Marketing specialists working across different industries have already noticed the rapid rise in popularity of new search platforms. Artificial intelligence (AI) is actively reshaping the way users search for information and interact with brands. According to Gartner, due to AI-generated responses, organic traffic from Google may decrease by as much as 50% by 2028. Therefore, if you want to be visible in AI-generated results, you need to take action now.
What to Do to Make Your Business Visible in AI Search Results?
New AI-powered search platforms, such as Perplexity.AI, and conversational AI assistants, such as ChatGPT, Grok, or Gemini, are becoming strong competitors to Google. ChatGPT is already among the 10 most visited websites worldwide, while platforms like Perplexity.AI are rapidly growing in user base.
According to Grand View Research, the global AI search and large language model (LLM) market is projected to grow annually by 24% to 36% between 2024 and 2030. This means that some users are already turning to AI-powered platforms as an alternative to Google — and their numbers will only continue to rise.
AI shopping assistants are gradually changing consumer behavior, giving preference to well-known brands. With AI platforms, users can move through the entire sales funnel in a single conversation and receive specific product recommendations.As a result, brands that want to remain visible and maintain traffic must start working now on positioning and content optimization for these new AI platforms. Early adaptation can help secure a competitive advantage and even drive conversions.
What’s the Difference Between Large Language Models (LLMs) and AI Search?
Large Language Models
The breakthrough of large language models came in 2022, and by 2025 we already have numerous examples of LLMs: OpenAI o1, OpenAI GPT-4o, Gemini 2.0, Perplexity Sonar, Claude 3.5 Sonnet, Grok 3, DeepSeek R1, Llama 3.1, Mistral AI Mistral 8x22B.
Models like Claude, Llama, and Grok are based on massive datasets and operate according to the knowledge acquired during training. However, their internal knowledge bases are limited, and new information is only incorporated when the model is retrained.
When asked a question, these models analyze information and provide responses based on their internal knowledge base, without real-time access to external sources or the internet. This works well for certain tasks, but some of the information may be outdated or irrelevant. Retraining is an expensive process — costing from several million to hundreds of millions of dollars — and is therefore done infrequently.
It’s worth noting that although these models by default rely only on internal knowledge, many of them can optionally incorporate real-time data through specific tools, such as Claude Web Search, Llama 3.1 with Brave Search, or Grok 3 DeepSearch.
AI Search
Platforms such as Google AI Overviews, Perplexity, and ChatGPT combine large language models with real-time web search to obtain the latest information from the network. Short search queries are converted into AI model prompts using a method called RAG (Retrieval-Augmented Generation). Such AI models are capable of answering questions in real time, relying not only on their internal knowledge but also on external web sources. In addition, they can provide links to the specific sources they have relied on.
What Is GEO Optimization?
Generative Engine Optimization (GEO) is a strategy used to adapt content for AI-powered search systems so that they can easily understand, use, and prioritize it. With proper optimization, when users submit queries in AI search, your content can be cited in the results and included in AI-generated responses and summaries.
How Does GEO Differ from SEO?
Essentially, GEO refers to the adaptation of content for AI, while SEO optimization aims to achieve the highest possible positions in traditional search engine results pages (SERPs) using keywords and backlinks. GEO optimization focuses on ensuring that content is included in the responses and summaries generated by AI models (Google AI Overviews, ChatGPT, Perplexity, etc.), even if it doesn’t rank highly in traditional search results.
| GEO | SEO | |
| Goal | Ensuring the brand is mentioned or cited in AI platforms (e.g., ChatGPT, Claude). | Increasing website visibility in search engines (e.g., Google). |
| Focus | Website optimization through contextual content to create interaction with AI systems | Keyword research and on-page/off-page optimization. |
| Primary Channels | AI-powered search engines and conversational agents. | Traditional search engines (Google, Bing). |
| Result Format | AI provides direct answers, often integrating information from multiple sources. | Users see a list of links (SERP – Search Engine Results Page). |
| Methods | Content that encourages AI to mention your brand (clear, credible, citable). | Website content optimization, link building, technical SEO. |
| Operates Through | Training AI chat models and their ability to process, interpret, and retell content. | Indexing of webpages and matching user search queries. |
Learn more in our article: The Future of SEO – Optimizing for Answer Engines (AEO).
How to Make Your Content Discoverable in AI Search Engines?
1. Evaluate Your Brand’s Representation in AI Models
Analyze how LLMs recognize your brand: what information they provide, which sources they use, and what topics they associate with your brand. Pay special attention to anchor text in backlinks, as it influences how AI perceives your topical authority. Useful tools: aiclicks.io, Google Natural Language API, Inlinks Entity Analyzer.
2. Leverage PR to Connect Your Brand With Relevant Topics
The main goal of public relations (PR) is to manage communication between a brand and its audience, building trust and reputation. Unlike traditional search engines, LLMs (e.g., OpenAI GPT, Google Gemini) understand information based on probabilities and semantic relationships rather than databases.
They establish semantic proximity between concepts — how closely certain ideas are linked. To be visible in AI searches, you must actively connect your brand to relevant, meaningful topics. Strong associations increase your chances of being cited.
Key metrics: Share of Voice, online mentions, backlinks from relevant topics.
3. Use Credible Sources and Statistics
Content with citations, statistics, authoritative references, and a professional tone is more likely to appear in generative AI search results. Equally important: being cited by reliable sources increases your chances of being included in AI responses.
4. Get Listed on Wikipedia
Wikipedia is a crucial information source for AI search. Brands with a Wikipedia article are more likely to appear in Google Knowledge Graph and AI-generated answers. To qualify, you need:
- Notability – mentions in reliable sources (articles, books, research).
- Verifiability – all claims supported by independent sources.
- Neutrality – no promotional content.
- Conflict of Interest Avoidance – don’t write your own article; use Wikipedia’s discussion section instead.
5. Optimize Your Website for Bing Search
While Google remains the largest search engine, Bing with its AI Copilot has become an important player. It uses the Prometheus model (based on GPT-4) to generate AI answers with links to trustworthy sources. Even if you don’t rank high on Google, optimizing for Bing improves your chances of being included in AI-generated summaries.
6. Review Autocomplete Suggestions
Currently, there are no reliable metrics for measuring LLM search volume. However, you can gain insights using autocomplete suggestions in AI systems. This shows which queries and questions are most commonly associated with your brand.
For example, type: “Is {brand}…” into an AI search tool to see frequently asked questions.
7. Continue With Traditional SEO
High rankings on Google and Bing still matter. Studies show that LLMs are more likely to mention brands that perform well in SERPs. Thus, classic SEO supports GEO results.
8. Engage on Reddit and Leverage User-Generated Content
Reddit is a key training source for LLMs, and AI models actively pull content from it. Participating in discussions and encouraging user-generated content can increase your brand’s visibility in AI model responses. While this is challenging for brands, it is achievable.
The use of AI search will only continue to grow. That’s why investing in long-term authority, creating high-quality AI-optimized content, and using PR strategies is crucial now.
Pro Tip: Track visitors coming to your site from AI tools and analyze what queries led them there. You can do this through short on-site surveys. This will help you better understand how people find information about your brand through AI search, optimize your content and ads, build more effective AI interactions, and evaluate the quality of AI-generated recommendations.
