AI SEO: How Brand Discovery is Changing through AI-Powered Search & Generative AI

AI SEO and Brand Discovery in 2025

Traditional SEO is no longer enough. As AI tools like ChatGPT and Google AI Overviews change how people search, brands need to understand how AI reads and surfaces content – and adapt their strategy accordingly.

Key Trends at a Glance

• AI SEO and Traditional SEO – More Similar Than You Think: High-quality content, conversational language, backlinks, and social proof still matter. The fundamentals of good SEO have not disappeared – they have just been extended by new AI-specific signals.
• AI Overviews Are Already Changing How People Search: Nearly 80% of users rely on AI summaries in traditional search engines. Brands that are not optimized for these overviews risk losing visibility even if they rank well in standard results.
• What Makes Content Visible to AI – Beyond Keywords: AI rewards clear quotes, statistics, unlinked brand mentions, user-generated content, and concept-based writing. Keyword stuffing no longer works – context and clarity do.
• Technical Setup Matters for AI Crawlability: Server-side rendering, correct robots.txt settings, and fast page loads help AI bots read your content efficiently. A Wikipedia presence also boosts how AI models reference and trust your brand.

AI & SEO – What You Will Learn

Traditional SEO has long been the primary channel for brands to generate online visibility. However, the rapid ascent of Generative Artificial Intelligence (Gen AI) and Large Language Models (LLMs) is reshaping how consumers find information, products, and brands online. If your brand has an established SEO strategy, you’re likely wondering: how will user behavior shifting to AI-driven search impact my business, and what should I do about it? Do you now have to move from SEO to AI SEO or Generative AI Optimization?

Let’s deep dive into the topic to understand:

1. If and how generative AI impacts your brand’s visibility
2. How it differs from traditional SEO

Image showing popular Generative AI platforms. Source: Unsplash

1. How much has Generative AI Impacted User Behavior?

Think about your own behavior and how you may use ChatGPT or similar LLMs in both work and personal contexts. We use these services for various purposes, including looking for information, comparing information, doing deep research, reasoning, or argumentation etc.

Users typically prefer LLMs when they need to conduct deeper research or understand complex information. They have not yet replaced search engines. According to Search Engine Journal, LLMs such as ChatGPT or Perplexity are only responsible for 0.25% of site traffic on average.

However, what you do need to be aware of is something called an AI Overview.

Understanding AI Overviews

You must have already noticed that Google’s snippets have now evolved into something called a Google AI Overview. Google is not the only Search Engine to have done this. AI Overviews are now commonplace on Bing and other competitors as well. According to Bain & Co., nearly 80% of users rely on AI summaries or overviews.

 This means two things:

1. Search Engines are already training users to receive and therefore expect conversational, condensed, and consolidated responses, almost as if they are using an LLM.
2. There may be a convergence of these tools in the future, especially with Google’s Gemini and Microsoft’s Co-Pilot, etc.

Image representing conversational styles of LLMs and AI Overviews. Source: Unsplash

2. What is AI SEO?

AI SEO refers to the process through which content can be strategically optimized to perform well in AI-powered environments. These environments can take several forms:

1. AI is increasingly influencing Search Engines such as Google and Bing, including AI Overviews in traditional search results to make content easier for users to digest.
2. Users may also interact directly with conversational AI platforms such as ChatGPT, Gemini, etc., using them to uncover information, solutions, or products.
3. It could also take on the shape of an intelligent ChatBot on a particular platform, such as Amazon’s AI, Rufus.

No Consensus Yet on How to Refer to AI SEO

The world of AI SEO, especially brand and product discovery through LLMs, is still nascent and constantly evolving. There has been an 5X uptick in LLM users since the beginning of 2024. However, the field is still new enough that it is experts refer to it using different terminology.

Image representing the numerous ways to identify AI SEO. Source: Flickr | Mariam Makram

Digital Marketing and SEO experts refer to optimizing content for discoverability through AI-powered search, and Generative AI/Large Language Models (LLMs) by the following (non-exhaustive) list of terms:

1. Generative AI Optimization
2. GEO – Generative Engine Optimization
3. AI SEO – Artificial Intelligence Search Engine Optimization
4. LLMO – Large Language Model Optimization

Are AI-powered search and discovery through LLMs similar to each other, then?

3. Similarities Between Traditional and LLMO

At its core, Gen AI SEO or LLMO shares many fundamental principles with traditional SEO. Both aim to make your content accessible and valuable to users.

1. Helpful, High-Quality Content: This remains the primary goal. Whether a human or an AI is interpreting your content, value, relevance, and accuracy are still crucial. Content that genuinely addresses user needs and questions will always be prioritized.

2. Conversational Language: As search moves towards natural language queries and AI-generated responses, writing in a conversational tone becomes even more crucial. Content that reads naturally and directly answers questions posed in human language will be favored.
3. Freshness and Timeliness: Frequently updated or recently published content signals relevance. AI models are trained on vast datasets, but for current events, trends, and product information, recency is key to providing accurate and up-to-date responses.
4. Social Proof: Signals of credibility, such as reviews, testimonials, mentions, and shares, continue to validate content’s authority and trustworthiness for both traditional algorithms and AI models.
5. Backlinks and Keyword Structure: While AI adds new dimensions, the foundational principles of a strong backlink profile (indicating authority) and a well-researched keyword structure (helping AI understand content topics) still hold significant weight. They provide crucial context and signals of relevance.

4. What’s Different? New Dimensions for AI SEO or LLMO:

1. Unlinked Mentions Get Tracked: AI’s contextual understanding is more sophisticated. While backlinks remain vital, AI can recognize authority and relevance even from unlinked brand or product mentions across the web, making the web’s overall narrative about your brand more important.

2. Quotes and Statistics Perform Better: AI models are adept at extracting specific data points and authoritative statements. Content that clearly presents quotes from experts or well-sourced statistics is more likely to be used in AI-generated summaries and responses, serving as factual anchors.
3. Technical Ability (Server-Side Rendering): For AI models to efficiently “read” your content, your website’s technical foundation must be robust. Server-side rendering (SSR) ensures that content loads quickly and is ready for crawlers and AI bots to read immediately. This prevents the AI bots from needing to execute complex client-side JavaScript, which can slow down the AI’s comprehension. Proper robots.txt and ccbot directives also ensure AI crawlers can access your relevant content.
4. Wikipedia Presence: LLMs often use Wikipedia for foundational information as they consider it a reliable and neutral source. A well-maintained and accurate Wikipedia page for your brand or relevant topics can significantly boost AI’s understanding and authoritative referencing of your entity.
5. User-Generated Content (UGC) Matters More: AI often synthesizes information from diverse sources, including forums like Reddit, Quora, and product review sites. Genuine user-generated content provides authentic insights into product use, common questions, and customer sentiment.
6. Context Over Mechanical Keywords: AI looks beyond mere keyword density. It assesses the actual context, social proof, statistical relevance, and clarity of information. Content that is well-written, naturally flowing, and demonstrates a deep understanding of a topic will outperform mechanically stuffed keyword pages. AI understands semantic relationships and natural language affinity far better than traditional crawlers.
7. Concept Optimization: Instead of rigid keyword usage, the focus shifts to concept optimization. You can write less mechanically as LLMs understand the relationships between different entities, ideas, and concepts. This allows for more natural, expansive, and truly comprehensive content that covers a topic thoroughly, anticipating user questions that they may not phrase with exact keywords.

5. Your LLMO Strategy: Where to Get Started

Interested in understanding how to update your content strategy to fit the changing landscape? Whether it is discoverability in AI Overviews, through LLMs or intelligent Chatbots such as Rufus, certain common principles apply.

There are concrete steps you can take to ensure your strategy evolves beyond Keyword Stuffing.

Want to know more?

Talk to us about a hands-on Workshop today!

FAQ: AI SEO and Generative Engine Optimization

Does a Wikipedia page help with AI search visibility?

Yes. LLMs frequently use Wikipedia as a trusted, neutral source. A well-maintained Wikipedia page for your brand improves how AI models understand, reference, and surface your brand in responses.+

This article was written by Sharanya Venkatesh, a digital marketing manager with an MBA from Oxford and strong expertise in SEO, content marketing, e-commerce, and analytics.

With a background in media and marketing, Sharanya specializes in content strategy, SEO optimization, cross-channel content performance, and measurement of digital marketing impact. Her work focuses on creating and optimizing content that improves visibility, engagement, and search performance across different audiences and platforms.