10 AI writing patterns that make your copy sound like everyone else's

TL;DR:

• AI-generated copy often sounds polished and generic because it follows predictable patterns in wording, structure, and framing.
• These include buzzword-heavy language, repetitive sentence rhythms, and vague, overextended claims.
• While AI improves efficiency, unedited output weakens clarity, differentiation, and conversion.
• The fix isn’t surface-level editing but deliberate rewriting based on audience, intent, and specificity.
• Strong source text is especially critical when content is translated, as vague AI copy becomes even flatter across languages.

“In today’s rapidly evolving landscape, businesses must leverage cutting-edge AI solutions to navigate the complexities of modern communication. Teams are under pressure. Deadlines are tightening. And the touchpoints? They keep multiplying. As organisations strive to deliver impactful content at scale, the intersection of innovation and authenticity becomes increasingly critical. By harnessing the power of advanced language models, forward-thinking teams can unlock new efficiencies while driving meaningful engagement across every touchpoint.”

You felt it, didn’t you? The sentences flow. The grammar holds. But something feels off, disconnected.

Have you started noticing this in your own content? This article will show you exactly what to look out for when it comes to AI writing patterns and what to do about it.

What is AI slop, and what does it cost you?

You’ve seen it before. A LinkedIn post that opens with “In today’s rapidly evolving landscape.” A product page promising to “leverage cutting-edge solutions to drive meaningful impact.” A landing page that could belong to any business.

Those AI writing patterns are often called “AI slop”: content that is technically correct but lacks originality and impact.

The problem isn’t AI itself. AI-assisted writing is already standard practice across marketing teams, and for good reason – the efficiency gains are real. The problem is that unedited AI output carries a signature. It defaults to the same structures and phrases, regardless of the brand or target audience. When these AI writing patterns stack up, the unedited output feels artificial. And readers feel it, even if they can’t name it.

That’s where click-through rates and conversion can suffer. Not because the text was AI-written, but because it reads like it. Used well, AI can speed up production; used lazily, it can flatten the persuasive impact of your copy. So, for brands competing on expertise and niche authority, this problem isn’t simply aesthetic. A landing page filled with generic AI content won’t exactly help your brand stand out.

But there’s good news, too. Once you know what to look for, these patterns become much easier to spot and edit out.

A practical guide to identify AI writing patterns

AI writing patterns tend to show up on all levels of the text: in the vocabulary, sentence structures, and the way ideas are framed. The overview below breaks these patterns into three levels: lexical (word choice), syntactic (sentence structure), and semantic (meaning and framing).

These patterns don’t only apply to text generated in English. The underlying structural issues are not language-specific. So, regardless of whether you work with English, French, or any other language, you will notice these patterns popping up in your AI-generated copy.

Level	Pattern	What it is	Why it feels like “AI slop”	Short example
Lexical	Inflated clichés and buzz-phrases	Overused corporate/tech vocabulary that signals importance without adding meaning	Sounds impressive but vague; interchangeable across contexts	We leverage robust solutions to navigate the complex landscape.
Syntactic	Monotonous sentence structure	Repetitive flow (statement → statement → rhetorical question → answer)	Predictable rhythm; feels templated rather than authored	AI is evolving fast. Teams are under pressure. What does this mean? It means change.
	Em dash	Overuse of the em dash to create the appearance of spontaneous prose	Mimics the rhythm of a confident writer but becomes a tic when used in nearly every sentence	The results speak for themselves – as they should. Because it isn’t just a tool – it’s a shift.
	Fronted focus	Leading with a dramatic fragment or single-word question for emphasis	As AI becomes the backbone of modern marketing, we help brands navigate uncharted waters.	The result? Burnout.
	Rule of three	Triplets of often abstract nouns or verbs	Creates rhythm but often replaces depth with symmetry	It enhances quality, increases speed, and drives impact.
	It’s not (just) X, it’s Y contrast	Binary reframing structure	Feels persuasive but formulaic; oversimplifies complexity	It’s not just automation, it’s transformation.
	Less like X, more like Y	Comparative metaphor formula	Signals insight without real explanation	It feels less like a tool, and more like a partner.
	As X happens, Y does Z	Artificial punchiness; stylised LinkedIn cadence	Generic cause-effect framing	As AI becomes the backbone of modern marketing, we help brands chart through uncharted waters.
Semantic	False ranges	Macro-trend setup leading to predictable consequences	Implies breadth without specifics	From strategy to execution, we deliver excellence.
Semantic	Abundant and contrived metaphors	Stacked metaphors, often mixing domains	It feels less like a tool and more like a partner.	As AI graduates from buzzword to bedrock, we build the runway for the future.

If you spotted more than three of these AI writing patterns in the last piece of copy you published, you’re not alone. This chapter is meant to help you recognise those patterns quickly and make more deliberate editing choices. If you want a practical guide that will help you fix them in your own writing, you can download it at the end of the article.

Post-editing AI copy is a skill, not a spell-check

There’s a tendency to treat AI output as a first draft that just needs a quick tidy. Fix the obvious clichés, break up a few long sentences, and you’re good to go. But that approach produces copy that is just slightly less generic. This is exactly why a human layer is still critical, even in AI-heavy workflows, as explored in our blog on why you still need a human editor for AI-generated content.

The AI writing patterns in this briefing aren’t surface errors; they’re structural defaults. Editing them out requires the same judgment that goes into writing good copy from scratch: knowing who the reader is, what they need to believe, and which specific claim will move them. Recognising a cliché is straightforward once you know what to look for. But replacing it with something a procurement director in Basel or a marketing lead in Seoul will actually respond to, that’s a different skill entirely, and it doesn’t come from running a draft through another tool. Developing that level of judgment is increasingly what separates replaceable output from genuinely valuable work, a theme explored further in becoming irreplaceable in the age of AI.

Another dimension of this problem that gets consistently underestimated is what happens when AI-generated copy gets translated. Machine translation has no way to compensate for vague source text. The vagueness transfers, and in many languages, the corporate register becomes even more stilted because the original phrasing had no idiomatic root to begin with. As a result, international audiences receive copy that is culturally flat. In markets where brand trust is built on relationship and specificity, that flatness is expensive. Fixing it starts with the source text.

Most marketing teams are using AI to produce more, which means the editing burden grows in proportion to the efficiency gains. The bottleneck shifts from writing to judgment. And judgment, unlike output, doesn’t scale automatically.

That’s where specialist post-editing comes in – not to replace your team’s instincts, but to apply a trained copywriting eye at the point in the workflow where generic output turns into copy worth publishing (and where post-editing delivers the most bang for your buck), in any language, in any market.

Your free AI writing guide

To help you get started, we’ve put together a practical guide covering all ten patterns, with an editing move for each one. It’s enough to sharpen your eye and improve what’s in front of you. When the volume grows beyond what a checklist can handle, or when that copy needs to work in five languages – that’s when you call SwissGlobal.