Google has already said, in writing, exactly what gets a site penalised — and it is not using AI. Here is the line it drew, the seven jobs AI does well on the right side of it, and the process this blog actually runs.
There is a lot of anxious advice about AI and search. Half of it says Google will punish you for touching the stuff. The other half sells you a tool that publishes four hundred articles a month. Both are wrong, and Google has been unusually clear about why.
In February 2023 Google published its guidance on AI-generated content. It does not prohibit using AI to create content; its stated focus is on the quality and purpose of the material rather than its origin. It rewards content that demonstrates genuine expertise and original insight, framed through its E-E-A-T criteria — experience, expertise, authoritativeness and trustworthiness. What it targets is “automation used to manipulate rankings”.
The spam policies, last updated 28 August 2026, give the enforcement version. Scaled content abuse is defined as “when many pages are generated for the primary purpose of manipulating search rankings and not helping users”. The examples are specific: using generative AI to create numerous pages without user value, scraping and transforming content with minimal added benefit, stitching together material from multiple sources, and pages built from keywords that lack coherent meaning.
Read those two documents together and the rule is plain. The offence is volume without value. An AI-assisted page that is genuinely useful, distinct and checked is fine by Google’s own account. Two hundred pages that say the same thing in different words are not, regardless of who or what wrote them.
Notice how few of these are “write the article”.
Before you write anything, feed AI your existing pages and ask what each one owns — its argument, its headings, the statistics it cites — and where the gaps are. This is the single highest-value step and the most skipped. Overlap is how a site cannibalises itself; the map is how you avoid it.
Ask what every existing page on a topic says, then ask what is true and useful that none of them say. Most search results on a query are the same article in different fonts. The page that ranks is the one that owns a question the others skipped.
Article, FAQ and breadcrumb schema, title tags, meta descriptions, alt text. Tedious, mechanical, easy to get slightly wrong, and exactly the kind of work AI does reliably from a template — provided the template is right and you check the output validates.
Given a draft and a list of your live pages, AI is good at spotting where a sentence should point to something you already wrote. A well-linked cluster passes authority between its own pages; a set of orphans does not.
Prices change, statistics age, products ship. Asking AI to re-check a page against current sources and flag what has drifted is far cheaper than rewriting, and a refreshed page usually outranks a new one on the same topic.
Run every draft through a pass that asks: which sentences assert a fact, and which of those have a source? The unsourced ones get a citation or get cut. This is the step that makes E-E-A-T real rather than decorative.
A well-researched article becomes a social post, a newsletter section, a short video script. That is not scaled content abuse — it is one piece of genuine work reaching people where they are. The distinction is that the research happened once, properly.
Producing the insight. AI will give you the median opinion on any topic, fluently. The median opinion is what already ranks. If a page contains nothing that came from your experience, your data or your judgement, it is a rewrite of the results page it is trying to beat.
Knowing what is true. A confident sentence with no source is a liability on a page that is supposed to build trust. Every statistic, price and claim needs to be checked at its origin by someone who will be embarrassed if it is wrong. If nobody on your team will be embarrassed, that is the problem to fix first.
Since the page you are reading is on a site that uses AI in its own content pipeline, here is the actual process, because a claim about method is only worth something if you can see the method.
That process makes each page slower to produce than a content mill’s. It also makes each one distinct, checked and linked, which is the whole of what Google says it is looking for. If you want a worked example of step two, every recent post on this blog carries its positioning against its neighbours — the Notion comparison is a good one to read for its structure rather than its subject.
If the answer to the last one is no, publish fewer.
Most of the seven jobs above are document work, and they happen in a workspace rather than a chat window: the coverage map as a spreadsheet, the drafts as documents with track changes so an editor can mark them up, the refresh checks as a scheduled worker that reads your live pages against current sources and leaves a report behind rather than sending anything. The AI marketing workflows course in the Academy walks through five of these on real material in forty-five minutes.
Free with no card, then Starter A$9.95, Pro A$29.99 and Pro Plus A$59.99 a month. Unlimited documents, spreadsheets, decks and designs on every plan.
Whatever you’re here to make, make more of it.
None of this is a ranking guarantee, and anyone who offers one is selling something. Google’s systems change, its guidance is deliberately general, and a page can do everything right and still sit on page three because somebody else did it better. What the process above does is remove the ways to lose: thin pages, duplicated pages, unsupported claims, and the volume trap. The rest is the quality of what you actually know.
Not for being AI-generated. Google’s own guidance says it does not prohibit using AI to create content and that its focus is on quality and purpose rather than origin. What its spam policies do target is scaled content abuse — many pages generated primarily to manipulate rankings rather than help users. The tool is not the offence; the intent and the volume are.
In Google’s words, it is when many pages are generated for the primary purpose of manipulating search rankings and not helping users. Google’s examples include using generative AI to create numerous pages without value, scraping and lightly transforming content, and stitching together material from multiple sources with minimal added benefit.
The work around the writing: mapping what you already cover and where the gaps are, drafting structured data and metadata, finding internal-linking opportunities, refreshing stale posts against current sources, turning one well-researched piece into formats for other channels, and checking a draft for claims that need a citation. Used that way it makes a small team produce fewer, better pages faster.
Google’s guidance says disclosure and production methods that prioritise the reader matter more than the tool. Practically, if a page’s value depends on who checked it, say who checked it. Readers trust a clear process more than a vague claim of human authorship, and so, by its own account, does Google.
As many as you can make genuinely distinct and genuinely checked, and no more. The moment production outruns verification you are drifting towards the definition of scaled content abuse. A cluster of twenty pages that each own a different question outranks two hundred that say the same thing in different words.
This article is general information about search-engine guidance and content practice. It is not a guarantee of any ranking outcome, not legal advice, and does not take account of your circumstances. Google’s guidance and policies are quoted as published on the dates shown and change without notice; read the current versions before relying on them. Google is a trade mark of Google LLC; Oppermind is not affiliated with, endorsed by, or sponsored by Google. Oppermind platform prices are current as at 12 September 2026, are in Australian dollars, and are subject to the plan terms at checkout.
The coverage map, the drafts with track changes, and a worker that refreshes stale pages against current sources — in one workspace.