Key takeaways
- Google's guidance rewards helpful, people-first content regardless of how it was produced. There is no penalty for AI use as such.
- The March 2024 spam policy update targets 'scaled content abuse' — producing many pages primarily to manipulate rankings, whether by AI, by humans, or both.
- The practical test is whether a page adds something a reader could not get from the ten pages already ranking.
- AI detector scores are not a Google ranking signal. Optimising for them is optimising for the wrong thing.
- The gate that matters is a named human reviewer who is accountable for accuracy and for the page being worth publishing.
What Google's guidance actually says
Two documents matter here, and both are more specific than the summaries of them that circulate.
Google's guidance on AI-generated content, published in February 2023, states that its focus is on the quality of content rather than how it was produced. Using automation to generate content primarily to manipulate search rankings violates its spam policies — but that has been the position since long before generative models, and it targets intent and outcome, not tooling.
The March 2024 core update and accompanying spam policy update introduced the term 'scaled content abuse': producing many pages primarily for the purpose of manipulating rankings and not to help users. Google was explicit that this applies regardless of whether the content is produced by automation, by humans, or by a combination.
The distinction in one line
The problem is not that a machine wrote it. The problem is publishing pages that exist to rank rather than to be read.
This is a more demanding standard than 'is it AI?', not a more lenient one. A human-written page that adds nothing to what already ranks is equally in scope. Conversely, an AI-assisted page with genuine expertise, original data and real editorial judgement behind it is squarely within the guidance.
What actually fails
The failure pattern in practice is consistent, and it is rarely a single bad page. It is volume without a value gate.
| Fails | Holds up | |
|---|---|---|
| Topic selection | Keyword list with volume above a threshold | Questions your audience actually asks |
| Brief | Target keyword and word count | The specific angle, sources and what this page adds |
| Draft | Generated and published | Generated as raw material, then rewritten |
| Facts | Unverified | Every claim checked against a source |
| Original input | None | Own data, examples, screenshots or experience |
| Review | None, or a spellcheck | A named person accountable for the page |
| Volume | As many pages as the pipeline allows | As many as can clear the review gate |
The left-hand column is what 'scaled content abuse' describes. Note that nothing in it is about AI specifically — an agency doing the same thing with cheap human writers produces the same result and is treated the same way.
A workflow that holds up
- Start from a question, not a keyword. A keyword tells you phrasing and demand. It does not tell you what the person wants to know or what would satisfy them. Write down the actual question and what a good answer requires before anything else happens.
- Read what already ranks. Open the top ten results properly. If you cannot articulate what your page will add that those do not already provide, you do not yet have a page worth making. This single step removes most of the pages that would have failed.
- Write a brief that constrains the draft. The angle, the sources to use, the specific examples or data to include, the questions that must be answered, and what to leave out. A model given a thin brief returns a generic draft; that is a brief problem, not a model problem.
- Generate as raw material. Use the output as structured notes, not as a manuscript. It is a fast way to get coverage of a topic on the page so you can start making decisions about it.
- Verify every checkable claim. Statistics, dates, quotes, citations, product capabilities, prices. Models produce fabricated specifics in the same confident register as accurate ones. Nothing goes live unsourced.
- Add what only you have. Own data, a customer example, a screenshot from your product, a result you measured, a mistake you made. This is the difference between a page that adds something and a page that recombines existing pages.
- Edit properly. Cut the padding, fix the structure, break the rhythm, commit to a position. Our editing guide covers the full pass in order.
- Route through a named reviewer. One accountable person per page who signs off on accuracy and on the page being worth publishing. This gate is what makes the volume question self-limiting, which is the point.
- Measure engagement, not just position. Rankings tell you Google's current guess. Scroll depth, time on page, return visits and conversions tell you whether the page was actually useful. Prune or rewrite what underperforms rather than adding more.
The constraint that does the work
Cap output at what your review gate can genuinely handle. Most content programmes that get into trouble did so by scaling generation without scaling review.
AI detector scores and SEO
This deserves stating plainly, because there is a lot of confused advice about it.
Google has not said it uses AI-detection scoring as a ranking signal, and there is no reliable public evidence that a third-party detector's percentage affects rankings. Those tools estimate how statistically predictable text is. Predictability is not the thing Google's quality guidance is about.
Do not optimise for a detector
Rewriting purely to move a detector score is optimising for a proxy nobody has established matters. It also risks degrading the writing — the edits that lower a score are not always the edits that help a reader.
There is a legitimate use for a detector score in this workflow, and it is narrow: as a rough flag that a draft may still read as generic. A high score is a reasonable prompt to ask whether the page has enough specificity and voice. Treat it as one signal among several, not a target.
That said, if your organisation has its own policy requiring content to pass a detection threshold, that is a real constraint to work within — just be clear that it is an internal policy rather than a Google requirement.
- Why detectors flag human writing — what these scores do and do not tell you
- Free AI detector — check a draft's score band
Where tooling fits
We make writing tools, so weigh this accordingly. The useful split is between the repetitive layer and the judgement layer.
Tooling handles the repetitive layer well: flattening stiff phrasing, removing filler, varying sentence rhythm, generating outline options, drafting meta descriptions. That work is rule-shaped and it scales.
The judgement layer does not scale the same way — deciding what a page should argue, verifying claims, contributing original material, and signing off on whether it is worth publishing. That is the part that determines whether the page survives, and it stays with a person.
Tools that fit this workflow:
- Blog post outline — structure options before drafting
- SEO meta description — draft descriptions at the end of the pass
- Remove fluff — strip padding from a generated draft
- Headline generator — alternatives to test
Paste a draft section to see rewrite options. English only. Free plan covers 500 words per month, 300 per request.
The pre-publish gate
If you adopt nothing else from this guide, adopt a written gate. Every page clears it or does not ship.
- We can state in one sentence what this page adds that the current top ten do not.
- Every statistic, date, quote and citation is verified against a source someone opened.
- The page contains at least one thing only we could have provided.
- A named person has reviewed it and is accountable for it.
- It answers the question it targets in full, without padding to hit a word count.
- We would send this to a customer without apologising for it.
Why the last one works
It is the most reliable heuristic on the list. If nobody on the team would put their name on the page in front of a customer, it is not ready — and no amount of keyword coverage changes that.
Sources
- Google Search's guidance about AI-generated content — Google Search Central, 2023
- March 2024 core update and new spam policies — Google Search Central, 2024
- Creating helpful, reliable, people-first content — Google Search Central