AI is integrated into most, if not all, systems that we use today, and it’s getting crazier by the day. Google has been at the forefront of the AI revolution since the early 2000s. Its search algorithm now features an AI Overview feature, which is powered by a customized version of the Gemini model. Google’s co-founder, Larry Page, once said, “The perfect search engine should understand exactly what you mean and give you back exactly what you need.” He made this statement back in a 2002 interview with Wired magazine. Now with generative AI, this is exactly what is happening. Google is reshaping how websites rank and how users interact with search results. Traditional SEO strategies, such as keyword stuffing and outdated backlink tactics, are losing relevance because the AI Overview feature prioritizes context, user intent, and, of course, high-quality content.
In this article, we’ll talk about SEO and explore how Google’s latest AI update is changing SEO forever, what these updates mean for you as a website owner, and how to stay ahead in the new AI-driven search landscape.
SEO Keywords to Context
Search Engine Optimization is the practice of optimizing websites and content to improve their visibility and ranking in search engine results pages (SERPs). For years, SEO was built around targeting specific keywords, and other strategies and techniques aimed at attracting organic (non-paid) traffic to rank higher on search engine results pages like Google, Bing, and Yahoo.
It’s standard practice to optimize your website for search engines by understanding keyword types and using various SEO techniques, though I won’t cover all of them here. Standard SEO practices have worked for years (and they still do) just not in the same way. The name of the game in SEO has always been pleasing the search engine algorithm ‘gods’ to get more web traffic.
The first algorithm, PageRank – introduced in 1998, operated by “counting the number and quality of links to a page to determine a rough estimate of how important the website is. The underlying assumption is that more important websites are likely to receive more links from other websites.” This was the premise behind backlinks.
The Google search algorithm has undergone a lot of updates and changes since then, some only mild and some with deep impact. I will focus on the introduction of AI-driven ranking systems like RankBrain, BERT, and MUM so we can understand that Google no longer focuses solely on exact keyword matching. Instead, it now also prioritizes understanding context and user intent.
Google Using Machine Learning
People might use the terms artificial intelligence (AI) and machine learning (ML) interchangeably, but they are slightly different. Artificial Intelligence refers to the use of technologies to build machines and computers that can mimic cognitive functions associated with human intelligence like learning, problem-solving, reasoning, and decision-making. The things that your human brain can do.
Machine learning is a subset of AI that focuses on enabling machines to learn from data and improve their performance over time without being explicitly programmed. So it is about pattern recognition from past data, making predictions and learning from experience.
Google has been using machine learning for a long time. Since 2001, machine learning has helped Google Search users correct their spelling by suggesting better spellings even when you don’t type your search perfectly.
In 2006, Google translate came and changed the game. It uses machine learning to automatically translate languages. Even though it is not perfect, it supports more than 133 languages spoken by people around the world, breaking down the language barrier like the tower of babel.
Google Search AI SEO Revolution with RankBrain
RankBrain was Google’s first AI-driven ranking factor which was introduced in 2015 and is still relevant today. RankBrain uses machine learning to help interpret unseen queries by analyzing the relationships between keywords and search intent. Before RankBrain, Google would scan webpages to see if they contained the exact keyword someone searched for, word for word. But now, RankBrain tries to figure out your search intent by matching new keywords it has never seen to keywords that Google has seen before.
Take the below example. I searched for “the reverse time movie” and google knows that i am most likely looking for Tenet (I am btw) by turning my search query into a concept and giving me results based on the concept.
This ability to understand context and ambiguous phrasing is exactly what RankBrain was designed to do, improving the relevance of search results. The significance of this is that it made it harder for websites relying on keyword stuffing to rank without offering valuable content.
Keyword stuffing is when you fill your content with the same keywords over and over again to trick the search engine into ranking your content higher for those keywords, even if the content is low quality. RankBrain understands not only keywords, but user satisfaction. Google search evolved to reward high-quality, user-friendly content that naturally incorporates relevant keywords.
Natural Language Processing and BERT
In November 2018, Google launched the open sourced BERT(Bidirectional Encoder Representations from Transformers), a groundbreaking language model that has significantly advanced the field of Natural Language Processing (NLP). Google introduced BERT into the search algorithm in 2019. Without getting to much into it, BERT is basically a deep learning algorithm that helps Google interpret the nuances of natural language.
Natural language processing a branch of AI that is at the center of much of the commercial artificial intelligence research being done today. Apart from its use in search engines, NLP has applications in virtual assistants such as Siri and Alexa, automated telephone response systems, and vehicle navigation systems.
In the Search Engine, when you type a query, BERT considers the entire context of a sentence and each preceding and following word within it, which enables a deeper understanding of language nuances. Rather than just matching keywords, it focuses on understanding the meaning of that word and the intention behind the search.
Before BERT, you could search for a question like, “Why does my coffee taste sweeter when I add milk?” and the engine might simply look for pages where the words “coffee,” “bitter,” and “milk” appear. With BERT, however, the search engine processes the full sentence and understands that you’re asking about the interaction between coffee and milk, perhaps due to enzymes, chemical reactions or flavor profiles.
This update made searches more conversational, rewarding content that answers queries in a clear, human-like manner. So, your content has to make sense and have a purpose rather than just repeating keywords.
MUM and The Future of Google Search
Google’s MUM (Multitask Unified Model), launched in 2021, took AI-driven search to a whole new level. It is apparently 1,000 times more powerful than BERT. MUM is an advanced AI model that builds on previous innovations like BERT and RankBrain, designed to understand complex queries that might involve several steps or require information from various sources.
On average, people need to make eight searches to find an answer to a complicated question, with more than half of the queries being more than four words long. Also considering that 15% of daily queries have never been searched on Google, and with the evolution of voice search, the algorithm must be adapted to this new state of affairs. MUM is multimodal, meaning that it can understand multiple forms of content such as text, images, and even video and audio.
It can multitask and simultaneously understand the search context, interpret nuances, and even analyze visual content to deliver more comprehensive and relevant results. It can also analyze results across 75 languages, and learn from sources that aren’t written in the language you wrote your search in. Insane stuff! This update makes SEO more about comprehensive, multimedia-rich content than ever before.
Also Read: How to Get A Free Business E-mail in 2025
With the rise of AI-powered search, MUM set the stage for what would soon become an even bigger game-changer: Google’s Search Generative Experience (SGE).
The Rise of AI-Generated Search Results
This is what I really wanted to talk about, and I’m sure it draws a lot of mixed feelings. One of the biggest disruptions in SEO is Google’s Search Generative Experience (SGE), which integrates AI-generated answers at the top of search results. Unless you’ve been living under a rock, you’ve definitely seen the AI Overview at the top of almost every Google search query you make. Its a super cool feature that makes the search experience much better in terms of retrieving the information you really want in a concise way, but has far reaching consequences for SEO and website owners.
What is SGE?
Search Generative Experience, also known as AI overviews, is an experimental feature on google search that provides AI-generated summaries directly on the search results page. It uses generative AI to give users overviews and summaries of search results, along with links to relevant sources. Generative AI is the well-known branch of AI responsible for creating new content. When you want to generate text, images, videos, code and other new content, you are using Gen AI.
The AI overviews in search are generated using a customized version the latest Gemini LLM, which can handle complex queries and advanced reasoning. Gemini is unique because it is fully multimodal from the ground up. It can process and generate text, images, audio, video, and code seamlessly. Bringing together Gemini and the already impressive search algorithm gives a powerful search experience that rivals ChatGPT, which powers OpenAI’s chatbot and is integrated into Microsoft Copilot, and Grok, Elon Musk’s LLM that is primarily text-based because it is trained on real-time posts from X (Twitter).
So what is the point of AI overviews? They are designed to give quick answers, help with planning and idea generation, and just like the MUM model, help with complex questions so you don’t have to break your question into multiple searches.
Google claims that the links included in AI Overviews get more clicks than if the page had appeared as a traditional web listing for that query. However, this still reduces the need for users to click on websites to find results to their search queries, meaning organic click-through rates (CTR) may decline, and competition for the remaining clicks will intensify.
How AI Overviews Impact SEO
Here are a couple ways that the SGE affects SEO.
Less traffic for traditional search results – It is obvious that AI answers may satisfy users without them clicking through to a website.
More competition for Featured Snippets – Sites that rank in these positions will still get visibility, probably even more, so optimizing for them is crucial.
Greater focus on authoritative content – Google’s AI prioritizes sources with strong expertise and credibility.
- Long-tail keywords will become more important – People are increasingly searching in full sentences rather than short keyword phrases.
Conversational content will win – Blog posts, FAQs, and guides should be written in a natural tone that mimics real conversations.
Structured data matters more – Schema markup helps search engines understand your content better, displaying it to users with much more information. This makes it more likely to appear in rich snippets or AI-powered search results. This is a very powerful and necessary SEO technique.
How to Future-Proof Your SEO Strategy
Having said all that, how do you adapt to the new changes? As AI continues evolving, SEO will require a more strategic, content-focused approach. Here’s how to stay ahead:
Focus on High-Quality, AI-Friendly Content
Write in a clear, user-friendly manner, avoiding jargon or robotic keyword usage. Google does not hate AI generated, you just have to optimize it to be human readable.
Avoid fluff and keyword stuffing. As mentioned earlier, Google’s AI prioritizes depth, context and relevance to the queries.
Optimize for AI-Generated Search Experiences
Ensure your content is concise and structured to appear in Featured Snippets. You can summarize the key points in your introduction or conclusion where possible.
Use FAQ sections and bullet points for better AI recognition whenever possible.
Optimize for voice search by including questions and answers in your content.
Build Strong E-E-A-T Signals
Google’s AI updates increasingly emphasize E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness) as a ranking factor. This came from the medic update in 2018, also dubbed the “Your Money, Your Life” or YMYL update because it is particularly significant for topics, such as finance, health, and law that require an extra level of seriousness because of the potential user impact. In this regard, this is how to Strengthen E-E-A-T:
- Get real experts to contribute to content– Google values articles written by professionals in their field rather than generic, AI-generated content. Have industry experts write or review content and ensure content is well-researched and fact-checked.
- Build high-quality backlinks from trusted sources – Websites with authoritative inbound links tend to rank higher. Improve your site’s authority with credible backlinks and trust-building factors.
- Clear author attribution – Including author bios, credentials, and links to authoritative sources boosts credibility.
Keep Up with Technical SEO Best Practices
Remember that the technical aspects of your site still need to be on point as much as possible. Here’s How to Stay Ahead in Technical SEO:
- Page Experience Signals – Google rewards fast-loading, mobile-friendly, and secure websites. Improve your Core Web Vitals such as loading speed, interactivity, and accessibility. Build and optimize for mobile-first indexing, ensuring pages perform well on all devices. You can also regularly audit your website’s performance using tools such as Google Search Console and PageSpeed Insights.
- Structured Data (Schema Markup) – As mentioned above, your schema markup helps AI understand your content and improves visibility in rich results. Use structured data to help Google categorize content accurately.
Lastly, it should go without saying, but stay updated on Google’s AI-driven algorithm changes and adjust accordingly.
Conclusion
SEO is evolving rapidly, and staying ahead means adapting to AI-driven search. Have you noticed any changes in your website’s traffic? High-quality, authoritative content is now more important than ever.
To succeed in this new landscape, focus on well-structured, user-friendly content rather than outdated and blackhat SEO tactics. AI-powered search will continue to evolve, with deeper integration of video search via Google Lens, enhanced voice search capabilities, and AI Overviews that allow users to their search or break it down in more detail.
Where do we go next? Only time will tell. If you embrace change and optimize accordingly, you will stay ahead of the curve.
