As a link building agency, we deal every day with text that’s either written entirely by humans, partly created with AI, or generated completely by tools. And just as often, we end up in conversations about the same question: “Will Google penalize this?” or “Can you guarantee this isn’t AI text?” – in short: the uncertainty runs deep.
Naturally, we keep a close eye on how AI tools are evolving. And yes, we’ve tested plenty of them – both generators and detection software. What stands out most: the AI detection tools are often anything but mature. Sometimes a tool sounds the alarm immediately on a text written entirely by hand; other times it fails to flag obvious AI content at all. Reliability? Not a chance. And the common assumptions about how to reliably spot AI text rarely hold up in practice.
How reliable are AI text detection tools, really?
By now there are tons of tools that claim they can tell whether a text was written by a machine or not. In theory that sounds great – in practice it’s more of a guessing game. We tried out many of these tools, using the same texts from different sources. The result? Wildly different verdicts on one and the same text.
One tool claims: “This text is 98% AI.” The next says: “More likely human.” And that’s not all – even within one and the same tool the results can swing dramatically. A text gets flagged as “clearly AI” today, and tomorrow the tool suddenly shows only a 30% probability. Small changes in wording, a moved paragraph, or a different heading are often enough to get completely different assessments. Some tools flag simple informational text as suspicious, while others let fully automated AI content sail right through. Reliability? That looks different.
Let’s just take a look at the supposedly objective criteria that some of these tools apply – for example Originality.ai, which is at least fairly transparent about its benchmarks. What it counts as a sign of AI, however, leaves anyone who works professionally with text scratching their head.
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“Avoiding software like Grammarly, ChatGPT, Quillbot, Microsoft Word Editor, or other tools”
Yes, you read that right: simply using Microsoft Word or a spell-checker can supposedly be an indication that your text isn’t “human” enough. In plain terms: even if you just write in Word, the odds go up that your text gets classified as AI.
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“Avoiding formulaic content. (intros, conclusions, recipes, works cited pages)”
Introductions, conclusions, source citations – in other words, all the things that make up a structured text – are supposed to be suspicious? Seriously?
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“Short content”
Short texts? Get flagged as AI faster. No matter how sensible, clear, or well written they are. Sheer length gets a say – for whatever reason.
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“Consistent paragraph length”
And then there’s the classic: paragraphs of equal length. What looks like structure to the human eye and helps you read is supposedly a warning sign. Set a break too regularly because it’s easier to follow, and according to the tool you write “too perfectly.” Sounds absurd – and it is.
These examples show pretty clearly how arbitrary many of the criteria in these tools actually are. Instead of real analysis, many work with vague patterns that do little more than blanket-suspect anything “too smooth” or “too structured.”
The takeaway? Trust your own judgment over a percentage readout. Good content stays good content, even when it’s written in Word or has a proper conclusion.
Why are expert texts suddenly considered suspicious?
What especially struck us with our own texts: the more professionally a text is written – with clear structure, precise language, and a thought-through outline – the more likely the tool sounds the alarm. Translated: the better you write, the greater the chance your text gets classified as AI-generated.
This mainly affects expert texts. When content is phrased in a way that’s factual, neutral, and to the point rather than loose and chatty, that alone seems to strike many tools as suspicious. Why? Because AI systems handle exactly this style well too – sober, informative, without a personal touch. And the very thing readers appreciate in this case is what throws the tools off.
So a well-crafted, high-quality text with considered phrasing and professional depth gets rated as “too smooth,” while a clunky comment with half-formed thoughts and a few spelling mistakes passes as “clearly human.” Anyone who works professionally is suddenly suspected of writing with AI – not because of the content, but because of the quality.
Absurd, but that’s exactly what happens. And it shows once again how distorted these tools’ benchmarks really are. Instead of content, depth, or clarity, all that often counts is: how random does the text feel?
Which phrasings are typical of AI, and how reliable is that?
To be fair: yes, there are certain phrases that AI tools recognize fairly reliably – simply because language models repeat them constantly. Phrasings like “In a world where…”, “This raises the question…” or “In conclusion, it can be said…” do in fact show up very frequently in AI texts. Uniform sentence rhythms, redundant statements, and extremely generic phrasing also rightly count as hints of generated content.
You have to give the scanners that much – such patterns are recognizable, and if you work a lot with AI content, you’ll start spotting them yourself at some point. But: that alone isn’t enough to say with certainty whether a text came from a machine or not.
Because human authors use these stock phrases too. Partly unconsciously, because they’re common in many types of writing. Partly quite deliberately, as a stylistic device, to structure a piece, or simply out of habit. Anyone who writes regularly automatically develops a certain language pattern. And that’s exactly what some tools then wrongly rate as “too generic” or “too AI-typical.” Which means: such phrasings can be an indication – but only one of many. That’s not truly reliable. And certainly not proof.
How can you spot genuine AI texts anyway?
If you really want to find out whether a text came from a machine, tools will only get you so far. Far more helpful are a few very practical questions:
- Does the text sound oddly smooth or empty?
- Is there no clear through-line?
- Are there contradictions, repetitions, or statements that say nothing?
- Does everything feel a bit “too generic”?
Things like this can be hints. But even those are still not proof. Bad human texts have all of these traits too. And good AI texts can avoid all of it – especially when they’ve been reworked afterward or enriched with extra information.
Do you need to fear Google penalties for AI text?
Short and straight up front: no. The widespread worry that Google automatically penalizes all AI text or ranks it lower is persistent, but it doesn’t hold up in practice. Google has communicated clearly and repeatedly: what matters is not who wrote the text, but what it delivers. Quality, relevance, and value for readers take priority. Regardless of whether the text was created by a human or with the help of an AI tool.
Of course, Google’s goal is to filter out spam and low-quality content – but that applies to hand-written texts too, if they’re weak, superficial, or manipulative in substance. A well-researched, cleanly written piece with genuine added value, by contrast, has nothing to fear. Whether the first draft came from an AI or not makes no difference, as long as the end result delivers.
Google itself has long been going all in on AI. In the Search Generative Experience (SGE), AI-generated answers are served directly. Its own products like Bard or Gemini are built entirely on artificial intelligence. It would be pretty contradictory for the company to lean on AI on one hand and penalize its use in website content on the other.
The reality is: Google evaluates content by impact and quality, not by origin. Anyone who works cleanly, covers relevant topics, and writes for real readers doesn’t need to worry about AI labels or possible penalties – neither now nor in the foreseeable future.
What’s the best strategy for dealing with AI content?
Instead of driving yourself crazy or questioning the origin of every text and optimizing it for hours to please useless tools, it pays off to take a more relaxed view of the topic. Yes, it’s important to look closely at automatically created content – especially when search visibility, credibility, or client projects are on the line. But that doesn’t mean AI is fundamentally a problem or automatically produces bad text.
Far more crucial is the question: Does the text deliver genuine added value? Is it clearly phrased, relevant in substance, well structured, and helpful for the target audience? If that’s the case, in the end it makes no difference whether the first version came from an AI or not. More and more professional workflows rely on a combination of human and technical support anyway – whether for brainstorming, the rough draft, or the polish.
So if you work with AI, do it deliberately and with purpose, but don’t skip it out of fear of “detection” or supposed Google penalties. What counts is the quality of the end result. And that still can’t be judged automatically – only by people who know what makes content good.