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Many marketers and writers have started creating their own list of “AI words” to avoid. Such keywords raise immediate suspicion because they appear too often in AI-generated writing. For example:
This list can also be useful when writing video scripts with AI. Whether you are working on a best explainer video, ad video, corporate video, YouTube video, or product demo video. Removing these overused words can make the script sound less AI-generated and more natural when spoken.
But avoiding certain words is not enough. Sentence formation matters just as much.
There are certain patterns that are repeatedly produced by large language models (LLMs). You have seen them used by ChatGPT, Claude, Gemini, and other AI Writing Tools. For example:
Traditional tactics like forced keyword stuffing look unnatural. On top of that, overused AI words make content feel generic and robotic. You might trick readers once with low-effort content, but they remember who wastes their time. Engagement drops, and search engines read that as a signal your content is low value and not worth top rankings.
Yes, and No. Even with explicit instructions and long keyword lists, AI will still miss things or follow rules inconsistently. That’s where human review matters. When you know the patterns to watch for, your judgment flags issues immediately. You can spot when something feels generic, robotic, or low effort.
We’ve seen cases where content written without any AI is flagged as 100% AI-generated, and vice versa. People know the rules of this game and can often use AI humanizing tools to easily game AI content detectors to make low-effort content appear human-written. Passing a detector does not mean the content is good. Readers still notice generic language, shallow thinking, and repeated patterns.
To help you write more systematically, I have curated a list of blacklisted words (updated Aug 2026). I have also added repetitive AI phrases and sentence patterns that AI tools tend to overuse.
We help B2B, SaaS and AI product teams ship on-brand creatives without fresh hiring, for launches, campaigns and sales.
These words and phrases are overused in AI-assisted writing. That is why many readers subconsciously associate them with AI-written fluff, aka, “AI-slop. Here is the list of AI-words to avoid:
Additional Instructions: Avoid using these words in any variation – singular or plural, tense changes, hyphenated forms, or suffixes like -er, -ing, -ity, -ful, etc.
Copy this AI keyword list along with the additional instructions to retrain your prompt. Whatever you do, avoid “AI workslop” in B2B copywriting. According to research by Harvard Business Review, “workslop” refers to AI generated work content that masquerades as good work, but lacks the substance to meaningfully advance a given task.
When you use low-effort AI content, readers know you didn’t care enough to write something real. You waste their time. They start believing you’ll take shortcuts when no one is watching. That’s not good for SaaS Content Marketing. This problem becomes systemic when the same content writing strategy is used across blogs, social posts, ad copy, landing pages, and documentation.
These sentence patterns and phrase structures show up frequently in AI-written content. When teams outsource content writing, these sentence patterns often show up unless writers are trained on what to avoid and editors actively watch for repetition. Educate your writing team.
Avoid using these patterns, or any close variation, especially in B2B and opinion-led content:
These are slightly trickier to catch, so let’s understand these patterns with a few examples:
| AI Sentence Patterns | Examples |
|---|---|
| It’s not about X, it’s about Y. | It’s not about posting more. It’s about posting smarter. |
| It’s not just X. It’s Y. | It’s not just speed. It’s consistency. |
| That’s not X, that’s Y. | That’s not marketing. That’s noise. |
| Not because X. But because Y. | Not because it’s easy. But because it works. |
| Not by doing X, but by doing Y. | Not by selling harder, but by educating. |
| No X. No Y. Just Z. | No theory. No fluff. Just execution. |
| X. Y. Z. | Focused. Aligned. Measurable. |
| And the X? Y. | And the fix? Better briefs. |
| The result? The outcome. | The result? Higher engagement. |
| Two word phrases x 2-3 times | Fewer questions. Less confusion. Better engagement. |
Use this awareness to make AI stop writing like a robot. These dramatic marketing clichés are the new cringe. Spotting AI-generated content will get easier when you read this blog again. Take a printout for reference.
You can also train AI around a specific brand voice instead of fixing the same patterns after every draft. For example, we built an AI copywriting workflow for Truckstop, trained to write more like a real truck driver: casual, knowledgeable, and authentic.
Their content team used these AI-generated drafts as a starting point, then improvised and added their own expertise before publishing blogs and social posts.
Read the Truckstop case study to see how we supported their broader marketing strategy across video, design, and an AI writing system.
My list of AI words grows daily. So I suggest you revisit this page after 4-6 weeks to stay up to date with the revised list. If you’re writing for LLM rankings, it will always pay to keep this list updated.
These phrases are common in enterprise decks, consultant reports, and internal strategy docs. In B2B marketing writing, they flatten your point by sounding generic and institutional.
Avoid using these unless you are quoting internal documentation or writing for formal compliance audiences:
I’m sure there are more, but you get the idea. Real copywriting means killing every AI-generated content pattern in your work. Write like you talk. Use specifics. Sound like an actual human being.
Even well-read, highly aware writers miss them too and, despite following keyword ban lists, still slip into this kind of AI garbage:
We review these patterns regularly while drafting scripts for product demos, explainer videos, and launch videos for B2B SaaS companies. browse our work.
Here are 12 additional tips to avoid AI detection in writing (with examples).
Words with obvious AI origins have an uncanny quality: technically correct, but emotionally vacant. Often rhetorical. Often stating the obvious. Sometimes hallucinated. That starts to sound like a typical politician’s speech.
Jokes apart, building an AI word list helped me avoid one of the most common B2B copywriting mistakes — driving away well-read, informed readers. You’re reading this because I used AI for the low-value parts of the work, so I could spend more time articulating real experience and knowledge.
AI detection tools and AI checker apps analyze statistical patterns in text, not meaning or intent. They look at sentence structure, predictability, word frequency, and rhythm compared to known AI outputs. They do not understand quality, usefulness, or experience. That’s why they often get it wrong.
AI is trained on large volumes of existing content and optimizes for what sounds broadly acceptable. Overused words and phrases appear frequently in its training data, so the model defaults to them. They are safe, generic, and statistically likely, even when they add little meaning.
Yes, but only with human judgment. AI can help draft and speed up low-value tasks, but humans must spot generic phrasing, remove templated patterns, and add real context. Human review is what turns fluent output into writing that feels intentional, specific, and earned.
In cold outreach campaigns, overused AI phrases like “I hope this helps” or “Feel free to reach out” signal fake friendliness. Receivers read them as mass emails, which leads to messages being ignored or, worse, marked as spam. Cold outreach messages need to sound specific and written for one person.
We help B2B, SaaS and AI product teams ship on-brand creatives without fresh hiring, for launches, campaigns and sales.
Rishabh Pugalia, CMO/Co-founder, ContentBeta. He advises B2B SaaS companies on brand visibility & product adoption through video & design. He believes in AI-assisted, human-in-the-loop workflows for scaling marketing ops.
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