Direct answer
Grammarly's AI detector is a useful first-pass signal, not a verdict: it scans submitted text for statistical patterns typical of generative models and returns a percentage, but Grammarly itself frames the output as probabilistic and non-definitive [1]. More importantly, a Grammarly result is produced by a different model, on different input, with a different threshold than the Turnitin AI writing report your institution sees — so the two numbers are not interchangeable [4]. If your draft contains AI-assisted or AI-drafted passages and the stakes are a graded submission, treat Grammarly as a smoke alarm and a real Turnitin-style report as the fire inspection.
How Accurate Is Grammarly's AI Detector?
Grammarly's detector works by scoring stretches of prose for the linguistic regularities that generative models tend to produce — uniform sentence rhythm, low lexical surprise, evenly distributed hedging — and then reporting how much of the text looks that way [1]. That is a legitimate signal, and it is the same broad family of approach used by institutional detectors. But "same family" is not "same instrument": accuracy figures quoted for any detector are averages over a benchmark corpus, and your specific 2,000-word essay is a sample of one [1].
The practical accuracy problem is threshold design. Detectors are tuned to trade false positives against false negatives, and vendors generally choose the setting that avoids accusing human writers too often — which necessarily means some genuinely AI-generated text slips under the line [2]. Turnitin, for example, suppresses an exact percentage and displays *% when its AI detection confidence falls below 20%, explicitly labelling those results low-confidence rather than presenting them as findings [2]. A tool that shows you a clean 0% is not promising you a clean report elsewhere.
There is also an input-scope gap that users rarely notice. Detectors evaluate long-form prose inside the file you give them; they do not meaningfully evaluate reference lists, tables, equations, code blocks, or short fragments, and results shift with document length [4]. Grammarly checks what you paste into it, which is usually a selection, not the submitted artefact — so even a perfectly calibrated detector is being asked a slightly different question than the one your professor asks [1][4].
Why Does Grammarly Say My Writing Is AI-Generated When I Wrote It Myself?
False positives are a documented, expected behaviour of statistical detectors, not a malfunction [3]. Highly formulaic academic registers are the main trigger: literature-review scaffolding, methods sections written to a template, definitional paragraphs, and heavily outline-driven argument all reproduce the same low-variance patterns that detectors associate with machine text [3]. If you write in the genre's standard shape, you can be penalised for writing well to convention.
Second-language and translated writing is the most cited exposure. When phrasing is grammatically conservative and vocabulary is deliberately safe — a rational strategy for an international student — the text looks statistically smoother than a native speaker's rough draft, and smoother text scores higher [3]. The same applies to text you have already run through a grammar checker: if you accepted every suggestion and flattened your own voice, you removed exactly the irregularities that detectors read as human [1][3].
The correct response to a flag is forensic, not cosmetic. Identify which passages were flagged, check whether those passages were quoted, templated, or AI-assisted, and keep your drafts and version history as evidence of process [3]. A detector score is a prompt to review your text and your workflow — it is not proof of misconduct, and institutions are increasingly expected to interpret it in context rather than act on the number alone [2][3].
Does a Grammarly AI Score Match What Turnitin Shows Your Professor?
No — and the mismatch is structural, not a bug in either product. Each detector is a separate model trained on its own data, with its own segmentation rules, its own confidence floor, and its own display conventions, so a 34% in one tool and an 8% in another can both be "correct" for their own instrument [4]. Grammarly is also evaluating the text you chose to paste; Turnitin evaluates the submitted file, and only the prose portions of it, which changes both the denominator and the flagged span [2][4].
The comparison that actually matters is against the report format your institution uses, because that is the document a human will read and act on. Turnitin's AI writing report presents an overall percentage of qualifying prose flagged plus sentence-level highlighting, and it deliberately withholds precision at the low end by showing *% below its confidence threshold [2]. Learning to read that layout — what is highlighted, how much of the document qualifies, where the confidence floor sits — is more useful preparation than chasing a percentage in a different tool [2].
So use Grammarly for what it is good at: catching obvious machine-sounding stretches early, and prompting you to rewrite passages you cannot defend. Then verify against a report that reproduces the institutional view, so the number you act on is the number your marker will see [4]. Students who check only in a consumer tool are optimising against the wrong target, and the gap typically surfaces at the worst possible moment — after submission [2][4].
If you want certainty rather than a second opinion, turnitin0 runs your actual draft through a genuine Turnitin AI detection report and a similarity report in one checkout — the same two PDFs your professor opens in the LMS, non-repository, typically back in under 15 minutes, with the *% low-confidence convention shown exactly as your institution will see it.
※ Turnitin0.com - Actual [Turnitin AI Report](https://www.turnitin0.com/guides/us/the-true-cost-of-ai) Cover, Score, Flag And Similarity Summary
FAQ
Is Grammarly's AI detector the same as Turnitin's?
No. They are independent models with different training data, segmentation, and confidence thresholds, so their percentages are not comparable [4]. Grammarly's output describes its own reading of the text you paste; Turnitin's report describes the submitted file in the format your institution reviews [2].
Can Grammarly detect text written by ChatGPT, Claude, or Gemini?
It can flag statistical patterns common to those models, but detection is probabilistic and depends heavily on how much the text was edited afterwards [1]. Heavily revised or human-paraphrased AI text is exactly where detectors lose confidence [3].
Why do I get different scores on different checkers?
Because each tool asks a slightly different question of a different sample: different model, different minimum length, different low-confidence floor, and often a pasted excerpt rather than the full submitted document [1][4]. Variation between tools is expected, not evidence that one is broken.
What should I do if a checker flags my own writing?
Keep your drafts and version history, locate the flagged passages, and check whether they are quoted, templated, or unusually formulaic [3]. If the text is genuinely yours, the evidence of process is your defence, not a lower score in a consumer tool.
Does a low Grammarly score mean I am safe to submit?
Not necessarily. A low score in one detector says nothing about how another instrument will read the same file, and Turnitin shows *% rather than a precise figure when confidence is low [2][4]. Confirm against a report that mirrors the institutional view before you submit.