The invisible market: is AI recommending your products or your competitors?
Chris Labbe
Head of AI and Machine Learning, G10X
AI is rapidly reshaping how people discover, compare, and choose brands. In B2B markets, 89% of buyers now use AI tools during purchasing decisions. In B2C, the impact is just as visible, with Bain reporting a 15-25% decline in traditional SEO traffic as consumers increasingly rely on AI-generated answers instead of search results.
As we move away from typing keywords into search engines and instead ask AI for recommendations, the way brands are found and compared is fundamentally changing. Answer engines such as ChatGPT, Perplexity, and Gemini now summarize options and shape what buyers think in a single response. Yet most brands have little visibility into how they appear in AI-generated answers or how they are positioned alongside competitors. And you can’t optimize what you can’t see. Here is what executives need to understand about Agentic Engine Optimization before market share begins to shift.
The search paradigm has fundamentally shifted
According to Forrester, 89% of B2B buyers now use AI when making purchase decisions. SEMrush forecasts that AI search will surpass traditional search within three years. Bain reports that B2C SEO traffic has already declined by 15-25% across sectors. This is not a future trend. It’s happening now.
The shift is fundamental. Buyers are no longer scrolling through pages of links. They are asking conversational questions and receiving synthesized answers instantly.
When an IT decision-maker asks ChatGPT, “What’s the best ITSM platform for enterprise deployment?” the tool delivers immediate recommendations pulled from multiple sources, often combining product descriptions, third-party reviews, and comparative opinions into a single answer. Your carefully optimized landing page may not appear at all in the AI-generated response.
The same pattern plays out in retail. A consumer searching for “best sustainable clothing for the office” receives a summarized list of recommended brands and products. If your brand is not included while competitors are, you are effectively invisible. In many cases, there is no “page one” to compete for.
This invisible market is large and expanding. Yet most enterprises are still relying on traditional analytics that track keyword rankings and website traffic, while offering no visibility into AI recommendations, which is increasingly where purchase decisions are shaped.
Why your SEO playbook won’t save you
For two decades, enterprise marketing teams optimized for Google’s ten blue links. Success meant tracking keyword rankings, building backlinks, and measuring performance by page-one visibility. That was the foundation of Search Engine Optimization (SEO), where the goal was simple: move higher on the list. Today, that playbook is quickly becoming obsolete.
In Agentic Engine Optimization (AEO), you must be present in answers to natural language questions across dozens of variations. Success is not a ranking. It is share of voice and sentiment: how often your brand is mentioned relative to competitors, and whether it is presented as the preferred option.
SEO treats backlinks as the primary authority signal. AEO depends on citations, context, and tone. A single negative mention in a widely referenced source can outweigh dozens of neutral backlinks. When Reddit users debate your product category, those discussions influence what ChatGPT recommends. When industry publications update comparison articles, LLMs can incorporate that perspective within days.
Content strategy must also change. Static, keyword-focused pages underperform in conversational AI. Research from Webflow shows that 95% of ChatGPT citations reference pages updated within the last 10 months, signaling a far stronger freshness bias than traditional search. Answer engines favor structured content, clear FAQs, and natural language that directly responds to user questions.
Measurement is another gap. Tools such as SEMrush and Ahrefs track Google rankings effectively, but they do not show whether ChatGPT or Gemini recommend your products, or whether Perplexity includes you in competitive comparisons.
The risk is straightforward. While you continue optimizing for traditional search, competitors investing in AEO are capturing share of voice where buying decisions are increasingly shaped. By the time declining traffic appears in quarterly reports, the shift in market share may already be underway.
The visibility gap: you can’t optimize what you can’t see
The biggest barrier to AEO is not strategy. It is visibility. Most enterprises have no structured way to monitor how AI engines represent their brand, products, or competitive position.
Consider these real examples we have seen firsthand.
A wealth management firm manually tests AI responses and discovers that when prospects ask about “best retirement planning services for high-net-worth individuals,” competitors appear in 78% of answers while the firm appears in just 11%. Leadership had no idea they were being excluded from buyer conversations until someone casually tested ChatGPT in a meeting.
A consumer searching for “best wireless over-the-ear headphones for a noisy city like NYC” receives a clear summary of pros and cons, along with recommended brands. If your products are not listed alongside Beats or Bose, you are not part of the consideration set. There is no results page to compete on.
These are not edge cases. They point to a systemic gap. Traditional analytics report website visits and keyword rankings, but they reveal nothing about prospects who formed opinions and made decisions based on AI answers without ever visiting your site. You also lack competitive benchmarking. You do not know how often competitors appear in responses to the questions your buyers are asking, or whether the citations about your brand are accurate and current across platforms.
The opportunity is significant. Organizations that gain visibility into their AEO performance can identify gaps, correct misinformation, and strengthen their presence before competitors recognize what has changed.
Building your AEO foundation: 4 strategic pillars
AEO requires a coordinated approach across four core pillars. Unlike traditional SEO, which centers on keywords and backlinks, AEO demands structured content, authoritative presence in AI-weighted sources, strong technical foundations, and continuous measurement.
Content built for real buyer questions
AEO begins with content designed to answer the real questions buyers ask throughout their journey, not just target keywords. This means mapping questions from sales calls, support conversations, and industry forums, then creating structured, comprehensive responses.
Content must be easy for AI systems to interpret. Schema markup clarifies meaning and relationships. FAQ formats create clear question-and-answer pairs. Tables, bullet points, and descriptive subheadings help AI extract relevant information efficiently. Natural conversational language is just as important as keywords.
Freshness now carries greater weight than in traditional SEO. Research shows that 95% of LLM citations reference content updated within the last 10 months. High-priority pages need a defined refresh cadence, with current statistics, accurate product information, and up-to-date examples.
Technical foundations for AI visibility
Technical infrastructure determines whether AI engines can find, interpret, and trust your content. Structured data through schema markup helps LLMs understand page context and meaning. Clean semantic HTML ensures accurate parsing. Page speed and uptime matter because some LLM platforms create their own browsing sessions to verify information.
If AI systems cannot reliably crawl and interpret your site, your content will not surface in their answers.
Authority in sources AI actually uses
Backlink strategies must evolve into authority building across the sources LLMs actively crawl and reference. This includes trusted third-party publications, relevant Reddit discussions where buyers seek advice, accurate Wikipedia entries, and a well-maintained Google Knowledge Panel.
Authority now includes sentiment and accuracy. Positive, detailed mentions carry more weight than neutral directory listings. A credible comparison article in a respected publication can influence AI recommendations more than dozens of generic backlinks. Digital PR must prioritize sources that LLMs reference when generating answers, not just high domain authority sites.
Measurement and continuous optimization
The final pillar is systematic measurement. Traditional SEO tools such as SEMrush and Ahrefs track Google rankings, but they do not measure performance inside AI systems. AEO requires tools and processes that query multiple platforms, track share of voice versus competitors, and monitor the sentiment and accuracy of AI-generated responses.
AI recommendations can shift quickly as new information is indexed or models are retrained. Continuous monitoring across systems such as ChatGPT, Gemini, Perplexity, and Microsoft Copilot is essential to identify gaps and correct inaccuracies before they affect revenue.
This is where the principle becomes concrete. You can’t optimize what you can’t see. Without structured, repeatable measurement across dozens or hundreds of relevant buyer questions, improving your AEO presence becomes guesswork rather than strategy.
Act now or risk invisible decline
Market share is already shifting, quietly. AI is influencing customer decisions today. The question is whether you will shape those recommendations or let algorithms define your brand based on outdated or competitor-led information. Companies that gain visibility into their AEO performance and act on it will capture share. Those who wait may only notice the impact when revenue starts to slide.
Early movers are not guessing. They are building content designed to win share of voice in AI-generated answers. They monitor how their brand appears across LLMs and correct inaccuracies quickly. They focus on authority in the sources AI engines actually reference. Most importantly, they can see the environment where buyers are forming decisions.
The winners will not simply be those with the largest SEO budgets. They will be the ones who recognize that buyer behavior has changed and that traditional metrics no longer tell the full story. Competitive advantage now depends on how AI engines represent your brand, products, and value.
Is your brand recommended in AI-generated answers?
If you do not know how your brand appears across major AI platforms, you are operating with blind spots.
G10X helps enterprises measure, benchmark, and strengthen their presence across AI platforms. If you are ready to see how your brand performs where modern buying decisions are shaped, get in touch to start the conversation.
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