. 

The goal is not simply to produce more content. The goal is to produce content that AI systems can confidently interpret as useful source material.

Your Content GEO checklist

The later posts in this GEO/AEO series will cover specific Content GEO tactics in depth. For now, use this as a strategic overview of what your GEO content program should be working toward: 

□  Write clear, factual, answer-first content that directly addresses user questions.

□  Optimize for semantic relevance and full coverage of related sub-topics.

□  Build evidence-based content with citations and sources.

□  Structure content into easily retrievable “chunks” (clear sections with H2/H3 headings.

□  Ensure entity clarity in ‘chunk’ passages (avoid pronouns replacing key entities).

□  Create multimodal content (video, audio, images) and add transcripts to video/audio; descriptive alt text to images.

□  Demonstrate E-E-A-T (Experience, Expertise, Authority, Trustworthiness) through expert authorship, original data, and transparent sourcing.

“The way forward is to treat content as a cross-platform ecosystem. Make videos, images, and audio AI-friendly with proper metadata, captions, and transcripts.

Ensure entity and topic alignment so AI systems recognize your authority, no matter the format.”

— Jon Clark, Managing Partner at Moving Traffic Media

• (Hear more from Jon in his Lumar GEO/AEO webinar session, “The New Metrics of AI Search – GEO/AEO KPIs You Should Track Now.” )

The bottom line: content is becoming AI source material

Content has always helped brands educate audiences, build trust, and drive demand. In the AI search era, it has another role: it becomes source material for the systems shaping how people discover, compare, and choose brands.

That does not mean every page should be written for machines first. It means content teams need to recognize that machines are now part of the audience. The strongest content will serve both: useful enough for humans to value, and clear enough for AI systems to understand, retrieve, and cite.

The brands that win in AI search will not be the ones that publish the most. They will be the ones that make their expertise easiest to understand, verify, and reuse.

About Lumar’s GEO / AEO explainer series

In this Lumar series, we’re exploring strategies for generative engine optimization (GEO), also known as answer engine optimization (AEO) — that is, how to boost your brand’s AI visibility and likelihood of earning mentions or citations from LLMs and AI-powered platforms like ChatGPT, Claude, Gemini, Perplexity, or Google’s AI Overviews and AI Mode.

Explore Lumar’s powerful platform features for GEO content optimization

• GEO Content Evaluation Tools
• AI Visibility Tracking Tools
• The Full Lumar GEO / AEO Platform

Get Lumar’s FULL guide to GEO / AEO

Ready to dive deeper into how to build a strong GEO / AEO strategy for AI search? Get our full, free “AI Search Optimization Playbook” now.

The post How to Optimize Your Content for AI Search Visibility appeared first on Lumar.

1. Technical GEO
2. Content GEO
3. Entity GEO
4. Brand Authority GEO (what we’ll be discussing here!)

What is brand authority GEO?

Brand Authority GEO is about building credibility, trust, and preference. Once AI recognizes your brand as an entity, it must decide whether your entity deserves to be included, cited, or recommended in its generative responses.

“Gaining visibility in AI isn’t about optimization—it’s about creating brand and trust signals so strong that AI would be foolish not to put you front and center.”

— Natasha Burtenshaw-deVries, Acquisition Marketing Manager at Well.ca 

The Ultimate Guide to GEO

Get the full GEO/AEO playbook

This post is an excerpt from our huge, 80-page guide to GEO / AEO – Get the FULL free AI Search Playbook here.

Why Brand Authority GEO matters

Why does building brand authority matter for generative engine optimization? How your brand appears across the web (not just on your own website!) influences:

• Whether AI trusts the content you produce 
• Whether your brand, its content, and its perspectives are selected for inclusion in AI answers over your competitors’ 
• How prominently your brand appears in AI answers
• The tone/brand sentiment of your AI mentions (neutral vs favorable vs negative)

How generative AI uses brand authority signals

Brand authority signals help AI models answer higher-order questions during their consideration of potential sources to use when constructing a generative answer, such as:

• Is this entity reliable?
• Is this entity respected within its field? 
• Do other trusted sources validate this entity? 
• Would citing this brand’s content improve answer quality?

Your brand’s perceived reputation — how AI systems will ‘understand’ its credibility — is shaped by signals that go beyond your own website. This means multichannel and multimodal strategies have become increasingly important in the age of AI search.

On trust and authenticity signals:

“As AI tools, platforms and processes accelerate the amount of AI slop being pumped out into the world, finding a way to cut through the noise will be more critical than ever.

‘Just create great content’ has never been enough. In 2026 search and AI platforms will be looking for new ways to discern and understand authenticity and trust.

When everyone says, ‘build your brand,’ what they often mean is: ’be a voice people trust.’”

— Andrew Cock-Starkey, Founder and SEO Consultant at Optimisey

Brand Authority GEO tactics

Brand Authority GEO is driven by external validation and real-world trust signals, including:

• PR and media mentions 
• Influencer and expert citations
• Customer reviews and testimonials 
• Multichannel content consistency and visibility 
• Demonstrated leadership and expertise over time

“Good content alone is not going to move the needle anymore. We need strong brand authority. Things that have long been seen as “nice to have” or “bonus SEO” are now must-haves, such as Digital PR to generate positive brand sentiment and brand mentions.”

— Tina Reis, Senior SEO Strategist at Muhlert Digital

“Brand authority & reputation management [will be crucial skills to hone in 2026]. Why? To be cited and trusted, we need to clearly communicate who we are, what we offer, and how we solve problems. LLMs prioritize authoritative content with a clear and consistent brand identity. 

These changes will require continued investment in brand recognition, developing strategies that go beyond the website, and creating content across social media. It’s essential to listen to what users are saying about your brand in forums and incorporate those insights into your site.”

— Ana Perez, SEO Manager

Brand authority in the GEO Funnel 

Brand Authority GEO focuses on making sure your brand is recognized as a trustworthy source of information that is likely to be relied upon as a resource when AI systems are generating responses. This aligns to the ‘AI Inclusion’ stage in the GEO Funnel: making sure your brand and its content is optimized for AI selection and inclusion in AI answers.

On brand reputation management for AI visibility:

“As AI and LLMs evaluate brand credibility, SEOs (more than ever) will need skills in monitoring online reputation, managing reviews and UGC platforms to ensure that signals of authority and trust are accurately represented across search.”

—Chloe Steele, SEO Account Manager at Verde Digital

• (Hear more from Chloe in our Lumar webinar session: “SEO & GEO Trends for 2026”)

Key differences between Entity GEO & Brand Authority GEO

Elsewhere, we’ve discussed a sub-discipline of GEO we’re calling Entity GEO — which  might, at first glance, seem to overlap with Brand Authority GEO.  To avoid confusion, below we’re outlining some of the key differences between Entity GEO and Brand Authority GEO, so you can see how each of these aspects of AI search optimization requires different tactics and activities. 

Outcomes of a strong Brand Authority GEO plan

The goal of implementing a Brand Authority GEO plan is to optimize your brand’s online reputation so AI systems are more likely to: 

• Prefer your brand over less trusted entities 
• Cite your content directly 
• Mention your brand favorably in recommendations 
• Use your perspectives as default answers

 How to build brand authority for GEO

In traditional SEO, a whole sub-industry developed around securing backlinks — for GEO, even brand mentions alone without a “dofollow” backlink can help establish your brand as a trusted, authoritative entity.

This means digital PR is having a bit of a renaissance, with the importance of authoritative brand mentions from credible sources that go beyond your own company’s website rising in importance once again.

As Raquel Gonzalez Exposito, CEO & Founder at Seoulful Connect, explains:

“I think brand reputation and authority will be more important than ever in 2026. We’ve always talked about becoming a reference in your niche and getting backlinks from reputable sources, but now it’s even more important to showcase that expertise through your own data, expert quotes or insights, and contributions from real professionals in the field, all of which help strengthen your topical authority.

As we know, brand authority isn’t built overnight. Most of the brands already showing up in AI-generated responses are there because they’ve been doing the work for years and have earned that recognition. We’ve always focused on getting dofollow backlinks, and that’s still relevant, but simple brand mentions will also matter more now, since AI models can recognize and display those sources.

That’s because AI doesn’t just evaluate backlinks; it looks at mentions, reviews, EEAT consistency, and other credibility signals. So, strengthening your digital PR and content marketing efforts will be key. You should also check how AI tools mention your brand to understand how they perceive your business, and identify ways to improve both visibility and trust.”

Press mentions matter for building brand authority, but there are other brand credibility signals you can work with: think industry awards, third-party review websites, influencer mentions on social media, forum threads, and partnership marketing mentions on others’ websites and social profiles.

“Even when content isn’t directly cited via links, LLMs still recognize brand mentions across the web. Digital PR, thought leadership, and high-authority citations all improve your chances of surfacing in AI-driven summaries.”

— Rejoice Ojiaku, Senior Content Specialist at Wise

• (Check out Rejoice’s Lumar webinar session: “SEO in the Age of AI: A Conversation on GEO, AEO & the Future of Search.”) 

“PR becomes much more important when mentions are taken as an element of success and not just links.”

— Emina Demiri-Watson, Head of Digital Marketing at Vixen Digital

Your brand authority GEO checklist

□ Digital PR & Media Mentions: Secure unlinked and linked brand mentions from tier-1 industry news sites and major trade publications. (Signals: trust/co-citation)

□ Expert/Influencer Citations: Get cited or interviewed by established, authoritative experts and influencers in your niche. (Signals:

respect within field)

□ Positive Brand Sentiment: Actively manage and generate positive reviews on all key third-party platforms (e.g., Google, Yelp, G2, industry-specific review sites). (Signals: reliability/preference)

□ Industry Association & Awards: Become an accredited member of relevant trade bodies and win recognized industry awards. (Signals: validation by trusted sources)

□ Sponsorships & Partnerships: Partner with established, non-competitive entities to associate your brand with positive, high-authority signals. (Signals: legitimacy/ecosystem trust)

 “The way LLM-type search surfaces work means a much wider breadth of opinion is summarized, so a multi-site presence and consistency in what is being said about you is more important than ever.

This means that effective digital PR, getting people to talk about your brand, your story, your data, on trusted websites, with consistency will pay even bigger dividends than before, link or not.”

— Mark Williams-Cook, Director at Candour

• (Hear more from Mark in our Lumar webinar session: “SEO & GEO Trends for 2026”)

“I believe in having your brand mentioned (linked or unlinked) in contextual and topically relevant articles on websites other than your own to improve visibility in LLMs and AI search. The more your brand appears across the web, the easier it is for AI crawlers to find it — and the more likely you are to be cited or mentioned in AI searches and LLMs.”

. . . 

“Work on strengthening your brand alongside your content efforts. Allocate part of your SEO budget to Digital PR and securing brand mentions on sites other than your own to improve trust and authority for both Google and LLMs.”

— Katarina Dahlin, Senior Growth Hacker at WhitePress

The Ultimate Guide to GEO

Get our free GEO/AEO Playbook

This post is an excerpt from our huge, 80-page guide to GEO / AEO – Get the FULL free AI Search Playbook here.

Get the Lumar tools you need for GEO / AEO

GEO / AEO Tools

Get the tools you’ll need for GEO.

Try Lumar’s comprehensive GEO platform, with tools for tech GEO, content GEO, and AI visibility tracking. Get started with a demo now.

About Lumar’s GEO / AEO explainer series

In this Lumar series, we’re exploring strategies for generative engine optimization (GEO), also known as answer engine optimization (AEO) — that is, how to boost your brand’s AI visibility and likelihood of earning mentions or citations from LLMs and AI-powered platforms like ChatGPT, Claude, Gemini, Perplexity, or Google’s AI Overviews and AI Mode.

The post Building Brand Authority for GEO / AEO appeared first on Lumar.

As in SEO, GEO strategies can be broken down into a few key pillars. Namely: 

• Technical GEO 
• Content GEO 
• Entity GEO 
• Brand Authority GEO

Here, we’re focusing on the fundamentals of Technical GEO — that means building a machine-readable foundation for your website and content so AI bots can easily access, understand, evaluate, and choose it for inclusion in their generated responses.

The Ultimate Guide to GEO

Get the FULL guide to GEO / AEO.

This post is an excerpt from our 80-page guide to GEO / AEO – Get the FULL free AI Search Playbook here.

First of all, what IS Technical GEO? 

Technical GEO ensures your website (and the content you host on it) is built in a way AI systems can access and process. It ensures your content can be discovered, rendered, and interpreted correctly by AI bots. 

This technical layer is the backbone that allows your Content, Entity, and Brand Authority GEO strategies to function further down the funnel; if AI cannot properly access or understand the primary source of information about your brand (your website), chances are, your brand will not be fully or accurately included in AI answers.

Why implement a Technical GEO strategy?

Tech GEO influences multiple aspects of the generative AI processes that takes a user’s prompt from asked to answered, including:

• AI Discoverability: How quickly AI and search engine bots discover new and updated content from your brand’s website. 
• Content Freshness: Ensuring the AI always extracts the most current version of your facts and data. 
• Citation Eligibility: Whether your content is technically eligible to be included in generated answers (ie, AI bots are not blocked by robots.txt or NoSnippet rules). 
• AI Renderability: Whether your pages render correctly when accessed by AI systems — necessary for AI to ‘read’ your content as intended.

Technical GEO’s place in the AI visibility funnel

The focal point of Technical GEO is AI discoverability — making sure your content is discoverable (& permitted for use) by AI systems. 

This aligns with the ‘Discovery’ stage in our GEO Funnel:

On Technical GEO:

“SEOs will need to understand how content is rendered [by AI systems] and ensure it is both crawlable and machine-readable.”

— Natalie Stubbs, Senior Technical SEO at Lumar

Key tips for Technical GEO / AEO audits

Before we dive deeper into key tactics for Technical GEO, familiarize yourself with some of the key activities you’ll need to cover as part of your Tech GEO plan (many of these will sound familiar to those who work in Tech SEO!):

Now, let’s dig into some of these key action-plan items to ensure your Technical GEO is in good shape…

Robots.txt: Are you blocking AI bots? 

For GEO, it is fundamental to ensure that AI bots can access your website’s content. If pages on your site are blocking AI bots (e.g., via robots.txt), these systems cannot crawl and process the content, thereby preventing it from appearing in AI-generated summaries and directly hindering your AI search visibility. 

If you want to appear in generative AI responses and AI search features, make sure your site isn’t unintentionally blocking important AI crawlers such as:

• GPTBot — If you want your brand or content to be cited in ChatGPT responses, you need to ensure you are not accidentally blocking OpenAI’s crawlers (like GPTBot) on your website.
• PerplexityBot — Perplexity is a major AI search engine. Blocking its crawler (PerplexityBot) from accessing your web pages can prevent your brand’s content from being included in its AI responses.
• Google-Extended — To appear in Google Gemini and other Google AI-related features, you should ensure your site is not blocking their AI-related crawlers (like Google-Extended).
• BingBot or BingPreview — Microsoft’s Bing search engine offers several controls available to limit inclusion in Bing Chat’s generative responses — check that your site is not accidentally set to block inclusion in Bing Chat, if you want your brand to appear there.
• CCBot — Common Crawl is a non-profit organization that continuously crawls the public web and freely provides its massive archives and datasets to the public. The data collected from these crawls is then made available in formats suitable for research and development. — Common Crawl is a foundational source of data for a significant number of AI models, particularly large language models (LLMs). It feeds many AI training datasets. Blocking the Common Crawl bot (CCBot) on your site limits AI models’ training exposure to your brand and content.

Make your content available to AI

Before AI bots can crawl and parse your pages for content that may be relevant to cite in their responses, the page must first be available for the bots to access. To enable your website’s content to be discovered and cited in AI-generated answers, make sure none of your target pages return availability errors such as client-side 4xx errors (like 404 errors) or server-side 5xx errors. Both traditional search and AI bots cannot crawl pages that are unavailable or unreachable, effectively excluding them from being referenced by generative models. 

Nosnippet issues for GEO

Are nosnippet tags preventing your content from appearing in AI responses?

In the era of GEO and AI search, the ability to control how your content is summarized is a powerful tool — or a critical issue if mismanaged.

The nosnippet directives (including the meta tag, X-Robots-Tag header, and data-nosnippet attribute) were originally designed to prevent search engines from creating rich text snippets in traditional search results.

Today, these same nosnippet directives are a direct signal to AI systems. By preventing a snippet from being generated, a nosnippet directive also prevents your content from being used as a direct input for AI-generated responses, AI Overviews, and other AI-powered SERP features.

The nosnippet meta tag is a crucial tool for GEO because Google has confirmed it prevents AI systems, including AI Overviews and AI Mode, from using a page’s content to generate AI-powered snippets and responses.

Per Google Search Central, the nosnippet directive tells Google:

“Do not show a text snippet or video preview in the search results for this page. A static image thumbnail (if available) may still be visible, when it results in a better user experience. This applies to all forms of search results (at Google: web search, Google Images, Discover, AI Overviews, AI Mode) and will also prevent the content from being used as a direct input for AI Overviews and AI Mode.”

And per Google Search Central’s documentation on appearing in Google AI features: 

“Technical requirements for appearing in AI features:To be eligible to be shown as a supporting link in AI Overviews or AI Mode, a page must be indexed and eligible to be shown in Google Search with a snippet, fulfilling the Search technical requirements.”

JavaScript rendering issues for AI bots

What an AI bot “sees” is not always what a human sees — and may not even be what traditional search bots see. Content discrepancies between the raw HTML and the rendered page, which is processed after JavaScript is executed, can lead to a critical “content blind spot” for AI systems.

As Matt G. Southern reports in Search Engine Journal, while Googlebot is highly capable of rendering JavaScript, many other AI crawlers are not as advanced and still rely on the static HTML:

“Traditional search crawlers like Googlebot can read JavaScript and process changes made to a webpage after it loads … In contrast, many AI crawlers can’t read JavaScript and only see the raw HTML from the server. As a result, they miss dynamically added content…”

This creates a new layer of technical GEO to manage. If any of your key content — the headings, paragraphs, and data that provide content authority — is only loaded via JavaScript, your most valuable information may be invisible to AI platforms.

The challenge for GEO is to ensure that a website’s technical foundation is robust enough for all crawler bots (including AI crawlers), not just Google’s.

“I think AI is not a revolution in search; it’s just an extension. AI search strategies put more light on previously undervalued areas of SEO that some of us ignored or took for granted.

In some areas, it’s time to go back to basics, e.g., with rendering. Google told us for years that they manage to render pages well (I still have pretty large doubts), but now AI search crawlers again don’t render JavaScript, and we again need to optimize how we render content to make sure AI search crawlers can find it.

Making your site cheaper to both render and understand content is getting more and more important.”

— Patryk Wawok, Co-founder & Head of Technical SEO at Organic Hackers

Indexability & GEO

Website indexability issues (such as pages being non-indexable via robots.txt, incorrect use of canonical tags, or using the unavailable_after directive) don’t just impact your traditional SEO and SERP results — they also have a knock-on impact on AI search results and AI-generated answers.

As Barry Schwartz explains in Search Engine Land, “To show in Google AI Mode & AI Overviews, your page must be indexed.”

ChatGPT & Bing’s search index

If, previously, you were primarily concerned only with getting your content indexed by Google, it may be time to expand your scope here for GEO… because ChatGPT’s search function appears to rely heavily on Bing’s search index.

Per OpenAI’s announcement about ChatGPT Search:

“ChatGPT search leverages third-party search providers, as well as content provided directly by our partners, to provide the information users are looking for.”

And as Danny Goodwin writes in SEL, “. . . One of those third-party search providers is Microsoft Bing. Based on its ChatGPT search help document, OpenAI is sharing search query and location data with Microsoft.”

Structured data & GEO 

How structured data may impact AI visibility: 

While the core training of large language models (LLMs) used in AI bots primarily relies on vast quantities of unstructured data and text, many AI-powered search features (like Google’s AI Overviews) that synthesize information from existing search engine indices may also indirectly benefit from structured data. This is because structured data helps traditional search engines better understand, categorize, and surface relevant content, which in turn can improve the chances of that content being selected and leveraged by the AI for its generative responses. 

LLMs are trained on massive datasets of text; predominantly unstructured human language (books, articles, web pages). Most AI systems’ “understanding” of context primarily comes from patterns in natural language, not from directly parsing and interpreting schema.org markup in the same way a search engine’s indexing system does. 

But AI-powered search features from Google (like AI Overviews) and Microsoft (Copilot) do not re-crawl the web independently for every query. Instead, they leverage the vast, continuously updated indices of their respective search engines (Google Search Index, Bing Search Index). And structured data plays a crucial role in how today’s search engines understand, organize, and retrieve information from the web.

Copilot’s knowledge sources documentation, for example, indicates a direct reliance on the Bing search index:

“When turned on, Web Search triggers when a user’s question might benefit from information on the web. It searches all public websites indexed by Bing.”

And remember that Google Search Central documentation on appearing in AI features that we mentioned previously? It says:

“Technical requirements for appearing in AI features: To be eligible to be shown as a supporting link in AI Overviews or AI Mode, a page must be indexed and eligible to be shown in Google Search with a snippet, fulfilling the Search technical requirements. There are no additional technical requirements.”

If structured data helps enable traditional SERP snippets and some LLMs and AI search features rely on traditional search engine indices for up-todate information, then having proper structured data in place may also help your content appear in these AI-powered search features.

In short, while AI itself may not “read” structured data in a semantic way during its core training, structured data is vital for how normal search engines today ingest, understand, and organize information. Since AI platforms and AI SERP features rely on these organized search indices to retrieve the most current information, robust structured data implementation on your website may have a knock-on effect of improving the chances of your content being considered relevant and chosen as a source for AI-generated responses.

On Structured Data & Knowledge Graph Integration:

“Structured data is no longer only about getting rich results within Google’s search results. It’s the foundation for machines to make sense of their training data. As language models keep getting smarter, the winners are going to be the brands that treat their website’s content like data: interconnected, contextual, and queryable.

Schema markup, linked-up entities, and keeping your metadata consistent will aid LLMs in interpreting meaning rather than just words on a page.”

— Jonathan Clark, Managing Partner at Moving Traffic Media

A further consideration on GEO/AEO and structured data comes from Jarno van Driel’s interview on the Search With Candour podcast.

When asked, “With the growth of … natural language processing … do you think that shifts how important structured data is going forward?”, van Driel responded:

“The question is, is it financially viable? … The big advantage of structured data — any structured data set, it doesn’t necessarily have to be JSON-LD — the big advantage of those is that they really require little compute to be turned into something useful. And the biggest issue with all those LLMs, even the next generation five or ten years from now, is that it will cost a lot more compute to analyze unstructured content than to digest a piece of structured content. 

So even if meaning or understanding are not involved, it’s just a matter of money. It’s cheaper for any party to deal with structured data than to turn unstructured data into structured data to be able to use it. So that’s really the biggest benefit; it’s just a cost-efficient way for those parties to do something with data. Knowledge graphs and those kinds of repositories wouldn’t function without those large [structured] datasets.”

Further learning: strategies to build your brand’s AI visibility

Here, we’ve covered the essentials of Technical GEO. In Lumar’s comprehensive GEO / AEO Strategy eBook, “Your AI Search Playbook,” you can learn tactics to cover the other 3 pillars of a strong AI search strategy, including:

• Content GEO
• Entity GEO
• Brand Authority GEO

Get your free copy of our full 80-page guide to GEO here.

GEO / AEO Tools

Get the tools you’ll need for GEO.

Try Lumar’s comprehensive GEO platform, with tools for tech GEO, content GEO, and AI visibility tracking. Get started with a demo now.

The post Technical Essentials for GEO / AEO – Is Your Website AI-Citable? appeared first on Lumar.

Each month, Lumar’s in-house tech SEO experts hand-pick some of the SEO industry’s top news stories from across the web to keep you up-to-date on all things SEO and website optimization.

For our April 2026 SEO & GEO/AEO news roundup, the top headlines include:  

• Google AI Mode is coming to Chrome’s address bar — users will soon be able to query AI Mode directly from the browser, with responses able to reference open tabs, images, and files.
• Google’s March 2026 core update is complete — specialist, niche sites continued to outperform content aggregators, extending a familiar trend in recent updates.
• Google bans back button hijacking — sites that use redirect tricks to prevent users from returning to previous pages will face manual spam actions or automated demotions starting June 15th, 2026.
• Google Search is evolving into a task engine — new AI Mode features let users track hotel prices, build full trip itineraries, and even have Google AI call stores to check stock.
• Cloudflare redirects AI training bots to canonical URLs — a new feature automatically turns canonical tags into 301 redirects for crawlers like GPTBot and ClaudeBot.
• AI traffic to US retail sites is surging — but most aren’t optimized for it — Adobe data shows high-intent AI-referred shoppers arriving at e-commerce sites that aren’t yet machine-readable.
• OpenAI ends its exclusivity deal with Microsoft — OpenAI can now pursue cloud deals with rivals like Amazon and Google, while Microsoft retains a non-exclusive license through 2032.
• OpenAI launches GPT-5.5, its most agentic model yet — with stronger multi-step reasoning and tool use, pushing ChatGPT further toward a closed-loop “super app” model.
• Anthropic released Claude Opus 4.7 with improved multi-step reasoning and multimodal capabilities.
• EU weighs classifying ChatGPT search as a “Very Large Online Search Engine” — at 159 million monthly EU users, it clears the 45 million threshold that would trigger DSA compliance obligations.
• (and more, below!)

Dive into the details behind the SEO and GEO/AEO headlines this month below…

But first: New AI visibility tools launched in Lumar this month!

Know where you stand in AI answers. New AI Visibility tools in Lumar track your brand’s AI presence, sentiment, and citations across the AI models your buyers are using — and tell you exactly what to do about the gaps.

Get a Demo of AI Visibility Tracking in Lumar

April 2026 SEO & GEO/AEO News Roundup:

Google announces greater integration for AI Mode in Chrome 

Google has been continuing its mission to better integrate AI Mode with everyday workflows. Soon, AI Mode will be available directly within Chrome via the address bar, allowing users to ask complex questions while staying on a page. AI Mode will also be able to reference open tabs, images, and files for extra context.

Clicking on links from these AI responses will also now open a side-by-side view, rather than replacing the current page. The goal is to reduce so-called ‘tab hopping’ and allow users to deep-dive into specific topics from one static location.

(Source: Google’s The Keyword Blog)

Google’s March 2026 core update completes its rollout

The update ran from March 27th to April 8th. There was no specific focus to this one, although SERP volatility was high. Much of the analysis that followed, including this article by Aleyda Solis, showed specialist, targeted sites performing better than content aggregators and comparison sites. It’s a familiar pattern that’s become a bit of a trend in recent updates, rewarding established brands that have built a strong reputation within their niche.

(Source: Google Status Dashboard)

Google makes recommendations for ‘Read more’ link inclusion

Google has published new guidance on optimizing content for ‘Read more’ link inclusion. These links have been cropping up more frequently in SERPs in recent months, but this is the first time Google has made any actionable recommendations to improve eligibility for the feature.

Recommendations focus on ensuring that content is accessible and directly visible on page load. Content hidden behind tabs or other expandable sections is less likely to appear here.

(Source: Search Engine Land)

‘Back button hijacking’ is about to be penalized by Google

Google has updated its spam policies to explicitly ban back button hijacking. This covers any behavior that stops users from returning to the previous page when they click the back button within the browser, such as redirecting them to a page they haven’t visited before.

Possible penalties include manual spam actions or automated demotions, which can impact the site’s performance in Google Search results. The new rules come into place from June 15th and sites have until then to disable this behavior.

(Source: Google Developers Blog)

Cloudflare turns canonical tags into redirects for AI training bots

Cloudflare has launched a new feature that automatically turns canonical tags into 301 redirects for certain AI training bots, such as GPTBot and ClaudeBot. The aim is to prevent AI crawlers from ingesting so much duplicate content, instead redirecting them straight to the primary version of each page.

The change will only impact AI training bots, so AI assistants will be unaffected. The change also won’t have any impact on Googlebot or human users. Even so, it brings canonical strategy into focus and is yet another way that AI crawlers will be acting differently from traditional search engines.

(Source: Cloudflare)

Google says efficiency is key when it comes to page weight concerns

In a recent episode of the Search Off The Record podcast, Gary Ilyes and Martin Splitt highlighted a growing discussion around increasing page sizes. The pair confirmed that larger pages aren’t necessarily a problem for Google. However, they do point to whether elements making up page weight are actually beneficial to users.

Bigger pages tend to rely heavily on things like JavaScript, images and structured data. Rather than looking at the size of the page in silo, it’s important to consider whether these elements are getting in the way of efficiency – both for crawlers and users. 

(Source: Search Engine Journal)

Google demystifies Googlebot and the 2MB fetch limit

In a recent blog post, Google has provided a rare glimpse into the inner workings of Googlebot. No longer referring to a single crawler, Googlebot has evolved into an umbrella term that covers dozens of different clients, all working to process content for use across Google’s wide range of products and platforms.

The blog post also references the 2MB limit, which sent shockwaves through the SEO industry when it was first mentioned back in February. Googlebot currently fetches up to the first 2MB of each individual URL. If your HTML file is larger than this, fetching will stop exactly at the 2MB cutoff. Each referenced resource in the HTML will have its own separate byte count and will not count towards the size of the parent page they were found on.

(Source: Google Developers Blog)

AI traffic surges for US retailers, but many sites are still not optimized for AI bots

A recent report from Adobe confirms that AI sources are sending rapidly growing volumes of high-intent traffic to U.S. retail sites, with shoppers using chatbots and AI browsers to research products and find the best deals. However, many e-commerce pages are still not fully optimized for AI search, especially when it comes to PDPs. This limits visibility in AI-powered searches and greatly reduces retailers’ ability to be cited within these AI shopping experiences.

(Source: Adobe)

The Ultimate Guide to GEO

Your FREE 80-page guide to AI search optimization

In this free GEO/AEO strategy guide, we share insights from dozen of experts — and outline a 4-pillar GEO framework to guide your AI brand visibility strategies this year.

Google Search is evolving into a task engine: AI travel-planning and AI calling features expand in search

Google rolled out a cluster of new features in April that let users complete real-world tasks without leaving Search. This month, Google launched hotel price tracking globally, letting users monitor individual properties and receive email alerts when rates change — directly from the search bar. Alongside that, AI Mode’s Canvas tool now builds full trip itineraries for all US users from a natural language prompt, pulling together flights, hotels, mapped attractions, and refining results through follow-up questions. And AI Mode gained agentic calling — the ability for Google’s AI to phone local stores, check whether a specific item is in stock, and report back — extending a capability that has been available in Search since November.

Taken individually, these are useful travel features. Taken together, they represent a meaningful step toward a more agentic version of Google Search; one where users don’t find information and then go do things, but where Search handles the doing directly. 

For SEOs and digital marketers, agentic features in Search will reward businesses whose data is accurate, structured, and machine-queryable, not just findable by humans. If AI Mode is calling your store to check stock, your Google Business Profile and inventory data are now effectively front-line marketing assets. Schema.org markup, consistent local listings, and real-time operational accuracy matter in ways that go well beyond traditional ranking signals. The window to get ahead of this is now, before agentic search is the default expectation rather than the notable new feature.(Source: Search Engine Journal ; Travel + Leisure ; Google’s The Keyword Blog)

OpenAI ends exclusivity deal with Microsoft

This week, OpenAI and Microsoft have restructured their long-standing partnership. The headline change: Microsoft has dropped its exclusive right to sell OpenAI’s AI models, opening the door for OpenAI to pursue cloud deals with rivals like Amazon or Google.

This is a mutual unwinding of exclusivity rather than a total breakup of the partnership. Microsoft retains a non-exclusive license to OpenAI’s models through 2032, but trades away exclusive distribution rights in exchange for no longer having to pay OpenAI a revenue share. OpenAI gains a cap on its payments to Microsoft and the freedom to operate across multiple cloud providers, which can help it expand its enterprise AI offerings.

(Sources: Forbes ; Reuters )

OpenAI launches GPT-5.5, enabling more agentic task handling in ChatGPT 

This month, OpenAI has launched GPT 5.5, describing it as its “smartest and most intuitive” model to date and a key step toward a unified AI experience that brings search, productivity, and task execution into a single interface. The new GPT 5.5 model introduces stronger multi-step reasoning, improved tool use, and more agent-like behavior — enabling users to complete complex tasks without leaving the ChatGPT environment. 

Per OpenAI’s announcement post:

“GPT‑5.5 understands what you’re trying to do faster and can carry more of the work itself. It excels at writing and debugging code, researching online, analyzing data, creating documents and spreadsheets, operating software, and moving across tools until a task is finished.”

GPT 5.5 is rolling out to Plus, Pro, Business, and Enterprise users in ChatGPT and Codex, with plans to bring the model to the API soon.  

For SEO and digital marketers, the bigger story is strategic. OpenAI is moving toward a closed-loop “super app” model, where users search, evaluate, and act all within the AI platform rather than clicking out to websites. This raises the stakes for achieving AI brand visibility, as brands increasingly compete to be cited or surfaced in AI responses, not just indexed and ranked in search engines.

(Sources: TechCrunch ; OpenAI announcement) 

Anthropic launches Claude Opus 4.7 with improvements in instruction-following and multimodal understanding

Like OpenAI, Anthropic also shipped a model update this month with the launch of Claude Opus 4.7. This latest Anthropic model is focused on improving performance in complex, multi-step tasks. Anthropic highlights that Opus 4.7 offers better instruction-following, greater ability to remember important notes across multiple sessions, and improved multimodal understanding. 

(Sources: Anthropic announcement ) 

 EU moves to classify ChatGPT as a “Very Large Online Search Engine”

The European Commission is assessing whether to designate ChatGPT’s search feature as a Very Large Online Search Engine (VLOSE) under the Digital Services Act, which would require stronger compliance with EU digital platform regulations. OpenAI’s transparency report revealed ChatGPT’s search feature averaged 159.1 million monthly active users in the EU — well above the 45 million threshold that triggers the classification. 

Per OpenAI documentation:

“For the six-month period ending 31 March 2026, ChatGPT search had approximately 159.1 million average monthly active recipients in the European Union.”

A VLOSE designation would place ChatGPT alongside Google, Microsoft, Amazon, Meta, and X, thereby requiring systemic risk assessments, algorithmic transparency, independent audits, and obligations for researchers to access data. 

(Sources: Reuters ; TechRepublic)

Did you know you can now optimize for AI search and LLM brand mentions with Lumar?

Lumar’s GEO tools for AI search optimization provide data-driven insights to help you optimize your website for AI-driven search visibility, earn more AI citations, and improve brand visibility across LLMs.

Explore Lumar GEO Platform Features

Get started with Lumar

Get Lumar pricing

The post SEO & AI Search Industry News – April 2026 appeared first on Lumar.

Entities for AI Search: How to Make Your Brand Recognizable to LLMs

Before a generative AI system can cite your content, recommend your product, or include your brand in an answer, it needs to understand one thing:

Who you are.

In AI systems, an entity is a clearly defined, uniquely identifiable thing or concept — such as a company, product, person, or idea — that can be distinguished from others and connected to related information when they are embedded in a vector space. LLMs and retrieval systems use entities (not just keywords) to organize knowledge, linking them to attributes, relationships, and contexts. For your brand to be surfaced in AI-generated answers, it needs to exist as a recognizable entity within this network of meaning.

That’s where Entity GEO comes in. This aspect of generative engine optimization (or GEO, also known as answer engine optimization, or AEO) focuses on ensuring AI systems recognize your brand as an entity in order to include it in generative responses to users’ prompts. Entity GEO is a foundational pillar of AI search optimization, moving beyond keyword matching to establish a verifiable brand identity for the machines.

Effective Entity GEO builds a consistent, accurate identity for your brand across the web (not just on your website). This includes maintaining consistent brand descriptions across platforms, using structured data such as Organization, Product, or Person schema, securing inclusion in trusted third-party databases and knowledge graphs, and publishing content that clearly connects your brand with the topics you want to be known for. These entity signals help AI systems reliably recognize your brand, associate it with the right areas of expertise, and reference it accurately in generated responses.

On Brand Entity-Building for GEO:

“The brands that train AI to recognize who they are — through consistent entity signals, schema, and thought-leadership — will own visibility in 2026.”

. . .

“AI doesn’t think in keywords; it thinks in entities and relationships. That means the old way of optimizing for rankings doesn’t guarantee you’ll show up in AI responses… My tip: stop chasing prompts and start tracking entity presence.”

— Aimee Jurenka, SEO Strategist @ RicketyRoo

In our 2026 AI Search Playbook, we discuss both Entity GEO and Brand Authority GEO. While Entity GEO and Brand Authority GEO are closely related, they serve two distinct functions when it comes to influencing generative AI systems. Understanding the difference is critical because AI must first recognize your brand as a distinct entity before it can evaluate whether or not that entity is authoritative and trustworthy enough to cite.

Think of it this way:

• Entity GEO answers “Who are you?”
• Brand Authority GEO answers “Should we trust you?”

Both entity recognition and establishing brand authority are required for consistent inclusion in AI-generated responses, but they operate at different layers of AI understanding. At the Entity GEO layer, AI systems are not yet judging whether your brand is good or authoritative. They are determining whether your brand:

• Exists as a distinct concept 
• Can be clearly identified and disambiguated
• Has stable, consistent facts associated with it

The Ultimate Guide to GEO

Get the full guide to GEO here

Learn more about the 4 primary types of GEO – including technical GEO, content GEO, entity GEO, and brand authority GEO — in our FREE 80-page strategy guide for AI search!

How AI uses entity signals

Entity signals help AI answer foundational questions about your brand and product or service offering, such as:

• Is this a real organization, product, or person? 
• Is this brand distinct from similarly named entities? 
• What does this brand do?

Entity GEO tactics

Entity GEO efforts center on identity consistency and factual corroboration, including:

• Ensure consistent, accurate brand descriptions across platforms (your website, social media profiles, third-party databases, press coverage).
• Use entity-building structured data on your website, for example: ‘Organization’, ‘Product’, ‘Person’ schema.
• Get your brand included in trusted third-party databases and resources (such as Wikipedia, G2, industry lists, etc.)
• Build topical authority through content to create a clear relationship between your brand and key topics related to your offering and industry.

“Optimizing content for a specific set of keywords is increasingly seen as outdated… Strategy will pivot towards topic clustering, leveraging structured data, internal linking, and entity-focused content to position brands as authorities on broader subjects.”

— Natalie Stubbs, Senior Technical SEO @ Lumar

Outcomes of strong Entity GEO

The goal of Entity GEO is to ensure AI systems can:

• Reliably recognize your brand 
• Correctly associate your brand with specific topics 
• Confidently reference your brand without confusion

“I see GEO / AEO as the next phase of my Topic Entity Strategy — shifting from optimizing for search engines to teaching AI systems how to understand your expertise.

• Traditional entities (like people, places, or brands) tell AI who you are.
• Topic entities tell AI what you’re known for.

By mapping your brand to the core concepts you want AI to associate you with, like “local SEO”, “AI visibility”, or “semantic optimization”, you create a retrievable web of meaning.

This approach moves GEO / AEO beyond theory: instead of tracking prompts or keywords,

I track topic entity presence; how often your expertise shows up in AI answers, how well it’s understood, and how consistently it’s connected back to your brand.

That’s how we measure, optimize, and benchmark visibility in the age of retrieval.”

— Aimee Jurenka, SEO Strategist @ RicketyRoo

Entity-building and the GEO/AEO funnel

We’ve previously introduced the ‘GEO Funnel’ concept as a way of understanding the stages of generative engine optimization:

1. AI Discovery: First, AI needs to be able to discover and retrieve your content.  
2. AI Understanding: Then, AI needs to ‘understand’ your content and who you are. 
3. AI Selection & Inclusion: Finally, AI systems need to ‘judge’ and evaluate your content and your brand against others’ to determine which is the most trustworthy source, the best content to cite, or the best brand to mention in response to a user’s particular query. 

Entity GEO focuses on making sure your brand is recognized as a unique entity by AI systems. This aligns with the ‘AI Understanding’ stage in the GEO Funnel. 

Tools you need for AI visibility

Ready to start optimizing for AI brand mentions?

Explore Lumar’s comprehensive GEO/AEO platform — and get a free demo to see the tools in action for yourself.

The post Entity-Building for AI Brand Visibility (GEO/AEO Explainer) appeared first on Lumar.

Introduction: A GEO / AEO Strategy Framework for AI Search Visibility

Today, the definition of “online brand visibility” has been fundamentally reshaped by the widespread consumer use of AI platforms like ChatGPT, Claude, and Gemini.

Traditional SEO remains essential, and strong SEO foundations directly support AI search performance. But winning in this new AI-augmented search landscape also requires Generative Engine Optimization (GEO) — a discipline focused specifically on making your brand a source that AI retrieves, understands, trusts, selects, cites, and recommends. GEO isn’t replacing your existing organic search strategy; it’s extending it to cover the AI search landscape that now sits alongside traditional search engines.

The goal hasn’t changed for marketing teams; you still want your brand in front of the right people, in the right place, at the right moment. What’s changed is that “the right place” is now increasingly inside an AI-generated answer. To build your brand’s online visibility, it’s no longer enough to satisfy a standard keyword query; you must now also satisfy AI reasoning by approaching your content as both a valuable resource for your human readers and a structured dataset for the machines. 

Our new Lumar AI Search Playbook introduces a four-pillar GEO strategy designed to help your brand become a trusted entity that AI systems are ready and willing to cite.

Download the full, free GEO strategy guide for 80 pages of AI search explainers, strategy guidance, and insights from 20+ search experts — or read on below for an introduction to the key GEO strategy frameworks that can help guide your AI search optimization efforts this year. 

Free GEO Strategy Guide

Get the full Lumar GEO strategy guide here.

This article is an excerpt from Lumar’s free 80-page master guide to GEO/AEO strategies. — Download the full 2026 AI search playbook here.

The 4-Pillar GEO Strategy Framework

To help better organize your approach to AI brand visibility, we’ve developed a 4-pillar GEO/AEO strategy framework. This helps you “bucket” your GEO efforts across key areas that increase the likelihood AI platforms will:

• Find your content
• Trust your content
• Select your content
• Mention and cite your brand in responses

Think of this framework as your roadmap for becoming a default source AI systems rely on when generating their answers.

The 4 Pillars of Generative Engine Optimization (GEO)

The GEO Funnel

The 4-pillar framework maps directly onto what we’re calling the GEO Funnel — the three stages AI systems move through when deciding whether to include your brand in a generated response:

• AI Discovery: Can AI bots find your content at all? Issues to check include blocked AI bots in robots.txt, nosnippet tag problems, and rendering issues.
• AI Understanding: Can AI bots correctly interpret your content? Issues to check include missing titles and H1s, thin content, and absent structured data.
• AI Inclusion: Will AI bots choose to cite your content? Issues to check include semantic relevance, E-E-A-T signals, existing AI bot engagement, and brand authority.

Optimizing across all four pillars means optimizing for all three stages of this funnel.

GEO / AEO Platform

Get the tools you need to build AI search visibility.

Ready to take AI search visibility seriously? — You need the right tools in place. Explore Lumar’s GEO/AEO platform now.

“Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) will dominate SEO in 2026 because they fundamentally redefine what “visibility” means. Instead of ranking as one of ten blue links, the goal becomes earning inclusion and attribution within AI-generated answers. Search experiences are rapidly evolving into dialogue-driven journeys where the model curates, contextualizes, and often executes user intent directly. This will expand from booking to buying and everything in between.

The challenge is that SEOs lose direct control over presentation and traffic paths. LLMs decide what to surface and how to frame it. So, to stay relevant, teams need to think like data publishers and knowledge architects, not just content marketers.

Practical steps include auditing entity coverage across your content, aligning schema markup with topic clusters, publishing factually consistent pages, and monitoring LLM-generated outputs where your brand appears.

Those who understand how information flows through AI systems, from ingestion to retrieval, will outperform those still chasing individual rankings.”

— Jon Clark, Managing Partner, Moving Traffic Media

Now, let’s dive into each of the four GEO pillars, one by one… 

Pillar 1: Technical GEO

What is Technical GEO?

Tech GEO is about ensuring AI bots can find, access, and understand your content — and making sure your website is machine-readable for AI systems.

This technical layer of AI search optimization is the backbone that allows your Content, Entity, and Brand Authority GEO strategies to function. If AI cannot access or understand the primary source of information about your brand — your website — chances are, your brand will not be fully or accurately understood or cited by AI.

Technical GEO influences four key outcomes:

• AI Discoverability: How quickly AI and search engine bots discover new and updated content from your brand’s website.
• Content Freshness: Helping AI extract the most up-to-date version of your facts and data.
• Citation Eligibility: Whether your content is technically eligible to be included in generated answers (i.e., AI bots are not blocked by robots.txt or NoSnippet rules).
• AI Renderability: Whether your pages render correctly when accessed by AI systems — necessary for AI to “read” your content as intended.

Technical GEO Checklist

• Check you are not blocking AI bots (GPTBot, PerplexityBot, Google-Extended, BingBot, CCBot) in your website’s robots.txt file.
• Ensure robots.txt and nosnippet directives are not preventing AI citation.
• Fix 4xx / 5xx errors so AI bots can access pages.
• Continue to optimize for indexability, as many AI tools still rely on traditional search engine indices to discover information.
• Implement structured data (schema) to make your website content more machine-readable.
• Maintain strong internal linking across topic clusters.
• Ensure key content is visible in raw HTML, not only rendered via JavaScript (which many AI systems struggle to process).

“SEOs will need to understand how content is rendered and ensure it is both crawlable and machine-readable.” 

— Natalie Stubbs, Senior Technical SEO, Lumar

Pillar 2: Content GEO

What is Content GEO?

Content GEO ensures your content is designed for both human understanding and AI retrieval, assessment, and selection. It focuses on publishing accurate, logically structured, semantically relevant, and comprehensive content that AI systems can extract, summarize, and cite confidently.

If Technical GEO determines whether your content is accessible to AI bots, Content GEO influences whether that content is deemed useful, trustworthy, and likely to be chosen. Where traditional SEO content aimed to satisfy keyword queries, Content GEO focuses on satisfying AI reasoning — ensuring your brand’s insights, explanations, and expertise become the material LLMs rely on when generating answers.

In an AI search landscape, your content takes on yet another role in your broader marketing toolkit: it becomes training material for the models shaping the future of online search.

Content GEO influences:

• AI Extractability: How easily AI can pull direct, factual answers from your pages.
• Citation Preference: Whether AI selects your content over a competitor’s as the authoritative source for a given query.
• Topical Association: How consistently AI connects your brand with expertise in a specific subject area.
• Query Fan-Out Completeness: Whether your content covers a topic thoroughly enough to satisfy multi-part or follow-up queries.

Content GEO Checklist

• Write clear, factual, answer-first content that directly addresses user questions.
• Optimize for semantic relevance and full coverage of related subtopics.
• Build evidence-based content with citations and sources.
• Structure content into retrievable “chunks” with clear H2/H3 headings.
• Ensure entity clarity in content chunks / passages — avoid pronouns replacing key entities.
• Create multimodal content (video, audio, images) and add transcripts and descriptive alt text.
• Demonstrate E-E-A-T (experience, expertise, authority, and trustworthiness) through expert authorship, original data, and transparent sourcing.

“In 2026, GEO/AEO will be essential for visibility, requiring content to be highly structured, fact-based, and semantically rich to be considered authoritative enough for AI to reference. 

Rather than chasing rankings alone, SEOs must now optimize for inclusion in zero-click, conversational responses — ensuring that brand-owned content is answer-ready and aligned with user intent at a granular level.”

— Rejoice Ojiaku, Senior Content Specialist, Wise

GEO Content Tools

GEO Content Evaluation Tools in Lumar

Explore new Lumar GEO content evaluation tools to optimize your content for AI inclusion & LLM brand mentions.

Pillar 3: Entity GEO

What is Entity GEO?

Entity GEO focuses on ensuring your brand is clearly recognized as a distinct, identifiable entity by AI systems. Before AI platforms can decide whether to trust or cite your brand, they must first understand who you are — what organization, product, or person the content refers to, and how that entity relates to specific topics, industries, and other entities.

In AI-driven search environments, visibility increasingly depends on this entity-level understanding rather than just keyword relevance in any singular piece of content.

Think of it this way:

• Entity GEO answers: “Who are you?”
• Brand Authority GEO answers: “Should we trust you?”

Both are required for consistent inclusion in AI-generated responses, but Entity GEO must come first. Without it, Brand Authority GEO has nothing to attach to.

Effective Entity GEO builds a consistent, accurate identity for your brand across the web — including consistent brand descriptions across platforms, structured data (Organization, Product, or Person schema), inclusion in trusted third-party databases and knowledge graphs, and content that clearly connects your brand with the topics you want to be known for.

Entity GEO Checklist

• Ensure consistent, accurate brand descriptions across platforms (website, social media, third-party databases, press coverage).
• Use entity-building structured data/schema markup on your website (Organization, Product, Person schema).
• Get your brand included in trusted third-party databases and resources (Wikipedia, G2, industry lists, etc.).
• Build topical authority through content to create a clear relationship between your brand and key topics in your industry.

“AI visibility will define SEO in 2026 because discovery is no longer confined to search engines; it’s happening inside AI conversations. Whether users are asking ChatGPT for recommendations, researching through Perplexity, or relying on Google’s AI Overviews, brands need to be retrievable in those ecosystems. The challenge is that AI doesn’t think in keywords; it thinks in entities and relationships. That means the old way of optimizing for rankings doesn’t guarantee you’ll show up in AI responses.

For SEOs, this shift requires a mindset change: from optimizing for algorithms to educating AI about your brand. That means building clear topic–entity connections, consistent schema, and credible signals across every channel so your expertise becomes part of the LLM’s “understanding” of your niche.

My tip for 2026: stop chasing prompts and start tracking entity presence. If your brand is being cited, summarized, or referenced by AI, you’re not just visible, you’re trusted by the systems shaping the future of search.”

— Aimee Jurenka, SEO Strategist, RicketyRoo

Pillar 4: Brand Authority GEO

What is Brand Authority GEO?

Brand Authority GEO is about credibility, trust, and preference. Once AI recognizes your brand as an entity, it must decide whether your entity deserves to be included, cited, or recommended in generative responses.

This pillar helps AI answer higher-order questions such as:

• Is this entity reliable?
• Is this entity respected within its field?
• Do other trusted sources validate this entity?
• Would citing this brand improve answer quality?

Brand Authority GEO influences whether AI trusts the content you produce, whether your brand is selected over competitors’, how prominently your brand appears in AI answers, and the tone of those mentions (neutral vs. favorable).

In traditional SEO, a whole sub-industry developed around securing backlinks. In GEO, even brand mentions without a dofollow link can help establish your brand as a trusted, authoritative entity. This means digital PR is having a renaissance — authoritative brand mentions from credible sources that go beyond your own website are rising in importance once again.

Brand Authority GEO Checklist

• Digital PR & Media Mentions: Secure linked and unlinked brand mentions from industry publications. (Signals: Trust/Co-citation)
• Expert/Influencer Citations: Get cited or interviewed by established, authoritative experts in your niche. (Signals: Respected within field)
• Positive Brand Sentiment: Actively manage reviews on key third-party platforms (Google, G2, industry review sites). (Signals: Reliability/Preference)
• Industry Association & Awards: Become a member of relevant trade bodies and win recognized industry awards. (Signals: Validation by trusted sources)
• Sponsorships & Partnerships: Partner with established entities to associate your brand with high-authority signals. (Signals: Legitimacy/Ecosystem trust)

“Good content alone is not going to move the needle anymore. We need strong brand authority.  Things that have long been seen as “nice to have” or “bonus SEO” are now must-haves, such as Digital PR to generate positive brand sentiment and brand mentions.”

— Tina Reis, Senior SEO Strategist, Muhlert Digital

“Brand authority & reputation management [will be crucial skills to hone for AI search visibility]. Why? To be cited and trusted, we need to clearly communicate who we are, what we offer, and how we solve problems. LLMs prioritize authoritative content with a clear and consistent brand identity.”

“These changes will require continued investment in brand recognition, developing strategies that go beyond the website, and creating content across social media. It’s essential to listen to what users are saying about your brand in forums and incorporate those insights into your site.”

— Ana Perez, SEO Manager

Putting It All Together: The GEO Funnel in Practice

The four pillars aren’t independent checklists — they build on each other sequentially. AI must first discover and access your content (Technical GEO) before it can understand it (Content + Entity GEO), and only then will it evaluate whether or not to select your brand or your content for inclusion in generated responses (Brand Authority GEO).

To improve your brand’s visibility across AI answers, treat GEO strategy as a holistic system — make it easy for AI systems to find your brand’s content, understand it, trust it, and cite it. 

Your GEO / AEO Toolkit

Get started with Lumar for GEO

Your 2026 buyers are talking to AI bots. Make sure the bots are talking about you with Lumar’s GEO Toolkit.

Free GEO / AEO Playbook

Get the full 2026 AI Search Playbook here

With insights from 20+ search experts, actionable checklists, and in-depth explainers on each pillar of GEO, Lumar’s FREE 80-page AI search playbook is a must-read for SEOs, content strategists, and digital marketing leaders alike.

The post The 4-Pillar GEO Strategy Framework to Win Visibility in AI Search appeared first on Lumar.

• Does your brand appear in AI answers for the topics that matter most to your business? 
• When your brand appears in AI responses, how is it being described — and is that description accurate, favorable, and consistent? 
• When you make technical or content changes on your website, can you measure whether those changes are improving your brand’s AI visibility over time?

For most teams tackling generative engine optimization (GEO) right now, these questions are genuinely difficult to answer with confidence. The data either doesn’t exist or exists in a form that doesn’t scale — via manual prompt tests, informal spot checks, or tools that count AI mentions without explaining what they mean. That’s what Lumar’s AI Search Visibility features are built to address.

AI Search Visibility is a dedicated prompt tracking and AI brand visibility reporting tool, launching today as part of Lumar’s growing GEO platform. It tracks your brand’s visibility across today’s most popular AI answer engines — ChatGPT, Google AI Overviews, Google AI Mode, Gemini, Perplexity, and Claude — measuring not just whether your brand is mentioned, but how it’s being represented. And because it lives inside the Lumar platform, your AI visibility data connects directly to your website crawl analysis and our GEO technical and content diagnostics — so visibility gaps can be diagnosed and acted on in a single workflow.

What Lumar AI Search Visibility does: core capabilities

AI Search Visibility is structured around a simple premise: systematic, repeatable tracking of your brand across the AI platforms your buyers are actually using today.

You configure the topics that matter to your business — the strategic thematic areas where your brand needs to win AI visibility and brand mentions — then define the specific prompts you’d like to track within each topic. Lumar runs those prompts across ChatGPT, Google AI Overviews, Google AI Mode, Gemini, Perplexity, and Claude, and extracts data from every answer, including: 

• brand mentions
• citation positions
• qualitative brand sentiment assessments

The result is a consistent, structured dataset of meaningful AI visibility metrics that your team can track over time — not a snapshot from a random afternoon of manual testing, but a repeatable view of your brand's AI presence across the platforms and topics that matter most for your business, auto-refreshed at a cadence that suits your workflow.
And, by combining this AI brand visibility data with Lumar’s technical website crawl data and SEO and GEO insights, users gain a unified view of their brand’s digital presence across both traditional and generative search landscapes.

AI visibility scores: a key GEO metric to track right now

At the center of Lumar’s AI Search Visibility toolkit is your AI Visibility Score: a single, weighted metric that combines brand mention frequency and citation quality across AI platforms into one easily reportable number.

The AI Visibility Score serves dual purposes: 

• For GEO practitioners and managers, it's a trend line — a reliable indicator that moves in response to the technical and content-focused optimizations your team is making to improve AI search visibility, giving you a feedback loop that basic AI mention counts alone can't provide. 
• For marketing leadership, it's a defensible GEO summary metric: something you can put in a board deck, track quarter over quarter, and use to justify continued GEO investment.

The AI visibility score reflects what's actually happening across your configured prompts and AI platforms — and because it's backed by up to two years of stored data, it supports the kind of longitudinal narrative that proves a GEO program is producing real results, not just busywork.

Beyond mere brand presence: AI brand sentiment scores

Whether your brand appears in an AI answer is one question. How it appears is a different (and arguably more important) one.

AI engines don't just mention brands. They describe them. They characterize a brand’s capabilities, frame positioning, note limitations, and place brands in context relative to competitors — often before a potential buyer has ever visited your site or spoken to your team. That description shapes brand perception in ways that a simple mention count won’t capture.

Lumar’s AI Brand Sentiment Score is built to measure this qualitative dimension of AI answers. It provides an assessment of how your brand is being presented by different AI systems — not just whether it's mentioned — so your team can understand whether AI search is reinforcing your brand positioning or creating a problematic narrative that needs to be addressed. 

For teams managing brand perception as well as AI search visibility, this is the data point that mention-only tracking tools fail to provide. AI Brand Sentiment Scores are the metrics that move GEO measurement from mere presence tracking to real brand intelligence.

Competitor AI mentions benchmarking with topic-level visibility

Understanding your own brand’s AI visibility is only half the picture. The other half is knowing which of your competitors are being cited instead of you, and for which topics.

For every prompt you configure in Lumar, our AI Search Visibility tools also surface the other brands being cited alongside (or instead of) yours. Competitor benchmarking gives you AI Visibility Score comparisons across the same prompt landscape, share-of-voice trend data over time, and a clear view of which topic areas competitors are winning and where opportunities exist.

The topic-level structure adds a second layer of strategic competitive insight. Prompts are organized within topic clusters, and AI Search Visibility provides aggregated roll-ups at the topic level — so alongside prompt-level citation data, you get a strategic view of which broader topical themes your brand is winning in AI search and where your topical authority is weak. That topic-level data is particularly useful for content strategy decisions and for leadership presentations where the headline story matters more than individual data points.

The integration advantage: why AI visibility data belongs in your website optimization platform

There's no shortage of tools that will tell you where your brand appears in AI answers. The more important question is what you can do with that information once you have it. 

Most AI visibility tools are simple monitoring tools. They surface where you appear in AI answers, and they stop there. The gap they leave open — between "we have an AI visibility problem" and "here's what's causing it and what to do next" — is where most GEO programs get stuck.

Because AI Search Visibility lives inside Lumar, your AI visibility data sits alongside deep website crawl analysis, technical GEO and SEO metrics, and content evaluation tools in a single workflow. That means teams can move from "our AI Visibility Score is underperforming in this topic area" to investigating the technical and content factors that impact it without switching platforms or reconciling data sets from siloed tools.  

Built for the whole GEO team

GEO programs typically involve at least three distinct stakeholders, each with different data and insight needs. Lumar’s AI Search Visibility is built to serve all three.

• For Technical SEO/GEO Managers: Reproducible, prompt-level AI visibility data across all major AI platforms, with the ability to connect visibility gaps to technical website factors like robots.txt, rendering, schema, or indexability, in the same platform. That’s AI visibility data you can diagnose, not just monitor.
• For Content Managers: Topic-level AI visibility data that shows where your brand's topical authority is strong in AI search and where coverage gaps exist — giving content teams a structured basis for prioritizing content creation, refreshes, and retirement decisions rather than relying on intuition alone. 
• For VPs of Marketing and CMOs: The AI Visibility Score and trend data provide leadership-ready metrics for GEO reporting — reproducible, methodology-backed, and designed to demonstrate that AI search investment is translating into measurable brand presence over time.

How to get started with AI visibility tracking in Lumar

Getting up and running with AI Search Visibility in Lumar is straightforward:

• Create a project. Set your brand name, domain, the AI platforms you want to track, and your preferred prompt tracking cadence — daily, weekly, fortnightly, or monthly.
• Configure your topics and prompts. Define the topic clusters that reflect your strategic search landscape, then add the specific prompts within each topic that your target buyers are likely asking AI engines.
• Lumar runs your prompts across all configured platforms, extracting brand mentions, citation positions, competitor data, and qualitative brand sentiment assessments from every answer. 
• Review your dashboard. Your Visibility Score, Brand Mentions Score, topic-level roll-ups, competitor rankings, and citation details are all surfaced in your Lumar AI Visibility Dashboard — and updated at your chosen cadence, with data retained for up to two years.

Get a platform demo 

Lumar’s AI Search Visibility features give your team the structured GEO measurement infrastructure to track brand presence across AI answer engines, understand how your brand is being represented, and connect that data to a clear path of action — all inside the Lumar platform.

Already a Lumar customer? Speak to your account team about adding AI Search Visibility to your plan.

GEO learning resources:

Free eBook Download: The 2026 AI Search Playbook

80+ pages of GEO/AEO strategy insights, expainers, and insights from 20+ SEO pros on how they are approaching AI search optimization in 2026.

Download the GEO guide

Go from AI Visibility analytics to a full GEO action plan

Connect AI prompt tracking data with the broader Lumar GEO suite: Lumar connects your AI brand visibility data to deep website crawl analytics so you can easily spot the pages that could be driving AI citations but aren't and fix whatever's holding them back. 

Lumar takes you from AI visibility diagnosis to a prioritized GEO action plan, all in one place.

Explore the full GEO / AEO Tool Suite

The post Track Your Brand Across AI Answers: Introducing AI Search Visibility Tools in Lumar appeared first on Lumar.

Each month, Lumar’s in-house tech SEO experts hand-pick some of the SEO industry’s top news stories from across the web to keep you up-to-date on all things SEO and website optimization.

For our March 2026 SEO & GEO/AEO news roundup, the top headlines include:  

• The presence of Google’s AI Overviews in search results grew 58% in one year. 
• Google will enable sites to opt out of AI Search features: Following guidance from the UK’s Competition and Markets Authority (CMA), Google has confirmed it’s working on a way to allow sites to opt out of generative AI features like AI Overviews.
• Google’s AI Mode is increasingly sending users back into its own ecosystem via self-referencing links.
• 67% of ChatGPT citations within a given topic are captured by only around 30 domains.
• Shopify launches “Agentic Storefronts” that allow merchants to sell directly inside ChatGPT, AI Mode, and more.
• Walmart’s 3x Conversion Gap: ChatGPT checkouts significantly underperformed compared to standard web traffic for the major US retailer, leading the company to rework its approach to agentic ecommerce.
• (and much more, below!)

Dive into the details behind the SEO and GEO/AEO headlines this month below…

But first: Lumar’s new, free 80-page guide to GEO/AEO has just launched!

With actionable checklists and in-depth explainers on each area of GEO, & real insights from 20+ SEO experts,, this 80-page playbook is a must-read for SEOs, content strategists, and digital marketing leaders alike.

Ready to take your GEO/AEO strategy to the next level? Get the free 2026 GEO/AEO guide now.

Get your free 2026 AI search playbook here

March 2026 SEO & GEO/AEO News Roundup:

Google is testing AI-driven title rewrites in search results

Google has confirmed it’s experimenting with AI to rewrite page titles in SERPs. Of course, Google rewriting titles is nothing new, but this is the first time Google has openly confirmed that AI is being used for this purpose. According to Google, the end goal is to generate titles that better match user intent and drive greater engagement. However, publishers are understandably concerned about the potential for AI to completely alter the tone and meaning of titles, diminishing user trust as a result.

(Source: Search Engine Land )

Google’s own dominance in AI Mode responses grows

New research from SE Ranking suggests that Google’s AI Mode is increasingly sending users back into its own ecosystem via self‑referencing links. Google.com is now the most cited source in AI Mode responses, accounting for roughly 17.4% of all citations. That’s up from 5.7% last year, and is more than the next six domains combined.

While organic links still appear in AI Mode, there’s clearly a focus on encouraging users to continue their search within Google. This raises real visibility challenges for publishers, with potentially even less traffic being sent to their own sites.

(Source: SE Ranking )

67% of ChatGPT citations within a given topic are captured by around 30 domains

A new study by Kevin Indig reveals that ChatGPT citations are significantly more concentrated than traditional search results. Analyzing 1.2 million ChatGPT responses, the research found that roughly 30 domains capture 67% of all citations within a specific topic. 

While ranking #1 on Google remains a strong signal—with 43.2% of top-ranking pages earning a citation—the AI is remarkably selective. ChatGPT retrieves approximately six times more pages than it actually cites, effectively “ignoring” 85% of the content it analyzes during its search process.

(Sources: Kevin Indig, Search Engine Land)

Google’s AI Overviews continue to surge across multiple industries

Google’s AI Overviews are rapidly expanding, with coverage growing by 58% YoY according to a new study from Brightedge. As of February 2026, AIOs appear in almost half of all search results, with a particular focus on nine major industries. It’s a clear shift away from AIOs being shown purely for informational queries. Their presence is now commonplace across a diverse range of sectors, including healthcare, travel and ecommerce. 

The average AIO block also now exceeds 1,200px in height and places the top organic result below the fold. With only around 17% of sources cited in AIOs also ranking in the organic top 10, there’s real pressure on sites from these industries to increase visibility within AI-led search features.

(Source: Search Engine Journal )

Analysis from Google’s Discover update shows a shift in distribution

New data from NewzDash reveals that February’s Google Discover core update caused notable shifts in behavior, with less diversity and fewer unique publishers appearing in top placements. Much of this change was due to a push towards regional personalisation in the results. Data from New York and California shows increased visibility for country and state-specific publishers over the update period. 

However, the data also shows a shift towards publishers that can show clear topical expertise. Specialist publishers are performing better post-update, with fewer generalist sites appearing in top placements. There’s also been a tilt toward more timely, authority‑driven topics rather than sensational clickbait, which was originally listed by Google as one of the main goals of the update.

(Source: NewzDash )

Google makes improvements to its Universal Commerce Protocol for AI shopping

Google has announced fresh updates to its Universal Commerce Protocol (UCP), improving core features like catalog and cart functionality. There’s also a more streamlined onboarding process for merchants wanting to be early adopters of the protocol. 

The update focuses on reducing friction and accelerating adoption, as UCP paves the way for bigger breakthroughs in agentic commerce. More information on the changes can be found in the official help documentation, published earlier this month.

(Source: Google: The Keyword Blog )

Google is winning the AI search race, but at a cost to publisher clicks

New data from Sistrix places Google at the top of the pile for AI Search, but argues that it’s distribution, rather than quality, keeping it there. Unlike its competitors, Google has the benefit of its AI models being baked into an already established Search product, with no change in user behaviour required. However, this win for Google comes at a heavy price for publishers. By integrating AI-powered features into the core Search platform, the number of organic clicks per search is decreasing. 

(Source: Sistrix )

Google will enable sites to opt out of AI Search features

Following guidance from the UK’s Competition and Markets Authority (CMA), Google has confirmed it’s working on a way to allow sites to opt out of generative AI features like AI Overviews. We’re yet to learn exactly how this would work, or whether it will impact sites outside of the UK. However, it’s a clear step towards giving sites more control over their presence in AI-powered search features. 

Site owners can currently opt-out of AIOs and AI Mode by using the nosnippet meta tag. However, its usage also has broader implications for traditional web search, image search and Discover. The new controls being worked on by Google will presumably be limited to AI features only.

(Source: Google: The Keyword Blog )

Google completes rollout of GSC-branded queries filter

Google has expanded its branded queries filter to all eligible Search Console properties, letting site owners easily distinguish between branded and non-branded traffic in the Performance report. The ability to do this is nothing new, but previously required manual regex filters that are now available at the click of a button.

(Source: Search Engine Land )

OpenAI shuts down Sora, its generative video tool

One of the more surprising AI product reversals this month came from OpenAI, which announced this week that it is shutting down Sora, its AI video app. The decision lands less than a year after Sora became one of the company’s most attention-grabbing consumer launches, and just months after OpenAI and Disney announced a $1 billion licensing deal, which would have seen iconic characters licensed for AI video creation.

OpenAI has said they are choosing to shut down Sora in order to refocus on other developments, like robotics, “that will help people solve real-world, physical tasks,” according to the BBC.  

Despite the massive viral interest at launch, Sora apparently struggled to convert hype into profit. Market intelligence firm Sensor Tower highlighted a staggering revenue gap between OpenAI’s Sora video product vs. its core ChatGPT product:  while ChatGPT generated $1.9 billion in global net revenue over the same period, Sora managed just $1.4 million, according to BBC reporting. 

According to reporting from The Guardian, the app’s brief run was overshadowed by familiar generative-media problems: deepfake concerns, moderation challenges, misleading content, and questions over copyright and creator rights. Disney responded by saying it understood OpenAI’s decision and remained committed to exploring AI responsibly, but the shutdown still marks a sharp end to what had looked like one of the most commercially significant entertainment partnerships in the generative AI market.

For digital marketers, this story is less about video creation alone and more about the fragility of AI platform ecosystems. It shows how quickly a product can go from breakout launch to strategic retreat — and why teams building on third-party AI platforms need to think carefully about dependency risk, content rights, and long-term platform stability.

(Sources: BBC, The Guardian, Al Jazeera, MediaPost, Sora on X)

Shopify launches agentic AI for e-commerce: merchants can now sell directly inside ChatGPT, Google AI Mode, and more

This month, Shopify rolled out Agentic Storefronts, giving its millions of merchants out-of-the-box access to sell inside AI chatbot interfaces — including ChatGPT, Microsoft Copilot, Google’s AI Mode, and the Gemini app — all managed from the Shopify admin dashboard with no additional integrations required. Shopify has also launched a standalone Agentic Plan for brands not using Shopify as their primary ecommerce platform, allowing them to list products in Shopify Catalog and gain visibility across the same AI surfaces.

Underpinning the Google-Shopify AI integrations is the Universal Commerce Protocol (UCP) — an open AI e-commerce standard co-developed by Shopify and Google. 

(Source: Shopify Announcement)

Walmart sees 3x lower conversion rates with ChatGPT checkout vs. on their own website

While Shopify announced more agentic AI ecommerce tools this month, Walmart revealed that its initial test of an AI-powered checkout experience inside ChatGPT suggests the model still needs work. According to reporting from Inc., Walmart’s conversion rates for purchases completed within ChatGPT were around three times lower than on Walmart’s own website, with customers finding the experience “unsatisfying.”

Despite the weaker performance with AI checkout, Walmart is doubling down. The retailer is embedding its own AI assistant, Sparky, into ChatGPT to maintain control over personalization, assortment, and the overall customer experience.  

Walmart is also maintaining its broader AI commerce strategy, with a separate Google Gemini partnership announced in January that has yet to launch.

Why it matters for SEO: This is an early real-world data point on AI-driven commercial conversion — and it confirms what many in the industry suspected: being discoverable in an AI interface is not the same as converting there. For SEO and ecommerce teams, it underscores the importance of owning the checkout journey and not assuming that AI surface visibility automatically translates into revenue.

(Sources: Search Engine Land, Inc., Retail Dive)

Did you know you can now optimize for AI search and LLM brand mentions with Lumar?

Lumar’s GEO tools for AI search optimization provide data-driven insights to help you optimize your website for AI-driven search visibility, earn more AI citations, and improve brand visibility across LLMs.

Explore Lumar GEO Platform Features

Get started with Lumar

Get Lumar pricing

The post SEO & AI Search Industry News – March 2026 appeared first on Lumar.

To cut through the noise around optimizing for AI search visibility, we went directly to the people closest to the problem: SEO strategists, technical leads, content specialists, and digital marketing directors actively navigating AI search in 2026. 

What follows is their collective thinking — unfiltered, often refreshingly blunt, and full of practical tips for anyone trying to stay visible in a world where AI increasingly decides what users see online.

GEO Strategy Guide

This post is an excerpt from our 80-page guide to GEO in 2026

Get the free full guide to AI search optimization here.

What SEO experts are saying about optimizing for AI search visibility in 2026…

We asked dozens of SEO, GEO, content, and digital marketing experts around the globe how they were thinking about GEO in 2026. Here’s what they had to say…

Entity-building is key for GEO

“AI visibility will define SEO in 2026 because discovery is no longer confined to search engines; it’s happening inside AI conversations.

Whether users are asking ChatGPT for recommendations, researching through Perplexity, or relying on Google’s AI Overviews, brands need to be retrievable in those ecosystems. The challenge is that AI doesn’t think in keywords; it thinks in entities and relationships. That means the old way of optimizing for rankings doesn’t guarantee you’ll show up in AI responses.

For SEOs, this shift requires a mindset change: from optimizing for algorithms to educating AI about your brand. That means building clear topic–entity connections, consistent schema, and credible signals across every channel so your expertise becomes part of the LLM’s “understanding” of your niche.

My tip for 2026: stop chasing prompts and start tracking entity presence. If your brand is being cited, summarized, or referenced by AI, you’re not just visible, you’re trusted by the systems shaping the future of search.”

— Aimee Jurenka, SEO Strategist at RicketyRoo

Multichannel brand visibility & content quality influence AI selection

“SEO best practices remain essential even as AI search grows.

Focus on building brand visibility across multiple channels, creating AI-friendly content with structured headings and quotable insights, researching real user questions, and incorporating first-party data and unique perspectives. Above all, make your content genuinely helpful.”

— Ana Perez, SEO Manager

Understand both your human and machine audiences

“AIs and LLMs are moving too fast to pin down any ‘this works’ tactics. Things that work now may not work tomorrow. The best route is still sticking to doing the fundamentals well: know your target audience; understand their pain points; create content that talks to them; understand the machines that surface that content in the contexts and on the platforms where your audiences are looking.”

— Andrew Cock-Starkey, Founder & SEO Consultant at Optimisey

Create content clusters to improve semantic relevance for LLMs 

“Clustering can be really powerful, and all the SEO basics – this will help the semantic language be understood more powerfully by LLMs if the website makes sense from a crawler perspective and from a topic perspective.”

— Angèle Chevalier, SEO & Content Strategist at CharlieHR

Site structure, EEAT, and customer reviews matter for GEO and SEO alike

“GEO is becoming a critical part of SEO as AI-driven search and LLMs shape how information is discovered, and has changed the way users search altogether. That said, it’s important not to lose sight of traditional SEO fundamentals – strong technical and on-page optimization, high-quality content that follows E-E-A-T principles should remain the foundation before adding specific ‘AI optimisation’ tactics. 

To move the needle with GEO, structured, authoritative, and easy-to-understand websites are key (which, in truth, isn’t anything new!). This includes maintaining accurate business listings, implementing schema markup, and ensuring your content clearly signals relevance and brand identity. Encouraging reviews and user-generated content that reference your business in context can also help LLMs and AI assistants associate your brand with relevant queries.”

— Chloe Steele, SEO Account Manager at Verde Digital 

SEO, PPC, brand, and social media marketing channels need to work together for GEO

 “LLMs and AI tools are heavily reliant on two things – old school SEO and brand presence across the web. Focus on ensuring citations, reviews, content and UX, and it’s been shown that AI presence increases. There is no “secret sauce,” no shortcuts; achieving results from LLMs requires dedicated actions and research, and this goes beyond marketing ­— it’s all about the customer journey. 

Considering the entire customer journey, from search/content digestion to the post-purchase phase, it’s clear that both users and AI play a significant role in this journey.  LLMs and AI tools gather and present all available information, both good and bad, to users. Therefore, considering this as part of the overall strategy, from search to reviews, the entire process needs to be taken into account. 

Digital marketing is no longer a silo of SEO, brand, PPC and social  ­—  all areas need to be considered and work as a team to get the best possible results.”

— Chris Evans, SEO Specialist

Optimize both technical site elements and trust-building signals to boost AI citations

“Schema, website technical health and thought leadership/authority all come to mind when I think of GEO. We need to understand the way that AI crawls and dissects content to provide a response, and therefore structure our content to make this as seamless as possible. E.g. adding unique, useful questions and answers, implementing schema so LLMs (and Google) understand content better. 

The thought leadership/authority comes in to help your business or product/service seem more trustworthy and subsequently be cited in AI responses more. All of these tactics are not dissimilar to traditional SEO, but now there may be greater emphasis on some ‘ranking factors’ that were previously overlooked before.”

— Dorothy Edgar, SEO Manager at Beauty-SEO 

SEO best practices are also GEO best practices — some, like digital PR and producing original content, are increasingly important

“Personally, I am yet to see any tactics or strategies that are new and different from what great SEOs have been doing anyway. Yes, we might now be giving more importance to some elements than before.

The SEO tactics that seem to be more important now than ever are:

• Understanding your users and how your brand is presented in Gen AI-powered search. This is particularly relevant for the next stage – agentic search. At the moment it is users who come to your website and a bad first impression can be fixed. What happens when it’s agents taking that row? If your messaging is segmented, not aligned across channels (owned and external) and you are not serving your users what they want, how long will it take for agents to stop visiting your website and for LLMs to stop serving it? 
• PR –  PR becomes much more important when mentions are taken as an element of success and not just links. This also connects to the first point – consistency in branding. 
• Original content – Personally, I have no issue with AI content. As long as it helps the user and is reviewed and edited by humans, I encourage it. The issue starts when no additional value is added to the content. As AI content increases, the companies that will get visibility are those who stand out in this sea of sameness. An industry colleague Dorron Shapow  developed a really nice framework to start people on the road of thinking about information gain (not the patent!). It’s called I.N.S.I.G.H.T. I would suggest you check it out.  
• Building websites that reduce cognitive friction – We have a great podcast on this with Arnout, and it aligns with agentic search – unlike users, agents will be much less forgiving when it comes to friction in your most important user journeys. SEOs will need to understand how to set up tracking to discover the bottlenecks and then work to unblock them, preferably before agentic search kicks in.”

. . .

“Two courses I always recommend for developing LLM literacy skills are Lazarina Stoy’s Intro to Machine Learning and Britney Muller’s AI for Marketing. Both are excellent! “

— Emina Demiri-Watson, Head of Digital Marketing at Vixen Digital 

Focus on answering real user queries

“New or refreshed content that focuses on exact queries people are asking (found, for example, by parsing data from Reddit or PAA results) is the key to a solid “GEO” strategy. This can be used as a testing ground since AI generally scrapes and pulls in content faster than traditional SEO results. In my own experience, I have seen AEO (answering FAQs or PAA results with on-site content) helps websites rank (or at least be mentioned/cited) quicker within AI Overview results.”

— Eric Hoover, SEO & AI Search Director at Kepler Group

Make AI prefer your brand over others as a trustworthy, authoritative source on key topics

“I think GEO/AEO is going to completely redefine what “SEO success” looks like. It’s not enough to just rank #1 on Google anymore ­— AI is pulling information from multiple sources, summarizing it, and even acting on behalf of users. If your content isn’t structured, unique, and trusted, it simply won’t get surfaced, no matter how good your traditional SEO is.

Tactics that can actually move the needle:

• Build brand authority and consistency – AI prefers to cite brands it recognises and trusts. A unified narrative across your website, social channels, and community platforms strengthens credibility.
• Focus on quality service content and comparisons – Detailed descriptions, service differentiators, FAQs, and side-by-side comparisons give AI clear signals of value and relevance.
• Leverage reviews and local signals – Fresh, authentic reviews, accurate Google Business listings, rich media, and local citations help AI understand trustworthiness and local context.
• Optimize for agentic actions – Structure content for AI-driven actions like bookings or purchases (product feeds, APIs, clear CTAs), so AI can directly drive conversions.

In my opinion, the biggest shift here is preference over position. The winners will be the brands that AI recognizes as authoritative, consistent, and actionable. 

GEO/AEO isn’t about tweaking rankings – it’s about building an ecosystem where AI chooses you because it can trust your content and your brand.”

— Irina Ginghina, SEO Director at Modern Citizens

Understand the differences in how LLMs process website content vs traditional search engines, but remember that SEO fundamentals remain essential for GEO

“My thoughts are that nothing has changed significantly, except for the fact that we have a new medium and a new way of presenting information. GEO/AEO are all essentially the same things done in “regular” SEO. There is a difference in how LLMs process websites, which just means a different look at Technical SEO, as well as possibly a different look at the way we produce content, but the essential whitehat tactics that have been used by SEOs for years remain unchanged. “ 

— Iva Jovanovic, Conference Organizer & Digital Marketing Specialist 

GEO is an evolution of SEO, not a replacement

“GEO/AEO is just another evolution of SEO so we need to be incorporating this new way of search into our strategies.

Our job as SEO’s is to reach our target audience and provide the best experience for them. 

So if that means working to show up in these new areas because that is where our audience is, then we should.

But it’s important to be aware that this isn’t the only way people search and so if our audience isn’t there then we need to understand how best to support them i.e. if they are looking for a local / offline experience.

In regards to moving the needle with GEO/AEO it remains the same as it always has, producing quality and relevant content that your target audience wants to see whilst ensuring that your site overall is technically sound so you are delivering the best customer experience.”

— Jess Batin, Head of SEO & CRO at Lantra 

How we think about online brand visibility is changing 

“We’re no longer just chasing that top spot in search engine results, but making sure our content stands out in AI-powered overviews, chatbots and conversational search. With more and more people having conversations with search engines, rather than just firing off a query and waiting for a response, how we think about visibility is changing.”

. . .

“GEO and AEO represent a seismic shift in the SEO landscape. Ever since RankBrain showed up on the scene, we’ve been moving from just trying to please the search engines to figuring out how to make our content appeal to the massive language models that are now interpreting and re-packaging our stuff. 

However, as we learn more about these models, we are discovering that much of the output is grounded in Google results, then reordered based on each LLM’s unique set of ranking attributes (freshness for example). So, traditional SEO (that helps you rank in Google) still has a strong claim to stand on when it comes to influencing citations in LLMs.

That said, below are some nuanced tactics focused on LLMs:

• Focus: entities and context
• Output: direct answers, citations and summaries
• Format: Snippets, questions and answer, structured formats
• Key Metrics: AI mentions, visibility in responses.
• Include FAQs at the bottom of of pages
• TLDR or summaries for quick parsing
• Don’t sleep on meta descriptions! Write unique, informative descriptions that spoil the content.”

— Jon Clark, Managing Partner at Moving Traffic Media

The new goal in search: become a definitive source for AI

“The goal post has shifted; it’s no longer just about ‘top 10 ranking’. It’s about becoming THE definitive source for your niche, so AI systems recognize, trust, and cite your content. 

Tactics that will help move the needle are: 

1. Building topical authority and creating comprehensive content

2. Providing original data and first-hand experience/insights 

3. Optimizing for multimodal search and thinking about taking up as much search real estate as possible 

4. Continuing to do SEO fundamentals and doing them well.”

— Josh Petit, SEO Manager at SnoCountry

Build your brand presence across the wider web to boost AI mentions

“Every industry and every site (and their audiences) are different. GEO/AEO with the ChatGPT 4 update has rolled right back into SEO. If the LLMs just scrape Google results, be there or pull the blinds and shut the curtains.

What does and will continue to matter is brand presence on the wider web ­— social media, YouTube and publications, a clear site structure, well written and executed content and keeping users engaged. This will inevitably help getting into those LLM mentions and keep the flow of sessions and sales going.

We can definitely also use LLMs as a useful tool for identifying how it understands the brand and the site, and the way it goes about retrieving information (via long-tail queries) and what links it provides to sites and when, to understand how we can capture traffic. Building out content around these long-tails and customer pain-points could likely get more visibility than purely focusing on search volumes.

Monitoring brand searches can also be an indication, as when there are no direct links from LLMs users might try to navigate to the pages via branded Google search. Just means we need to connect more dots in our tracking and reporting.”

— Kamilla Revfy, Senior SEO Manager at Rebel

Optimize for third-party brand mentions (linked or unlinked) to improve AI visibility

 “I believe in having your brand mentioned (linked or unlinked) in contextual and topically relevant articles on websites other than your own to improve visibility in LLMs and AI search. The more your brand appears across the web, the easier it is for AI crawlers to find it — and the more likely you are to be cited or mentioned in AI searches and LLMs.”

. . .

On strengthening brand signals (brand mentions, brand searches, social media) for better visibility in Google and LLMs: 

“Before, it might have been enough to just have good content and rank on any site — but now you also need to make sure your brand is strong enough to rank in Google, as Google prefers to rank stronger brands (with more referring domains, brand mentions, and brand searches) higher. You now also need to optimize for AI searches and LLMs — not just Google — and therefore ensure your brand is visible on other sites to be cited in LLMs and rank at the top in Google.

Work on strengthening your brand alongside your content efforts. Allocate part of your SEO budget to Digital PR and securing brand mentions on sites other than your own to improve trust and authority for both Google and LLMs.”

— Katarina Dahlin, Senior Growth Hacker at WhitePress

Make sure your GEO tactics align with broader business objectives

“When it comes to GEO, AEO, or any AI-Search-related acronym of choice, much of what I’ve observed tends to be either fleeting algorithm-hacking or recycled strategies from a decade ago. Yes, there are nuances and various means to an end; however, I’ve always believed in focusing on business objectives vs obsessing over the latest, popular trends – as some of these come and go like the seasons. 

I think it’s crucial to critically evaluate each tactic by asking a simple question: “In 12-18 months, will this genuinely contribute to the brand’s larger objectives?” If the answer is a firm “Yes!”, then those opportunities warrant investment. For example, in our work with a SaaS company, we identified YouTube search as a significant opportunity to reach its audience. This strategy coincidentally aligns with current trends in LLM citations.”

— Kevin Kapezi, Director & SEO Consultant at Growthack.io

AI search considers a wide breadth of inputs: build your multi-site brand presence

 “AI surfaces are not IR systems, when searches happen, they are relying on traditional indexes. It’s still all the same principles of SEO, just how we do them is tweaked.”

. . .

“Search engines have traditionally had more success the more power they take away from webmasters. The most obvious example is PageRank. Rather than relying on the words the webmaster provided, it ‘democractized’ popularity signals which proved incredibly effective. 

The way LLM-type search surfaces work means a much wider breadth of opinion is summarized, so a multi-site presence and consistency in what is being said about you is more important than ever.

This means that effective digital PR, getting people to talk about your brand, your story, your data, on trusted websites, with consistency, will pay even bigger dividends than before, link or not.”

The challenge, ironically, is AI; there are fewer journalists and a huge spike in AI spam sent to them. I would focus on building those relationships and cutting AI out, so they know you can be relied upon.” 

— Mark Williams-Cook, Director at Candour 

Keep your content fresh — and don’t dismiss unlinked brand mentions

“Content freshness becomes a major factor: Search engines have always valued content that’s relevant and up-to-date. LLMs and AI bots will place even greater emphasis on content freshness, opting to cite content that has been recently published or updated. I can see reworking and refreshing outdated content playing a pivotal role in many site’s SEO strategies for 2026, as even evergreen pieces now require regular updates to maintain visibility.

Unlinked brand signals will carry greater weight: LLMs and AI-based search models will continue to prioritize content from authoritative sources, rather than focusing solely on how well individual webpages are optimized for specific keywords. Unlinked brand mentions will also carry more weight, as bots evaluate overall brand sentiment and trustworthiness when deciding which sites deserve visibility.

Shifting responsibilities brings collaboration potential: I can definitely see more SEO teams expanding to cover GEO and AI optimization as part of their day-to-day responsibilities. This is the perfect opportunity to rethink where SEO teams sit in many organizations, as collaboration with developers and engineers becomes even more critical. SEOs need to understand how LLMs discover, process and interpret their content if they want to boost visibility in AI-powered search. This inherently means more technical fluency is required, as well as greater cooperation with adjacent teams.”

— Natalie Stubbs, Senior Technical SEO at Lumar  

Brand trust matters more than ever

On GEO: “While I am still a firm believer to not throw out your focus on SEO in lieu of GEO, it’s clear that this is a crucial part of SEO moving forward and that AI is becoming an option for users in addition (but not instead!) of search. “

. . .

 “It’s become clear that gaining visibility in AI isn’t about optimization—it’s about creating brand and trust signals so strong that AI would be foolish not to put you front and center. Focus on brand first and content optimization second to get the traffic and impact from AI that drives real results, not just visibility as a vanity metric.”

— Natasha Burtenshaw-deVries, Director of Organic Growth at Flywheel Digital 

AI struggles with JavaScript rendering — ensure your website content is accessible for AI bots

“I think AI search is not a revolution in search, it’s just an extension. AI search strategies put more light on previously undervalued areas of SEO that some of us ignored or took for granted. 

In some areas it’s time to go back to basics e.g. with rendering. Google told us for years that they manage to render pages well (I still have pretty large doubts) but now AI search crawlers again don’t render JavaScript and we again need to optimize how we render content to make sure AI search crawlers can find it. Making your site cheaper to both render and understand content is getting more and more important.”

— Patryk Wawok, Co-founder & Head of Technical SEO at Organic Hackers

Semantic relevance and brand authority are key aspects of GEO

“A lot of SEOs have been talking about new techniques to appear in AI search results and LLM-generated responses. But at the end of the day, the foundation still lies in SEO fundamentals. AI systems pull their information from web content indexed in search engines. They ground their responses in that data to verify accuracy.

That means if your website isn’t properly optimized, LLMs won’t be able to access or use your content effectively. So, maintaining a strong technical setup, ensuring your robots.txt isn’t blocking key pages, building topical authority and EEAT, and strengthening your external brand reputation are still essential. 

It’s also valuable to analyze how your brand (and your competitors) are appearing in AI-generated responses: what information is being surfaced, which sources are cited, and how your content is represented. These insights can help you refine your SEO strategy and position your site better for both traditional search and AI-driven visibility.”

. . .

On semantic analysis: 

“Now it’s not enough to just research some keywords and optimize for them. We need to focus on creating topical authority and semantic relations within our content to have higher chances of ranking in AIO or AI tools.”

. . .

On brand authority for GEO: 

“I think brand reputation and authority will be more important than ever in 2026. We’ve always talked about becoming a reference in your niche and getting backlinks from reputable sources, but now it’s even more important to showcase that expertise through your own data, expert quotes or insights, and contributions from real professionals in the field, all of which help strengthen your topical authority.

As we know, brand authority isn’t built overnight. Most of the brands already showing up in AI-generated responses are there because they’ve been doing the work for years and have earned that recognition. We’ve always focused on getting dofollow backlinks, and that’s still relevant, but simple brand mentions will also matter more now, since AI models can recognize and display those sources.

That’s because AI doesn’t just evaluate backlinks; it looks at mentions, reviews, EEAT consistency, and other credibility signals. So, strengthening your digital PR and content marketing efforts will be key. You should also check how AI tools mention your brand to understand how they perceive your business, and identify ways to improve both visibility and trust.”

— Raquel González Expósito, CEO & Founder @ Seoulful Connect

From keywords to credibility: structured, factual content wins in GEO

“As search engines evolve into answer engines powered by generative AI, traditional SEO practices focused on ranking for blue links are being replaced by the need to be cited within AI-generated summaries. 

In 2026, GEO/AEO will be essential for visibility, requiring content to be highly structured, fact-based, and semantically rich to be considered authoritative enough for AI to reference. Rather than chasing rankings alone, SEOs must now optimise for inclusion in zero-click, conversational responses—ensuring that brand-owned content is answer-ready and aligned with user intent at a granular level.”

. . .

“GEO/AEO (Generative Engine Optimisation / Answer Engine Optimization) represents a fundamental shift in how users interact with search. Rather than clicking through a list of blue links, people are increasingly receiving direct, conversational answers powered by large language models like ChatGPT, Google SGE, or Bing Copilot. This means that the traditional SEO focus on rankings is giving way to optimising for visibility within AI-generated responses—where your brand or content might be cited, summarised, or completely bypassed. 

To truly move the needle in GEO/AEO, SEOs must shift from simply targeting keywords to creating factually sound, semantically structured, and highly credible content. 

Here are a few [GEO] tactics that can make a real difference: 

1. Build Topical Authority Through Depth and Interlinking: LLMs favour sources that demonstrate comprehensive coverage of a subject. Creating tightly connected content clusters around core topics—supported by internal links—signals depth and helps AI systems identify your site as a trusted source. 

2. Use Structured Data and Semantic Mark-up: Schema.org mark-up helps search engines and LLMs better interpret and attribute your content. While it doesn’t guarantee inclusion in AI responses, it does support machine comprehension—especially for entities, products, FAQs, and reviews. 

3. Publish Clear, Evidence-Based Content With Named Sources: AI models often reference content that is factual, well-sourced, and aligned with user intent. Including original data, cited studies, or quotes from experts improves the chances of being selected or paraphrased by an answer engine. 

4. Optimize for Queries With Strong Informational Intent: Focus on long-form, question-led content that answers common user queries in a conversational but structured format. Well-formatted subheadings (e.g., H2/H3), summaries, and TL;DRs make it easier for LLMs to extract and repackage content accurately. 

5. Enhance Brand Mentions and Digital PR: Even when content isn’t directly cited via links, LLMs still recognise brand mentions across the web. Digital PR, thought leadership, and high-authority citations all improve your chances of surfacing in AI-driven summaries. 

In short, GEO/AEO isn’t just another ranking update—it’s a new paradigm. The focus now is on being the best possible source for the answers users seek, not just the most optimised page for a keyword. 

Those who adapt early—by embracing structure, authority, and semantic clarity—will secure disproportionate visibility in the future of AI-powered search.”

. . .

“In 2026, the real competition won’t just be for position one—it will be for the AI’s attention. If your content isn’t structured, factual, and credible enough to be cited in a large language model’s response, you may be invisible to the user entirely. 

As AI continues to collapse the traditional SERP into conversational answers, SEOs must rethink what visibility means. Optimizing for inclusion in LLM outputs—rather than just rankings—requires a shift in strategy, content design, and measurement. It’s not about being found, but about being the source.”

— Rejoice Ojiaku, Senior Content Specialist @ Wise

AI search is essentially long-tail search

“I think many people are forgetting that LLMs still run on Google and Bing and AI search is essentially long-tail search. This isn’t anything new to SEOs and, frankly, strategies focused on including long-tail keywords, informative content, and improving formatting or internal linking for context building should’ve already been part of everyone’s strategies.”

. . .

“Google’s shift to AI Mode has shaken people even more so than LLMs entering the scene. I think this is partially due to users now worrying that Google will completely remove the view we’ve used since Google launched in 1998. 

We’re seeing tests to check whether Google can remove pagination in SERPs, AI Overviews are testing PPC, AI Mode is being pushed with giant buttons and pop ups on every scroll. It’s clearly a new way of searching they will try to push as not enough users are utilizing Gemini due to the need to sign in (unlike ChatGPT or Perplexity).

We have yet to see any data from Google on how they track CTR from AI Mode, how GA4 and GSC will report on it, or what it could mean for the websites that are still visible in traditional SERP view vs AI Mode answers. This is something Google will have to work hard on to convince users to move towards as many businesses could be negatively impacted by this change. SEOs will need to watch closely, test how they perform in Gemini vs other LLMs as that is likely what will drive AI Mode.”

— Sara Kavanagh, Director of SEO at Candidsky 

AI visibility depends on how well LLMs can understand, extract, and cite your content

“GEO/AEO (Generative Engine Optimization / AI Engine Optimization) represents a fundamental shift in search. The goal is no longer just ranking on traditional SERPs, but ensuring that your content is accurately retrieved, cited, and surfaced by large language models (LLMs) and AI-driven assistants. Today, visibility depends on content structure, authority, and semantic clarity, not just keywords or backlinks. Essentially, GEO/AEO is about shaping how AI “understands” your content, its entities, context, relationships, and factual authority. Brands that fail to optimize for AI risk being invisible in zero-click answers or misrepresented in AI-generated summaries.

Tactics that can truly move the needle include:

1. Rigorous Schema & Structured Data (The Data Layer): Use entity-rich, specific schema types like HowTo, FAQ, Product, FactCheck, and About (for authors/organizations). This ensures LLMs can accurately ingest your content and cite it reliably in AI-generated answers.

2. Query Fan-Out & Topical Cluster Architecture: AI often expands a single query into multiple sub-queries. Structuring content in tightly knit topical clusters ensures your brand becomes the authoritative source across the entire topic, capturing both the main question and all related follow-ups.

3. Evidence-Rich, High-Quality Content: LLMs prioritize factual, verifiable content. Include citations, statistics, expert authorship, and short structured answer blocks (100–150 words) marked up with FAQ or HowTo schema. Linking entities to recognized concepts (e.g., via schema or Wikipedia) reinforces authority and improves retrievability.

4. Cross-Platform & Multi-Modal Optimization: GEO/AEO is not limited to text. Optimizing videos, images, and audio with structured metadata increases your chances of being surfaced across YouTube, visual search tools, marketplaces, and social platforms.

5. AI Testing & Prompt-Driven Audits: Regularly test how your content is retrieved by AI using realistic prompts. Identify gaps in entity coverage, clarity, or factual accuracy, and iterate. Understanding AI behavior allows you to proactively ensure your content is trustworthy and retrievable.”

. . .

“Of course, while my main focus is on Multi-Modal and Multi-Surface Discovery, I’ll also be looking closely at two other critical trends:

1. Passage-Level & Vector-Based Optimization: Search is evolving beyond traditional page-level indexing. AI-driven engines now retrieve specific passages from content and rely on dense vector embeddings to understand context and meaning. For SEOs, this means granular, semantically rich content will outperform generic, keyword-stuffed pages.

By 2026, success in SEO won’t be about ranking a page, it will be about ensuring the right passage from your content is surfaced in response to an AI query. Traditional keyword targeting alone won’t suffice. SEOs need to structure content into clear sections, use semantic clustering, and optimize each passage for clarity and relevance. Tightly scoped, well-organized content ensures AI systems can accurately extract the information they need, increasing the chances of being cited in AI-generated answers.

2. Citation and Reference Authority: Clicks will no longer be the ultimate measure of success. LLMs will prioritize trustworthy, verifiable content that can be cited in AI-generated responses. Zero-click answers mean that authority, not traffic, defines visibility.

This creates a challenge for SEOs: how do you build credibility in a system that may never direct users to your site? The answer lies in structured data, factual citations, entity linking, and transparent authorship. By embedding data points, references, and authoritative signals into content, SEOs can make their brand visible to AI systems, even if users never click through.”

. . .

“Finally, focus on trust and authority. AI prioritizes sources that are accurate, consistent, and citable. By building credibility through factual transparency, structured references, and reliable content, you can maintain visibility even in zero-click and AI-first search environments. SEOs who combine technical rigor, semantic understanding, and disciplined execution will be best positioned to thrive in 2026 and beyond.”

— Stephen Akadiri, Senior SEO & Organic Growth Specialist at Grey 

Brand authority and unique, high-quality content take center stage for GEO

 “SEO fundamentals are still the same, but we have shifted priorities: Good content alone is not going to move the needle anymore. We need strong brand authority. 

Things that have long been seen as “nice to have” or “bonus SEO” are now must-haves, such as Digital PR to generate positive brand sentiment and brand mentions. 

When it comes to content, I see people trying to compensate for traffic losses by generating long-tail content at scale with AI, but the end result is still the same type of generic content that has lost clicks to begin with. 

I think the key to organic visibility now is to focus on high-quality pieces with unique data, be it thought leadership that you can’t find anywhere else or first-party data and whitepapers. It’s about becoming a source, not rehashing existing content from sources.”

— Tina Reis, Senior SEO Strategist at Muhlert Digital  

Your GEO Tech Stack

Explore Lumar’s GEO Toolkit

From AI prompt tracking to technical GEO audits and in-depth content evaluation tools for GEO/AEO, Lumar has you covered.

The post GEO/AEO in 2026: SEO Experts Weigh in on AI Search appeared first on Lumar.