My biggest takeaway from Google’s August spam update is that it wasn’t targeting AI content itself as much as how AI is being used to produce content at scale.
Google does not appear to penalize content simply because AI helped create it.
The greater risk is scaled, low-value content published primarily to capture search traffic.
AI-assisted content still needs human oversight, original insight, and a clear purpose for readers.
Ranking drops during the update do not prove that AI-generated content caused the decline.
Google does not appear to penalize content merely because AI was involved in creating it. The bigger concern is content produced at scale primarily to manipulate search visibility, especially when it offers little original value.
My thesis, one we’ll test rigorously as we go, is that using AI to ideate, build briefs, or take a first pass at a draft shouldn’t get you penalized. That’s using a tool within a broader editorial process.
On the other hand, publishing 10 pieces a day copied directly from ChatGPT, OpenAI’s generative AI assistant, is a no-go. That number is an illustration, not a documented Google threshold. The underlying issue is indiscriminate volume without sufficient review, differentiation, or reader value.
It also helps to separate two related terms:
Google’s stated position has been that AI-assisted content creation is not inherently a problem. We don’t shy away from telling clients that we use AI as a tool. Through Profound, clients can also see the AI agents we’ve built to automate parts of our process.
The risk increases when sites mass-produce content mainly to capture search traffic. Pages that offer little original value and appear designed for algorithms rather than people are more exposed, regardless of whether AI, a human writer, or both created them.
The dividing line is not simply “AI” versus “human.” It is the purpose, quality, and execution of the content.
|
|
|
|
Using AI to generate ideas or organize research |
Publishing large volumes of unedited AI output |
|
Building briefs before expert review |
Creating repetitive pages for similar keywords |
|
Producing a first draft for human editing |
Rephrasing existing information without adding value |
|
Adding firsthand experience or original insight |
Publishing primarily to capture search demand |
|
Checking accuracy, usefulness, and relevance |
Prioritizing output volume over reader needs |
“Thin” content provides little useful information or depth. “Repetitive” content duplicates the same ideas across multiple pages with minimal differentiation. Both can exist without AI, but generative AI makes them easier to produce at much greater volume.
The clearest initial signal was ranking volatility, not proof that Google had identified and penalized AI-written copy.
When the update was announced, I think every organic growth manager was holding their breath. Many of us have warned clients that “AI slop” – low-quality, minimally reviewed AI output – would eventually create search risk.
The volatility gave us ranking movement to investigate. It did not, by itself, prove that AI-generated content was the cause.
That distinction matters. We shouldn’t assume Google is detecting whether a bot wrote a page. AI copy is becoming harder to distinguish from human copy, and Google hasn’t provided evidence here that AI detection alone is the operative mechanism.
The more useful question is whether affected content shows broader spam or quality patterns, including:
Our running list of risky practices will probably keep growing as the search landscape evolves. But this update does not require a major directional shift for good practitioners.
It reinforces what Google has said for years and what we’ve echoed to clients: prioritizing useful, high-quality content over pure volume remains the safer strategy for organic growth.
AI can absolutely be part of a strong content workflow. There still needs to be strategy, human oversight, original insight, and a reason for each page to exist beyond targeting another keyword or prompt.
We’re investigating affected sites for common patterns, but we’re not automatically attributing every ranking loss to the spam update.
Our next step is to examine sites with significant declines for signs of:
That analysis is easier said than done. Timing alone does not establish causation, and the available data does not prove that AI-generated content specifically was penalized.
A responsible review also needs to consider other explanations, including technical changes, seasonality, competing sites, lost links, preexisting declines, and other ranking systems or updates. Ranking movement across industries makes it even more important not to generalize from a small number of examples.
We’ll be careful not to jump to conclusions until we can identify consistent patterns and empirical support in our own research.
Do not abandon AI, but do audit how and why your team uses it.
For every AI-assisted page, check whether it:
If rankings declined, avoid deleting or rewriting pages solely because AI was involved. Start by assessing usefulness, originality, repetition, and publishing intent. The goal should be to improve weak content, not merely disguise how it was created.
No. Google does not say that AI-generated content is inherently penalized simply because AI was used. The greater risk is low-value, repetitive, unoriginal, or scaled content created primarily to manipulate search rankings rather than help users. Google’s spam policy specifically applies to scaled content abuse regardless of whether the content is produced by AI, humans, or a combination of both.
There is no universal editing threshold. Human review should ensure the content is accurate, useful, distinctive, aligned with strategy, and strengthened by original insight or relevant expertise.
You cannot determine causation from timing alone. Review content quality and publishing patterns while also checking technical changes, seasonality, links, competitors, other updates, and any decline that began before the spam update.
Interested in a free strategy call? Schedule time with us.