I read manuscripts for a living, and I can now spot a machine-drafted chapter in about a paragraph. AI is good at producing content and bad at the thing that makes content worth reading, so it leans on the same small set of impressive-sounding phrases over and over. Words that once carried weight are now the tell. Who decided that sounding professional meant saying nothing? Readers dismiss anything that feels overly polished or robotic. The skill worth building is catching these before a reader does, and swapping in language a person would actually say out loud.
The tell is almost never a single word; it’s the clustering, several of these abstractions stacked together until the whole passage reads like a machine reaching for professional-sounding filler.
Think of these phrases like packing peanuts. They fill space. They look like content. They protect you from the harder work of saying something specific, which is the whole reason they are there. Nobody wants them, and the moment a reader digs in expecting substance, all they find is Styrofoam. The fix throughout this list is the same: replace the packing peanuts with the real thing. Every vague phrase below has a concrete alternative, and the concrete version is always shorter, clearer, and unmistakably human.
What are the 40 phrases that make writing look AI-generated?
You’ve seen every one of these, and each looks harmless on its own. Stacked three to a paragraph they’re a signature, and I cut them out of client manuscripts every week. Here’s what to cut and what to use in its place:
| The flagged phrase | Why it’s flagged | Use instead |
|---|---|---|
| “Seamlessly integrated” | Overused in tech articles | “Works together smoothly,” or describe how the integration functions |
| “In today’s fast-paced world” | Cliché and vague | Cut it entirely; start with your actual point |
| “Cutting-edge technology” | Robotic, no personality | Name the specific technology and what it does |
| “Let’s dive in” | AI loves it in intros | “Here’s what you need to know,” or skip the transition |
| “Transformative experience” | Corporate jargon | Describe what changed and how |
| “Firstly, secondly, lastly” | Overly formal, no flow | Natural transitions, or just number your points |
| “At the forefront” | Empty and overused | Explain what specifically puts them ahead |
| “Game-changer” | Marketing fluff | Describe the actual impact with specifics |
| “Unlock your potential” | Sounds like a slogan | Be specific about the skill or outcome |
| “Unveil, unlock, unleash” | Bots love these “UN-” words | “Share,” “discover,” “release,” or a verb for the real action |
| “Best-in-class” | No real meaning | “Rated highest for customer service” beats it every time |
| “Leveraging data” | Technical and sterile | “Using data to find patterns,” or what the data revealed |
| “Holistic approach” | Overused in wellness/marketing | “Looking at the full picture,” or the specific elements |
| “Utilizing resources” | Too formal | “Using” works fine; the longer word adds nothing |
| “Taking it to the next level” | Self-help and salesy | Describe the specific improvement |
| “Streamline your workflow” | Buzzword, no specificity | “Cut three steps from your process” |
| “Paradigm shift” | Jargon, often misused | Describe what changed and why it matters |
| “Disruptive innovation” | Buzzword | Explain what the innovation does and who it affects |
| “World-class” | Vague, unquantifiable | Give specific metrics or awards |
| “Optimize performance” | Technical and broad | “Speed up load times by 40%” |
| “Maximize your potential” | Generic self-help | Identify the specific skill or area |
| “Achieve your goals” | Canned motivation | Name the goal: “Land your first client” |
| “Strategic alignment” | Corporate jargon | “Getting everyone working toward the same target” |
| “Scalable solution” | Overused in startups | “Works whether you have 10 users or 10,000” |
| “Enhance efficiency” | No personality | Describe the time or money saved |
| “Thought leadership” | Business buzzword | “Expert perspective,” or show it through the content |
| “Future-proof” | Marketing speak | Explain what makes it adaptable to coming changes |
| “Unprecedented growth” | Exaggerated and vague | Give the numbers: “Revenue jumped 340% in six months” |
| “Key takeaways” | Overused in summaries | “What matters most,” or “The short version” |
| “Invaluable asset” | Meaningless hyperbole | Describe specifically what value they bring |
| “Unique value proposition” | Often misunderstood jargon | “What makes you different,” then explain it |
| “Push the envelope” | Cliché and vague | Describe the specific boundary being tested |
| “Customer-centric” | Marketing speak | Show it through specific policies or actions |
| “Win-win situation” | Overused and trite | Explain who benefits and how |
| “Out-of-the-box thinking” | Brainstorming cliché | Describe the unconventional approach taken |
| “Leverage synergies” | No clear meaning | “Combine strengths,” and say whose |
| “Agile mindset” | Business-transformation buzzword | “Willing to change direction when needed” |
| “Results-driven” | Empty corporate speak | Show the results; numbers beat adjectives |
| “Break down silos” | Business jargon | “Get departments talking to each other” |
| “Seize the opportunity” | Cliché call to action | Name the specific opportunity and the action |
Where does the vocabulary problem sit in the larger picture?
At the surface. Every phrase in the table above is a word-level problem, and word-level is the layer that’s easiest to see and easiest to fix. Swap the phrase, move on.
There are four layers below it. Sentences that all run the same shape. Paragraphs that arrive at the same rhythm. Scenes that resolve rather than complicate. And underneath all of it, the spine, where a machine picks the safe structure over the interesting one and no amount of editing reaches the decision.
A passage can contain none of these forty phrases and still read as machine-written, because the tells go deeper than vocabulary. I worked through all five layers in The Five Layers of AI Writing Tells, starting with the same territory this article covers in the word-level piece and descending to the spine, which is where the real problem lives.
What is the pattern behind AI writing phrases?
Notice what they share: they’re vague, they sound impressive without saying anything specific, and they could apply to almost any situation. That’s why AI defaults to them. A language model has no experiences to draw from, so it reaches for language that sounds professional without committing to a detail. The result glides along saying nothing.
The fix is getting specific instead of swapping one empty phrase for another. Instead of calling something a transformative experience, say what transformed. Instead of claiming unprecedented growth, give the numbers. Specificity is the single thing that most reliably separates human writing from bot output, because specifics come from lived experience and machines don’t have any.
The challenge of being mistaken for AI isn’t going away, but awareness of these overused phrases, paired with concrete replacements, keeps your writing authentically yours. Real writers bring shading, emotion, and personality, and your voice is what separates you from the bots. The goal isn’t to sound less polished. It’s to sound like a specific human who was there.
This connects to the wider problem of writing that reads as soulless, the fixes when your book sounds like AI, and knowing what AI is good at. The AI writing hub covers the rest, and if you want a book that uses AI the right way while the voice stays yours, that’s the work I do. Cut the packing peanuts. Ship the real thing.