Detectors give you a number. This guide gives you signals you can check by reading: patterns that appear often in AI-assisted writing and hold up better than a probability score.
Signal one: uniform rhythm
Human writing varies sentence length naturally. AI-assisted text tends to settle into a comfortable, repeated rhythm. If every sentence runs about the same length and the same shape, the text may have been generated or heavily edited.
Read aloud. The ear catches uniform rhythm faster than the eye.
Signal two: vague qualifiers
Text that leans on phrases like "many experts suggest," "in today's fast-paced world," or "it is important to note that" is often padding. These openers carry no information. They appear constantly in AI output because the model fills space with plausible, low-risk phrasing.
Signal three: the wrong level of specificity
AI drafts describe things at a comfortable distance. They say "a leading platform" instead of naming it, "significant growth" instead of the figure, "recent research" instead of the citation. If a text gestures at specifics without delivering them, verify the source.
Signal four: repetition with different words
Models restate the same idea in new phrasing to fill space. If you can delete a paragraph and lose nothing, the paragraph was probably doing that. Check for sentences that say the same thing twice.
Signal five: perfect but flat structure
Well-structured writing is good. Perfectly symmetrical structure with every paragraph the same shape is often generated. Humans leave rough edges: a short punchy paragraph, a digression that earns its place, an unexpected example.
The review workflow that beats detection
Instead of asking "was this written by AI?", ask "should this be published as is?" Run the draft through a review checklist:
- Facts verified against the source.
- Claims the author can stand behind.
- One idea per paragraph.
- Specifics replace qualifiers.
- Tone matches the audience.
Vortixy automates part of this: it reviews clarity, structure, voice, and factual consistency, and returns an editable revision. You keep the final decision.
When you genuinely need to know
If policy requires you to determine whether a text is machine-generated, pair at least two detection tools with a manual reading using these signals. Treat agreement as supporting evidence and disagreement as a prompt for deeper review. Never treat a single score as conclusive.