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  • Google AI: Judge doubts spam update hits AI content

    Google AI: Judge doubts spam update hits AI content

    This week, the SEO world is buzzing with activity: a judge questions Google’s monopoly on AI content, a spam update pulls the rug out from under automated publications, and the old debate about geotargeting flares up again. Let’s break down what this means for your cache, especially in the context of Google AI.

    Legal Battles: Google AI and “Unfair” Content Usage

    A federal judge questioned Google’s practice of using web content for its AI overviews, calling it “grossly unfair.” This jeopardizes the current “traffic in exchange for content” model.

    Details of Penske Media vs. Google Case

    • During the antitrust hearing for Penske Media, Judge Amit Mehta questioned whether Google’s AI overviews could be considered a “product improvement.”
    • Digital Content Next CEO Jason Kint quoted the judge, who called the situation “really unfair” and noted that the improvement is being developed “at the expense of publishers.”
    • Judge Mehta has not yet ruled on Google’s motion to dismiss the lawsuit.

    “Publishers have no control over how Google uses their content,” Kint noted, emphasizing that opting out of Google indexing is not a realistic choice for publishers dependent on search traffic.

    Google Spam Update: A Blow to AI Publications

    Although Google has not officially stated that it is targeting AI-generated content in the August spam update, reports from website owners indicate problems for automated publications. Is cheap AI content worth such risks?

    Initial Observations and Conclusions

    • Roger Montti collected examples where fully automated sites lost visibility, while resources using AI with human refinement suffered less.
    • These are currently anecdotal reports, not official confirmation of changes in Google’s algorithms.
    • Google released the S-CTS system to detect coordinated synthetic abuse on video platforms, but this is not related to Google Search.
    • The mere fact of AI authorship is not a reason for a drop in rankings. Google’s policy concerns large-scale content created to manipulate rankings, regardless of the author.

SEO consultant Takuma Oka warns that his sample is small and the conclusions are not definitive. What matters is not the AI itself, but the method and purpose of mass production.

SEO vs. GEO: What John Mueller Says

John Mueller from Google once again commented on the “SEO vs. GEO” discussion, clarifying that there are no special requirements for generative AI answers in search. That is, testing hypotheses cheaply does not mean that basic principles can be forgotten.

Nuances for AI Answers

  • Mueller stated that Google sees nothing special that needs to be done for generative AI answers in search.
  • This applies to Google Search, not to ChatGPT, Perplexity, or other AI systems.
  • If you are already optimizing your site for Google, Mueller does not offer a new technical checklist for AI overviews.

Dan Akedju summarized: “The fundamentals are the same. The extraction level is different.” This is a key point: favorable CPM only when the platform’s features are taken into account.

AI Recommendations: Brands are Recommended, but Others are Cited

New data shows that a brand recommendation in an AI answer does not guarantee a direct link to your site. This affects ROI and requires a review of metrics.

Shero Commerce Analysis

  • Shero Commerce analyzed 1,851 citations in Google AI Mode, ChatGPT, and Perplexity.
  • Brand-owned pages received only 2.8% of citations.
  • When a brand was recommended by name, its own page received a citation in only 31% of cases. Third-party resources were often cited.

Aleyda Solis emphasized: “Your brand may be recommended in the answer… while the citation (and click) goes to a magazine or marketplace.” This means that the cost of uniqueizing one video or the price of generating 100 AI videos should pay off not only with mentions but also with direct links.

ChatGPT and Reddit: Complex Citation Dynamics

Promptwatch data showed a sharp drop in Reddit’s citation share in ChatGPT in mid-August, but new tests show that Reddit still plays an important role in the information extraction process.

Google AI: The judge doubts, the spam update hits AI content — illustration 2

Variability of ChatGPT Behavior

  • In one query, ChatGPT purposefully searched for information on r/whatnotapp: out of 71 extracted pages, 48 were Reddit threads, and 6 out of 8 final citations went to the subreddit.
  • Four days earlier, Suganthan Mohanadasan found that ChatGPT extracted 84 Reddit threads for another query but did not cite any.

Mohanadasan summarized: “Reddit citations were not simply ‘turned off.’ They seem to be query-dependent.” This demonstrates that price comparison of various sources and their citability is a dynamic process and requires constant monitoring.

Conclusion: Visibility vs. Value – New Metrics

This week, it became clear that visibility and real value are beginning to diverge. Publishers share information, but don’t always get traffic. Brands receive recommendations, but links go to others. Reddit may be a data source for AI, but not appear in final citations. “AI visibility” is becoming too broad a concept, requiring more precise metrics to assess ROI.

It’s important not only to be indexed, but also to get a mention, a citation, a click, and ultimately, a conversion. How much money will each dollar spent bring – that’s the main question. Re-evaluate your strategies and metrics to avoid wasting your budget.

Frequently Asked Questions

What is “unfair” use of content by Google AI?

Judge Amit Mehta opined that Google, by using publishers’ content for its AI overviews without adequate compensation or control from publishers, creates an unfair advantage, as publishers cannot opt out of Google indexing without losing traffic.

Is Google’s spam update really targeting AI-generated content?

Google has not officially confirmed this. However, according to reports from website owners, resources that use fully automated content generation have lost visibility. At the same time, sites where AI content was refined by humans suffered less. The focus is on large-scale content created to manipulate rankings, regardless of the generation method.

What does John Mueller advise regarding SEO for AI answers?

Mueller states that there are no special requirements for generative AI answers in Google Search. If you are already optimizing your site for Google, no additional technical checklists are needed for AI overviews. However, it is important to remember that different AI systems extract and select sources differently.

Why might a brand be recommended by AI, but the link goes to another site?

Shero Commerce research showed that AI systems often recommend brands by name, but cite third-party resources (e.g., magazines or marketplaces) instead of the brand’s official pages. This means that brand visibility does not always convert into direct clicks and traffic to your resource.

How has ChatGPT’s behavior regarding Reddit citations changed?

Data shows that Reddit citations in ChatGPT have become more complex and depend on the specific query. In some cases, Reddit is actively used and cited, in others, a lot of data is extracted, but there are no citations. This indicates the dynamism of algorithms and the need for constant analysis of sources that AI systems prefer for specific topics.

  • Google vs. AI Content: What Did the August Spam Update Bring?

    Google vs. AI Content: What Did the August Spam Update Bring?

    Google’s recent August spam update appears to have targeted mass-generated AI content for SEO. Reports from online sources indicate that part of this update involved the removal of materials created by neural networks solely to manipulate search rankings. This aligns with Google’s recent research on identifying such spam, which is an important clue for anyone involved in AI video for advertising or mass video generation by neural network.

    It’s important to understand: using AI itself doesn’t make content spam. However, any material created for the purpose of ranking for keywords often balances on the line between regular content and spam. It seems Google has implemented new mechanisms to detect AI-generated content that crosses this line, which may explain the decline in rankings for many sites actively using neural networks for UGC advertising.

    Impact on AI-Generated Content

    Experts are actively discussing the consequences of the update. For example,

    Oka Takuma (@OkaTakuma1) wrote: “Regarding this Google spam update, it seems that sites automatically publishing content using Claude Code, Codec, etc., are being universally filtered and losing rankings. Google may automatically identify such content by attaching some kind of ‘AI credit,’ similar to generated images or videos.”

    He also noted that sites that started with manual publishing and then switched to LLM automation have survived in some cases. This is explained by accumulated domain trust. Sites entirely created with automation from scratch do not have “trust signals” from Google.

    Manual Review as a Buffer

    Oka Takuma provided an interesting example, mentioning a Japanese magazine that publishes AI-generated content and was not affected by the update. The reason is simple:

    “…but so far it has not received any penalties (naturally, we conduct a manual visual review by humans before publishing articles).”

    This highlights the importance of human control, even when using technologies such as AI avatar with subtitles or AI voiceovers. Manual review can be a lifeline for AI production by subscription.

    Not AI, but the Purpose of Use

    Seiichi Satoweb (@seiichi_satoweb) believes that the problem is not with AI content itself, but with its mass production to manipulate search results. He noted:

    “Companies managing media should check their rankings from August 18th to 21st. …If it dropped, I think the first thing to suspect is not the quality of the articles, but the ‘mass production method’.”

    Google defines malicious use of mass-generated content as creating a large number of pages primarily to manipulate search rankings, rather than to support users. This is critically important for those looking for AI content production or where to order for crypto similar services.

    • Mass video generation by neural network for SEO purposes can be risky.
    • AI clips with face swap or AI avatar with subtitles should serve a real purpose.
    • Focusing on quality, not quantity, is key to survival in Google’s new reality.

    “AI Junk” and its Consequences

    On forums like Blackhat World, users complain about the prevalence of “AI junk” in search results. One participant wrote:

    “They finally realized that AI junk is taking over the SERPs. I recently searched for a quick tutorial on how to change settings in an app and saw 4 sites in a row, clearly AI-generated to create articles answering that question — all looked absolutely identical, with the same AI formatting of subheadings and bullet points, poor spacing between sections, 3 sentences inflated to 500 words. AI junk pages are the new doorways, and Google is struggling to deal with it.”

    This confirms that the effectiveness of AI versus real UGC is still questionable when it comes to low-quality content. Generating 100 videos or an AI conveyor of 500 videos per day must be supported by a quality strategy, not just volume.

    Google vs. AI Content: What did the August spam update bring? — illustration 2

    Google’s New System: S-CTS

    Google recently published research on a new system called S-CTS (Scalable Cluster Termination System). This system is designed to identify and terminate networks of AI-generated spam. This means that an AI video factory for e-commerce or video generation from text via mass generation API are now under close scrutiny.

    How much does one AI creative cost or the cost of 1 minute of AI video — these metrics now need to be evaluated not only from a production perspective but also from the perspective of potential SEO risks.

    Conclusion: The Future of AI Content

    Google’s August spam update clearly showed that the era of mindless mass generation of AI content for SEO is coming to an end. Now that AI UGC for crypto projects or creating AI commercials are becoming increasingly accessible, it is critically important to focus on quality, uniqueness, and real value for the user. It’s not just about a neural network writing scripts and editing, but about creating something meaningful and useful.

    For those who want to scale their content production, solutions like Synthesia alternatives should be used wisely and supported by a strategy that does not contradict Google’s principles. Only then can sustainable success be achieved in a world where scaling was impossible — now it’s possible, but with an eye on quality.

    Frequently Asked Questions

    What is “AI junk” in the context of Google?

    “AI junk” is low-quality, mass-generated artificial intelligence content created primarily to manipulate search rankings, rather than to provide valuable information to users. It is often characterized by repetitive phrases, poor formatting, and a lack of originality, as in the case of AI video for advertising created without proper oversight.

    How does Google distinguish quality AI content from spam?

    Google does not penalize the use of AI per se. The main focus is on the purpose of content creation and its value to the user. If an AI avatar with subtitles or AI voiceovers are used to create useful, unique material that has undergone human review, it is not considered spam. The problem arises with mass video generation by neural networks solely for SEO without regard for quality.

    What is Google’s S-CTS system?

    S-CTS (Scalable Cluster Termination System) is a new Google system designed to identify and terminate networks engaged in AI-generated spam. It is a tool to combat large-scale operations producing low-quality content that use mass generation APIs to create thousands of pages or videos.

    Can AI be used to create UGC content?

    Yes, neural networks can be used for UGC advertising, but with caution. The key to success is creating valuable and unique content that is perceived as authentic. The effectiveness of AI versus real UGC will depend on how well AI integrates with the creative process and how thoroughly the content is human-reviewed to avoid “AI junk.”

  • Brand mention in ChatGPT matters more than links: 92.8% of conversations without a click

    Brand mention in ChatGPT matters more than links: 92.8% of conversations without a click

    92.8% of dialogues in ChatGPT end without a transition to the website — this is Profound data that Kevin Indig analyzed in the digest on July 21. Measured on live traffic of a real product, the figure can be trusted. All search promotion relied on a single deal: you get to the top of search results, a person clicks the link to your site, and converting that visit into a lead is your concern. The link was the point where a business first touches a customer. In the AI response, this deal breaks at the very first step: the click most often simply doesn’t happen.

    Why 92.8% of dialogues in ChatGPT end without a transition to the website

    For several months, I’ve been measuring how ChatGPT, Perplexity, Alisa AQI, and GigaChat name brands in their responses: I run control prompts and see which model mentioned whom and which didn’t. Behind these runs, a figure surfaced that breaks the usual SEO logic — and made me change what I track for clients altogether. Let me break it down in order.

    Three weeks ago, we ran prompts for a client in the food delivery niche through ChatGPT. Usual routine: you type a question like “which delivery service to choose in Moscow,” and look at the response. At that point, the client had far more links from external sites than the nearest competitor. In Ahrefs — a service that calculates a site’s link weight — this is immediately visible: both the overall authority score is higher, and the number of different sites linking to it is one and a half times greater. ChatGPT named the competitor. The client — no. Didn’t mention it at all, not once in twenty prompts.

    I double-checked three times, changed the wording of the question, the date of the dialogue, and the region. The result was the same. For an hour and a half, I honestly couldn’t understand what was going on. Twenty years of website promotion taught a simple rule: the more links point to you, the higher you rank in Google and Yandex results, and therefore the more readily neural networks should name you. Here, the rule didn’t work. Only there was no search results page in the usual sense. There was a model that decided on its own whom to name and whom not to. And it decided not by a link counter.

    A brand mention cannot be bought with links — it accumulates like reputation

    At the same time, AI traffic itself is tiny in volume — Ahrefs reports that ChatGPT accounts for about 0.19% of all link transitions on the internet, compared to 42% for Google. Ridiculously small if you compare head-on. But here’s what’s more interesting: those few who do click from ChatGPT convert far more readily — conversion is about 7.1%, and the visit itself is valued 4.4 times higher than a regular one. Fewer people reach the site, but those who do — came ready to make a purchase or any other target action.

    Brand mention in ChatGPT matters more than links: 92.8% of conversations without a click

    And here’s an important twist. If the decision is made BEFORE the click, inside the model’s response itself, then you need to fight not for the click. You need to fight for how you’re named at the moment when the click hasn’t happened yet and, most likely, won’t happen at all. A mention in a ChatGPT response is not structured like a spot in search results. A spot can be earned by working on the site — links, loading speed, technical cleanup. A mention can’t be bought that way. The model gathers it from two sources: from the texts it was trained on and from pages it pulls up right during the response. And what decides is not the number of links, but how the brand is generally written about — in reviews, on forums, in industry articles, in comparisons.

    Search promotion used to be about taking top positions, because a position led to a click on the site. Promotion in AI answer engines works differently: you have to fight for the mention itself, because a click may not happen at all, and the person will still make a decision — based on how the model named the brand. A link is a one-time asset. It works as long as the page holds in the search results, as long as the site is alive, as long as the algorithm values it. A mention accumulates differently: it is reputation that has already settled into the texts on which the model was trained and which it reads now. Remove one article — the mention will not go anywhere; it is spread across dozens of sources.

    This is where my mistake with that food delivery client was. His link profile was strong, but almost all of it came from aggregators and directories, where the brand is simply listed in a list. The competitor had fewer links, but had three detailed editorial reviews describing how the service differs from others. The model was trained on them, among other things. It did not count links — it read context. The first place in Google, by the way, does not at all guarantee a mention in ChatGPT. We checked this on several clients separately: search and AI engines have different selection mechanics, and the first place in regular search results does not by itself turn into a line inside the model’s answer.

    Where a link still brings a client, and where the question is closed right in the answer

    The link has not died entirely — it is important not to confuse this. In regular Google, 68% of searches in the US by early 2026 also end without a click, according to SparkToro citing Search Engine Land. An answer without a click to the site has also come to good old search, it is just that it was visible there earlier — through blocks with ready answers, knowledge cards, and direct answers at the top of the results.

    The link still works where the decision is made AFTER the first touch: price comparison, reading reviews, technical documentation, everything that requires going into details that simply do not fit in the model’s short answer. It works in niches with a long decision-making cycle — there, a person will still reach the site, just later. The link does not work where the question is closed with one phrase in the answer. “Which delivery service to choose” — closed with a phrase. “How much does delivery from a specific restaurant in a specific area cost tomorrow evening” — not closed, a click is needed there. The same business lives on both sides of this boundary — it all depends on which specific query the user asked.

    Brand mention in ChatGPT matters more than links: 92.8% of conversations without a click

    What I now measure for clients instead of search positions

    I stopped looking only at positions in the search results and added a separate measurement: how often and in what context models mention the client’s brand directly, without a click, without a transition. We run control prompts — real audience questions — through ChatGPT, Perplexity, Alisa AI, and GigaChat, and see whether the model names the brand, in what order relative to competitors, and with what wording. ChatGPT is not the only one here. Perplexity builds its answer almost entirely from cited sources and shows them as a list — the model readily takes from articles on third-party platforms. Alisa AI mixes in fresh Yandex results, GigaChat answers in its own way. A brand that sounds in one model may be silent in another — so one ChatGPT is not enough for the measurement.

    From this, three things emerged that I now advise any marketer to track:

    • Share of mentions among top competitors for your own key questions: a specific percentage for a specific set of prompts, without general ratings.
    • Tone of phrasing: the model may mention the brand neutrally, or it may add an evaluative word like “trusted” or “expensive” — this influences choice more than the mere fact of mention.
    • Sources from which the model apparently draws this phrasing: often it’s one or two articles — these should be prioritized for strengthening, instead of spreading the budget across dozens of platforms.

    With that food delivery client, we ultimately didn’t chase new links. We wrote several detailed materials about the product on platforms that the model clearly reads and cites — and after a month and a half, the mention appeared, and visibility in AI responses grew. The client had more links, but ChatGPT named a competitor. Now we know why.

    Frequently Asked Questions

    How to measure brand mentions in ChatGPT?

    Run control prompts — real audience questions — through ChatGPT, Perplexity, Alice AI, and GigaChat. Calculate the share of mentions among top competitors, record the tone and the sources from which the model draws information.

    Brand mention in ChatGPT matters more than links: 92.8% of conversations without a click

    Can you buy a mention in neural networks with links?

    No. Links work in classic search, but neural networks don’t count them directly. A mention depends on how the brand is written about in reviews, articles, and forums — it’s reputation that accumulates in the texts on which the model is trained.

    What to do if the brand is not mentioned in ChatGPT?

    Find the platforms that the model cites most often and place detailed materials about the product there. Strengthen editorial reviews, comparisons, and expert articles — they influence mentions more than link mass.

    Should you abandon SEO in favor of neural networks?

    No. Links still work in niches with a long decision-making cycle and for transactional queries. The optimal strategy is to combine classic SEO with work on mentions in AI responses.

    Conclusion

    The bottom line is simple: 92.8% of dialogues in ChatGPT end without a click, but the decision to choose a brand has already been made. A link is a one-time asset; a mention is cumulative reputation. To win in AI search results, stop chasing links and start managing how you are written about in the texts that models read. Run control prompts, track the share of mentions and tone — and you’ll see where you’re really losing customers. Start with an audit of your mentions today.