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Google and AI content is a topic that is at the top of mind for SEOs, digital marketers, and web publishers in 2025.
It encompasses several questions and concerns:
Why? Well, in the current media landscape, it’s easy to feel as if AI-generated content is everywhere, and that concern is not without precedent.
From helpful editing (think AI grammar checking) to full-on farmed AI-generated content with the purpose of gaming Google’s algorithm — AI content is present in Google’s search rankings, and it’s here to stay.
In response, we set out to give a data-backed, statistical count of AI’s presence in Google search rankings to answer the question: how much AI content is present in Google?
By sampling the top 20 search results from 500 popular keywords from the beginning of 2019 to the present day, we’re tracking the saturation of AI in search results, all the way back to the release of GPT-2.
Now, let’s take a closer look at the impact of AI in top search results on Google.
Check out the live dashboard at the top of this page to see the latest results on how much AI is in Google in 2025.
The quick answer: As of July 2025, 19.56% of the top 20 search results are AI-generated.
So, what influenced this dramatic percentage of AI-generated content in Google search?
What started as psychedelic dog-like face images and robotic, nonsensical text monologues has morphed into the modern, intelligent, and increasingly difficult-to-detect AI content that we encounter every day.
Every article consumed, image viewed, and video watched now triggers a small paranoid question in any responsible editor or consumer’s mind: “Did a human make this?”
Despite obvious ChatGPT sayings and commonly used ChatGPT words and phrases, which often make people think it’s easy to spot AI-generated text, the reality is that several studies have found that humans can’t detect AI content.
With the seemingly continuous release of new AI models, where does that leave editors, publishers, and marketers?
In 2025, it’s essential to include AI detection as part of the editorial process to establish transparency and publish with confidence.
In general, over the course of our study, we’ve found a continuously increasing presence of AI content, despite some month-to-month fluctuations and dips.
Before GPT-2 was released to the public (in 2019), AI content was detected in only 2.27% of our sampled websites.
Since then, continuous OpenAI GPT model releases from ChatGPT (2022) to GPT-4 (2023 - which has since retired), to GPT-4o (2024), and GPT-4.5 (as a research preview in 2025), AI models have become increasingly accessible.
And… the percentage of AI content in Google has continued to trend upwards overall.
Today, AI content has reached an all-time high of 19.56% in July 2025.
Understanding how Google and other search engines see your content is important to maintaining your site’s integrity and authority as a content leader.
So, is AI spam, and does Google consider AI content spam?
To provide perspective on Google’s approach to AI-generated content and if AI content can impact site reputation, first, let’s look at Google’s helpful content policy.
Google has always focused on providing users with high-quality, relevant information.
They want people to continue using their search engine. So, the closer they tailor their results to what searchers are looking for, the better.
Google’s helpful content guidelines follow what it calls E-E-A-T: Expertise, Experience, Authoritativeness, and Trustworthiness.
This prioritizes people-first content that’s created for readers (not search engines) and thus provides unique value and insights.
First and foremost, Google cares about the quality of the content.
Google’s AI-generated content guidelines, published in 2023, refer to their historical approach to mass-produced content:
“about 10 years ago, there were understandable concerns about a rise in mass-produced yet human-generated content. No one would have thought it reasonable for us to declare a ban on all human-generated content in response. Instead, it made more sense to improve our systems to reward quality content, as we did.” - Google Search's guidance about AI-generated content
Accordingly, they consider the appropriate use of AI acceptable so long as it complies with Google’s guidelines.
For instance, where routine content production uses helpful automation — with the examples of weather forecasts and sports scores provided — Google already has mechanisms in place that recognize these as helpful automations.
They understand how automation, when used properly, is constantly innovating to provide value.
Consider their own investment in AI with Gemini and the integrations of AI within search, such as AI Overviews released and then expanded in 2024, which provide quick AI-generated summaries at the top of search results.
However, AI content specifically made to manipulate search engine rankings does not comply with spam policies and is NOT permitted.
“Examples of scaled content abuse include, but are not limited to: Using generative AI tools or other similar tools to generate many pages without adding value for users…” - Google’s Spam Policies
In 2025, Google updated their Search Quality Rater Guidelines, emphasizing that if all or almost all of a page’s main content is AI-generated and little or no originality is added, raters should apply the lowest rating.
“The Lowest rating applies if all or almost all of the MC on the page (including text, images, audio, videos, etc) is copied, paraphrased, embedded, auto or AI generated or reposted from other sources with little to no effort, little to no originality, and little to no added value…” - 2025 Google Search Quality Rater Guidelines
We found that even after Google’s implementation of its helpful content policy, first introduced in August 2022, the machine-content saturation still increased.
It is, however, notable that with the introduction of AI to the general public via ChatGPT, we did expect to see a spike in AI content in Google, which our data does not confirm.
This suggests that Google’s helpful content and spam policies have been at least partially successful at keeping AI spam at bay.
AI can help and hinder SEO. While it’s true that AI writing can help you create content quickly or that an AI SEO tool can recommend content optimization tips to keep material fresh and visitors coming back, when used incorrectly, it can also hurt SEO efforts.
Google is smart enough to detect AI content that’s stuffed with keywords, low quality, or repetitive.
Further, Google advises their search quality raters that when the main content of a page is fully or mostly generated with AI, then it should be considered the lowest quality.
The feedback that raters provide does not directly affect rankings in the SERP. However, the feedback can influence Google’s approach to algorithm improvements.
Yes, Google does penalize AI spam, as found in our study into Google’s March 2024 update.
Here’s a quick snapshot of the study:
Read the full study: Can Google Detect and Does it Penalize AI Content?
In addition to actions that Google and Google search raters may take. AI can also indirectly impact your SEO by dropping user engagement.
If users can’t find what they’re looking for, they leave the site, resulting in high bounce rates that tell the search engine the site isn’t providing users with relevance and value.
When this happens often enough, the page’s ranking drops or can even disappear from search results.
The increasing presence of AI in Google is not to be understated.
Large Language Model (LLM) based AI tools are trained on very large human content datasets, often sourced from the internet via an automated scraping/crawling process (which has resulted in a number of ChatGPT lawsuits).
If not curated carefully, as the internet becomes more and more saturated with AI-generated content, these training datasets will as well.
A study from May 2023 suggests that through multiple iterations of LLM training on datasets containing machine-generated content, models generate more generic and predictable results and become more likely to misperceive their learning task over time.
To offset this, the authors stress the importance of the continuing availability of non-machine-generated training materials for future model learning.
With future models of GPT and other AI models well on their way, and the continuously increasing rate of AI content in websites, said datasets will become more and more difficult to source.
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The data collection phase of this project was designed with the goal of generating a representative sampling of the average results one would see on Google after searching an informational keyword.
We automated each step, allowing us to analyze large quantities of data. The process is novel to us, and we believe, as well, to the general search engine community.
To seed the data points for our study, 500 Google Search keywords were chosen, with the resulting set having the following properties:
Keywords were informational; i.e., they are searched when looking for an answer to a question. Informational keywords generate search results with large amounts of article text, making them good targets for AI Scanning.
Example keywords include: “how to screenshot on mac”, “best albums of all time”, and “what are carbohydrates”.
The set of chosen keywords has a similar search volume (read: popularity) distribution to that of the set of all informational keywords.
To illustrate: imagine we are choosing 10 keywords to represent the top 100 informational keywords. If 10% (i.e., ten) of the top keywords had a search volume of 2,000/month, then following our methodology, 10% (i.e., one) of our chosen 10 keywords would have a search volume of 2,000.
Keywords should not have large fluctuations in popularity and/or search volume over time. Keywords such as those involving movies, sports events, video game releases, etc, were not considered.
For each keyword, we used a search engine optimization (SEO) tool to find their respective top 20 search results. We repeated this process every second month, from January 2019 to present day, resulting in a list of 10,000 websites for each two-month period.
For each list of websites/time period, we checked the Internet Archive to see if a website snapshot was available within its respective period. If a snapshot was available, we used a port of the Arc90 Readability Algorithm to extract the main article text from the Archive snapshot.
All scraped text was run through a data cleaning process, fixing extraneous white space and other punctuation artifacts, removing most non-article text such as citations and footnotes and ensuring that all text was sufficiently long enough to be run through the Originality.ai AI detector.
Text from websites that were not article-based, like YouTube and Reddit, was removed.
The text was then run through the Originality.ai detector, and its score was recorded.
As the originality score represents the detector’s confidence that a text contains AI from 0 to 1, we consider a score of 0.5 or above to be a positive AI detection.
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If you plan to use AI content and want to maximize your SEO, you’ll need a two-pronged plan. That means combining AI’s efficiency with human oversight.
AI is great at creating unique ideas and content briefs or outlines. Take a step back and use AI for what it’s best at. It’s incredibly efficient for looking at trends and brainstorming topics your audience will love. Then, the writing itself is best left to you, the content creator.
AI simply doesn’t know your audience like you do, and despite all its training, it can’t “learn” the kind of insights you’ve developed from working with that audience.
Those insights are the very things that your audience is looking for and what will help your site rank higher on Google. Finally, after the content is written, human editors can refine and polish the final draft for publishing.
Use an AI Checker to identify and highlight instances of AI use. Then, edit for grammar, flow, clarity, and readability.
Incorporate your unique voice and avoid unnaturally sprinkling in keywords or unusually superfluous vocabulary.
If you decide to use AI for content creation, disclose the use of AI according to your organization’s code of ethics. Being open and transparent about AI as a tool rather than a catch-all writing solution will help you cultivate trust.
Essentially, you’re not writing for a search engine; you’re writing for humans. When you write content that’s interesting, engaging, unique, and relevant, Google notices. Doing so consistently helps build your authority and authenticity.
What else can you do to create the kind of content that Google and other search engines love?
Here are a few best practices:
Create a style guide that includes the tone, style, and structure you want your content to follow. The more specific, the better. AI writes according to its countless hours of training. As a human, you’ve developed a style and voice that your audience will seek out.
AI is great at saying very little in a large space, as it blathers on and on about broad topics with fluff and filler, which is precisely what Google and your site visitors want to avoid.
Create content that directly and genuinely answers the user’s questions.
AI “writes” quickly based on the topic and the vast amount of data it’s trained on. It’s essentially playing a numbers game that mimics real human writing.
In doing this, it has the tendency to make up facts (called AI hallucinations) and possibly go off on an unrelated tangent.
That’s where natural human language (and fact-checking) comes in.
Your anecdotes, examples, stories, and insights give you an edge, while fact-checking content adds validity to your publications (and helps to prevent scenarios like the AI book list scandal).
People read your content to hear your observations and experiences.
Take steps to regularly review and revise your content. Even if you wrote something a few months ago, many industries change rapidly. Go back and update old articles with fresh new information that indicates your content is relevant to Google.
Two things are clear: AI content is becoming more present, and Google is increasing its efforts to keep unhelpful AI content at bay.
Using tools like Originality.ai can help ensure that the content on your website is original, helpful, and plays well within Google’s rules for search engine results.
Sources: Ilia Shumailov et al. (2023). The Curse of Recursion: Training on Generated Data Makes Models Forget. Retrieved from arXiv:2305.17493
