The Two Types of AI Search Systems
Not all AI systems work the same way. Understanding the difference is critical because it determines how quickly GEO results appear and what strategies work for each.
Real-Time Retrieval Systems
These pull from the live web every time someone asks a question. They break the question into sub-queries, search the web, pull the most authoritative sources, and synthesize an answer in real time.
GEO results can appear within days to weeks once content is indexed.
Training-Dependent Systems
These answer from what they were trained on. Content that exists widely across the web before a training cutoff gets incorporated into the model's knowledge permanently.
Results compound over 6–12 months as new training runs incorporate your web presence.
How Each Platform Works Under the Hood
ChatGPT with Search
When web search is enabled, ChatGPT uses Google's search index via SerpAPI. It generates multiple sub-queries from the user's question, searches each one, retrieves the top results, reads the content of those pages, and synthesizes an answer that names specific businesses. The quality and relevance of your web content directly determines whether you get cited.
Perplexity
Perplexity runs its own web crawler called PerplexityBot. When someone asks a question, it searches its own index plus live web results, evaluates source authority, and generates an answer with inline citations. Perplexity is particularly transparent about its sources — it shows which websites it pulled from, making it easy to verify whether your content is being found.
Google AI Overviews
Google's AI Overviews pull directly from Google's organic search index. When Google determines a query is best answered with an AI-generated summary rather than a list of links, it synthesizes an answer from the top-ranking pages. Strong Google SEO directly feeds Google AI Overview visibility — making SEO and GEO complementary for Google specifically.
Gemini
Google's Gemini uses a combination of Google Search data, Google Maps data, and its own training knowledge. For local service queries, it often references Google Business Profile information, reviews, and website content. Gemini's integration with Google's ecosystem means that businesses with strong Google presence have a natural advantage.
Claude (Anthropic)
Claude is a training-dependent system — it answers from knowledge absorbed during training, not from live web search. Claude is being integrated directly into Apple's Safari browser, which will give it enormous reach. For businesses to be recommended by Claude, they need a broad, consistent web presence that gets incorporated during training runs. This takes longer but creates durable authority.
The 6 Signals AI Uses to Decide Who Gets Recommended
Across all platforms, AI systems evaluate a consistent set of signals when deciding which businesses to name. The weight of each signal varies by platform, but the core set is the same.
Entity Recognition
Can the AI verify that your business exists as a real, specific entity? This requires your business name, location, and services to appear consistently across multiple trusted sources — your website, Google Business Profile, directory listings, social media profiles, and third-party mentions. Inconsistencies weaken entity recognition.
Topical Authority
Is your business consistently and deeply associated with the service being asked about? A roofing company that has extensive, detailed content about roofing across its website, blog, directory profiles, and citations builds stronger topical authority than one with a single-page website that mentions roofing once.
Citation History
Has your business been mentioned by other sources that the AI already trusts? Mentions in industry publications, local press, business directories (especially Clutch, G2, and Expertise.com), and authoritative websites all create citation signals. The more trusted the citing source, the stronger the signal.
Recency
Has your business published or been mentioned in content recently? AI systems favor current information. A website updated this month carries more recommendation weight than one last updated in 2023. Regular publishing — blog posts, updated service pages, new reviews — maintains the recency signal.
Cross-Platform Consistency
Does your business present identical information everywhere? When your Google Business Profile, website, LinkedIn, Facebook, and directory listings all show the same name, address, phone number, and service descriptions, the AI has high confidence in its data. Conflicting information across platforms reduces confidence and reduces recommendation likelihood.
Reviews and Social Proof
Do real customers validate your business? Review count, review recency (velocity), average rating, and the specificity of review content all contribute. A business with 200 recent, detailed reviews describing specific services generates far stronger recommendation signals than one with generic five-star reviews from years ago.
Query Fan-Out: Why AI Searches Differently Than Humans
When a human searches Google, they type one query and look at the results. When an AI system processes a question, it does something fundamentally different: it breaks the question into multiple sub-queries and searches all of them simultaneously. This is called query fan-out.
Here's a real example. When someone asks ChatGPT “who is the best electrician in Austin?” the AI might generate and search these sub-queries simultaneously:
The AI then reads the top results for each sub-query, looks for businesses that appear authoritatively across multiple sub-queries, and synthesizes a recommendation based on the aggregate evidence.
This is why a single optimized homepage is not enough for GEO. Your business needs to be the authoritative answer for every sub-query the AI generates — not just the original question. This is exactly what Elevair's hidden pages strategy is designed for: each page targets a specific cluster of sub-queries that AI systems generate for your industry and market.
What This Means for Local Business Owners
The mechanics of AI recommendation are complex, but the takeaway for local business owners is simple: AI systems recommend businesses they can verify, trust, and cite. If your business has a strong, consistent, well-documented online presence with fresh content and real reviews, you are far more likely to be recommended than a competitor with a thin or outdated web presence.
The window of opportunity is open right now. In most local markets, the number of businesses with a deliberate AI visibility strategy is close to zero. The first businesses to invest in GEO will capture recommendation positions that become progressively harder for competitors to displace as authority compounds.
Walker Deyo, co-founder of Elevair, recommends a simple test: “Open ChatGPT right now and ask who the best [your trade] in [your city] is. If your business isn't in the answer, your competitors are already ahead of you — even if they don't know it yet. The question is how long you wait before you fix that.”