Why Brands Are Losing Traffic to Google AI Overviews And How to Win Back Visibility
Jun 23, 2025 • 4 Minute Read • Tod Szewczyk, Managing Director, Marketing Services Practice
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How to Structure Content for AI Search Discovery
Jul 14, 2025 • 6 Minute Read • Tod Szewczyk, Managing Director, Marketing Services Practice
Search used to be about options—offering a list of blue links to sift through. Now, it’s about instant, trusted answers.
For brands, if you don't structure your content for AI search tools to find, parse, and trust, you risk being invisible.
This shift isn’t just about technology getting smarter—people changed first. We should have seen this coming.
We live in a “convenience economy” where speed, ease, and frictionless experiences are non-negotiable. A 2024 Morgan Stanley survey found that 77% of U.S. consumers say inconvenience is a deal breaker. Whether shopping or researching, the expectation is to make it easy for the consumer.
Think about it: mobile tech put the world in our pockets. Computer vision lets us shop just by walking out the door. Now, AI-powered answer engines are changing search. They simplify things and provide what people want, when they want it.
The internet can seem like a digital jungle filled with a million blue links. It can be messy and overwhelming. Tech giants, like Google, kept innovating, but the experience often fell short of expectations.
Today, AI search is the natural next step: from digging through links to simply asking for and receiving the answer instantly.
In this new world, structuring your content for AI is essential to remain visible and competitive. This guide will show you how to prepare AI-ready content, become visible in trusted ecosystems, and measure success in new ways.
Zero-Click Search & Why Immediate Answers Are Replacing Clicks
Like water flowing down a river, people want the fastest path to answers, and AI has quickly become the shortcut of choice.
A widely cited Spark Toro study shows the relentless pace of change. In 2024, over 60% of searches ended without a click. Consumers are getting the information they need and moving on. And increasingly, they're turning to AI to get there.
Attest's second annual report on AI shows that 49% of U.S. consumers use AI tools to research a purchase.
The shift is even more pronounced in B2B. However, B2B buyers are still clicking. According to TrustRadius, 72% of B2B buyers encounter AI-generated summaries, like Google AI Overviews, during research, and 90% still click through to verify sources.
This behavior reveals a fundamental truth in B2B:
Buyers want immediate answers, but they still value verification and deeper exploration. It's no longer just about where they find the answer; it's also about how fast they get that answer and whether they can trust it once it's there.
This emerging practice is framed in two complementary ways: Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO). While related, these concepts focus on slightly different aspects of how AI tools surface brand content.
What is Answer Engine Optimization (AEO)?
Answer Engine Optimization (AEO): The practice of structuring digital content so it can be easily discovered and directly surfaced as an authoritative answer in AI-driven platforms, such as Google’s SGE, Bing Copilot, and other conversational search experiences. Answer engines are platforms designed to return a direct answer, rather than a list of links.
What is Generative Engine Optimization (GEO)?
Generative Engine Optimization (GEO): A broader approach to optimizing content for generative AI tools and large language models (LLMs). GEO ensures that brand content is accessible, trustworthy, and aligned with how AI systems retrieve and synthesize information into responses for end users.
How AI Tools Are Redefining the Buyer's Journey
Generative AI systems like Perplexity, Gemini, ChatGPT, Microsoft Bing's Copilot and other LLMs or AI search experiences are changing how B2B buyers research, compare, and shortlist vendors. These systems generate answers and pull from trusted sources across the web.
This transformation is accelerating rapidly. At Google I/O 2025, "Search Live" revealed a glimpse into what's next: point your phone at a product and get instant, AI-generated context. These contextual insights mean no scrolling or scanning, just answers.
What matters today isn't ranking; it's being cited. If your content isn't structured for machine interpretation, you're not even part of the consideration set.
The buyer journey now starts with questions AI tools are trained to answer.
Are you prepared to rethink how you approach content strategy and search optimization for AI interpreters?
Step 1: Make Your Content AI-Ready with Structured Data
AI scans, parses, and pulls from what it can identify, so you'll need to structure your data and content for AI machines to understand.
Here's why it matters and what to do:
LLMs like ChatGPT and Gemini rely on clear signals to know what content to access and trust. The proposed llms.txt standard will let you signal which parts of your site—like white papers or product sheets—are AI-accessible. This means you can guide AI directly to your highest-value content.
To ensure machines interpret your content correctly:
- Use structured formats like FAQs, glossaries, and explainers to address niche, expert-level queries.
- Implement semantic schema (e.g., FAQPage, TechArticle, Product, HowTo) to make content machine-readable.
- Boost your E-E-A-T signal through named, credentialed authors, peer reviews, and proprietary data.
AI favors trustworthy sources and cites reputable B2B sources like Crunchbase, LinkedIn, Wikipedia, and G2, which are platforms that are part of trusted knowledge graphs.
Step 2: Increase AI Visibility by Leveraging Trusted Knowledge Ecosystems
Knowledge ecosystems are the trusted hubs AI relies on to gather and verify information about your brand and products. If you’re not in these ecosystems, you won’t show up.
AI search leans heavily on high-authority repositories and cross-format signals. It prioritizes content from authoritative, well-structured, and frequently updated sources because these provide the trustworthy signals that shape AI-generated answers.
Here's how to show up effectively:
- Publish on authoritative content outlets. Get your content featured on TechCrunch, VentureBeat, and similar websites in your space that are trusted by AI.
- Maintain enriched profiles. Keep LinkedIn, Crunchbase, G2, and GitHub profiles complete and current if relevant.
- Leverage video content. Host demos and explainers with timestamps, transcripts, and VideoObject schema to boost AI understanding.
- Diversify content formats. Use podcasts, case studies, white papers, and interactive tools to expand your presence.
- Optimize technical docs. Make manuals, changelogs, and product documents semantically clear and rich with internal links.
AI tools scan all these resources to understand your solutions and capabilities, because AI discovery depends on authority and accessibility. Show up where it's looking and make it easy for it to understand what you do.
Step 3: Measure AI Visibility Beyond Traditional Metrics
Clicks don't tell the full story. Just because someone didn't click doesn't mean they didn't choose you. Traditional metrics miss the growing influence of AI-mediated discovery.
Shift your focus:
- Track AI brand mentions and citations across Perplexity, Gemini, and ChatGPT.
- Run simulated buyer queries to see where and how your brand appears in AI responses.
Go beyond clicks:
- Measure the pipeline impact from AI-informed leads, even when visits come from other channels.
- Monitor visual brand recognition through camera-driven AI tools, especially for hardware or physical assets.
Key metrics to watch:
- Citation frequency in AI-generated summaries
- Mentions in conversational query results
- Conversion quality from AI-triggered pathways
AI is changing how buyers discover and choose brands. Your measurement strategy must evolve with it.
Balancing Machine Indexing and Human Engagement in AI-Driven SEO
Traditional SEO is set up for crawlers and keyword rankings. Today's search environment demands content that's indexable, understandable by AI, and valuable enough to be cited in real-time responses.
These three steps above are just the beginning. Winning in AI-powered search requires ongoing , faster iteration, and strategic alignment with optimizing for summaries, citations, and trust.
We’re entering a visual-first, answer-centric era of discovery in which search happens across formats, devices, and tools—often before the user even lands on your site.
So your content needs to:
- Answer the questions that answer engines and generative engines are trained to understand
- Provide the depth and clarity humans still crave
- Be structured, cited, and available across all AI knowledge ecosystems
As stated, we should have seen the shift coming. And if you're wondering what's coming next, my prediction is an even more visual, conversational, and intelligent search experience.
Ready or not, AI search is here. It's already shaping audience behavior. But you don't have to figure this out alone. From strategy to schema, visibility to verification, we can help.