AI writing tools like ChatGPT, Claude, and Gemini have made it faster than ever to produce content at scale. But that speed comes with a tradeoff: it's increasingly difficult to know whether the article you're reading, the email you received, or the essay a student submitted was written by a person — or generated by a machine.
Fortunately, AI-generated text leaves behind measurable patterns. In this guide, you'll learn how AI detectors work, what they look for, and how to run a free check on any piece of text right now.
Why Detecting AI Content Matters
The stakes are different depending on your context. For educators, AI-generated essays undermine academic integrity. For content marketers, Google's Helpful Content guidelines reward genuine human expertise — heavily templated AI content risks ranking penalties. For hiring managers, knowing whether a candidate actually wrote their application changes everything.
How AI Text Detectors Work
Perplexity
Perplexity measures how "surprising" each word choice is given its context. Human writers make unpredictable choices — unusual metaphors, regional slang, unexpected transitions. AI models are trained to minimise perplexity, consistently choosing the statistically most likely next word. Low perplexity across an entire document is a strong signal of AI authorship.
Burstiness
Human writing naturally varies in rhythm. We write short punchy sentences. Then we write longer, more complex ones that build on the previous idea. AI-generated text tends to maintain a suspiciously uniform sentence length and cadence from start to finish — that lack of "burstiness" is a red flag.
Hedging Language
Certain transitional phrases appear disproportionately in AI output: "It's worth noting that", "Furthermore", "In conclusion", "Additionally". These phrases aren't wrong — but when a 400-word article uses all five, you're almost certainly reading machine-generated text.
Generic Phrasing vs. Specific Detail
Humans write from experience. They reference specific people, places, dates, and personal anecdotes. AI models generalise. When writing consistently stays at "studies show that..." and "many experts believe..." without ever getting concrete, that abstraction pattern suggests AI authorship.
Absence of Natural Errors
Real humans make minor inconsistencies: a comma splice here, an unconventional capitalisation there. AI output is eerily clean. Paradoxically, a complete absence of small imperfections is itself a signal worth noting.
What AI Detectors Cannot Do
No detector is 100% accurate. If a human writer edits AI output heavily, adds personal anecdotes, and varies the sentence structure, detection becomes much harder. Think of an AI score as a probabilistic signal, not a verdict. A score of 85% AI doesn't mean the text was definitely machine-written — it means the linguistic patterns are strongly consistent with AI generation.
Check Any Text for Free — Right Now
CachePlex includes a free AI Text Detector powered by Google Gemini. Paste up to 500 words, click Analyze, and get back an AI probability score, a plain-English verdict, a breakdown of specific AI signals found, and a pattern analysis covering sentence uniformity, filler phrases, personal voice, and more.
No sign-up. No credit card. Three free scans per day.
3 free scans/day · No sign-up · Powered by Google Gemini
Tips for Better Results
For the most accurate reading, paste a self-contained section of text rather than a random excerpt. Introductions and conclusions are where AI patterns are most detectable. If you're checking a long document, test the opening two paragraphs and the final paragraph separately.
The Bottom Line
AI content detection is a probabilistic science, not a courtroom proof. But understanding what detectors look for — perplexity, burstiness, hedging phrases, generic abstraction — also makes you a better writer. The same signals that betray AI authorship are the ones that make human writing compelling: specificity, rhythm, and a voice that sounds like a real person had something to say.