Grammarly AI Detector Review: How Accurate Is It Really?

Grammarly spent fifteen years teaching people to write more clearly. Now it sells a tool that flags clear writing as artificial. That tension is the most interesting thing about the Grammarly AI detector, and it explains most of what follows.

This review covers what the detector actually measures, what the published accuracy numbers are worth, how it stacks up against Turnitin and GPTZero, and what to do if it flags work you wrote yourself.

What the Grammarly AI detector is

It is a free web tool plus a feature inside Grammarly's editor. You paste text, it returns a percentage described as how much of the text appears AI-generated. Grammarly Pro adds a sentence-level breakdown and a higher word limit; the free tier gives you the number and little else.

That single percentage is the root of most misunderstanding about it. It is not a probability that you cheated. It is not a confidence score. It is a summary statistic derived from how predictable your word choices are.

How it actually works

Like nearly every detector on the market, Grammarly's model is built on two measurements:

• Perplexity — how surprising each word is given the words before it. Language models are trained to pick likely next words, so their output tends to sit in a narrow, predictable band.
• Burstiness — how much sentence length and structure vary across a passage. Human writing tends to lurch between short sentences and long ones. Model output tends to even out.

Low perplexity plus low burstiness reads as machine-written. That is the whole mechanism, and it is worth internalising, because it tells you precisely who gets misclassified: anyone whose natural writing is clear, conventional, and consistent.

The detector has no access to your document history, your drafts, or your keystrokes. It sees the finished text and nothing else.

Accuracy: what the numbers actually say

Here I want to be careful, because this is where most reviews of this tool go wrong.

Grammarly has not published a peer-reviewed evaluation of its detector. Almost every specific accuracy figure circulating online comes from a blog post published by a company that sells either a competing detector or a humanizer. Those are not neutral sources, and it shows in how far apart their numbers land.

Across the third-party tests published through 2026, the reported figures cluster roughly like this:

A 14% false positive rate and a 34% false positive rate imply completely different tools. The honest reading is that nobody outside Grammarly has run a large, methodologically clean, independent evaluation, and you should treat any confident single number — including any you find on this site's competitors — with suspicion.

What we can say with confidence is the direction: it catches most unedited AI text, it misses a meaningful share, and it flags human writing often enough to matter.

The false positive problem is real and it is documented

The strongest evidence on detector false positives is not about Grammarly specifically, but it applies to the whole category, and it is peer-reviewed.

In 2023, Liang et al. published "GPT detectors are biased against non-native English writers" in Patterns. The researchers ran seven widely used detectors against 91 TOEFL essays written by non-native English speakers and 88 essays by US eighth-graders.

The results:

• On the US student essays, the detectors were near-perfect.
• On the TOEFL essays, the average false positive rate was 61.22%.
• All seven detectors unanimously misclassified 18 of the 91 TOEFL essays as AI-written.
• 97.8% of the TOEFL essays were flagged by at least one detector.

The mechanism is exactly the perplexity issue described above. Second-language writers reach for more predictable vocabulary and simpler constructions. That is what fluency looks like when you are still acquiring a language, and detectors read it as machine output.

The most damning detail: when the researchers rewrote those same essays using more elaborate, literary vocabulary, the false positive rate collapsed from 61.3% to 11.6%. The tools were not detecting AI. They were penalising a particular register of human English.

Detector vendors, Grammarly included, have improved their models since 2023, and the gap has narrowed. But the underlying signal has not changed, because there is no other signal available.

The Grammarly paradox

Here is the part that deserves more attention than it gets.

Grammarly's core product nudges you toward shorter sentences, simpler words, active voice, and fewer hedges. Accept enough of those suggestions across a document and you have systematically reduced its perplexity and flattened its burstiness — the two things the same company's detector treats as evidence of AI authorship.

I want to flag clearly that this is an inference from how the two systems work, not a measured finding. I am not aware of any controlled study on whether accepting Grammarly's suggestions raises your score in Grammarly's own detector. It would be a genuinely useful experiment and nobody appears to have run it.

But the logic is hard to escape, and if you are a student who edits heavily in Grammarly before submitting, it is worth knowing that the polish itself may be working against you.

How it compares to Turnitin and GPTZero

For most people reading this, the practical question is not whether Grammarly's detector is good, but whether it predicts what their institution's detector will say.

The critical point: a clean Grammarly score does not mean a clean Turnitin score. Different training data, different thresholds, different models. Passing one detector tells you very little about another, and we have covered this specific mismatch in more depth in does passing ZeroGPT mean you'll pass Turnitin.

Turnitin is the one that actually carries consequences, because it is the only one of the three your institution sees. If you want to understand what it is measuring, how Turnitin AI detection works breaks down the scoring.

What to do if Grammarly flags your own writing

If the work is yours, the flag is a measurement artefact, not a verdict. Practical steps:

1. Keep your drafts. Version history in Google Docs or Word is the single most effective rebuttal available. It shows the messy middle that AI output never has.
2. Do not rewrite in a panic. Rewriting a flagged document to satisfy a detector often makes the prose worse and rarely moves the score much.
3. Check a second detector. Wide disagreement between tools is itself evidence that the number is unreliable — and it is common.
4. Know the research. If you are formally accused, the Liang study above is the citation to bring. A documented 61% false positive rate on non-native writing is a serious problem with the evidence being used against you.

If English is your second language, detector bias against non-native writers covers why this hits you harder and what to do about it. If you are dealing with an accusation right now, our full guide to AI detector false positives walks through gathering evidence and escalating.

Should you use it?

As a free sanity check before submitting something important, yes. It costs nothing and it will catch obviously unedited AI text.

As a source of truth about your own work, no — and neither will any other detector. The category is built on a proxy measurement that cannot distinguish "written by a model" from "written plainly by a person." Until something better than perplexity comes along, every tool in this space inherits the same ceiling.

The most useful thing you can do is not chase a green score. It is to write with genuine variation in your sentences and keep the drafts that prove you did.

Grammarly now sells a humanizer next to the detector reviewed here, and the two do not agree with the rest of the field. When I tested them together in September 2026, the detector scored Grammarly's own humanized output at 0% while an independent detector scored the same passage 99.1% AI. The numbers are in our Grammarly AI humanizer review.

If you are working with AI-assisted drafts and want them to read like your own voice rather than a model's, RewriteAI's humanizer restores the sentence-level variation that both AI generation and heavy grammar-tool editing strip out.