Why Does My Writing Sound Like AI?

By Jack Stovell · 2026-08-21 · Guides

Here's the direct answer, because you didn't come here for suspense. Your writing sounds like AI because it shares statistical habits with AI text: sentences that all land the same length, transitions pulled from the same small stock pile, closing lines that hedge instead of commit. That's it. That's the whole diagnosis.

Now the honest bit underneath it, which is where this gets less insulting.

Habit one: uniform sentence rhythm

AI models, left unguided, produce sentences that cluster tightly around the same length. Eighteen words. Nineteen. Twenty. Metronomic. And here's the thing: plenty of humans do this too, especially once they've been through a few rounds of "clean this up" edits, or years of corporate writing training that rewards evenness over variety.

Before: "The quarterly results show growth across most sectors. The marketing team performed particularly well this period. Sales figures also improved compared to last quarter."

After: "Growth, mostly. Marketing did well; sales too, though not as sharply. The quarter wasn't perfect, but nobody's asking for perfect."

Same information. Wildly different pulse. The second version breathes because the sentence lengths swing around instead of marching in step.

Habit two: stock transitions

"Furthermore." "It's worth noting." "In today's fast-paced world." These phrases exist because they're safe, structurally load-bearing, and completely invisible to whoever wrote them. That's exactly why models default to them: they're the statistically likely next words, over and over, and safety looks a lot like sameness at scale.

Before: "Furthermore, the results indicate a positive trend. Moreover, this trend is likely to continue."

After: "The results point up. That's likely to hold, and here's why."

Cut the padding, and the sentence has to earn its place. That's usually an improvement whether a model wrote the first draft or you did, half-asleep, at 4pm on a Friday.

Habit three: hedged closes

This is the one that gets careful writers into trouble. You've been taught, correctly in most contexts, to qualify your claims. "This may suggest." "It could be argued that." "Perhaps, in some cases." Reasonable instincts. But strung together at the end of every paragraph, hedging starts to read like evasion, and evasion is a texture models produce constantly, because they're trained to avoid committing to anything that might be wrong.

Before: "This approach might work better for some teams, though results could vary depending on context."

After: "This works better for most teams. Context changes the margin, not the direction."

Notice the second version isn't reckless. It's just decided. Fair enough, you might say, but what if I'm wrong? You can be wrong and direct at the same time. Hedging doesn't protect you from being wrong; it just makes the wrongness harder to spot, which is worse.

Habit four: low burstiness

Burstiness is the technical term for chaos in sentence length, the difference between a five-word sentence sitting next to a thirty-word one, versus everything landing in the same narrow band. Human writing, when it's actually good, is bursty. We write long when the idea needs room, short when it doesn't, and we don't apologise for either.

AI text, uncorrected, smooths that out. So does over-edited human text. So does writing produced under deadline pressure by someone following a style guide a little too faithfully. The tell isn't "a machine wrote this." The tell is "nobody made a rhythm decision here."

The honest twist

Here's the part that tends to get skipped in these articles, and it's the important bit: none of these habits are new. Stock transitions predate ChatGPT by decades; they're what happens when institutional writing gets sanded down for safety across a hundred rounds of committee edits. Hedged closes are what academic training does to a person, on purpose, for good reasons that stop being good once they calcify into a tic. Even sentence uniformity has a long history in corporate style guides that reward consistency over voice.

The models didn't invent this. They learned it from us, from decades of exactly this kind of writing, and now they produce it fluently and at scale. So the tell isn't really "AI wrote this." The tell is "this was written by someone, or something, optimising for safety over voice." That's why careful, entirely human writers get flagged too, and why chasing a detector score is chasing the wrong signal. The problem was never proving you're human. It's that safe, average writing and AI writing occupy the same statistical neighbourhood, and you don't want to live there either way.

What to actually do about it

Not detection. Measurement. There's a real difference: one asks "will this pass," the other asks "does this sound like me." You want the second question.

Start by looking at your own patterns properly. ScriptGrain runs a two-pass stylometric analysis across 45 attributes of your writing, sentence rhythm, transition habits, hedge rate, the lot, and the free tier gets you one profile and one analysis, no card needed. If you want something faster and lower-stakes first, there's a free browser-based tool at scriptgrain.com/tools/writing-style-analysis that checks 12 attributes client-side, no signup, nothing to install.

Then write with deliberate variance. Short sentence. Then a longer one that actually goes somewhere and earns its length. Cut the hedge from your closing line and see if the paragraph survives, it usually does, and it's usually better for it.

At the end of the day, distinctive writing isn't about dodging a scanner. It's about having a rhythm that's yours, measured, not assumed. Fair enough if that takes a bit of practice. Most things worth having do.