Blog · Can People Tell I'm Writing with AI? Usually Yes, and Here's the Real Reason Why
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The tell isn't the tool. AI writing exposes when an idea wasn't fully worked out. Here's why AI-assisted writing sounds generic and how to make it sound like you.
A client sent me a keynote script last month and asked for my feedback. Every sentence was grammatically correct. Nothing was misspelled. Nothing was factually wrong. And yet the presentation as a whole felt wrong. She had used an AI tool to create the whole thing, and she wanted to know if it worked.
The honest answer: probably yes, but not for the reason she was worried about. Her audience wouldn't spot a specific "AI tell." They'd just find the writing forgettable, and they wouldn't be able to name why.
If you've been drafting something important with AI and you're wondering whether it shows, this piece is for you. The tell isn't the tool. It's that AI writing exposes when the underlying idea wasn't fully worked out, because the tool can only format language around what you give it. A half-formed idea comes back as polished, empty prose. A fully-formed one can come back sounding like you.
AI writing sounds robotic because it averages. These tools predict the most likely next words based on enormous amounts of existing text. That's a strength for grammar and a weakness for voice. When you aim for the most probable phrasing every time, AI writing inevitably sounds like…other AI writing.
There are a handful of tells that change over time as LLMs become more advanced. A handful of transition words doing heavy lifting over and over. Phrasing that could describe anyone's project, anyone's company, anyone's Tuesday. And the big one: examples that gesture at the general instead of showing the specific. "This approach drove meaningful results" is not an example. The time your pilot program saved one nurse forty minutes a shift is an example. AI reaches for the first kind because it doesn't know your second kind.
AI is good at formatting language. It's not good at having a specific idea.
It can tidy grammar, suggest a structure when you're staring at a blank page, offer ten ways to phrase a transition you were stuck on, and turn a messy voice memo into a readable first pass. For a lot of professionals writing in a second language, that assistance removes significant friction.
What it can't do is know why your recommendation matters to the specific room you're walking into, because that reasoning lives in your head and your experience, not in the training data. When you ask it to write something without giving it your actual thinking, it fills the gap the only way it can, with plausible, generic filler that sounds like a presentation without being yours.
This is the distinction that matters. If your point is clear in your own mind, AI can help you give it words. If your point is fuzzy, no amount of polish fixes it, because you can't format your way to an idea you haven't had yet. Clean sentences on a soft point just make the softness harder to spot until you're already at the podium.
When someone tells me their AI-drafted content sounds generic, I usually ask what they typed to get it. The answer is almost always something like "write a presentation about our new onboarding process."
A vague request forces the tool to serve a broad, imaginary audience. It has no idea who's in your room, what they already believe, what they're skeptical about, or what you actually want them to do differently on Monday. So it writes for everyone, and writing for everyone means writing for no one in particular. You get the average onboarding presentation. Grammatically flawless. Completely forgettable.
The fix is being precise with your ideas and intention. Asking the tool to "make it more engaging" or "sound more professional" doesn't fix the content. Try including a real example from your own experience, and defining the audience you'll be talking to.
Instead of "write about our onboarding process," try telling it: "my audience is regional managers who think the current onboarding is fine, my point is that new hires quit in the first ninety days because week one overwhelms them, and here is the specific story of the hire we lost in March and what we changed." Now the tool has a spine to build on. It still isn't doing your thinking. It's arranging language around the thinking you already have.
None of these involve a magic prompt that removes the robot. The robot goes away when your ideas show up.
Do your thinking before you open the tool, not after. Say your point out loud to yourself in one plain sentence. If you can't, that's your real assignment, and no draft will rescue you from it. A talk built on a clear point survives nerves, questions, and a broken slide deck. A talk built on borrowed phrasing collapses the moment someone asks you something off-script.
Read every draft out loud. Your mouth catches what your eye forgives. Sentences that looked smooth on screen will trip you, flatten you, or make you sound like a brochure. Where you stumble or go monotone, the writing isn't yours yet.
Hunt for the generic and replace it with concrete details. Every time you find a sentence that sounds abstract, swap in the specific version only you can tell. Real numbers from your own work. How the actual problem looked and sounded. The moment it went wrong. Specificity is what makes writing sound human, because specificity is the one thing the tool cannot invent for you.
Sometimes, but not usually the way people worry about. Readers rarely spot a specific "AI tell." They just find the writing forgettable, generic, or oddly even in rhythm, without being able to name why. If your underlying idea is clear and specific, AI-assisted writing can sound like you. If the idea is fuzzy, AI writing tends to expose it.
Not necessarily. The tool becomes a problem when it substitutes for your thinking, not when it assists it. Authenticity was never about whether a machine touched the words. It's about whether the idea underneath is actually yours, worked out well enough that you could defend when asked about it.
Give it three things: a clear point you're trying to make, one specific example from your own experience, and a defined audience. Vague prompts produce generic output because the tool has to fill in the gaps.
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