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Is a plagiarism score the same as an AI score?

No. A similarity score counts how much of your text matches documents in a database, while an AI score estimates how machine-like your writing reads — the first points at something you can open and read, the second does not.

Last reviewed 15 August 2026 · The HumanFlow team

The similarity score is a matching exercise. The tool holds a corpus of student papers, journals and web pages, finds runs of text in yours that appear there too, and reports what proportion matched. Every percentage point is attached to a specific source you can click through to.

The AI score is an estimate. Nothing is being matched against anything; a classifier is judging how closely the statistical shape of your prose resembles machine-generated text it was trained on. There is no source behind the number, because there is no source.

That difference decides how much weight each can bear. A 40% similarity score is an observation you can check in five minutes — often it turns out to be a correctly quoted block, a reference list, or a methods paragraph shared with your own earlier submission. A 40% AI score cannot be checked by anybody, including the vendor.

The two also fail differently. Similarity over-reports when quoting is heavy and under-reports when text has been reworded. AI detection over-reports on plain, formulaic and second-language writing. Neither failure tells you anything about the other.

When this answer changes

Some tools now report both numbers in one interface, which makes them easy to conflate. If a figure is being quoted at you, ask which of the two it is and which report it came from — they are separate rows in the same document.

A high similarity score can occasionally be evidence of AI use rather than of copying, if generated text has reproduced source material closely. That is an argument someone has to make from the matched sources, not from the AI percentage.

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