AI content and SEO: Google isn’t looking for AI, it’s looking for content that serves no purpose

A blog post, a product page, a newsletter, a page optimized for a keyword: all of these used to take hours to produce. Today, ChatGPT, Claude or Gemini deliver them in seconds. Many companies are tempted to publish more, often much more. And almost all of them ask the same question: can Google detect AI-generated text, and does it penalize it?

The answer is no. But the question that matters is a different one: does your content say something that can’t already be found everywhere else on the web?

What Google actually penalizes

One misconception persists. Google has never said it demotes content because it was written with AI. As early as February 2023, the search engine made its position clear: what it evaluates is the quality of the content, not how it was produced.

In March 2024, Google added a spam policy on “scaled content abuse”: producing large numbers of pages mainly to manipulate rankings rather than to help users. The policy says it applies regardless of how the content is created, whether through automation, human writing or a mix of both.

The guidelines for Google’s quality raters, updated in January 2025, point the same way. They call for the lowest rating for pages whose main content is auto-generated with little effort, little originality and little added value. The target is automation without value, not the tool. A mediocre human text is still mediocre, and a solid text written with AI assistance is still solid. The problem starts when AI is used only to churn out volume, with no editorial thinking at all.

The real risk: becoming interchangeable

Ask five assistants the same question: “What are the benefits of a content strategy for a business?” You’ll get five clean, well-structured and nearly identical answers: visibility, brand awareness, traffic, engagement, trust, conversion. None of it is wrong. But none of it is useful either, because thousands of pages already say the same thing.

Above all, generative AI has changed one thing: good writing is no longer scarce. A flawless text, broken up with H2s and bullet points and built around a keyword, is no longer a skill. It’s the starting point. The challenge is no longer producing content. It’s producing content worth reading.

The end of the volume race

For a long time, cost held content strategies back. Fifty articles meant hundreds of hours of work. Today a company can generate them in a day. But if everyone can do it, why would Google rank your fifty articles above everyone else’s?

Google says that mass-producing unoriginal content with no added value can lower a site’s visibility, or even get some pages removed from the index. Publishing more and more quickly hits its limits. The question is no longer how many articles you can publish, but how many topics you actually have something to say about.

Unique doesn’t mean original

This is another common confusion. A text can pass every plagiarism check without adding anything new. Rewording ten competing articles gives you a summary, not added value.

Originality comes from the information you bring: an internal figure nobody else has, customer feedback, a well-argued position, a real case, the view of an in-house expert, a comparison no one had made, a chart built from public data, a problem encountered in the field. Or simply a clearer answer than anyone else’s to a complicated question. The raw material of content is no longer text. It’s information.

AI should speed up the work, not replace the thinking

Used well, AI is a very useful tool for an editorial team. It helps structure a topic, analyze documentation, explore angles, spot related questions, rephrase a difficult passage or compare several article outlines.

But asking it for “a 1,500-word SEO article on group income protection insurance” and publishing it as is skips the part of the job that now has the most value: the thinking. AI is very good at producing a plausible answer. On its own, it doesn’t know why your company has the standing to speak on the subject.

AI detectors are looking in the wrong place

Generative AI brought AI detectors with it, along with their scores like “83% human” or “96% AI.” For a long time, these numbers looked scientific without really being so. OpenAI even withdrew its own detector in 2023 because it wasn’t accurate enough.

Pangram.com changed the game. Launched in Brooklyn in 2023 by Max Spero and Bradley Emi, the tool is now considered one of the most reliable on the market. In 2025, a University of Chicago study found that it clearly outperformed its competitors and produced almost no false positives on long texts. That same year, researchers from the University of Maryland, UMass Amherst and Microsoft found that it matched a panel of human evaluators experienced with language models. Pangram also drew attention by reporting that about 21% of peer reviews for papers submitted to the ICLR 2026 conference had been generated by AI. It still has limits: it is less reliable on short texts, on the newest models and on content that is only partly AI-assisted.

But a reliable detector is still just a detector. Pangram can tell you, with good probability, that a text was written by a machine. It will never tell you whether that text is useful. And that is the only question Google cares about.

Google isn’t trying to find out whether a human typed the sentences. It’s trying to filter out content designed to manipulate its results and pages mass-produced with nothing in them for the reader. Its policies do list generative AI among the tools that can be used to produce this kind of page, but what gets penalized is the lack of value, not where the text came from.

So reworking an article to move it from “70% human” to “95% human” is not an SEO strategy. It can even backfire if, to fool a piece of software, you damage a text that used to be clear. An article flagged as AI but full of new information is more likely to rank well than a “100% human” text that repeats what ten competitors already say.

SEO in an age of information scarcity

For years, SEO rested on a simple idea: find a keyword, create the page and answer better than the competition. AI has removed much of that scarcity. Producing 1,500 words is no longer worth much. What matters is what those words contain.

Paradoxically, this gives companies with real expertise a clearer advantage than before. Their sales teams hear customer objections every week. Their consultants solve concrete problems. Their customer service teams know which questions keep coming back. Their leaders see the market changing. Their internal data sometimes shows things no one has published yet.

This is the raw material of a modern content strategy. AI can then turn it into articles, interviews, studies, newsletters, videos, LinkedIn posts or sales pages. But it cannot be that raw material.

Publish less, say more

AI isn’t killing web writing. It is gradually getting rid of one way of writing for the web: producing text because an SEO tool said you needed it. Google keeps tightening its rules against content made mainly for rankings, especially when automation makes it possible to produce that content in bulk.

For brands, the takeaway is simple. The point isn’t to write as if AI didn’t exist, but to use it without becoming interchangeable. When anyone can generate an article in thirty seconds, publishing no longer sets you apart. Having something to say does.