Short answer: the detection tools built to answer this question are not reliable enough to trust on their own. Independent 2026 benchmark testing found no AI detection tool exceeds roughly 85% accuracy across current models, and false positive rates on genuine human writing run 3-12%. The better approach is learning to read the real signals yourself, the same five patterns we named in our first piece on AI slop and confirmed again when we audited twelve real small business websites against them.
Why detection tools cannot be trusted alone
Vendors advertise accuracy rates near 99%. Independent testing tells a different story. One 2026 benchmark running outputs from multiple current AI models through the leading detection tools found that none exceeded roughly 85% accuracy, with 15-30% of genuinely AI-generated content going undetected entirely. The same testing found false positive rates of 3-12%, meaning real human writing, disproportionately from non-native English writers and technical authors, gets incorrectly flagged as AI-generated.
Detection accuracy drops further once AI-generated text has been paraphrased, translated, or lightly edited by a human. A detector built to catch clean, unedited AI output is not built to catch AI output that someone has already revised.
The signals that actually work
Rather than relying on a single tool's score, read the content itself against the same patterns that define AI slop:
- Generic phrasing. Sentences that could describe almost any business in the category, with nothing tying them to this one specifically.
- Unattributed claims. Superlatives and statistics with no named source, no year, no citation behind them.
- No named human. Nothing in the piece reads like it came from one specific person with a real name and a real point of view.
- Repeated structure. The same sentence pattern, or the same paragraph in different words, showing up more than once.
- No verifiable detail. Nothing a reader could actually check, no specific fact a competitor could not casually copy.
A piece that fails several of these is worth treating skeptically, regardless of what any detection tool says about it.
What Google actually says about this
Google's own Search Central documentation is direct on this point: content quality is evaluated through signals like Experience, Expertise, Authoritativeness, and Trust, not through whether a human or a model produced the words. Generic, unoriginal, unreviewed content is treated as low quality either way. Specific, accurate, genuinely useful content is treated as high quality either way. The question worth asking is not "did AI write this," it is "does this say something only a real, specific source could say."
Why this matters beyond curiosity
This question comes up most often when someone is deciding whether to trust a piece of content, a vendor's marketing, a competitor's claims, an unfamiliar source. The honest answer is that no detection tool will settle that for you reliably. The five signals above will, because they describe what trustworthy writing actually looks like, independent of who or what produced it.
Frequently asked questions
Are AI content detection tools accurate?
Not reliably. Independent 2026 benchmarks found no detection tool exceeds roughly 85% accuracy across current AI models, with 15-30% of AI-generated content going undetected and false positive rates of 3-12% on genuine human writing.
What are the real signs that content was written by AI?
Generic phrasing that could describe any business, claims with no attributed source, no named human behind the words, structure or phrasing that repeats itself, and an absence of any specific, verifiable detail a competitor could not casually copy.
Does Google penalize content for being written by AI?
No. Google's own documentation states it evaluates content quality through signals like Experience, Expertise, Authoritativeness, and Trust, regardless of whether a human or a model produced it. Generic, unoriginal, unreviewed content is penalized, not AI authorship itself.
Can AI-generated content pass detection tools if it is edited?
Often, yes. Detection accuracy drops significantly on paraphrased, translated, or lightly edited AI content, which is one of the main reasons these tools should be treated as one signal among several, not as proof.