AI detectors are not fully accurate, and their results should be treated as rough indicators rather than proof. They often mislabel human text as AI- generated and can also miss AI-written text, especially if it has been edited or paraphrased.

How accurate they tend to be

Many comparative tests of multiple detectors find average accuracy rates around 60–70%, with the best paid tools in controlled tests sometimes reaching 80–85% on specific benchmarks. Even tools that advertise very high lab accuracy (for example, “98% accurate”) acknowledge non‑trivial error rates and margins of error when used on real student or web writing.

False positives and false negatives

Studies and academic guidance note that AI detectors can produce many false positives (human work marked as AI) and false negatives (AI work marked as human), especially when judging a single piece of writing. There is also evidence that non‑native English writers and some neurodivergent writers are flagged at higher rates, because their language patterns resemble what detectors are trained to see as “AI‑like.”

Practical takeaway

Because of these limitations, major academic and teaching centers advise against using detectors as the sole basis for accusing someone of using AI. They are best used, if at all, as one small piece of evidence alongside things like drafts, writing history, and direct conversation with the writer.