How to make your writing not sound like AI
To make your writing not sound like AI, vary sentence length hard, cut connector words and hedges, add one concrete detail per paragraph, state a real opinion, and use first person. Then run a detector on the result, fix the highest-scoring paragraphs, and re-check.
If you're here because a detector, a professor, or an editor flagged words you actually wrote — that's infuriating, and you're not imagining it. Careful, formal writing gets flagged all the time, precisely because it's careful and formal. The fixes below make your writing less flaggable and genuinely better, whether every word is yours or you polish drafts with AI first. This is the craft-level companion to our pillar on how to not sound like AI.
Why does my writing sound like AI when I wrote it myself?
AI detectors don't detect AI. They detect statistical typicality — how predictable your word choices are. AI text is predictable because models literally generate the most probable next word. But human writing can be predictable too, and three groups write that way naturally:
- Professionals trained into corporate register: hedged claims, passive voice, "per my last email" neutrality.
- Formal students who internalized the five-paragraph essay: topic sentence, three supports, restated conclusion, every time.
- Non-native English writers who learned textbook English — which is more regular, and therefore more predictable, than the sloppy English natives write. This group gets it worst: a Stanford study in the journal Patterns found detectors flagged over half of essays by non-native speakers while barely flagging native ones.
So the accusation says nothing about your integrity. It says your style overlaps with the machine's default. The good news: the overlap is made of specific, fixable habits.
What are the 9 fixes?
1. Break your sentence rhythm
This is the highest-leverage fix. Predictable writing paces evenly — 18 words, 20 words, 17 words. Put a four-word sentence next to a thirty-word one. Read a paragraph aloud; if your breathing never changes, neither does the rhythm.
2. Delete the connectors
"Furthermore", "moreover", "additionally", "thus", "in addition". These are the load-bearing words of both AI text and formal training. Cut them cold. Ideas that belong together don't need an usher.
3. Stop hedging
"This could potentially suggest that outcomes may improve." You were taught to hedge to sound rigorous; the model hedges to avoid being wrong. Either way it reads machine-cautious. Pick your strongest claim and make it flat out. If a claim genuinely needs a qualifier, hedge once — "probably" — not three times in one sentence.
4. Add concrete detail — one per paragraph
A number, a name, a date, a small failure. "The migration was challenging" is anyone's sentence. "The migration ate three weekends and one of them was my anniversary" is only yours. This is the one move no model can make, because it doesn't know your life.
5. Have an opinion
Balanced on-the-one-hand prose is the shared dialect's core. Say what you actually think, including where you might be wrong. Disagreement with the consensus is nearly impossible for AI to fake convincingly.
6. Use first person
Where the format allows it, "I found", "we tried", "I'd skip it". Formal training says avoid "I"; that avoidance is now a tell. Even academic writing has moved toward first person for methods and judgment calls. "It was determined that the approach was flawed" hides a human; "I ran it twice and it broke both times" is one.
7. Cut the corporate abstractions
Leverage, utilize, facilitate, robust, streamline, stakeholders alignment. Swap each for the plain word: use, help, solid, simplify. If a sentence survives with all abstractions removed, keep the survivor.
8. Let structure be lopsided
Three parallel bullet points, matched paragraph lengths, "not only X but also Y" — symmetry reads as generated. Spend four paragraphs on the thing that matters and one sentence on the thing that doesn't.
9. End when you're done
No "In conclusion" paragraph that replays the introduction. Your last real point is your ending.
What do the fixes look like on a real paragraph?
Here's a paragraph that would flag, from a genuinely human-written project update:
Before: "The onboarding redesign presented several challenges. Moreover, stakeholder feedback indicated that the timeline may potentially need to be adjusted. It is important to note that the team remained committed to delivering a robust solution. In conclusion, the project demonstrates the value of effective collaboration."
Four sentences, four tells: connectors, hedging, corporate abstractions, formula ending. Same facts, rewritten:
After: "The onboarding redesign fought us. Legal alone sent back three rounds of feedback, which pushed the ship date from March 3 to March 24. I still think the delay was worth it — activation is up 11% in the first two weeks."
Nothing was invented. The rewrite just commits to claims, names numbers, and lets the sentences breathe. That's the whole method.
How can I test if my writing sounds AI-generated?
Run the loop the accusers run — before they run it:
- Score the text with a detector. Note the overall number, but care more about which paragraphs score highest — you can check if your text sounds AI in under a minute.
- Diagnose those paragraphs against the nine fixes. It's almost always rhythm, connectors, or missing detail.
- Fix and re-score. Watching the number drop tells you which edits actually work for your style — most people are surprised which ones matter.
- Keep receipts. Drafts, version history, notes. If a false accusation escalates, your process is stronger evidence than any score. (OpenAI shut down its own AI-text classifier because its accuracy couldn't be defended — cite that if you need to.)
Two or three rounds of this loop and the habits start sticking. You'll catch "furthermore" before your fingers finish typing it.
What about drafts you polished with AI?
Plenty of flagged writers aren't pure victims of statistics — they wrote the ideas, then let ChatGPT smooth the prose, and the smoothing installed the dialect. Nothing wrong with the workflow; just don't ship the smooth version raw. Run the same loop: score it, humanize it in your tone, add back the specifics the model sanded off. The nine fixes apply identically whether the predictability came from your training or the model's.
The highest-stakes version of this is job applications, where recruiters now assume AI by default — see our guide on how to make a cover letter not sound like AI. And for the complete picture across every use case, the pillar on how to not sound like AI covers the seven tells with before/after examples.