You can usually tell AI wrote something by looking for three things at once: sentences that all run about the same length, connectors like "moreover" and "furthermore" doing the work that real reasoning should do, and a suspicious absence of names, numbers, and dates.
Whether it matters for your blog depends on what the reader gets, not on which tool produced it — Google's guidance has long been that it rewards helpful content regardless of how it's made, while readers punish writing that says nothing specific.
So the honest answer is: detection is a useful editing skill, but the tool used is not the problem. The problem is vagueness, and vagueness is fixable.
How to spot AI-written text
Start with rhythm. Human writers naturally mix short punches with long, winding sentences. AI drafts tend to settle into an even, mid-length cadence that feels smooth and slightly hypnotic.
Read a paragraph aloud — if every sentence takes roughly the same breath to say, that's a signal. Second, look at the transitions. Words like "moreover," "furthermore," and "in conclusion" often appear where a human would just start the next thought.
They're grammatical filler, not logic. Third, hunt for specificity. A human writing about meal planning will mention a real constraint — a nut allergy, a Tuesday night when nobody has energy, a $60 weekly budget.
An AI draft will say "consider dietary restrictions and budget accordingly." That sentence is true and useless. Fourth, check the claims.
If a post cites a statistic, a study, or a price, can you find where it came from? AI tools sometimes generate confident-sounding numbers that don't exist, which is why it's worth reading our guide on how to stop ChatGPT from making up fake facts in your content.
Fifth, notice the ending. AI drafts love a summary paragraph that repeats the introduction in different words. Humans usually just stop when they've made their point.
Does it matter for your blog?
Here's the verdict: the tool doesn't matter, the output does. A reader who learns something real doesn't care whether a person or a model drafted the first version. What they punish is the feeling of having read 800 words and learned nothing — and that feeling comes from vagueness, not from AI.
This is why detection is worth learning anyway. It's not about catching a machine; it's about catching the moment your draft stopped saying anything. If you can spot the flat, even, generic passages, you can fix them before a reader does.
That's the whole skill. The tool is irrelevant to the reader, but the tell-tale signs of an unedited draft are very relevant to you.
A worked example
Take a sentence like: "When planning meals for the week, it's important to consider your family's preferences and nutritional needs." Now compare it to: "My son won't touch anything green, so Monday is pasta with hidden zucchini, and I buy the cheap jar sauce because the good stuff triples the bill."
The first sentence could have been written by anyone about anything. The second could only have been written by one specific person about one specific Tuesday. That difference is the detection signal, and it's also the fix.
When you find a flat passage, don't just reword it — replace the generality with a fact only you have. The rewrite isn't about making it sound human. It's about making it carry information.
Where this advice breaks down
Detection signals are probabilities, not proof. A careful human writer can produce even, mid-length sentences all day, and a heavily edited AI draft can pass every check above. You cannot reliably prove authorship, and you shouldn't try — accusing someone of using AI based on style alone is a good way to be wrong in public.
The signals are for editing your own work, not for judging other people's. There's also a cost to over-editing: if you rewrite every sentence to sound idiosyncratic, you can end up with prose that's harder to read than the flat version you started with. Clarity still wins.
Finally, some formats genuinely don't need specificity — a short how-to list, a definition, a product spec sheet. In those cases a clean, even tone is fine, and hunting for personality is wasted effort. Use the signals where they matter: opinion pieces, case studies, anything where the reader came for a point of view.
And remember that our AI tool database tracks 360 tools with pricing and capability snapshots recorded at verification time, most recently in September 2026 — useful when you're choosing a drafting tool, but no database can tell you whether your draft says anything worth reading. That part is still on you.