How Will AI Find It Works
We chose these 11 dimensions because they consistently appeared across the published GEO research — from Princeton's citation studies to BrightEdge's analysis of what LLMs actually reference. The scoring is built on a simple premise: AI search engines treat content the same way a careful researcher does. They look for specificity, authority, and structure. They skip generic filler the same way you do.
Detection Risk Signals
These dimensions measure patterns that make content look machine-generated. Lower scores are better — a low score means the content avoids these patterns.
Repetitive Patterns
Open any AI-generated article and count how many paragraphs start with “Furthermore,” “Additionally,” or “Moreover.” Repetitive phrases, parallel list structures, and formulaic transitions are the most visible markers of template-generated content. AI search engines increasingly deprioritize content with these patterns — not because repetition is always bad, but because uniform structural repetition correlates strongly with machine output.
Generic Phrasing
Generic phrasing is the single strongest indicator of machine-generated content. “Leverage,” “cutting-edge,” “streamline,” “game-changer” — these words add no information. They fill space. AI search engines recognize content saturated with corporate filler and deprioritize it in favor of writing that makes specific, bounded claims. The fix is almost always the same: replace the adjective with a number.
Passive Voice
Excessive passive voice (“was implemented,” “has been shown,” “can be achieved”) is a documented machine writing pattern. Active, direct voice produces more definitive statements. Research from Search Engine Land's 2026 ChatGPT citation analysis found that cited passages are nearly 2x more likely to use definitive language than hedged framing. “We reduced churn by 14%” gets cited. “Churn was reduced” does not.
Content Quality Signals
These dimensions measure writing quality that signals human authorship and expertise. Higher scores are better.
Sentence Variety
Human writing has rhythm. Short sentences land. Longer, more complex constructions develop an idea across clauses. Machine-generated content tends toward uniform mid-length sentences — 15 to 25 words, similar construction, paragraph after paragraph. High variation in sentence length is one of the core markers that both AI detectors and citation engines use to assess whether content was written by a person working through ideas or a model completing a prompt.
Lexical Diversity
Vocabulary range relative to text length. If the same key terms appear repeatedly without synonyms or varied phrasing, it indicates machine generation. A writer with genuine expertise naturally reaches for more precise terms — “correlation” instead of “connection,” “deprioritize” instead of “skip.” Diverse vocabulary reflects depth. Narrow vocabulary reflects a model cycling through its most probable next tokens.
Natural Flow
Here's the difference between human and machine transitions: a machine writes “Furthermore, it is important to consider...” A human writes “That's the obvious part. The less obvious part is...” This dimension measures how organically paragraphs and ideas connect — through contextual bridges, callbacks to earlier points, and implicit logical connections rather than mechanical connector words.
Authority & Citability Signals
These dimensions measure factors that directly increase the likelihood of AI search engines citing your content. Higher scores are better.
Personal Elements
First-person experience, named examples, and original voice. The Princeton GEO study found that original quotations boost AI visibility by 37%. AI search engines preferentially cite content with first-hand authority because it provides information not duplicated across thousands of other pages. Content without original voice is interchangeable — and interchangeable content gives an AI engine no reason to cite yours over anyone else's.
Concrete Data
Specific numbers, statistics, dates, and cited sources. Vague claims are uncitable — an AI search engine cannot reference “many studies show” or “experts agree.” A specific, attributed claim — “a 2025 BrightEdge analysis of 10,000 pages found a 0.334 correlation between brand authority and LLM citation” — gives the model something it can extract, attribute, and repeat. The Princeton GEO study found that adding statistics to content increased AI visibility by 22%.
Structural Clarity
Clear headings, definitive statements, and extractable answer blocks. 44% of ChatGPT citations come from the first 30% of a page. If your key point is buried deep in the content, it will not be cited.
Emotional Intelligence
Content that shows judgment, weighs options, or acknowledges complexity demonstrates human expertise. A blog post that says “this approach works perfectly for every team” is less authoritative than one that says “this approach worked for our 12-person team but broke down when we tried it with 50 — here's why.” AI search engines retrieving information for users value balanced perspectives because they produce more trustworthy answers.
Cultural Anchoring
Real-world references, temporal markers, and current context. Machine-generated content tends to exist in a temporal vacuum — it could have been written at any point. Anchored content — referencing specific market conditions, recent research, or current events — demonstrates freshness and relevance. Perplexity, ChatGPT, and Gemini all weight recency when selecting sources to cite. Content without temporal markers gets deprioritized in favor of content that demonstrates awareness of the current moment.
Research Foundation
Every scoring dimension traces back to published GEO research. These are the primary sources informing the 11-dimension analysis.
Princeton GEO Study (2024)
Citations and original quotations boost AI visibility. Statistics increase visibility by 22%. Original quotations boost visibility by 37%.
BrightEdge AI Citation Analysis (2025)
Brand search volume is the strongest predictor of LLM citations (0.334 correlation), outweighing backlinks. Brand recognition predicts LLM citations.
Semrush AI Overviews Study (2025)
AI Overviews appear in 88% of informational queries. Content structure and freshness are primary citation drivers.
Search Engine Land ChatGPT Citation Analysis (2026)
44% of ChatGPT citations come from the first 30% of a page. Cited passages are nearly 2x more likely to use definitive language.
HubSpot AI Content Optimization Report (2026)
Direct, fact-first sentences are cited more frequently. Hedged language reduces citation probability.
Writesonic AI Crawler Study (2026)
LLMs process plain body text only — metadata, CSS, JavaScript, and most HTML structure is stripped before processing.
Honest Scoring
Will AI Find It is a diagnostic tool, not a prediction engine. The 11 dimensions are informed by published GEO research — they measure content quality patterns correlated with citation likelihood.
AI search engine behavior is not standardized across providers. Perplexity, ChatGPT, Gemini, and Google AI Overviews each make citation decisions differently. Will AI Find It scores the writing quality patterns that research suggests these systems weight — it does not guarantee citation by any specific engine.
Last updated: April 2026