One of the least-discussed realities of AEO is that “AI search” isn’t a monolith. ChatGPT works differently from Google’s AI Overviews. Perplexity retrieves information differently from Gemini. Each platform has its own retrieval architecture, its own weighting of sources, its own notion of what makes a citation credible.
If your AEO agency is treating all of these platforms the same way, they’re leaving real visibility on the table.
The Platform Landscape in 2026
Understanding the major AI search platforms — and their differences — is foundational to smart AEO targeting.
Google AI Overviews are perhaps the most commercially significant for most brands. They appear at the top of Google search results for millions of queries daily, pulling synthesized answers before the traditional “ten blue links.” Being featured in an AI Overview can drive significant awareness — and being absent when a competitor is featured is a meaningful disadvantage.
ChatGPT (including with browsing enabled) is used heavily for research, product discovery, and decision-support queries. The model draws on both its training data and real-time web retrieval. Appearing credibly in ChatGPT answers often requires both strong on-site content and off-site citation presence in sources the model trusts.
Perplexity is increasingly popular for research-oriented queries. It’s aggressive about source citation, which creates both more transparency and more opportunity for brands to appear prominently if they’re well-optimized.
Gemini / Google’s conversational AI is evolving rapidly and deeply integrated into Google’s broader search ecosystem. Optimization signals that matter for traditional Google search also tend to matter here, though the retrieval logic has its own nuances.
Microsoft Copilot sits in an interesting position — deeply integrated into the Microsoft ecosystem and frequently used in professional and enterprise research contexts.
Why Platform-Specific Strategy Matters
Here’s a concrete illustration. A B2B software company wants to appear in AI answers when enterprise buyers research their category. For ChatGPT, the most important signals might be: presence in high-authority third-party publications that the model has learned from, consistent factual information about the product across the web, and content that directly addresses the specific questions enterprise buyers ask. For Google AI Overviews, structured data markup, content freshness, and alignment with the specific query format Google is optimizing for become more significant.
An AEO agency for ChatGPT and Google AI Overviews that understands these platform-specific nuances will develop a more targeted strategy — not a one-size-fits-all approach.
What Platform-Specific Optimization Actually Looks Like
For Google AI Overviews: Google draws heavily from its own index. This means on-site optimization matters significantly — clear, well-structured content with appropriate schema markup, content that directly matches the format of AI Overview-worthy answers (concise, factually specific, clearly attributed), and strong traditional SEO signals (E-E-A-T, site authority, content freshness).
Google also draws on Featured Snippet optimization as a closely related signal. If your content was winning featured snippets before AI Overviews, it’s likely to perform well in AI Overviews too — with some additional optimization.
For ChatGPT and similar LLM interfaces: These systems rely more heavily on their training data and on real-time retrieval from high-authority sources. Here, off-site citation building is particularly important. Getting your brand and content cited in major publications, industry media, and authoritative databases matters more relative to on-site optimization. Content should be written in natural, authoritative language — not keyword-optimized in the traditional sense.
For Perplexity: Perplexity is particularly retrieval-heavy. It actively searches the web for answers to each query and cites sources prominently. Being indexed on credible, frequently-updated sources and having content that directly, clearly answers research-style questions is important here.
The Case for Integrated, Multi-Platform Thinking
While platform-specific tactics matter, the foundation of strong AI visibility is consistent across all of them: high-quality, accurate, authoritative content; well-defined entity presence; credible off-site citations; and factual consistency across your web footprint.
The brands that will dominate AI search across all platforms are the ones building that foundation seriously — and then layering platform-specific optimizations on top.
An AI answer engine optimization agency that thinks only about one platform (or that treats all platforms identically) is operating with a fundamentally limited view of the landscape. The right partner will help you understand your specific visibility gaps across the platforms that matter most for your audience — and build a sequenced program that addresses them in order of impact.
Practical Priority Setting
Not all platforms matter equally for all brands. A consumer brand selling kitchen appliances may find that Google AI Overviews drive dramatically more impact than ChatGPT visibility. A B2B data analytics vendor may find that Perplexity and ChatGPT are more important channels for their research-heavy buyers.
Start by understanding where your specific buyers are doing AI-assisted research. Conduct customer surveys. Include “where did you first hear about us / learn about this category” in sales conversations. Run your own queries across platforms and see which ones surface competitors most aggressively.
That intelligence should shape your platform prioritization — and should be the starting point of any serious platform-specific AEO strategy.