Just when you thought you had SEO figured out, here comes AI travel search and shuffles hotel discovery all over again. Traditional search rankings still matter, but AI-powered answer engines and generative platforms are changing how visibility works.
More and more people rely on the suggestions from this somewhat magical and scary creature to make travel decisions. Some studies even state that 40% of travellers already use AI tools to plan trips.
Now, travellers are no longer presented with a lengthy list of blue links to click through one by one for a generic search answer. Instead, they ask highly specific questions about their needs and receive a curated shortlist of hotels that precisely match their requirements.
You’re probably wondering: How can my hotel get selected by AI?
The good news is that you are not alone. Most hotels have no visibility into how AI assistants such as ChatGPT and similar tools describe or recommend their hotels, and no idea how to control them.
We might not have the final answer yet, as things are still evolving, but in this blog, you’ll find the basics of how AI hotel discovery works in a language that you’ll understand and the first steps you can take now that will put you ahead of the competition in the discovery stage.
If you want to be able to participate in today’s marketing discussion and prepare your hotel for the present (it’s no longer the future), you need to know the codes. The first one is a well-known, long-feared friend: SEO.
SEO stands for Search Engine Optimisation, and it’s primarily concerned with how traditional search works. When a user searches for a topic or product, they get a list of possible matches based on keywords. To be ranked at the top of the list, businesses need to meet complex SEO criteria to guarantee online visibility, as people tend to click only on the first few links on the list.
Check out simple SEO best practices here
With AI tools, travellers are moving beyond simple keywords, such as “Best hotel in Rio de Janeiro.” Their searches are now much more specific, and they expect a direct, curated answer rather than a long list of possible matches.
Instead of searching for a destination, travellers are increasingly searching for a feeling or a desired outcome. When a traveller asks for a romantic hotel in Rio de Janeiro, they want one to celebrate their wedding anniversary, not a generic 'best of' list. For hotels, this shift means success hinges on the specific narrative they manage to show AI.
Here is where AEO, or Answer Engine Optimisation, plays a key role: it is the practice of structuring content so that AI-powered answer engines can quickly interpret it and generate direct responses, not just links in search results. AI tool scans structured, trusted sources to provide a concise answer specific to that traveller.
AEO requires hotels to structure their data and content in a way that aligns with how AI systems retrieve and validate information. Fundamentally, AEO best practices ensure your property’s content is clear, factual, and correctly formatted to maximise the likelihood of being referenced in an AI-generated answer.
In a nutshell, AEO supports hotel discoverability in direct answer formats.
Generative engine optimisation, or GEO, focuses on how AI models summarise and blend information about your property. Instead of pulling a short answer, generative engines create a narrative response. It shapes how your hotel is described in broader AI-generated recommendations, and it’s the first step in helping AI assistants like ChatGPT discover, understand, and recommend a hotel’s content, almost like an extension of SEO.
If AEO ensures your hotel appears when travellers ask direct questions requiring comprehensive structured data, GEO, on the other hand, ensures your hotel appears in curated recommendation sets and AI-planned itineraries, requiring a deep digital footprint across editorial, community, and review platforms.
Just like SEO efforts, hotel brands are working on GEO to make sure indexing and discoverability within the models are strong. Everything needs to be optimised for natural language as search becomes conversational.
In a nutshell, GEO supports hotel discoverability in broader contextual recommendations.
It’s important to note that both GEO and AEO influence awareness and impact discovery before the click. When executed strategically, they maximise AI search visibility. They share the same foundation, similar strategies, and there is an overlap in their approaches. That’s why in the hospitality industry, many use both acronyms interchangeably.
Since they share the same foundation, your hotel doesn’t need to have two different teams for AEO and GEO to maximise visibility. In fact, if you've been working on technical SEO for the last 15-20 years, then you've laid some really good groundwork. After all, SEO still matters, too.
Later in this article, you’ll learn simple best practises that will help you increase (or start) your AI visibility so your hotel gets recommended.
The shift is clear: travel search is moving away from traditional keywords towards intent-driven exploration. As search becomes more conversational, generative AI platforms are redefining how guests discover, evaluate, and ultimately choose hotels.
The growing trust in AI among consumers is well-supported by recent data. According to Phocuswright Research, 39% of US travellers already use AI for their trips. Furthermore, Expedia Group’s AI Trust Gap report highlights that 40% of travellers in the UK, US, and India are now using AI to build their itineraries.
As explained before, tools such as OpenAI’s ChatGPT and Google’s Gemini deliver direct, conversational answers rather than lists of links, diminishing the need to click through multiple tabs. If your hotel isn’t in that answer, you don’t exist. There’s no more scrolling through ten blue links, or hopping from link to link “surfing the web”.
This means that the hotel industry’s reliance on its own websites for bookings is facing an existential crisis from AI-powered tools. AI tools respond to queries with tailored answers, pulling from a wide range of data sources to make recommendations.
This new behaviour compresses the discovery funnel. Travellers rely on the information provided by AI and engage with it as a conversation, often without needing to click on links. In many instances, a hotel’s website may only receive clicks as the guest reaches the booking stage.
Although the website will remain a crucial direct channel, it will no longer be the only point of interaction with the hotel. Consequently, hoteliers may experience a decrease in web traffic from search.
It is also important to note that AI systems need to be able to understand your hotel and the information about it online. If a hotel’s digital footprint is generic or fragmented, AI models will default to better-documented competitors and OTAs.
Currently, only one-sixth of the world’s hotel properties appear in AI-generated search results. This presents a massive opportunity for your hotel to gain a competitive edge. As hospitality brands race to ensure they are featured in detailed AI responses, those who act now will build a significant, long-term advantage—much like the early adopters who dominated organic search during the first decade of SEO.
The one-million-dollar question is: who gets recommended?
To generate a recommendation, AI tools aggregate signals from multiple sources, including structured website data, review volume and recency, consistency across all platforms, traditional search results, and third-party mentions. The challenge for hotels is that many of these influential signals are not fully under their direct control.
A hotel’s visibility is therefore increasingly determined by the completeness and consistency of its information across all digital channels. Data on OTAs, review sites, and industry publications all contribute to how a property is perceived and whether it meets the traveller's specific requirements and desires.
A hotel’s website is no longer the sole source of truth for its identity. Inconsistencies across channels and data sources reduce AI confidence, whereas alignment and consistency significantly strengthen it. AI systems favour 'understandable' hotels—those with clear, factual information, rich content, strong reviews, and distinctive positioning are more likely to be included in recommendations.
In fact, AI search tools tend to cite third-party sources rather than brand-produced content. Many of them reference platforms such as TripAdvisor, Conde Nast and Forbes, meaning it is increasingly vital to have credible signals where third-party voices reinforce your brand’s claims. This is concerning, as nearly half of all hotel brands are currently being misrepresented.
Hotels that take a strategic approach to AI search — by structuring content, refining their narrative, and actively managing reviews and third-party profiles — stand a far better chance of being recommended. Consistency in brand messaging and information across all platforms significantly increases the likelihood of appearing in AI results. Ultimately, clear and high-quality information is essential for a property to remain visible within conversational AI recommendations.
In the snippet below, digital marketing expert Adam Hamadache, CEO of Formula Digital, discuss who appears in AI hotel search, comparing who appears on page one on Google:
To make your website AI-friendly, you must ensure it is structured so AI systems can easily crawl and interpret its data. While many hotel sites currently suffer from gaps in schema markup and structured data, prioritising these technical elements allows AI to read the underlying code rather than just the design.
Beyond technical fixes, hotels and DMOs should focus on creating original content that doesn't exist elsewhere, effectively controlling their narrative through distinctive positioning. By mapping content to specific guest preferences (such as family-friendly or wellness-centric stays), you provide the clear intent and authoritative data required to be featured in AI-generated recommendations.
Update your listings and website to ensure a cohesive brand message and high-quality content across all channels. Given that AI systems prefer information verified by third-party sources, hotels must provide clearer, more descriptive details, especially concerning amenities, location, guest type, and on-property experiences.
A new content standard rewards original property knowledge over generic, templated descriptions, favouring lifestyle hotels that invest in specific, voice-forward content and are known for their distinct offerings, not just their price. Inconsistencies—particularly in pricing and availability, which change constantly—reduce AI confidence and are likely to result in your property being excluded from recommendations or receiving conflicting outputs.
Large Language Models (LLMs) interpret and synthesise information across a range of sources, but they lean heavily toward authoritative third-party publishers and trustworthy content, such as coverage from reputable media outlets, rather than a hotel's own website visibility or self-promotion. This shift makes earned media crucial, as AI systems prioritise independent voices over brand-produced content.
Guest reviews provide the essential 'human proof' and legitimacy AI tools demand. To surface in recommendations, properties must manage review volume and ensure content is specific and factual, not merely aspirational. AI systems aggregate sentiment signals from widely indexed platforms like TripAdvisor, favouring verifiable attributes and experiences.
Critically, every AI-recommended property had an average score of 8.6 out of 10 or higher. Therefore, every guest review should be treated as a brand signal, with response strategies that reinforce exclusivity and personalisation.
Despite what some may think, AI-generated recommendations are not always trustworthy. There have been cases where it suggested destinations that do not exist, like fake restaurants, or sent tourists travelling in search of turquoise pools invented by an LLM.
While the era of unreliable travel information did not begin with generative AI (fake reviews and content farms have long existed), AI exacerbates the problem by instantly producing misinformation confidently at scale, mimicking deep expertise.
A critical issue is that AI systems can base their recommendations on outdated information, including old reviews and inconsistent property details. When a guest arrives at a hotel expecting amenities or experiences mentioned in an old review that no longer exist, it leads directly to guest frustration and a poor experience.
This problem is compounded because the most capable AI systems cite authoritative third-party sources, meaning their citation architecture is only as good as the sources they reference. Therefore, having a strong and active guest review management strategy is essential to ensure that the legitimate, current brand signals are the ones being picked up by these models.
Ultimately, the battle for visibility in the age of generative AI is a narrative competition, not one based primarily on price or location. Media outlets and other third-party voices with genuine expertise, editorial independence, and a commitment to accuracy stand to become more influential.
Travellers have always needed someone they could trust, and hoteliers must focus on controlling their brand story and cultivating trusted external signals to win the discovery stage.
As travellers increasingly shift from traditional Google searches to AI-driven planning, hotels face an urgent need to invest in an AI strategy or risk obsolescence within a short timeframe. While uncertainty remains over the development of AI travel search, hotels can already begin laying the essential groundwork.
The AI visibility competition is just starting, and the field is being levelled. This offers independent and boutique hotels a unique advantage to win direct demand by leveraging their distinct narratives in this machine-readable landscape.