How to position your brand in AI conversations with Agentic eXperience
The world of search engines has changed radically. Looking back, search engine optimization (SEO) consisted almost entirely of pleasing traditional crawling and structured indexing algorithms. Today, users no longer just look for a list of links; they interact directly with virtual assistants, large language models (LLMs), and generative search engines like ChatGPT, Gemini, Perplexity, or AI Overviews.
Faced with this reality, a critical question arises for any digital business: What does an Artificial Intelligence see when it reads your website? If your platform is not prepared, you run the risk of becoming completely invisible to the most important discovery channels of the moment. To solve this problem and open the doors to new digital traffic, it is essential to understand how to unify traditional SEO with GEO (Generative Engine Optimization).
Key concepts for AI positioning
To gain visibility in the answers that AI assistants offer to users, the digital strategy must evolve and integrate three disciplines that complement and enhance each other:
What is AX (Agent Experience)?
This focuses on the technical infrastructure. It ensures that autonomous agents and AI can navigate, read, and execute actions on your website without technical friction (DOM, JS, rendering).
What is AEO (Answer Engine Optimization)?
It seeks the immediate answer. It optimizes structured data to win the featured snippet (snippet) or the direct answer to specific user questions.
What is GEO (Generative Engine Optimization)?
Focused on deep knowledge. It is the strategy aimed at entering the training corpus and the model’s memory to consolidate your brand as the semantic authority in your sector.
Key note: Most shared actions benefit both channels. Doing GEO correctly also implies optimizing traditional SEO, as both feed on semantic clarity and technical accessibility.
What is making you invisible to LLMs
Often, brands assume that having a good ranking on Google guarantees appearing in chatbot recommendations. However, there are invisible technical barriers in traditional analytics reports that severely penalize agentic conversion:
1. Silent WAF blocks
It is very common for a server’s security rules (WAF) or the robots.txt file to block the activity of navigational agents by default. For example, if the ChatGPT agent tries to access your catalog to show real-time offers and the connection is rejected by the firewall, your brand becomes invisible to that user, diverting the opportunity to the competition.
2. Inconsistency of dynamic data
In sectors with high stock or rate fluctuations (like tourism or retail), sometimes one price coexists in the structured data (Schema markup), another in the static HTML, and a different one loaded dynamically by JavaScript. LLMs, unable to validate a coherent price or interact like a human, lose trust in the source, stop citing it, and send the user to competitors whose data is consistent.
3. Obsolete content on orphan pages
AI crawlers index massively. If you keep old or discontinued pages on your server that lack internal links, AI models can still find them and use them as a current source of truth. This causes misaligned or “hallucinated” responses that damage user trust.
Agentic eXperience: Luce IT’s SEO and GEO solution
To solve these pathologies before they affect your business, Luce IT has developed Agentic eXperience (AX), an innovative solution that audits, adapts, and monitors your web platform to turn it into the definitive source of truth for generative engines.
Our methodology addresses the problem progressively and frictionlessly, divided into key phases:
- Phase 1 (Audit + Roadmap): We execute real tests of how AI agents access and interact with your website. We identify blind spots in dynamic content extraction and optimize semantic HTML along with structured data. In addition, using tools like Quantum Metric, we prepare your environment to analytically separate human traffic from the navigation patterns of agentic AI.
- Phase 2 (Competitive Intelligence): We evaluate brand perception and your business’s Prompt GAP against your main competitors, analyzing what models like GPT, Claude, or Gemini say about you and detecting opportunities in your main business verticals.
- Phase 3 and Future: We help deploy advanced infrastructures such as MCP (Model Context Protocol) servers to expose your tools and APIs directly to AI environments in a secure, governed manner ready for agentic commerce.
Essential KPIs to measure your success in the Generative Era
To successfully manage this transition, it is necessary to incorporate a dashboard with specific metrics that go beyond the traditional click:
| Category | Key Metric | Description |
| AI Visibility | AI Share of Voice | % of mentions and recommendations of your brand on ChatGPT, Gemini, and Perplexity compared to your competitors. |
| AI Visibility | Prompt Rank Position | Position in which your brand appears within the response text to key sector prompts. |
| AI Visibility | AI Citations / Links | Number of times LLMs formally cite your domain as a verified source. |
| Traffic and Business | Traffic from AI Search | Volume of sessions and revenue directly attributed to channels like Perplexity, ChatGPT, or AI Overviews. |
| Infrastructure | AX Score | Agentic accessibility score (correct rendering, absence of WAF blocks). |
| Infrastructure | AI Bot Crawl Rate | Crawl frequency of specialized bots (GPTBot, ClaudeBot, PerplexityBot). |
The time to act is now
The window of opportunity to shield your business’s visibility from Artificial Intelligence is open, but it narrows every month as competitors adopt machine-ready strategies. The best thing about this approach is its efficiency: in its first phase, it requires no development or involvement from your company’s IT team, as we execute all extractions and analyses autonomously with our own tools.
Do not let your brand be left out of the conversations that define today’s purchasing decisions. To discover how to unify your positioning and prepare your technical platform, we invite you to learn all the details of our asset and request a personalized audit of your web ecosystem on Luce IT’s Agentic eXperience page.
Frequently Asked Questions about SEO and GEO
Is GEO a substitute for traditional SEO, or do they coexist?
It is not a substitute; they coexist and enhance each other. The vast majority of shared technical actions benefit both channels. For example, implementing structured data (Schema.org), having clean semantic HTML, and keeping content updated are essential requirements both for Googlebot to index your website and for AI bots to read it correctly. While traditional SEO continues to attract traffic from human users using classic search engines, GEO (Generative Engine Optimization) adapts that same information so that the memory of large language models (LLMs) chooses you as the priority response.
What is the difference between AEO (Answer Engine Optimization) and GEO?
Although both are part of the new optimization paradigm for Artificial Intelligence, they focus on different goals within the response:
- AEO (Answer Engine Optimization): Focuses on the immediate and concise answer. It seeks to optimize structured data and very specific text fragments to win the snippet or answer direct questions like “how much does it cost” or “where to buy”.
- GEO (Generative Engine Optimization): Focuses on deep and semantic positioning. Its goal is to introduce your brand’s concepts, values, and catalog into the model’s training and grounding corpus, ensuring that the AI organically considers you a trusted authority in your sector.
How can I check if my website is blocking AI bots?
There are three very common critical barriers that often go unnoticed in traditional audits:
- Firewall Blocks (WAF): Obsolete security rules that confuse AI navigational agents (like GPTBot or ClaudeBot) with malicious traffic and deny them access.
- Inconsistency of dynamic data: Platforms where price or stock varies randomly between internal microdata, static HTML, and final user interaction, destroying the AI model’s trust.
- Obsolete content on orphan pages: Old or discontinued pages that lack internal links but are massively indexed by LLM crawlers, causing outdated or erroneous recommendations.
How does dynamic content via JavaScript affect ranking in AI chatbots?
It affects it very negatively if not managed correctly. Language models acting in agent mode often struggle to execute complex JavaScript code or interact with the webpage in the same way a human would. If crucial business data—like live rates or product availability—is only painted on the screen after user interaction, the AI will see an empty page. Unable to validate the information, the chatbot will stop citing you as a source and recommend a competitor that offers readable data directly in the DOM or its microdata.
What role do editorial mentions and digital PR play in GEO?
They play a fundamental role. Since Artificial Intelligence models are trained on massive volumes of public text extracted from the internet, your brand’s reputation outside your own website is vital. Being positively mentioned and receiving editorial links in relevant media, authoritative blogs, or sector portals not only transfers domain authority for traditional SEO, but also introduces your business narrative directly into the knowledge and grounding corpus of LLMs, shaping the perception the AI has of your brand.
