Found in AI: AI Search Visibility, SEO, & GEO

Cassie Clark

Found in AI is a podcast for marketers, founders, and content strategists who want to understand—and win—AI search visibility in the new era of search. Hosted by Cassie Clark, fractional content strategist and AI search visibility consultant for startups and enterprise brands, the show explores how platforms like ChatGPT, Perplexity, Gemini, and Google’s AI-powered search experiences discover, select, and surface content. Each episode breaks down real-world experiments, SEO, GEO / AEO, and content marketing strategies designed to help brands get found in AI-generated answers, not just traditional search results. You’ll learn how to: -Optimize content for AI-driven search and answer engines -Blend traditional SEO with AI search optimization -Build entity authority across search, social, and AI platforms -Drive traffic, leads, and trust as search behavior continues to evolve If you’re trying to future-proof your content strategy and understand how AI is reshaping discovery, Found in AI gives you the frameworks, insights, and tactics to stay visible—wherever search happens next.

  1. 3d ago

    Google Updates Content Guidance as AI Agents Reshape Search

    Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe AI search is moving beyond citations and recommendations. As consumers use AI to discover businesses (and personal agents begin browsing the web on their behalf), brands need to think about the entire information environment surrounding them. In this episode of Found in AI, Cassie Clark breaks down Google’s updated guidance on main content and fake authors, new data showing rapid growth in AI-powered local search, and Profound’s research into personal agents like Muse and Instinct. Together, these developments point to a larger shift: AI visibility is becoming less about optimizing for a single answer and more about whether humans and AI agents can discover, understand, verify, and act on information about your brand. In this episode: What Google’s new “good main content” guidance means for SEO and GEOWhy content structure matters without becoming another GEO hackWhy brands cannot manufacture authority with fake expertsHow AI is changing local business discoveryWhy AI recommendations still trigger additional verificationHow personal agents like Muse and Instinct browse the webWhat agent-driven discovery could mean for websites and marketersWhy AI visibility and agent readiness are becoming connected problems-- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com.  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/

  2. 5d ago

    Are AI Visibility Tools Measuring the Wrong Things?

    Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe In this episode of Found in AI, Cassie Clark talks with Peter Rota, an SEO professional with 15 years of experience, about the rapidly growing market for AI visibility tools — and where those platforms still have room to improve. Cassie and Peter discuss why actionability remains one of the biggest challenges with AI visibility software, what teams should look for when evaluating a platform, and why a visibility score alone may not tell you very much. They also dig into one of the biggest AI search measurement questions: should brands care more about being cited, mentioned, or actually recommended? Peter shares his own hierarchy — recommendation, mention, then citation — and explains why citations can sometimes come dangerously close to becoming a vanity metric if they aren't connected to meaningful business outcomes. In this episode: Where AI visibility tools are useful — and where they still fall shortWhy AI visibility data needs to lead to actionWhat to consider before paying for an expensive AI visibility platformWhy prompt-based visibility scores don't tell the whole storyWhy mentions and citations shouldn't be combined into one metricThe difference between being recommended, mentioned, and citedWhen citations risk becoming a vanity metricWhy the intent behind the prompt mattersHow to identify a perception gap between your website and an AI system's understanding of your brandWhy lower-funnel prompts may be more valuable to trackWhether your next AI search investment should be software or a person who can actually turn the data into strategy-- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com.  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/

  3. Oct 1

    Google AI Mode Monitoring + Why AI Citations Don’t Equal Recommendations

    Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe Google is expanding AI Mode’s monitoring capabilities, letting users have Google continuously watch the web for new information instead of repeatedly running the same search. In this episode of Found in AI, Cassie Clark looks at what persistent search could mean for content freshness and AI search visibility. Cassie also breaks down new research from Graphite analyzing nearly 500,000 AI shopping responses across ChatGPT and Google. While large and small retailers appeared at similar rates among cited sources, major retailers were significantly more likely to become the actual recommendation — another example of why citation presence and recommendation presence should not be treated as the same AI visibility metric. Plus, Google Search Console adds reporting for multimodal searches originating from tools including Google Lens and Circle to Search, and new research from Perplexity explores why retrieval systems may need more than the single passage containing an answer to provide enough context for a useful response. In this episode: Why Google AI Mode monitoring changes the traditional search journeyWhat persistent search means for content freshnessWhat Graphite found after analyzing nearly 500,000 AI shopping responsesWhy being cited by an AI system does not guarantee your brand will be recommendedHow prompt language can affect which retailers AI recommendsGoogle Search Console’s new multimodal search reportingWhy search intent increasingly exists without a traditional typed queryWhat Perplexity’s contextual embedding research tells us about AI retrievalWhy structuring content for AI shouldn’t mean removing useful context-- Found in AI covers AI search visibility, generative engine optimization (GEO), answer engine optimization (AEO), AI search measurement, and the changes marketers need to understand as platforms like ChatGPT, Google, and Perplexity reshape search and discovery. Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email her at cassie@cassieclarkmarketing.com.  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/

  4. Sep 29

    Who’s Responsible for What AI Says About Your Brand?

    Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe In this episode of Found in AI, Cassie Clark welcomes back Tommy Landry, founder of Return On Now and author of The Signal and the Source, for a conversation about the connection between AI governance and AI search visibility. Internally, companies are connecting AI to CRMs, reporting systems, content workflows, sales data, and other sources of business information. Externally, AI systems are interpreting websites, third-party platforms, brand messaging, reviews, documents, and other signals to understand what a company is and what it does. And when those signals are incomplete, outdated, inconsistent, or just plain wrong, AI can still produce a very confident answer. Cassie and Tommy discuss why companies need human checkpoints around AI-powered workflows, who should be responsible for those checkpoints, and why AI governance can't simply be handed to one department. They also explore what this means for GEO and AI search visibility, including why brands need to think beyond citations and start paying closer attention to how they're actually represented inside AI-generated answers. In this episode: How internal AI governance connects to external AI visibilityWhat happens when AI is working with inaccurate or outdated company dataWhy inconsistent messaging across sales, marketing, and other departments can become an AI visibility problemWhere humans need to remain in the loopWho should be responsible for reviewing AI-generated outputsWhy AI governance requires subject matter expertiseHow automated content workflows can create brand and messaging problemsWhy AI search visibility is about more than tracking citationsWhat it means to measure your brand's AI representationWhy accurate positioning matters before a customer ever reaches your websiteHow third-party signals can shape what AI systems understand about your companyWhy AI governance is becoming a cross-functional business problemTommy also shares the thinking behind his new book, The Signal and the Source, and his framework for managing AI across both internal workflows and external visibility. Find it on Amazon. -- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com.  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/

  5. Sep 24

    AI Agents Are Taking Over. Yahoo Wants to Keep the Links.

    Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe AI is moving beyond answering questions and toward taking action on our behalf. But as agents handle more of the customer journey, what happens to the websites and publishers that make AI-powered discovery possible? In this episode of Found in AI, Cassie Clark breaks down two developments that reveal different sides of the future of search. First, Meta introduces Muse, a personal AI agent designed to complete tasks on a user’s behalf. Cassie explores what the shift from AI answers to AI actions could mean for brand discovery, the customer journey, and why being recommended by an AI engine may no longer be enough. Then, we turn to a story that deserves more attention: Yahoo Scout. Yahoo CEO Jim Lanzone is making the case for an AI search experience that keeps publisher links visible and preserves opportunities for referral traffic. Cassie examines why that approach matters, what it could mean for the economics of the open web, and why marketers need to look beyond citations when measuring AI visibility. In this episode:  What Meta’s Muse reveals about the shift from AI search to AI agents  Why brands need to think about agent readiness, not just AI visibility  How Yahoo Scout approaches AI-generated answers and publisher links  Why citations and referral traffic are not interchangeable  What the future of AI discovery could mean for marketers, publishers, and the open web Stories covered: Meta: Introducing Muse, a Personal AI Agent The Next Web: Yahoo Scout, Jim Lanzone, and the Future of Publisher Links -- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com.  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/

  6. Sep 22

    Does ChatGPT Recommend the Same Brands to Everyone? [NEW RESEARCH]

    Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe Does ChatGPT recommend the same brands to everyone? In this episode of Found in AI, Cassie Clark talks with Joao from Friction AI about new research examining how personalization changes the brands recommended by ChatGPT, Gemini, Claude, and Perplexity. The study compared responses collected through APIs, anonymous AI accounts, and accounts that had been primed with specific user personas over two weeks. The results show that personalization does influence brand recommendations — but the effect varies considerably depending on the AI platform. Cassie and Joao discuss: How ChatGPT, Gemini, Claude, and Perplexity respond differently to personalizationWhat changed between API, anonymous, and personalized responsesWhy geography can affect the brands and sources AI systems surfaceWhat personalization means for local and global brandsWhy creating more content isn't automatically the answer when your brand isn't appearingWhat marketers should understand about the methodology behind AI visibility toolsWhy personalization doesn't make AI visibility measurement useless — it makes repeated measurement more importantRead the research: The original research report: The Personalization Gap: How a Model's Knowledge of the User Reshapes Brand Recommendations in Generative AI Cassie's insights Friction AI's insights -- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com.  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/

  7. Sep 15

    AI Search Visibility Is a Brand Problem

    Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe In this episode of Found in AI, Cassie Clark talks with Leah Nurik, CEO and co-founder of Brandi AI, about why brands need to think much more broadly about what influences their visibility in AI-generated answers. Cassie and Leah discuss why GEO is becoming a brand marketing and communications problem, not simply an extension of traditional SEO. They also dig into the role PR and earned media can play in establishing authority, why the sources that matter for AI visibility vary by industry, and why authentic storytelling may be more durable than trying to find shortcuts for influencing AI systems. They also talk about what makes a story compelling enough to earn media coverage, how brands can identify stories that actually add something new to their industry, and what may happen as AI-generated answers become a bigger part of the buyer journey. In this episode: Why Leah believes AI search represents a new buyer journeyWhy GEO extends beyond traditional SEO and your websiteHow PR and earned media can influence AI visibilityWhy authority signals differ from one industry to anotherThe role of peer reviews, user-generated content, and third-party coverageWhat makes a brand story interesting enough for journalists to coverWhy uniqueness matters for both PR and AI searchHow brands can build visibility that may be more resilient to model changesWhere AI search could be heading over the next five years-- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at cassie@cassieclarkmarketing.com.  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/

Ratings & Reviews

5
out of 5
5 Ratings

About

Found in AI is a podcast for marketers, founders, and content strategists who want to understand—and win—AI search visibility in the new era of search. Hosted by Cassie Clark, fractional content strategist and AI search visibility consultant for startups and enterprise brands, the show explores how platforms like ChatGPT, Perplexity, Gemini, and Google’s AI-powered search experiences discover, select, and surface content. Each episode breaks down real-world experiments, SEO, GEO / AEO, and content marketing strategies designed to help brands get found in AI-generated answers, not just traditional search results. You’ll learn how to: -Optimize content for AI-driven search and answer engines -Blend traditional SEO with AI search optimization -Build entity authority across search, social, and AI platforms -Drive traffic, leads, and trust as search behavior continues to evolve If you’re trying to future-proof your content strategy and understand how AI is reshaping discovery, Found in AI gives you the frameworks, insights, and tactics to stay visible—wherever search happens next.

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