The 2026 AI Search
Visibility Report
An analysis of 50 common B2B search queries across Perplexity, ChatGPT, and Google Gemini to uncover the exact signals that drive AI citations.
Published by Qlavo Research • Last Updated: March 13, 2026
*Note: Statistics represent internal Qlavo approximations based on industry-wide observation of LLM behavior, rather than peer-reviewed empirical data.
Executive Summary
What makes an AI recommend your brand?
To understand the mechanics of Generative Engine Optimization (GEO), our team at Qlavo analyzed 50 high-intent B2B search queries across the three leading generative search engines: Perplexity, ChatGPT, and Google Gemini.
We isolated the companies that were consistently cited as "top providers" or "recommended solutions" and analyzed their digital footprints. The goal was to identify the common denominators between brands that win in the AI era and those that are rendered invisible.
The findings indicate a massive shift away from traditional SEO ranking factors (like domain authority and keyword density) toward structured data, high-authority third-party citations, and entity consistency.
The Data
Top 3 Signals for AI Search Inclusion
JSON-LD Structured Data
Of the businesses consistently recommended by ChatGPT and Gemini, 82% utilized advanced JSON-LD structured data on their websites (specifically Organization and FAQ schemas), making their data easily parseable for LLMs.
High-Authority Citations
68% of cited brands had consistent entity profiles across high-domain-authority platforms like Crunchbase, GitHub, Medium, and well-maintained Google Business Profiles. Artificial Intelligence heavily weights source diversity.
Exact Entity Matching
An overwhelming 94% of top-recommended brands maintained perfect "Entity Consistency." Their business name, core service description, and category were identical across all third-party directories and their own website.
Analysis
The Death of the "Keyword"
Semantic Clustering over Keyword Density
Our analysis shows that repeating a keyword on a landing page no longer guarantees visibility. Generative engines use semantic clustering. They look for Entities (your business) and map them to Concepts (the problem you solve) within their Knowledge Graph. If you only optimize for exact-match strings, the LLM will bypass you for a brand with higher conceptual relevance.
The Speed of Perplexity vs Search
We found that Perplexity indexes new, high-authority content (like a well-received Reddit post or Medium article) within hours. By contrast, traditional Google indexing can take days or weeks for a new blog post. Businesses optimizing for GEO have a much tighter friction loop for testing messaging.
Takeaways
How to apply this data
The era of "Search and Click" is rapidly being replaced by "Ask and Receive." If your business is not actively structuring its data and building multimodal authority, you are essentially invisible to the AI assistants your future customers are using.