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

Cassie Clark
  • 5.0 (5)
  • Marketing

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. 2d ago

    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/

  2. 4d ago

    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/

  3. 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/

  4. 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/

  5. Sep 17

    OpenAI Is Turning ChatGPT Ads Into Conversations

    Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe OpenAI is testing a new kind of ChatGPT ad that doesn't just send users to a landing page. It starts a conversation. In this Found in AI news update, Cassie Clark breaks down OpenAI's new Sponsored Agents, Google's latest agentic commerce tools, and a new publisher licensing program that raises some interesting questions about how much Google can actually measure inside AI search. You'll learn: How OpenAI's Sponsored Agents could change the traditional ad-to-website journeyWhy ChatGPT ads point toward a much bigger shift in agent-mediated commerceHow Google is bringing Business Agents and more AI shopping capabilities into the customer journeyWhy Google's new AI share-of-voice reporting for retailers is worth watchingHow Google's pay-per-value publisher program complicates the conversation around AI search measurementWhy marketers need to think beyond AI visibility and start preparing for agent readiness-- 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 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/

  7. Sep 10

    ChatGPT’s Search Index, llms.txt Confusion & the Rise of AI Shopping

    Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe In this Found in AI news update, Cassie Clark breaks down Peec AI’s research into OpenAI’s Labrador retrieval index, including the separate indexes identified for web content, news, shopping, YouTube, PDFs, and more. Then, we look at Common Crawl’s analysis of more than 584,000 llms.txt files and what it tells us about the confusion surrounding llms.txt, robots.txt, and AI crawler access. Finally, Microsoft is preparing businesses for a future where AI agents don’t just help consumers discover products — they help choose and buy them. Microsoft’s latest agentic commerce guidance shows why structured, accurate, and current product data could become critical as AI moves from answering questions to taking action. In this episode: What Peec AI discovered about ChatGPT’s Labrador search indexWhy ranking in Bing isn’t a proxy for ChatGPT visibilityHow freshness appears within ChatGPT’s retrieval infrastructureOpenAI’s experiments with its own shopping indexWhat Common Crawl learned from 584,107 llms.txt filesThe difference between llms.txt and robots.txtWhy llms.txt does not control AI crawler accessMicrosoft’s recommendations for preparing for agentic commerceWhy structured product data matters when AI agents are shoppingThe difference between AI visibility and agent readinessWhy businesses should prepare for AI discovery even while the technology continues to changeSources Peec AI: “ChatGPT Built Its Own Search Index”Search Engine Journal: “Common Crawl Finds Widespread Confusion Around llms.txt & robots.txt”Microsoft Advertising: “How Businesses Win When AI Does the Shopping”-- 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/

  8. Sep 3

    Google Is Moving From AI Search to AI Agents

    Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe Google is giving us a pretty clear look at what comes after AI search visibility: AI agents that don't just recommend brands, but help consumers take action. In this week's Found in AI news update, I'm looking at several recent Google developments that make much more sense when considered together. Google DeepMind says Gemini is evolving from a model into an agent. Meanwhile, Google is adding more of the customer journey directly into Search and AI Mode, including flight price tracking, hotel research and booking, product discovery, visualization, price comparison, and more. So, what happens when getting recommended by an AI engine is only step one? In this episode: Why Google DeepMind is thinking beyond the chatbotHow AI Mode is expanding from travel research into hotel bookingWhat Google's home decor features tell us about the changing buying journeyWhy AI search visibility is still critical, but may actually be the beginning of the journeyThe difference between being recommended by an AI engine and being ready for an AI agent to take actionWhy agentic commerce will require more than content and SEO teams alonePlus, I share why marketers should start asking a new question: Once an AI engine finds, understands, trusts, and recommends your brand, can an AI agent actually do something with it? Resources mentioned: Google DeepMind on Gemini's evolution from model to agent Google's new AI Mode travel and hotel booking capabilities Google's AI-powered Search features for home decor Programming note: Found in AI is taking a short Labor Day break, so there won't be a Tuesday episode next week. We'll be back with a new episode the following Thursday. I'm 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/

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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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