AI writing tells in web copy: how to spot website text written by AI
Partner · Web development, SEO and GEO
You recognize website copy written by AI first by its default sentences: the ones the tool writes when nobody gave it any facts. On a home page, that means two short fragments stacked one above the other, a tagline that could fit any business and three benefits in three adjectives. On a services page, it means cards cut from the same mould. In an FAQ, it means questions nobody asks. Wikipedia, linguists and the AI companies themselves document these tells. They suggest that AI was used, but they prove nothing: a writer in a hurry produces them too. Detectors, for their part, are often wrong. For a business, the point is to make sure every sentence on its site says something true that a competitor could not sign, whether AI wrote it or not.
- AI writing tells are documented by studies published in PNAS and Science Advances, by Wikipedia and by Anthropic's and OpenAI's own guides.
- Web pages have tells of their own: paired fragments, interchangeable taglines, identical service cards, rhetorical FAQs, meta descriptions poured into the same mould.
- The tells change. Wikipedia already lists the em dash and the promotional tone as "historical" signs, because recent models are correcting them.
- Google judges the effort, originality and usefulness of the page, whatever tool wrote it.
- The risk is commercial. According to a Raptive survey, content perceived as AI-written loses almost half of the reader's trust, even when a human wrote it.
On this page
Default copy
An AI's default copy is what it writes when the prompt gives it neither facts nor a voice: sentences that fit every business in the same industry because they are about none of them in particular. These sentences are not random. They reproduce the most frequent and best-rated phrasings in the texts the model read and in the answers its raters preferred during training. That is why two sites written with the same tool, without specific facts, can say almost the same thing in almost the same words.
Why AI-written website copy all sounds the same
Our article on the design tells of Claude Code and ChatGPT Codex shows that AI, left to itself, often designs the same website. The same mechanism is at work in copy. It has even been measured more precisely, because researchers have been studying how models write since 2022.
The first cause is training. After reading enormous amounts of text, a model like ChatGPT or Claude is fine-tuned on the preferences of people who compare its answers (reinforcement learning from human feedback, often shortened to RLHF). A team of researchers showed in 2023 that this step significantly reduces the diversity of answers. In 2025, a team that includes Stanford's Christopher Manning traced part of the cause to the data itself: raters prefer text that feels familiar. The model therefore learns to write whatever most resembles what people have already read.
The second cause is flattery. Anthropic researchers showed in 2023 that humans, and the models that imitate them, sometimes prefer a flattering, well-turned answer to a correct one. On a website, that tendency produces copy that compliments the reader and the business instead of informing them.
The third cause is the prompt. "Write the home page for a renovation company" contains very little information. The model fills the gap with whatever fits every renovation company. Anthropic acknowledges this in its documentation: without direction, Claude tends toward generic outputs, the ones at the centre of what it has seen most often.
The result has been measured on humans writing with AI help. A study presented at the ICLR conference in 2024 observed a significant drop in the diversity of texts written with help from an OpenAI model. Another, published in Science Advances in 2024, showed that stories written with AI resembled each other more than stories written without it. At Cornell, in 2025, 118 participants from India and the United States wrote with AI suggestions: their writing drifted toward a Western style and grew more alike. "People start writing similarly to others," says one of the authors, Aditya Vashistha.
A tell is not a mistake. Default copy can be correct, readable and rank well. But it could describe your competitor just as well as it describes you.
Sentence-level tells
These tells show before you even read the words. They come from the shape of the sentences, and they are the ones readers who use ChatGPT regularly spot fastest.
Paired fragments
Two short groups of words, built the same way, stacked like two lines of verse: "Craftsmanship that lasts. Service that reassures." Neither has a subject or a conjugated verb. They create a sense of rhythm without asserting anything. You find them mostly in hero headlines, under photos and at the top of sections. The three-fragment version is just as common: "Simple. Fast. Effective."
Negative parallelism
"It's not just a website, it's a showcase." "More than a supplier: a partner." Wikipedia lists this construction among the most consistent signs of generated text, along with its variants "not only… but also" and "rather than." It contrasts the business with a flaw nobody accused it of.
The rule of three
Three adjectives, three benefits, three cards: "fast, reliable and accessible." Wikipedia notes that models overuse this structure, which makes a thin point look complete. On a services page, it often forces the writer to invent a third benefit when the business has two real ones.
The question followed by its answer
"The result? Satisfied customers." "Why choose us? Because…" Nobody asked the question: it exists to restart a sentence that had nothing to say.
Cascading participles
"Combining expertise and creativity, our team supports you by offering tailored solutions." A study published in PNAS in 2025 measured that instruction-tuned models use these present participial clauses two to five times more often than humans (5.3 times for GPT-4o).
The sentence that announces instead of saying
"In today's fast-paced digital world…", "In the digital age…", "Whether you're a small business or a large enterprise…". These openings delay the information by a full line. A web page visitor wants theirs right away.
The sentence that ends on attitude
"Nothing is left to chance." "We'll tell you frankly." The sentence ends on what the business thinks of itself rather than on a fact. It is the correction we make most often on the copy of our own site.
None of these tells is an error. Copywriters used them long before AI, and the fragment tagline even has its masterpieces. The difference is frequency: generated copy piles them up, while a writer saves them for the place where they land.
Tells, page by page
No study measures the tells specific to web pages: the research covers articles, scientific abstracts and press releases. What follows therefore comes from two sources. First, what Wikipedia, Google and the studies document. Second, what we observe at Falia on the sites we revise. The two overlap.
| The page | The tell | What the visitor was looking for |
|---|---|---|
| Home (hero) | A fragment tagline or an abstract promise: "Elevate your business," "Your trusted partner," "Unlock your potential" | What the business does, for whom and where |
| Services | Identical cards: an icon, a two-word heading, two lines that start with "We" | What is included, for which kind of client and the starting price |
| About | "Driven by passion," a mission and three values (integrity, excellence, innovation) with no date, name or place | Who the people are, how long they have been at it and what they have done |
| FAQ | "Why choose our company?", answers that restate the question | The questions people really ask before buying: price, timelines, service area, guarantees |
| Testimonials | Praise with no last name, no company and no project detail | A real person and a result they can check |
| Local pages | "Nestled in the heart of Laval," the same page copied for ten cities | Where the office is, which areas are served and how quickly |
| Product pages | The same three enthusiastic sentences from one product to the next | Dimensions, materials, use, care |
| Meta descriptions | The same mould on every page: "Discover our services for… Contact us today!" | A reason to click this page rather than another |
| Calls to action | "Don't hesitate to contact us," "Learn more" everywhere | What happens after the click |
| Blog posts | An introduction that announces the topic, question headings, an "In conclusion" section | The answer, in the first paragraph |
Three of these rows have solid backing. For meta descriptions, Google's documentation says identical or similar descriptions on every page of a site are not helpful. For FAQs, Google announced in August 2023 that FAQ rich results would only be shown for well-known, authoritative government and health websites: an FAQ now serves the reader, not the display in Google. For testimonials, the U.S. Federal Trade Commission adopted a rule in August 2024 that bans fake reviews and testimonials. It explicitly targets AI-generated ones. Our article on customer review rules in Canada covers the framework that applies here.
Product pages have had their public moment too. In January 2024, several outlets spotted Amazon listings whose title was a ChatGPT refusal, along the lines of "I cannot fulfill this request." That is the extreme case: nobody had read the copy.
Vocabulary and tone tells
Overused words are the best-measured tell. In July 2025, a team of researchers published an analysis of 15 million scientific abstracts in Science Advances. They found 379 style words whose frequency jumped in 2024, such as "delves," 28 times more frequent than expected. According to the authors, at least 13.5% of 2024 abstracts had been processed with a language model. Another team showed the same year that these words likely owe part of their frequency to RLHF, the stage where humans rate the answers.
The PNAS study cited above goes further: GPT-4o uses words like "camaraderie," "palpable," "tapestry" and "intricate" more than 100 times as often as humans. Business writing is not spared. A Stanford study published in February 2025 estimates that up to 24% of the text in corporate press releases and nearly 10% of small-business job postings were attributable to a model.
On websites, the same families of words keep coming back:
- Propulsion verbs: elevate, unlock, empower, transform, supercharge, support you "every step of the way."
- Abstract nouns: solutions, expertise, excellence, synergy, ecosystem, journey.
- Showroom adjectives: tailored, innovative, seamless, cutting-edge, world-class, turnkey.
- Brochure places: "in the heart of," "nestled in," "at the crossroads of." Wikipedia lists them among the markers of the models' promotional tone.
None of these words is forbidden. "Tailored" is accurate when the product really is made to measure. The tell is the word standing in for a fact: "tailored solutions" says neither what is tailored nor to what.
Tone follows vocabulary. Wikipedia flags vague attributions ("experts agree," "many studies show") and sentences that summarize what was just said. It also notes that the openly promotional tone has been receding in models since 2024: it is one of the tells the AI companies have started to correct. Marketing jargon, for its part, existed long before AI. Wikipedia's page on the subject makes the point: text that is nothing but jargon gets deleted, whether a human or a machine wrote it.
Formatting tells
For a long time, models wrote their answers with heavy formatting, because a chat interface displays it well. On a website, these habits show immediately. The English Wikipedia and the French Wikipedia help page list several of them:
- Repeated bold, up to one word per sentence.
- Lists everywhere, especially the list where every item opens with a bold lead-in followed by a colon.
- An emoji before every heading or list item: the rocket, the green check mark, the light bulb.
- Title Case In Every Heading, where sentence case would be expected.
- The em dash, often surrounded by spaces. Wikipedia now lists it among the historical signs, valid from 2022 to September 2026. An analysis by The Economist published in July 2026 found that, among the major models, only Claude still used more of them than professional writers. In November 2025, OpenAI CEO Sam Altman celebrated on X that ChatGPT finally followed the instruction not to use them.
- Mixed quotation marks and straight and curly apostrophes in the same text, when pieces come from different sources.
We use bold lead-in lists ourselves in this article. The rule is the same as for design: a trait becomes a tell when it is everywhere and nobody chose it.
Tells specific to French
A language model writes French with an accent. Researchers at EPFL in Lausanne showed in 2024 that, in the inner layers of a multilingual model, concepts are represented in a space closer to English than to other languages. It is a lead, not proof, but it matches what you read. Several tells in generated French copy come from English, which matters for any Quebec business with a French site:
- A capital letter on every word of a heading. The Office québécois de la langue française points out that French headings and subheadings take a capital on the first letter only.
- The serial comma before the last item of a list, which French does not use.
- Calques: phrases translated word for word from English, like "réaliser" in the sense of "to realize," or "opportunité" where French would say "occasion."
- Straight quotation marks and missing spaces. The OQLF calls for French guillemets and a space before the colon, semicolon, exclamation mark and question mark. Generated text that leaves them out often betrays writing that was thought out in English.
- Stock courtesy formulas: "N'hésitez pas à nous contacter," the French "Don't hesitate to contact us."
- European French on a Quebec site, or the reverse: a model picks the vocabulary most frequent in its data, which is not necessarily your customers'.
The French Wikipedia help page adds a useful caution: machine translation produces similar flaws. Clumsy copy was not necessarily written by AI. It may have been translated.
What the AI companies acknowledge
Anthropic and OpenAI do not deny these tells: their documentation describes them, along with the instructions to correct them.
Anthropic's prompting guide offers a ready-made instruction against excessive formatting. It asks Claude to write in flowing prose paragraphs and never to output a series of overly short bullet points. The same guide recommends telling the model what to do rather than what to avoid. Claude's system prompts, which Anthropic publishes, point the same way. Those of Claude Opus 4, in 2025, told it never to open an answer by saying a question was good or fascinating. Those of October 2026 ask it to avoid over-formatting with bold, headers and lists.
At OpenAI, the GPT-5 guide introduced a verbosity parameter in August 2025 that controls the length of answers. The Model Spec, the document that describes how OpenAI's models are expected to behave, has a whole section against sycophancy: the model exists to help, not to flatter. In the spring of 2025, OpenAI had already rolled back a GPT-4o update it judged too sycophantic.
This documentation has a practical consequence for a business: the tells can be partly corrected through instructions. They do not disappear, though, because they shift from one model version to the next. The em dash has receded. Other tells will take its place.
Can you prove that a text came from AI?
No: neither a careful read nor a detector can prove it with certainty. OpenAI withdrew its own text classifier in July 2023 because of its low accuracy. A Stanford study published the same year in the journal Patterns ran essays written by non-native English speakers for the TOEFL exam through seven detectors: on average, 61.22% of them were wrongly classified as AI-generated. Writers whose language is simpler, or more predictable, are the first to be wrongly accused.
Humans sometimes do better. In 2025, U.S. researchers showed that people who often use ChatGPT for writing are very good at spotting generated text: across 300 articles, the majority vote of five such readers was wrong only once. They picked up on AI vocabulary, formality and lack of originality. The tells described above are therefore exactly what gives a text away. They remain clues: Wikipedia itself advises never to rely on a single trait, or on a detector alone.
Our note on Claude's watermark explains what the invisible marks added to generated text actually allow you to conclude.
What Google thinks
Google judges the result, whatever the tool. Its position has been on record since February 2023, in a post headed "Rewarding high-quality content, however it is produced." What remains forbidden is automation used primarily to manipulate rankings.
In March 2024, Google sharpened that line with its scaled content abuse policy: pages produced in large numbers to rank rather than to help. In April 2024, it announced a 45% reduction in low-quality, unoriginal content in its results. Its Search Quality Rater Guidelines, in the September 2025 version, give the lowest rating to a page whose main content is almost entirely copied, paraphrased or AI-generated with little effort, little originality and little added value. They also state that the use of generative AI alone does not determine a page's rating.
The data points the same way. In July 2025, Ahrefs compared the share of generated text on 600,000 pages with their Google rankings: the correlation was 0.011, effectively zero. Our article Does Google penalize AI-generated content? goes through these documents one by one.
The link to the tells is direct. Default copy is unoriginal by definition: it says what any page in the same industry would say. In its guidance on generative AI content, Google also asks site owners to fact-check and review all generated content, metadata included. Google penalizes the lack of facts these tells signal, not the tells themselves.
What these tells can cost your website
The main risk comes from the visitor, more than from Google. Three recent studies measure their reaction.
- Trust drops. In 2025, Raptive surveyed 3,000 American adults. Faced with content they believed was AI-written, trust fell by 48%, perceived authenticity by 57% and emotional connection by 60%. The effect held even when a human had actually written the text: what counts is the impression.
- Suspicion is enough. In 2024, Bynder showed 2,000 people texts written by AI and by humans. Half recognized the generated text. Without knowing which was which, 56% actually preferred the AI version. But 52% said they felt less engaged by text they suspected was generated.
- The "AI" label hurts credibility. A study published in PNAS Nexus in 2024 showed that a headline labelled as AI-generated seems less credible, even when it is true or written by a human.
These figures come from the United States and the United Kingdom. They cover content in general, not services pages. They still show something useful: your visitors could judge your business on the impression your copy gives before they read what it says.
The most concrete cost lies elsewhere. Default copy does not say what sets you apart. If three businesses in your industry have the same tool write their sites without giving it facts, their pages can promise the same expertise, the same support and the same tailored solutions. The visitor comparing them then remembers only the price. The Nielsen Norman Group measured this long before AI, in 1997: promotional copy slows reading because readers have to filter out the exaggeration to find the facts. A concise, objective version of the same text was 124% more usable.
The last cost concerns visibility in AI answers. To answer, ChatGPT, Gemini or Perplexity need precise facts: a price, a timeline, a place, a name. Our article on the answer-first method shows how to structure a page so it gets cited. A page made of general formulas has nothing to offer an AI looking for an answer.
Rewriting default copy: six examples
The examples below were made up for this article. Each shows the same operation: replace the formula with the fact it was hiding.
| Where | Default copy | Rewritten copy |
|---|---|---|
| Hero headline | Craftsmanship that lasts. Service that reassures. | We have been building solid wood kitchen cabinets in Saint-Jérôme since 1998. |
| Service card | Tailored solutions to meet your needs. | We design every kitchen from measurements taken in your home, then show you the 3D plan before we cut any wood. |
| About | Driven by passion, we put excellence at the heart of everything we do. | The workshop has eight cabinetmakers. Marc and Julie founded it after fifteen years with a large manufacturer. |
| FAQ | Why choose our company? | How long does it take between measuring and installation? |
| Call to action | Don't hesitate to contact us! | Book a visit: we take the measurements in your home within two weeks. |
| Meta description | Discover our quality cabinetmaking services. Contact us today! | Solid wood kitchen cabinets made in Saint-Jérôme: a 3D plan before production and installation by our own cabinetmakers in the Laurentians. |
Each rewritten version is longer, more precise and less polished on the surface. It still has a decisive advantage: no competitor could copy it without lying. That is the simplest test we know. Replace your company's name with a competitor's: if the sentence is still true, it says nothing about you.
Avoiding the tells: seven decisions
Whether your copy is written by an agency, a freelancer, your team or AI, these seven decisions reduce default copy. They take little technical skill and a lot of facts.
Provide the facts before asking for the copy
AI cannot invent your timelines, your service area, your starting prices, your clients' names or the year you were founded. If the prompt does not contain them, it replaces them with formulas. A services page therefore starts with a list of verified facts, not with the prompt "write a services page."
Write a voice guide that includes what to avoid
A brand guide that describes your voice and names the phrasings to avoid serves everyone who writes for you. It serves AI too: placed in the project's instructions file, it is reread at every work session.
Ask for prose and complete sentences
Anthropic recommends it itself: telling the model to write in paragraphs gives better results than forbidding lists. Ask for a subject and a verb in every sentence, card headings included.
Turn recurring tells into checks
When the same tell comes back twice, it deserves a check that looks for it before release. That is what we did for the em dash, the comma before "et" and calques. Our article on editing a website with AI describes how to write the instruction and then verify the result.
Have someone who knows your customers review the copy
AI does not know that your customers say "quote" and not "proposal," or that they never ask "why choose you." A review by someone who talks to them every week catches what no list anticipates.
Read the copy out loud
A fragment, a writer's phrase or a cascade of participles is easy to catch by ear. If you would not say the sentence to a customer on the phone, it should not be on your website.
Run the competitor test
Before release, replace your name with those of your three main competitors in every heading and paragraph. Every sentence that stays true needs rewriting with a fact that belongs only to you.
Our article on SEO writing with AI shows where AI helps most in this work. The one on the limits of AI in web design counts the brand's voice among the decisions that stay human.
Five questions to ask about your website copy
- Does our home page headline say what we do, for whom and where?
- Would our copy still be true with a competitor's name on it?
- Do our services pages contain facts AI could not have invented: timelines, service area, starting prices, client examples?
- Are the questions in our FAQ the ones our customers actually ask on the phone?
- Who reviews the copy before it goes live? Which tells are blocked by a check?
AI writes fast. The facts that set you apart, it can only get from you.
Copy written with AI from your facts and your voice, checks that block tells before release and human approval before every publication: that is our AI-managed website offer.
Want pages that rank in Google and get cited by AI? Our SEO agency writes every page from your facts.
Frequently asked questions about AI-written website copy
How can you tell if a website's copy was written by AI?
Several clues together suggest it: short paired fragments, taglines that would fit any business, lists with bold lead-ins, words like "solutions" or "elevate" in place of facts. No single clue proves it. A writer in a hurry writes this way too.
Does Google penalize website copy written by AI?
Not as such. Google judges a page's usefulness, originality and effort, whatever the tool. Its guidelines do, however, give the lowest rating to pages generated with little effort and no added value. Default copy risks falling into that group.
Are AI text detectors reliable?
No. OpenAI withdrew its own detector in July 2023 for lack of accuracy. A Stanford study showed that seven detectors wrongly classified, on average, 61.22% of essays by non-native English speakers as AI-written. A detector can offer a clue, never proof.
Is it a problem if my website copy sounds AI-written?
The risk is commercial. According to a 2025 Raptive survey, content perceived as AI-written loses 48% of the reader's trust, even when a human wrote it. Default copy can also describe your competitors as well as it describes you.
Can you use AI to write a website without these tells?
Yes, for the most part. Give it the facts before asking for the copy, put your voice guide in the project's instructions file and ask for prose in complete sentences. Add checks that block recurring tells, then have someone who knows your customers review the result.
Which words give away AI-written text?
Studies have measured the overuse of "delve," "tapestry" and "pivotal." On websites, the same families keep coming back: "elevate," "unlock," "solutions," "seamless," "in the heart of." These words are not wrong. They become a tell when they replace a fact.
Why does AI-written copy all sound the same?
Because models are trained to write what their raters prefer, and raters prefer familiar phrasing. A prompt without facts then leaves the model to fill the gap with whatever fits every business. Several studies have measured this loss of diversity.
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Geneviève puts the strategy for your engagement into action. She leads all our web development projects: Shopify, WordPress and the new ways of building a site with AI. She manages our team of developers and translates your business needs into technical language. She runs your organic search (SEO), your visibility in AI answers (GEO) and your site's conversion rate optimization (CRO). Her work is at the heart of three goals: Attract customers with SEO and AI, Improve your site's conversion, and Strengthen your visibility in AI answers. With Gabriel, she also builds the landing pages for your advertising campaigns. She writes mainly about SEO, AI visibility and web design.
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