The reason you cannot find a Chegg AI score is that Chegg does not publish an AI detector. Chegg Writing is a plagiarism checker, a grammar checker and a citation tool, and Chegg also owns EasyBib, which is the same category of product. None of those pages advertises an AI detection score, an AI probability, or an AI writing indicator. If you ran your work through Chegg and saw no AI verdict, nothing failed.
The more useful part is why a plagiarism checker was never going to give you one. A similarity checker searches for your sentences somewhere else. Text a language model just generated has never existed before, so there is nothing for it to match, and it comes back clean. That is not a gap in Chegg's implementation. It is what the two tools measure being different things, and it is the single most consequential misunderstanding in this whole subject.
Set out plainly, with an explicit note about what we could and could not verify directly.
Chegg's writing product is built around three things: a plagiarism checker that compares submitted text against online sources and published content, a grammar and writing checker, and citation generation. Chegg also owns EasyBib, long established in the same space, whose plagiarism checking sits behind a paid tier. These are competent, long-standing tools for the jobs they name.
No AI detection score appears in Chegg's published feature list for that product. There is no AI writing indicator, no AI probability, and no equivalent of the AI percentage that Turnitin surfaces to instructors.
Chegg's site returns HTTP 403 to automated requests, so we could not read its current pages programmatically the way we read other vendors' claims. That has two consequences we would rather state than paper over. We are not quoting a price, because we could not confirm a current one at source. And our statement that no AI detection score is published rests on Chegg's published feature naming rather than on a direct reading of every page today.
Secondary sources broadly assert that some AI-related pattern matching may sit inside Chegg's plagiarism scan without being reported as its own score. We are not repeating that as fact. On this keyword the search results are dominated by sites selling humanizers and competing detectors, which is exactly the kind of source that gets these details wrong, and an unreported internal signal is unverifiable by construction. What matters for your decision is the part that is not in doubt: there is no AI score for you to read.
Verification note: chegg.com returned HTTP 403 to automated requests on 29 September 2026, so no price or page text is quoted from it here. Claims about the product's scope are based on its published feature naming. If Chegg ships an AI detection score, this page should be corrected.
This is the part worth understanding properly, because it explains a whole category of confusion and it is not a criticism of any particular vendor.
| Plagiarism check | AI detection | |
|---|---|---|
| Question asked | Has this text appeared elsewhere? | Does this text look machine-written? |
| Method | Matching against an index of sources | Statistical properties of the writing itself |
| Answer type | Matched passages you can open and read | A probability estimate |
| On freshly generated text | Comes back clean | May flag it |
| On honestly quoted sources | Flags them, correctly | Usually indifferent |
A similarity checker builds an index of web pages, published articles and archived student papers, then looks for stretches of your text that appear in it. When it finds one, it shows you the source. That is genuinely strong evidence, because you can click through and compare.
A language model does not retrieve sentences. It generates a new sequence token by token, and the specific wording it produces has, in the ordinary case, never been written before. There is no source document to match, so the index finds nothing and the similarity score is low. A clean plagiarism report on generated text is the expected result, not a malfunction.
Because the same product now often reports both, people conflate a low similarity score with a clean bill of health. Two well-documented cases show how far the confusion runs. Blackboard ships SafeAssign, which is a similarity checker and not an AI detector, and Anthology published its decision not to build AI detection after finding error rates too high and the models biased. And Moodle's own documentation states it comes with no pre-installed plagiarism prevention methods at all, so what it checks depends entirely on which plugin an administrator installed. Neither platform does what most students assume it does.
The inverse confusion is just as common and more damaging: treating a high AI score as plagiarism. They are separate allegations with separate evidence and separate consequences, and conflating them is how appeals get mishandled. We set the distinction out at length in AI plagiarism vs AI generation.
You probably want both, and swapping one for the other would leave a real hole. This is not a page arguing plagiarism checking is obsolete.
An AI detector catches none of the above. It has no index, makes no comparison to sources, and will pass a perfectly plagiarised paragraph without comment if the prose happens to look human. The two tools are complements, and the sensible arrangement is to run a similarity check for attribution problems and a separate statistical reading for the authorship question.
Keep using a plagiarism checker for what it does. Add a text-signal tool when the question is authorship. And when the question is whether you wrote something, note that neither tool is your strongest evidence: version history and drafts are, and they cost nothing. How to prove you did not use AI covers what to keep.
Including the limits, in the same place as the claims, because a page that only lists strengths is not telling you enough to decide.
We publish 88% to 92% on long-form English of 300 words or more across 15 model families, and 70% to 78% under about 100 words. We do not publish a single headline accuracy figure, because one number would be more persuasive and less true, and because the short-text band is the case you most need to know about.
Our false-positive rate is 5.85% across 1,180 academic papers, with per-document results downloadable at our benchmark. That is a mid-single-digit number we can evidence rather than a sub-1% claim we could not support, and publishing the data is the point: you can find a paper we got wrong.
We make no claim to outperform Chegg, since Chegg publishes no AI detector to be compared against. Where we sit relative to tools that do is at our comparison.
Starting with the one that brought you here.
Chegg publishes no AI detector and no AI score. Chegg Writing is built around plagiarism checking, grammar checking and citation generation, and Chegg also owns EasyBib, which is the same category of product. None of those advertises an AI writing indicator or an AI probability. If you ran work through Chegg and saw no AI verdict, nothing went wrong. Note that chegg.com returns 403 to automated requests, so this rests on its published feature naming rather than a direct page read.
No, and no similarity checker can, for a structural reason rather than an implementation one. A plagiarism checker searches an index of web pages, published work and archived papers for stretches of text matching yours. A language model generates new wording token by token, so in the ordinary case the exact sentences have never existed before and there is nothing to match. A clean similarity report on generated text is the expected outcome, not a failure.
No, and this is the most consequential misunderstanding in the subject. The two tools answer different questions: plagiarism checking asks whether your text appeared elsewhere, AI detection asks whether it looks machine-written. Generated text typically scores low on similarity and may still be flagged by a detector. The reverse also holds: a perfectly plagiarised passage can pass an AI detector if the prose reads as human.
We are not quoting a figure. Chegg's site returned HTTP 403 to automated requests when we checked on 29 September 2026, so we could not confirm a current price at source, and we would rather say that than repeat a number from a review site. Check chegg.com directly for current pricing, and note that EasyBib's plagiarism checking also sits behind a paid tier.
No. They catch different problems and a detector cannot replace a similarity check. Only similarity checking catches accidental plagiarism, which is the most common integrity problem in student work: a paraphrase that stayed too close to the source, a quotation whose marks were lost in editing, or a note copied verbatim into a draft. It also catches missing attribution and self-plagiarism, and it produces matched passages you can show someone, which a percentage cannot.
Turnitin dominates, largely because institutions already licensed it for similarity checking before AI detection was added, so enabling it cost nothing extra. Copyleaks and GPTZero also sell into education. Notably the major learning platforms ship no AI detector of their own: Moodle's documentation states it comes with no pre-installed plagiarism prevention methods, Blackboard's SafeAssign is a similarity checker, and Canvas provides a socket that an external tool plugs into.
A statistical reading of whether text looks machine-written, which Chegg does not publish, with sentence-level highlights rather than a single percentage. Accuracy is published as bands, 88% to 92% on long-form English of 300 words or more and 70% to 78% under about 100 words, with a false-positive rate of 5.85% over 1,180 academic papers and the per-document data downloadable. We keep plagiarism risk as a separate view so the two questions do not collapse into one number.
The other question, kept as a separate view rather than folded into an AI score.
Try the tool →SafeAssign is a similarity checker, and Anthology published why it did not build a detector.
Read the detail →What institutions actually run, at what scale, and with what published error rates.
Read the answer →1,180 academic papers, 5.85%, per-document data you can download and audit.
Check our numbers →Where our own detector fails, listed by us rather than discovered by you.
Read the limits →Another tool that bundles checking with academic writing support, compared honestly.
See the comparison →Get the reading a plagiarism checker structurally cannot give you: sentence-level highlights, accuracy published as bands instead of a headline number, and a false-positive benchmark you can download. 3 checks a day, no account.