Table of Contents:
- What is AEO?
- Technical Issues: How to Prepare a WordPress Site for AI?
– Semantics and Clean Code: The Foundation of Machine “Understanding”
– Structured Data (Schema.org): Labels That AI Reads
– Content Architecture: Formatting for “Zero Result” - Content Issues: How to Prepare Website Content for AI?
– Authority and E-E-A-T (Experience and Trust)
– Visibility Beyond Your Domain - FAQ – Most Common Questions about AEO
– What is the difference between SEO and AEO?
– How to check if my site is visible in AI?
– Will AEO replace traditional SEO?
– How much does it cost and how long does it take to implement an AI-First strategy?
What is AEO?
AEO is the process of optimizing content so that AI-based Answer Engines consider your site to be the most reliable and direct source of information. While SEO fights for a position in the link ranking, AEO fights for being the single answer provided to the user by AI.
At Brave New, we tested this on ourselves. In Q3 2025, we implemented AI optimization on our site. The effect? Nearly 75% of new inquiries from foreign agencies interested in white label cooperation came directly from answer engines (ChatGPT, Gemini, or Perplexity). This best illustrates the change in decision-makers’ behavior—today, AI does the initial research for them. This is not the sound of the future—it is happening now.
Below you will find specific tips you should apply to make your site a “source of truth” for artificial intelligence. We have divided the tips into 2 groups (technical and substantive) and 5 areas to make navigation easier.
Technical Issues: How to Prepare a WordPress Site for AI?
1. Semantics and Clean Code: The Foundation of Machine “Understanding”
LLMs (Large Language Models) are powerful data analysis machines, but they can be lazy. For AI models, your page is not a set of colors, but a string of characters that must be processed with minimal resource consumption. The less “noise” in the code, the greater the chance that the AI will correctly interpret your offer.
- Clean code is fundamental, so consider the Code-to-Text Ratio: Clean, light code allows LLMs to quickly extract what is most important: the substantive content of your offer. This gives lightweight sites written from scratch an advantage over cheap ready-made themes. Popular themes (ready-made solutions) often generate hundreds of lines of unnecessary code (redundant <div> containers, unused JS scripts, and CSS styles). For the AI bot, getting through such chaos is energetically and temporally costly.
- Logic means more than keywords: AI is no longer just looking for phrases, but for the relationships between them. Correct use of semantic HTML5 tags (such as <article>, <section>, <aside>, or <nav>) informs the bot which part of the page is the main message and which is only a supporting element.
- Loading speed is crucial: AI models that browse the network in real-time (like Perplexity or SearchGPT) have a limited context window (the amount of data the model can process at once). If your page loads too slowly or its structure is too convoluted, the bot may only retrieve a fragment of the data or incorrectly assign priorities to information.
Example: At Brave New, we solve this problem by eliminating unnecessary code layers. We build projects based on the proprietary BerkaWP starterplate, which generates only the necessary HTML tags. Thanks to this, AI bots see your information architecture in a transparent and organized way, which directly translates into higher accuracy of LLM-generated responses about your brand.
2. Structured Data (Schema.org): Labels That AI Reads
HTML code is responsible for the readable skeleton of your page, and Schema.org is direct instruction for artificial intelligence. It is a metadata language that translates human description into parameters understandable to databases. Thanks to it, the bot does not have to guess what is an offer, what is a customer review, and what is an expert’s name.
- Present facts, instead of counting on interpretation: Instead of forcing the AI to guess whether a given string of digits is a price or a phone number, we provide it in JSON-LD format (“telephone”: “+48 123 456 789”). Thanks to this, the models immediately know that the given element is a specific product, price, or positive customer review.
JSON-LD format is recommended by Google and is AI-friendly.
- Build a Knowledge Graph: A Knowledge Graph is a digital data structure that connects scattered information about your brand into a logical network of connections between people, services, and facts, enabling artificial intelligence to understand the context and relationships in your business. Properly implemented Schema allows AI to associate your brand with specific people (Entity), locations, and services. It is thanks to this data that your company can appear in direct comparisons of offers generated by AI.
3. Content Architecture: Formatting for “Zero Result”
AI is not looking for keywords, but for specific answers to user queries. What can you improve in this area?
- Format for scanning: Use a clear hierarchy of headings (H1-H4). They should form a logical sequence of questions and answers.
- Tables and lists as a “road map”: Data presented in a table (e.g., comparison of service packages or technical specifications) or in the form of a list is much easier for ChatGPT to process than the same description hidden in a long paragraph.
- Add FAQ sections that are the engine of AEO: Users ask AI questions in full sentences. Creating an FAQ section with specific definitions (“What does the implementation process look like?”, “What does an AEO audit include?”) makes your content an ideal candidate for a “zero result” in answer engines.
- Specific answers at the beginning: Use the inverted pyramid principle—the most important answer to the customer’s question should appear in the first paragraph of the section.
Content Issues: How to Prepare Website Content for AI?
4. Authority and E-E-A-T (Experience and Trust)
What is E-E-A-T?
E-E-A-T is a set of Google guidelines used to assess content quality based on four key pillars: Experience, Expertise, Authoritativeness, and Trustworthiness.
These pillars are assessed based on verifiable evidence confirming the author’s competence, the quality and uniqueness of the published content, and the reputation and recognition of the brand in credible external sources. In other words, E-E-A-T is proof for Google and AI that you are not another anonymous bot, but a real, flesh-and-blood expert.
AI promotes sources it considers credible.
How to prove your expertise to the bots?
- Case Studies with real data: AI learns from facts. Publishing specific results (like our statistics on lead acquisition through AI) builds your authority in the eyes of algorithms. The format Problem > Solution > Numerical Result can be useful for content creation.
- Expert Signatures: Every substantive article should have an assigned author. AI analyzes the connections between specific people and their knowledge available online (e.g., on LinkedIn or industry portals).
5. Visibility Beyond Your Domain
AI learns from the entire internet. Your brand must be present in places that models consider credible knowledge bases.
- Closing the Authority Loop: Your site must link to your profiles on external services (business directories, LinkedIn, industry rankings), and they should link back to you. This creates a cohesive knowledge graph of your brand.
- Industry portals and review aggregators (e.g., Clutch): A signal for the models: “This brand is active and recommended by others.”
- Google My Business Profile: An essential element in building local and global trust in the Google ecosystem (Gemini).
Substantive publications on external portals (e.g., guest posts) and active social media are a signal for the models: “This brand is active and recommended by others.”
FAQ – Most Common Questions about AEO
What is the difference between SEO and AEO?
Although both fields aim to increase a brand’s visibility online, their fundamentals and the way information is delivered differ significantly. Traditional SEO (Search Engine Optimization) focuses on fighting for the highest position in the link ranking, trying to attract the user directly to your site. In contrast, AEO (Answer Engine Optimization) is the game of being the “only right answer” that the AI model will generate and present to the user without the need to click on any links. The table below shows the key differences in the approach to both strategies.
| Feature | Traditional SEO | Answer Engine Optimization (AEO) |
|---|---|---|
| Goal | High position in search results (SERP) | Being the generated answer in the AI chat window |
| Consumption Method | User clicks a link and searches for information | AI provides a ready-made solution with attribution |
| Keywords | Short phrases (e.g., “white label agency”) | Natural language queries (e.g., “who do you recommend for…”) |
| Main Factor | Domain authority and links | Data credibility and clarity of code structure |
How to check if my site is visible in AI?
The simplest way is to ask the question directly in ChatGPT or Perplexity: “What do you know about [Your Brand]?” or “Who do you recommend for [Your Service]?”. If the AI does not mention you, it is time for AEO optimization.
Will AEO replace traditional SEO?
No, AEO is an evolution of SEO. Traditional search engines still generate traffic, but answer engines are taking over the research and vendor selection stage, especially in highly specialized services.
How much does it cost and how long does it take to implement an AI-First strategy?
The first effects in the form of improved content understanding by bots are visible after just a few weeks from the implementation of clean code and structured data. The cost depends on the scale of the service, but it usually pays for itself quickly through the higher quality of leads acquired.
Effective online activities currently depend on three pillars: “bulletproof” development that removes barriers between code and the bot, high-quality content that genuinely addresses user problems, and consistent authority building (E-E-A-T). Only the combination of flawless technical architecture with substantive knowledge makes artificial intelligence recognize your brand as a credible leader worth recommending further.
At Brave New, we do not guess how AI works: we implement standards that we have tested ourselves in battle. We will help you eliminate unnecessary technical “noise” and optimize your site in a way that makes it visible to AI – Contact us.