AI search offers a valuable new marketing channel for hoteliers. Planning a vacation is a complex task that traditionally involves countless searches, browser tabs and hours of comparing options.
Based on a simple prompt, generative AI can provide travelers with:
Generative AI tools (like ChatGPT) and AI agents (like OpenAI Operator) are becoming travel planners, meaning hotels need websites that AI can easily read, interpret, and make reservations.
AI agent ready websites need to allow agents to access “key Information” quickly including product details, pricing, reviews, and availability without human intervention, ensuring accurate responses to user queries.
An AI LLM is a Large Language Model—a type of artificial intelligence designed to understand, generate, and reason with human language.
In practical terms, an LLM:
In the context of search and discovery, LLMs power AI assistants and AI-driven search engines:
As AI search increasingly replaces traditional search engines, hoteliers need to update their website in order to be found by potential guests. This is because conventional websites are designed for humans, emphasizing visual presentation, navigation, and overall user experience. By contrast, AI agents engage with websites through structured data and metadata interpretation. When a site is not optimized for these interactions, hoteliers can risk missing out on traffic and potential travelers who increasingly depend on AI-powered tools.
To shape AI-driven recommendations, it’s essential to understand how information flows from your internal systems into the models themselves. Hotels often rely on fractured sources of information coming from their PMS, CRS, channel managers, CRMs, and review platforms. With each platform storing slightly different variations of the same thing, a disjointed picture of the most pertinent information creates friction points for AI – LLMS.
The challenge is consistency. Large language models (AI - LLMS) perform best when they identify a unified, reliable representation of your hotel property across all touchpoints. If one system lists a SPA, another leaves it out, and a third calls it something else, the model’s confidence erodes. In that uncertainty, it may favor a competitor whose data points are cleaner and more consistent.
Many issues that cause AI overviews or planners to skip your property stem from these quiet inconsistencies, not from a lack of keywords. Aligning your data across systems provides AI - LLMs a stable foundation of facts to work with.
Five strategies designed to make your website AI - LLM-friendly include:
What is Semantic HTML?
Think of it like “labeling” boxes in storage. Instead of using blank boxes (or , which don’t say much), you use boxes with clear labels like:
When your website uses these tags correctly, AI tools can instantly identify the most important content and where to find it.
It is easier for AI agents to “read” your website when it is structured using Semantic HTML. Well-defined header tags make your content more readable. Using Semantic HTML can help clearly indicate what each part of your site refers to and not just how it looks.
If you have been optimizing your website, you might have already heard of SCHEMA. It’s an old SEO technique that has made a comeback, thanks to AI and AI LLM search.
Schema markup is like a “hidden label” you can add to various pages of your website so that it becomes easier for search engines, and now AI agents, to understand what your content is about.
For example, if you already indicate a certain page is a blog post - with the help of schema, it becomes easier for search engines and AI agents to understand what type of content to expect from the page.
Schema relies on a standardized vocabulary from Schema.org that is recognized by Google, Bing, ChatGPT-style AI agents, and other platforms. As a result, while human users typically see only the meta title and meta description on a search results page, search engines and AI agents can access far richer contextual information when Schema is used.
Depending on your hotel - here are some common schema types you might want to use:
Standardization starts with deciding how you will name and categorize every amenity, room type, and policy, then making sure to use those exact labels everywhere.
Instead of embedding features within broad marketing language, use clearly labeled sections—such as “Roof Infinity Pool,” “Family Suites,” “Pet Policy,” or “Conference Facilities”—and describe each with two to three concise, factual sentences.
Plan and create distinctive and well-structured pages or sections for:
AI driven LLMs frequently extract and recombine such content into responses. For example : “This hotel features a rooftop infinity-edge pool, pet-friendly accommodations, and family suites with separate living areas.” The clearer and more precise these content elements are, the more accurate and persuasive the resulting synthesized descriptions will be.
AI-powered search extends beyond simple keyword matching. Large language models such as ChatGPT, Gemini, and Claude favor well-structured, FAQ-oriented content.
When implemented effectively, FAQ-driven content strengthens AI visibility, supports stronger search performance, and drives higher engagement. This strategy extends beyond traditional SEO, ensuring that content is optimized for AI-powered search engines and conversational interfaces.
How to Write FAQ-Driven Content for LLMs
Use search insights from Google’s “People Also Ask,” Search Console, and AI chat
interactions.
Look at competitor FAQs and industry-specific AI queries to see what’s ranking.
Keep answers brief and direct—LLMs prefer responses under 50 words.
Address the core of the question immediately, then provide additional details if needed.
Format each question as an H2 or H3 so AI can recognize them easily.
Use bullet points and numbered lists for easy data scanning.
Include relevant terms in both the question and answer.
For AI Optimization (AIO), consider phrases that AI tools favor in search results.
Use FAQ schema to improve visibility in rich results and AI-generated responses.
AI prioritizes fresh content, so revisit and refine FAQs regularly.
Track which questions AI surfaces and adjust based on performance.
If you haven’t already - create a well-structured, extensive FAQ page on your website to address relevant questions in a straightforward way. Remember to talk about topical issues like: “What potential guests will ask about”: your accommodation, destination, region and country during their research or planning phase?.
For example:
Query: Which hotels in Bangkok are easily accessible from the airport by public transport?
FAQ: Is the Asoke Hotel easily accessible from the Bangkok airport by public transport? Yes, Asoke Hotel is easy to reach by train and bus from the airport in less than 30 minutes. (Make sure to include further details about the train/bus guests can take.)
Query: Are pets allowed in Asoke Hotel Bangok ?
FAQ: Are pets allowed in Asoke Hotel Bangkok ? Yes, pets are welcome to stay at Asoke Hotel Bangkok. We just ask that you inform us in advance if you plan on bringing your fluffy friend.
AI - LLM’s tend to prioritize content that is regularly updated. Websites with stale, outdated information can be penalized in AI recommendations, as AI - LLMs prefer fresh, current content that reflects the latest details.
What to do:
Maintain a blog or news section with monthly updates about local events, seasonal packages, promotions, and any new hotel offerings.
Clearly label updated pages with a visible date (for example, “Updated Dec 2025”) to signal to AI models that the content is actively maintained and regularly refreshed.
AI - LLMs tend to prioritize content that demonstrates recency and relevance. When your site is regularly updated, it signals to AI that your hotel is actively engaging with current trends, which can improve your visibility in search results and boost your chances of being recommended.
Conclusions:
As AI-powered search engines and conversational models continue to advance, hotels that do not optimize their websites for LLMs risk falling behind. The 1st mover advantage not only preserves competitiveness, but also strengthens direct booking channels and reduces reliance on costly OTAs.
As AI-driven discovery reshapes the hospitality sector, hotels that act early on AI optimization will secure a clear competitive lead, ensuring visibility in AI-generated recommendations while slower-moving competitors fall behind.
The conclusion is straightforward: by optimizing for LLMs now, hotels can establish leadership in AI-powered search and benefit from outsized visibility as adoption rapidly expands.
