8 Ways AEO/GEO/AIVO Is Different From Traditional SEO

A common belief in digital marketing is that a strong SEO strategy is all that’s needed to ensure visibility in AI chat engines. While a solid foundation in SEO is certainly the price of admission—after all, LLMs use search engines like Google and Bing for their information—it’s a dangerous oversimplification.

AI search is not human search. Generative engines behave in unique ways, and understanding these differences provides a significant competitive advantage. Sticking solely to traditional SEO best practices means leaving opportunity on the table and failing to prepare for the future of search.

Here are eight critical distinctions between traditional SEO and Answer Engine Optimization (AEO) that demand a shift in strategy.

1. AIs Use Longer-Tail Keywords in Searches

Human search queries are often short, averaging 3-4 keywords. In contrast, when making web searches, AI models search 5-10 highly specific, descriptive queries that can be 8-12 keywords long as part of a fan-out strategy.

The takeaway: Instead of just focusing on smaller 3-4 keyword ssearches, content must be optimized for these detailed long-tail 8-12 keywords and questions to be surfaced by AI.

2. Unlinked Brand Mentions Carry New Weight

For years, the do-follow backlink has been the primary goal of off-page SEO. In the AEO landscape, unlinked brand mentions on reputable sites, forums, and communities like Reddit or Quora are powerful signals. Whereas brand mentions were not useful for standard search, LLMs ingests mentions to understand a brand’s authority and place in the market.

The takeaway: Mentions - even without links - matter. A robust digital PR and community engagement strategy is now a crucial component of discoverability.

3. Bottom-Funnel Content Is Credited More Often

Broad, top-of-funnel (ToFu) content used to be a great technique to generate site-clicks and brand awareness. For AI Chats, this ToFu content is now read and summarized by the LLMs without any attribution. Bottom-of-funnel (BoFu) content, which is evaluative in nature (e.g., “Top 10” lists, “Brand vs. Brand” comparisons), is far more likely to result in brand mentions and links.

The takeaway: Prioritize creating unique, high-value MoFu and BoFu content, as AI is more inclined to mention your brand at this stage than for simple how to and top of funnel content.

4. Bing Optimization Is No Longer Optional

While Google dominates human search, recent studies have shown OpenAI now uses a combination of Bing and Google search as part of its realtime web-search results. OpenAI’s use of Bing will likely stay or even increase given Google’s Gemini is a direct competitor to ChatGpt. Many companies still neglect Bing, creating a significant opportunity for those who invest in the platform.

The takeaway: Actively optimize for Bing results using the Bing Site Webmaster and techniques that no longer work in Googl like exact-match keywords and cross-linking.

5. Being in the Top 10 Matters, Not Just #1

Traditional SEO follows a power law where the #1 ranking captures the lion’s share of clicks. This model is flattening. AI engines typically ingest and synthesize information from the entire first page of results (often the top 8-10 links).

The takeaway: The strategic goal shifts from winner take all with the #1 spot to consistently appearing in the top 10 “consideration set” for a cluster of relevant topics.

6. Content Must Be Accessible Without JavaScript

Google’s crawlers are sophisticated at rendering JavaScript-dependent content, but many AI crawlers are not. They often only parse the raw HTML, completely missing any content that loads via client-side JS.

The takeaway: Ensure that all critical information, such as product details or testimonials, is server-side rendered or embedded directly in the HTML to guarantee it’s visible to AI.

7. Popular Brand Names Are Included in Search Keywords

AIs learn from association. When querying search engines, generative models often include well-known brand names to add context. For example, a search in GPT-5 for “best coffee in San Francisco” often resulted in web searches for “best coffee San Francisco Blue Bottle SiteGlass Philz.” - including the coffee shops Philz, Blue Bottle and SightGlass IN the search query!

The takeaway: Including relevant competitors, partners, and industry leaders in your content helps AI correctly categorize your brand and understand its position in the market.

8. AI Chat Personalizes Based on Your History

Features like ChatGPT’s “Memory” function are making AI-driven search deeply personal. An AI assistant will leverage a user’s history and preferences to conduct hyper-specific searches on their behalf.

The takeaway: Generic, one-size-fits-all content will lose effectiveness. Creating detailed content that serves specific customer segments and niche use cases is essential for success. RivalSee is a great tool for this.

The Takeaway

While standard SEO provides a necessary foundation, it is no longer sufficient. A new, layered approach of AEO/GEO/AIVO is required to compete and win in the age of AI. Understanding how these models discover, process, and credit information is the key to building a resilient, future-proof digital strategy.

And no, LLMs.txt do not matter yet.