Scale was never the problem
Google’s Scaled Content Abuse policy doesn’t penalise volume and it doesn’t name AI as the trigger – it penalises four other things and Google is explicit about all four: content that’s repetitive (stitched together through synonyms, translation or other automated reformatting), low-value (adds little or nothing a user didn’t already have), unoriginal (recombined from elsewhere without new substance) and built with the primary intent of capturing rankings.
A hundred category pages for a market launch fail none of those tests if each one carries genuinely different product data and answers a genuinely different query. A hundred pages that differ only in swapped city names or synonym-substituted headlines fail all four at once, however they were produced. That’s the actual distinction to design content operations around, more than whether AI was involved.
Google has made this point before, in a different context: when mass-produced but entirely human-written content became a concern roughly a decade ago, the response wasn’t to ban human writing. It was to build systems that reward quality regardless of who or what produced the page. The same logic now applies to AI.
What actually changed
Google folded Scaled Content Abuse into its core Spam Policies as part of the March 2024 update and the definition has stayed stable since. The policy targets pages created “with the primary purpose of manipulating search rankings, rather than helping users”, typically producing large volumes of non-original content that provides little or no value, regardless of how it’s created.
Generative AI is named as one method among several – so is scraping feeds and search results, mechanically combining content from different pages and publishing through multiple sites to disguise the scale of the operation. The common thread across every example in Google’s own documentation is the four-part test above.
Enforcement here works differently to a normal ranking drop and that’s worth understanding before it matters. Google enforces this policy both algorithmically, through the ranking systems that quietly demote low-value pages, and through manual actions that appear directly in Search Console. Independent SEO analysts who track enforcement patterns have documented that manual actions for scaled content abuse tend to apply sitewide or at the directory level. A cluster of thin, templated pages can drag down a domain’s visibility well beyond the pages themselves. That’s the practical stake behind the audit below: the risk isn’t contained to the pages that fail the test.
Where the exposure concentrates
Google’s original 2023 guidance on AI content was explicit that content succeeds or fails on E-E-A-T (experience, expertise, authoritativeness, trustworthiness). Google’s own framing at the time was direct: its focus is on the quality of content more than on how it’s produced and that focus is what has let it deliver reliable results for years.
That guidance has since been sharpened: Google’s 2025 update to its Search Quality Rater Guidelines instructs human raters to apply the lowest quality rating to any page whose main content is entirely or almost entirely AI-generated with little or no originality added. That’s a materially firmer line than the 2023 post drew and it lands the hardest in Your Money or Your Life (YMYL) categories: content that could affect a person’s health, financial stability or safety.
Thin, interchangeable pages carry the most risk in exactly this category, which makes it directly relevant for brands in financial services or healthcare-adjacent categories, where scaled comparison and product pages are common and the margin for genuinely unhelpful content is smallest.
The audit most teams haven’t run
Few content or SEO teams have actually checked their existing templated pages against Google’s four-part test. It’s a different exercise to a normal content audit: not “is this page ranking”, but “if Google’s automated systems or a human reviewer read fifty of our category pages side by side, would the pattern look like genuine variation or like the same page wearing fifty different labels”.
That’s usually where the gap shows up. Not in one bad page, but in the aggregate pattern across a template. Given that enforcement can hit sitewide, that aggregate pattern is what’s worth checking before it becomes a Search Console notice.
What to do about it
- Run every templated page through the four-part test before publishing more. Repetitive, low-value, unoriginal, ranking-motivated: a page that fails even one deserves a second look before it goes live.
- Use real product and market data. Where a template has a section with nothing specific to say, that’s a signal the page shouldn’t exist yet. It shouldn’t be a filler.
- Put a named reviewer on scaled production. Looking at pages as a group can reveal repetition and templating issues that are easy to miss when each page is reviewed in isolation. Human review should then focus on the value each page adds, not just whether the copy is grammatically correct.
- Treat internal linking as a relevance signal. Links that reflect a genuine relationship between pages read very differently to users and to Google.
Brands that already run scaled content through this kind of structured review have less to change than the “will AI content get penalised” headlines suggest. The risk sits with production that scales the volume without scaling the judgement behind it.
AI can help create more content, faster. What it cannot replace is the editorial decision about whether that content is accurate, useful, distinctive and genuinely worth publishing. That judgement becomes even more important when content is produced across different products, categories or markets.
That’s the audit worth running before the next pages go live and it’s a conversation you could have with us.
Article author
Claudia Morera
Account Executive
