Paste any text below and analyze it for common AI writing patterns. This detector uses six statistical signals — sentence uniformity, vocabulary diversity, burstiness, AI phrase density, hedging frequency, and transition word overuse — to estimate the probability that text was generated by AI. All analysis runs entirely in your browser.
Pro tip: AI-generated text tends to have remarkably uniform sentence lengths (15–25 words per sentence) and rarely uses very short (under 5 words) or very long (over 40 words) sentences. Human writing is “burstier” — mixing punchy fragments with complex, winding thoughts.
How AI Content Detection Works
AI content detection relies on statistical analysis of writing patterns rather than on any single telltale sign. Large language models generate text by predicting the most probable next token, which creates measurable regularities in sentence structure, word choice, and rhythm. This tool examines six independent signals and combines them into a weighted probability score. Sentence uniformity measures whether sentence lengths cluster in a narrow range, which is a hallmark of AI output. Vocabulary diversity checks the ratio of unique words to total words, since AI tends to recycle the same pool of terms. Burstiness captures variation in sentence complexity: human writers naturally alternate between short punchy statements and longer elaborate thoughts, while AI maintains a steady mid-range cadence. AI phrase density counts specific phrases that appear far more often in AI output than in human writing. Hedging frequency measures how often the text uses cautious qualifiers, which AI overuses to sound balanced. Transition word density flags the overuse of connectors that AI inserts to maintain the appearance of logical flow.
Each signal produces an individual score between zero and one hundred, where higher values indicate a stronger AI pattern. The composite score is a weighted average: sentence uniformity contributes 25 percent, vocabulary diversity 20 percent, AI phrase density 20 percent, burstiness 15 percent, hedging 10 percent, and transition density 10 percent. The final percentage represents the estimated probability that the text was generated by AI rather than written by a human.
Common AI Writing Patterns That Give It Away
AI writing exhibits several recurring patterns that experienced readers can spot and that statistical tools can measure. The most reliable indicator is sentence length uniformity. Human writers naturally produce sentences ranging from three words to forty or more, while AI-generated text clusters tightly between fifteen and twenty-five words per sentence with remarkably low variation. This creates a monotonous rhythm that feels smooth but lifeless.
Another strong signal is the overuse of certain transitional and hedging phrases. AI models are trained on text where connectors are common, so they insert words like "Moreover," "Furthermore," and "Additionally" at rates far exceeding typical human usage. Similarly, AI frequently hedges with words like "potentially," "arguably," and "generally" to avoid making definitive claims. Certain vocabulary choices have also become associated with AI output, including "delve," "tapestry," "multifaceted," "nuanced," and "plays a crucial role." While any one of these words is perfectly normal in human writing, finding several of them in a single passage raises the probability of AI authorship.
Vocabulary diversity is another distinguishing factor. AI tends to produce a type-token ratio between 0.40 and 0.55, meaning it reuses words more frequently than most human writers, who typically fall between 0.55 and 0.75. AI text also tends to lack personal anecdotes, humor, deliberate rule-breaking, incomplete sentences, and the kind of idiosyncratic word choices that make human writing distinctive.
Can AI Content Be Detected Reliably?
No AI detection method is perfectly accurate, and it is important to understand the limitations. Statistical heuristic analysis like this tool provides a probability estimate, not a definitive verdict. False positives can occur with highly formulaic human writing such as legal documents, academic abstracts, and corporate reports, which often share structural similarities with AI output. False negatives occur when AI text has been edited by a human or when the original prompt encouraged varied sentence structure and informal tone.
Detection becomes less reliable with shorter passages. Below one hundred words, there is not enough data to establish meaningful patterns, which is why this tool requires a minimum word count. Text that has been paraphrased, heavily edited, or mixed with human-written content will show intermediate scores that reflect the blended nature of the writing. The best approach is to treat the score as one data point among several. A high score warrants closer inspection but should not be the sole basis for accusing someone of using AI. Context, writing history, and subject matter all play a role in interpreting results.
How to Humanize AI-Generated Text
If you use AI as a drafting tool and want the output to read more naturally, focus on the signals that detectors measure. Start by varying your sentence lengths dramatically. Follow a long compound sentence with a punchy two-word fragment. Ask questions. Use contractions. Throw in a sentence that starts with "But" or "And" the way real people talk.
Remove the transition words that AI scatters through every paragraph. You do not need "Furthermore" or "Moreover" to connect ideas that already flow logically. Cut hedging words unless genuine uncertainty exists. Replace "it could potentially be argued that" with a direct statement. Delete AI-favorite phrases entirely: "It is important to note" adds nothing, "delve into" can become "explore" or "dig into," and "plays a crucial role" can become "matters" or "shapes."
Add personal touches that AI cannot fabricate convincingly: specific examples from your experience, opinions stated with confidence, humor, slang, and cultural references. Break grammar rules on purpose when it serves the tone. These elements introduce the burstiness and unpredictability that make writing feel authentically human.
AI Content Detection for Educators and Publishers
Educators face the challenge of evaluating student work in an era where AI writing tools are freely available. AI detection tools can be helpful as one component of academic integrity processes, but they should never be used as the sole evidence for an accusation. Statistical detection produces probability estimates, and a high score does not prove AI authorship. Students who write in a second language, follow rigid essay templates, or have a naturally formal style can trigger false positives.
Publishers and content platforms use detection tools to maintain editorial standards and identify content that may need additional review. Flagged content can be sent back to authors for revision or compared against previous writing samples from the same author. Detection is most useful as a screening step rather than a final judgment. The most effective approach combines automated detection with human editorial review, looking at whether the content matches the author’s known voice and whether it contains the kind of specific detail that AI struggles to produce convincingly.
AI Content Detector FAQ
How accurate is this AI content detector?
This tool uses six statistical signals to estimate AI probability. It is most accurate with passages of 200 words or more. Like all detection tools, it provides a probability estimate rather than a guaranteed verdict. Accuracy improves with longer text samples and decreases with heavily edited or mixed content.
Does this tool store or transmit my text?
No. All analysis runs entirely in your browser using client-side JavaScript. Your text never leaves your device and is not sent to any server. This makes the tool safe to use with confidential or sensitive content.
Can AI-written text be edited to avoid detection?
Yes. Editing AI output to vary sentence lengths, remove stereotypical AI phrases, and add personal voice can reduce detection scores. The more thoroughly text is edited and rewritten, the closer it becomes to genuinely human-authored content, which is arguably the point of using AI as a drafting assistant rather than a finished-product generator.
What is the minimum text length for analysis?
This tool requires at least 100 words for meaningful analysis. Shorter passages do not contain enough data to establish reliable patterns across the six detection signals. For the most accurate results, provide 200 words or more.
Why does formal human writing sometimes score as AI?
Formal writing styles such as legal documents, academic abstracts, and government reports share structural characteristics with AI output: uniform sentence lengths, hedging language, and heavy use of transition words. These are legitimate features of formal register writing, and a detection tool cannot distinguish between a human choosing to write formally and AI generating formal text. Context matters for interpretation.
Looking for related tools? Try our Reading Level Analyzer to check readability alongside AI detection, or explore all Writing & Content tools.