You've spent months refining your SEO strategy for the AI era. You’re building topical authority and focusing on user intent. But when you test your key topics, you notice something unsettling: ChatGPT recommends one set of brands, Google's AI Overviews (AIO) another, and Google's AI Mode seems to have its own unique opinion.
If this sounds familiar, you're not alone. New research from BrightEdge confirms this isn't just a feeling; it's a statistical reality. AI search platforms disagree on which brands to recommend nearly 62% of the time.
This isn't a flaw in the system; it's a feature. Each AI platform acts like a different kind of researcher with its own unique preferences and data sources. Understanding these "personalities" is the first step to building a resilient strategy that wins visibility across the entire AI ecosystem, not just on one platform.
A Tale of Three AIs: The Researcher, the Historian, and the Connoisseur
The BrightEdge study analyzed tens of thousands of queries across ChatGPT, Google AIO, and Google AI Mode and found that each platform has a distinct character when it comes to citing brands.
AI Platform | The Archetype | Key Characteristics |
|---|---|---|
Google AI Overviews (AIO) | The Networker | Cites the most brands (averaging over 6 per query). It values breadth and pulls from a wide range of live search results to provide comprehensive answers. |
ChatGPT | The Historian | Cites fewer, highly trusted brands. It often relies on its vast training data, rewarding brands with a strong, historically established presence on a topic. |
Google AI Mode | The Connoisseur | Cites the fewest brands. It is highly selective, favoring sources with heavy third-party validation and deep credibility. |
This divergence explains why your brand might be a star on AIO but invisible on ChatGPT. AIO is impressed by your wide-ranging content that ranks across many related queries, while ChatGPT is looking for the deep-seated reputation baked into its training data.
Why Do They Disagree? It's Not "Authority," It's Data and Math
While it’s tempting to think of these differences in terms of a simple "authority" score, the reality is more technical. The disagreement stems from how each AI is trained and what data it prioritizes. For a model like ChatGPT generating responses from its training data, what looks like "authority" to an SEO is more likely a combination of three factors:
- Frequency: How often is your brand mentioned in the vast library of books, articles, and websites the AI was trained on? The more you appear, the more "top of mind" you are for the AI.
- Prominence: When your brand is mentioned, is it the main subject of an article or a passing reference in a footnote? Higher prominence gives you more weight.
- Contextual Strength: How tightly is your brand associated with key topics? If your brand is consistently mentioned alongside "enterprise cybersecurity," the AI builds a strong, almost inseparable connection between those concepts.
In contrast, Google's AIO and AI Mode are grounded in live search results, meaning your traditional SEO efforts have a more direct and immediate impact on the sources they can pull from.
Finding Common Ground: The Unifying Power of User Intent
Despite their differences, the AIs do agree on one thing: commercial intent matters. The research found that queries containing words like "best," "buy," "deals," or "where" generated brand mentions 65% of the time across all platforms.
This is a critical insight. It proves that even in the complex world of AI, the foundational principles of search marketing hold true. When a user signals they are ready to make a decision, all forms of AI are incentivized to provide concrete, brand-specific answers. As your keyword research from the "Why Keyword Research is Still Your Most Essential Marketing Tool" guide shows, understanding and targeting this intent remains a cornerstone of any successful strategy.
The Solution: The "Citation Network Effect"
So, if you can't optimize for each AI's unique personality individually, what's the solution? The answer lies in creating a "citation network effect." This is the idea that earning a mention on one platform creates the validation and source material needed to be cited on another. This "citation network effect" is the ultimate outcome of a well-executed, integrated strategy that combines the creation of deep, authoritative content (GAIO) with broad, multi-platform authority building (SEvO).
Imagine your company publishes the definitive guide on 'sustainable packaging for e-commerce.' Because it's a true 'Answer Asset,' it starts ranking for dozens of queries, leading Google AIO to cite it. Impressed by your original data, a major industry publication then references your guide. This high-authority mention provides the external validation AI Mode craves, and over time, both your original post and the third-party mention become baked into ChatGPT's training data, solidifying your brand as the historical authority on the topic.
Visualizing the Citation Network Effect:
Your goal isn't to create separate strategies for each platform. It's to create a single, powerful strategy where your high-quality content and brand reputation become so pervasive that all AIs, regardless of their starting point, are led back to you.
Conclusion: Your SEO Foundation is the Keystone
Ultimately, this new research doesn't reveal a need to abandon traditional SEO; it proves the need to double down on it. Your existing SEO work is the keystone upon which all AI visibility is built.
- For Google AIO and AI Mode: Strong, topic-focused SEO ensures your content is discoverable in the live search results they use for grounding.
- For ChatGPT: A powerful brand and content strategy is what populates the training data of tomorrow, building the long-term "authority" it relies on.
The 62% disagreement gap isn't a problem to be solved; it's an opportunity to be seized. It creates more paths to visibility, not fewer. The brands that will win this new era are not those who try to game one specific AI, but those who build a brand and a content ecosystem so authoritative that every AI is forced to agree on their relevance.
