Content made with AI stops reading like AI when a person brings what the tool can’t: first-hand experience, specific facts, a real opinion and a voice, and then edits out the generic patterns AI tends to produce. Google judges content on whether it’s helpful, not how it was made. The goal isn’t to disguise AI. It’s to publish something genuinely worth reading.
I use AI tools in my own writing process, for research, structure and first drafts. Everything published under my name is checked, edited and rewritten where needed, with the experience and examples coming from me. This post explains how that works and why it matters.
What Google says about AI-generated content
Google says generative AI can be useful for research and adding structure to original content, but using it to generate many pages without adding value for users may violate its spam policy on scaled content abuse. It asks site owners to focus on accuracy, quality and relevance, including in titles, descriptions and structured data.
Google’s guidance on using generative AI content makes several practical points:
- AI can help. It can be useful when researching a topic and adding structure to original content.
- Scale without value is the problem. Generating many pages without adding value for users may violate the scaled content abuse policy.
- Accuracy matters, especially for automatically generated content, and that includes metadata such as titles and meta descriptions.
- Consider explaining how content was made, where that makes sense for your audience.
- Ecommerce has extra rules. Google Merchant Center has policies for AI-generated content, including metadata on AI-generated images.
So there’s no penalty for using AI as such. The risk is publishing content that adds nothing, or that’s inaccurate.
Why AI content often reads the same
AI tools produce the most likely wording for a request, so without direction they drift towards the same safe phrases, balanced structures and vague claims. Readers have learned to spot those patterns, and content full of them feels generic even when it’s accurate.
The giveaways I see most often:
| Pattern | Example | What to do instead |
|---|---|---|
| Inflated openings | “In today’s ever-changing world, businesses must adapt to succeed” | Start with the answer |
| Stock vocabulary | “unlock”, “elevate”, “navigate the complexities” | Use plain words |
| Everything in threes | “fast, friendly and professional” | Say what’s actually true, however many things that is |
| Balanced non-answers | “It depends on your needs” with no guidance | Give a clear recommendation and when it doesn’t apply |
| Vague authority | “Experts agree that this is the best approach” | Name the source or leave it out |
| Rhetorical contrasts | “It’s not just X, it’s Y” | Make the point directly |
| Generic endings | “The future looks bright” | End with something useful |
| Uniform rhythm | Every sentence the same length | Mix short and long sentences |
What only you can add
The part of a page AI can’t write is what you know from doing the work: real examples, numbers from your business, photos, customer questions, mistakes and opinions. That’s also what Google describes as non-commodity content, and it’s what makes readers trust a page.
Before editing a draft, list what you can add:
- A real example. A job, a customer, a product you’ve tested or a problem you’ve solved.
- Your numbers. How long it takes, what it costs, what happened.
- Your opinion. What you’d recommend, and when you wouldn’t.
- Your customers’ words. The questions they ask and the mistakes they make.
- Evidence. Photos, results or data only your business has.
Google’s AI optimisation guide makes the same distinction: a first-hand review gives a unique perspective based on personal experience, while a summary of existing content simply restates what’s already available.
An editing process that works
Use AI for research and a first draft if it helps, then edit in stages: check every fact against a primary source, add first-hand detail, rewrite in your own voice, remove generic patterns, and read it aloud. Each stage fixes a different problem, so skipping one shows.
- Brief it properly. Give the tool the question, your audience, your key points and your examples before it drafts anything.
- Check every fact. Verify claims, figures and quotes against primary sources. AI tools can state wrong information confidently.
- Add what only you know. Put in the examples, numbers and opinions from your list.
- Rewrite in your voice. Use the words you’d use with a customer. Contractions, plain language and your own phrasing.
- Remove the patterns. Go through the table above and cut or rewrite every instance.
- Cut what doesn’t help. Delete repetition and padding. Google says it has no preferred word count.
- Read it aloud. Anything you wouldn’t say to a customer needs rewriting.
- Check titles and descriptions too. Google’s guidance specifically mentions accuracy in metadata.
My own process runs along these lines: a written voice guide, a list of banned phrases, a check for AI writing patterns, primary sources for every claim, and markers wherever a fact or example still needs confirming before anything is published. The content writing system page describes it in more detail.
Why “AI humaniser” tools miss the point
Tools that rewrite AI text to avoid detection change the wording but don’t add experience, facts or judgement, so the content stays just as generic. Google doesn’t rank content on whether it looks human-written. It rewards content that’s helpful and accurate, which no rewording tool can supply.
Search for advice on making AI content sound human and most results are tools promising to get past AI detectors. For a business, that’s the wrong goal. A customer reading your page doesn’t care whether a detector flags it. They care whether it answers their question and whether they can trust you.
Rewording generic content produces reworded generic content. Adding a real example, a verified figure and a clear recommendation produces something worth reading.
When not to use AI at all
Avoid relying on AI for content where accuracy has serious consequences, such as health, legal and financial information, unless every claim is checked by someone qualified. Also avoid it for content that’s meant to show personal experience, like reviews, unless that experience is genuinely yours.
Some cases need particular care:
- Health, legal and financial advice, where errors can cause real harm
- Reviews and testimonials, which must reflect genuine experience
- Figures and statistics, which need a verifiable source
- Anything about named people or businesses, where mistakes can be unfair or defamatory
- Product images and details in shopping feeds, which have their own policies
What I learned
AI has made first drafts faster, but it hasn’t made good content any faster to finish. The time has moved from typing to checking, adding and editing. When I’ve been tempted to shortcut that, the result has always read like everything else on the subject.
The most useful change was writing down my own voice rules and banned phrases, and checking every draft against them. It turned “make it sound less like AI” from a vague feeling into a checklist.
If you’d like help producing content that’s quick to make but still worth reading, generative AI marketing covers setting up the process for your business.
FAQ
Does Google penalise AI-generated content?
Not for being AI-generated. Google judges content on whether it’s helpful, reliable and people-first, however it’s produced. Using AI to generate many pages without adding value for users may violate its scaled content abuse policy. Accurate, genuinely useful content made with AI assistance isn’t against Google’s guidelines.
Should I say when content was made with AI?
Google suggests considering whether to explain how content was created, where that makes sense for your audience. Many businesses publish a short statement about how they use AI. For ecommerce, Google Merchant Center has specific policies, including metadata on AI-generated images. Being open usually builds more trust than hiding it.
Can people tell if content was written by AI?
Often, yes, when it’s unedited. Generic phrases, balanced non-answers, vague claims and uniform sentence rhythm are familiar to many readers. Content that includes first-hand examples, specific facts and a clear opinion reads as human because a person has genuinely contributed to it, whatever tools were used.
Are AI humaniser tools worth using?
For a business, rarely. They reword text to avoid detection, but they don’t add experience, accuracy or judgement, which are what make content useful and trustworthy. Time is better spent checking facts, adding real examples and editing in your own voice, which improves the content for readers and search engines.
More on content:
If you’d like a second opinion on your content, get in touch or ask for a free assessment.
Sources
- Google Search’s guidance on using generative AI content, Google Search Central, accessed 15 September 2026. Supports: AI useful for research and structure, scaled content abuse, accuracy including metadata, explaining how content was created, Merchant Center policies for AI-generated content.
- AI optimization guide, Google Search Central, accessed 15 September 2026. Supports: first-hand review versus summary of existing content.
- Creating helpful, reliable, people-first content, Google Search Central, accessed 15 September 2026. Supports: no preferred word count.