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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 GEO
• Why content structure matters without becoming another GEO hack
• Why brands cannot manufacture authority with fake experts
• How AI is changing local business discovery
• Why AI recommendations still trigger additional verification
• How personal agents like Muse and Instinct browse the web
• What agent-driven discovery could mean for websites and marketers
• Why AI visibility and agent readiness are becoming connected problems

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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/

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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 short
• Why AI visibility data needs to lead to action
• What to consider before paying for an expensive AI visibility platform
• Why prompt-based visibility scores don't tell the whole story
• Why mentions and citations shouldn't be combined into one metric
• The difference between being recommended, mentioned, and cited
• When citations risk becoming a vanity metric
• Why the intent behind the prompt matters
• How to identify a perception gap between your website and an AI system's understanding of your brand
• Why lower-funnel prompts may be more valuable to track
• Whether your next AI search investment should be software or a person who can actually turn the data into strategy

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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/

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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 journey
• What persistent search means for content freshness
• What Graphite found after analyzing nearly 500,000 AI shopping responses
• Why being cited by an AI system does not guarantee your brand will be recommended
• How prompt language can affect which retailers AI recommends
• Google Search Console’s new multimodal search reporting
• Why search intent increasingly exists without a traditional typed query
• What Perplexity’s contextual embedding research tells us about AI retrieval
• Why structuring content for AI shouldn’t mean removing useful context

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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/

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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 visibility
• What happens when AI is working with inaccurate or outdated company data
• Why inconsistent messaging across sales, marketing, and other departments can become an AI visibility problem
• Where humans need to remain in the loop
• Who should be responsible for reviewing AI-generated outputs
• Why AI governance requires subject matter expertise
• How automated content workflows can create brand and messaging problems
• Why AI search visibility is about more than tracking citations
• What it means to measure your brand's AI representation
• Why accurate positioning matters before a customer ever reaches your website
• How third-party signals can shape what AI systems understand about your company
• Why AI governance is becoming a cross-functional business problem

Tommy 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.

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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/

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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

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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/

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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 personalization
• What changed between API, anonymous, and personalized responses
• Why geography can affect the brands and sources AI systems surface
• What personalization means for local and global brands
• Why creating more content isn't automatically the answer when your brand isn't appearing
• What marketers should understand about the methodology behind AI visibility tools
• Why personalization doesn't make AI visibility measurement useless — it makes repeated measurement more important

Read 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

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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/

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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 journey
• Why ChatGPT ads point toward a much bigger shift in agent-mediated commerce
• How Google is bringing Business Agents and more AI shopping capabilities into the customer journey
• Why Google's new AI share-of-voice reporting for retailers is worth watching
• How Google's pay-per-value publisher program complicates the conversation around AI search measurement
• Why marketers need to think beyond AI visibility and start preparing for agent readiness

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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/

Send us Fan Mail

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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 journey
• Why GEO extends beyond traditional SEO and your website
• How PR and earned media can influence AI visibility
• Why authority signals differ from one industry to another
• The role of peer reviews, user-generated content, and third-party coverage
• What makes a brand story interesting enough for journalists to cover
• Why uniqueness matters for both PR and AI search
• How brands can build visibility that may be more resilient to model changes
• Where AI search could be heading over the next five years

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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/