When travellers ask AI where to stay, some properties appear automatically — and others don’t. Lucy Clifton demystifies Generative Engine Optimisation (GEO), how it differs from traditional SEO, and how brands build the authority AI systems rely on.
For centuries, travellers have relied on intermediaries to navigate the unfamiliar — from the handwritten itineraries of the Grand Tour to Murray’s Handbooks of the 1830s, Michelin’s culinary stops and Baedeker, which came to define travel itself. In the 19th century, young travellers crossed Europe carrying the crimson guide in their luggage, trusting its verdicts with near-religious devotion. Baedeker didn’t merely describe the world. It filtered it, and its ratings shaped the fortunes of hotels and cities alike, directing the flow of travellers across Europe. Inclusion meant recognition. Omission consigned even the finest establishments to obscurity.
Today, the gatekeepers have changed, but the instinct to defer to them has not. Guidebooks gave way to travel agents, online booking platforms and search engines, which reshaped how travellers discovered hotels entirely. Now, a new authority is emerging — one that does not present a list of options, but defines the answer itself. In practical terms, inclusion influences which hotels are considered, shortlisted and ultimately booked.
When Anthropic began rolling out an AI agent in late 2024, it marked the arrival of something fundamentally new: a system capable of using computers as a human would, navigating browsers, interpreting information and taking action. OpenAI and Google followed, signalling a shift from artificial intelligence that answers questions to intelligence that shapes decisions.
The hotel sector — long frustrated by the fees online travel platforms impose, ranging from 15 per cent to 20 per cent — heralded the technology’s potential.
The European hotel association HOTREC has warned that while AI agents may reduce reliance on online travel agencies, they risk creating a new “dependency cycle” in which visibility is determined not by search rankings but by inclusion in AI-generated responses. In short, AI is not removing gatekeepers. It’s becoming one.
Hey ChatGPT, what’s the best hotel in…?
Travellers increasingly begin their research by asking AI questions. Where should I stay in Paris? What are the most romantic hotels in Mallorca for couples? Where to stay in Tokyo for design and culture? What are the best luxury hotels in Dubai? In answer, AI systems do not present an open landscape. They edit a selection — one shaped by Generative Engine Optimisation (GEO), the discipline that determines which hotels appear and which remain invisible.
Travellers don’t receive ten links. They receive an answer. That answer includes some hotels and excludes others. Meaning the most important travel recommendations now come from systems that never visit your website.
As AI systems become a primary gateway for discovery, GEO is emerging as a critical component of digital visibility for luxury hotels. It does not replace traditional SEO. It determines whether your hotel appears in AI recommendations for where travellers should stay.
Defining Generative Engine Optimisation
Many artificial intelligence terms have now entered mainstream dictionaries. Chatbot was recognised in 2018, reflecting the rise of conversational interfaces. More recently, dictionaries have expanded the meanings of existing words to include AI-specific senses: prompt now refers to the instruction given to an AI system, while hallucination describes a confident but incorrect response generated by a model. Although Generative Engine Optimisation hasn’t yet appeared in dictionaries, it’s already defining which hotels appear in AI-generated answers.
If there were a dictionary definition, it would probably read:
Generative Engine Optimisation (GEO) noun: The practice of structuring digital content, data and online presence so that generative artificial intelligence systems recognise, understand and cite a brand, property or entity when producing responses to user queries.
Unlike traditional search engines, generative systems don’t present ranked lists. They synthesise information into direct responses. Hotels are not ranked. They are selected.
The implications of this shift are explored in Spotlight Communications’ recent white paper, developed in collaboration with digital visibility consultancy Make Lemonade Fizz. Our findings point to a broader structural change across the luxury hospitality sector, as AI-driven discovery reshapes how hotels are encountered. As its co-founder Maria Sze explains, “Every credible mention is now machine-readable proof of trust.” As she puts it more bluntly: “AI doesn’t read your ads. It reads your reputation.”
Where SEO determines whether your website appears in search results, GEO determines whether your hotel appears in the answer itself.
This is a fundamentally different form of visibility. Generative Engine Optimisation determines whether your hotel is included in the answers travellers now rely on to decide where to stay.
SEO versus GEO
Search used to be about getting to the top of the page. Now it’s about getting to the answer.
Search Engine Optimisation helps hotels climb the Google rankings, putting them in front of travellers who are actively browsing. But Generative Engine Optimisation plays a different game. Instead of chasing clicks, it determines whether a hotel is mentioned at all when someone asks AI where to stay.
SEO is built on links, keywords and technical performance. GEO is built on clarity, credibility and recognition — ensuring AI systems understand exactly what a hotel is and trust it enough to recommend.
The distinction is simple but profound. SEO brings visitors to your website. GEO decides whether travellers hear your name in the first place.
And as more travel decisions begin with a question to AI, that difference is becoming decisive.
Why Luxury Hotels Should Care About GEO
Luxury travellers have always been early adopters of new technologies — from booking villas online in the early days of Airbnb to adopting digital concierge services and biometric airport processing. AI-assisted planning follows the same pattern, with systems such as ChatGPT and Perplexity shortlisting destinations, comparing properties, and refining decisions before a traveller has visited a single hotel website.
By the time a traveller clicks, much of the selection has already happened.
When someone asks AI to recommend the best luxury hotels in Mallorca, or resorts with meaningful conservation programmes, or places in Tokyo known for design, the system doesn’t generate an exhaustive list. It produces a defined answer. Certain hotels are named. Others are not.
For example, when travellers ask ChatGPT for design-led hotels in Copenhagen, Hotel Sanders or Nobis Hotel appear consistently. When travellers ask for the best hotels in Cannes, the answer usually includes Spotlight’s client Hôtel Martinez, (“The legendary Art Deco palace with private beach, right on the Croisette”) and Carlton Cannes (“The quintessential Riviera grand hotel, loved for its Belle Époque vibe”). If asked for the hotels with the best views on Lake Como, the top three usually include Grand Hotel Tremezzo, Passalacqua and another Spotlight client, Grand Hotel Villa Serbelloni. None of these hotels are there because of advertising, but because their editorial coverage, structured listings and clear positioning make them legible to AI systems.
These properties become the reference points against which alternatives are judged. Those excluded are entirely absent from the decision.
This shifts the moment at which visibility matters. Discovery is no longer determined solely by search rankings, advertising spend or brand recognition. It’s shaped earlier — at the point where AI systems assemble the shortlist itself.
For luxury hotels, where positioning, perception and reputation drive long-term value, inclusion at this stage is critical. Because before a traveller can choose your hotel, they must first encounter it.
The GEO Cheat Sheet for Hotels
If AI doesn’t recognise your hotel clearly, it can’t recommend it. But recognition alone isn’t enough. Generative systems favour information they can understand, trust and reuse with confidence. That depends on three further factors: precision, authority and relevance.
1. Be specific enough to be cited
AI systems don’t respond well to vague marketing language. They favour clear, factual statements they can extract and repeat accurately.
Claims such as “world-class luxury” or “unforgettable experiences” carry little meaning to a machine. Specific details — beachfront location, 42 suites, resident marine biologist, Michelin-starred restaurant — are far more useful. They give AI systems something concrete to work with.
The easier it is to describe your hotel precisely, the easier it becomes to recommend.
2. Be present where AI looks for truth
Generative systems are trained on, and prioritise, sources they recognise as authoritative. Editorial coverage in respected publications, inclusion on established travel platforms and accurate presence across trusted databases all strengthen credibility.
This is where PR takes on a new function. It is no longer simply about visibility to human readers. It is about establishing your hotel as a recognised entity within the wider information ecosystem that AI systems rely on.
Hotels that appear consistently in authoritative sources become easier for AI to trust — and more likely to be cited.
3. Answer the questions travellers are actually asking
GEO is shaped not just by what you say, but by how closely it matches real traveller questions.
Increasingly, the questions travellers ask AI follow clear patterns. Where should I stay on the Amalfi Coast? What are the best boutique hotels in Marrakech? Which hotels in London are known for the best cream teas? These are not abstract searches, but direct requests for recommendations. Generative systems respond by naming specific properties — and the hotels included in those answers enter consideration first.
Content that answers these questions directly is more likely to surface. Content that remains generic is easier to overlook.
The clearer and more relevant your information is, the easier it is for AI systems to connect your hotel with the traveller seeking it.
Paywalls and the New Architecture of Visibility
Not all editorial coverage is equally visible to generative systems. In practice, publications fall into three categories — open access, soft paywalls and hard paywalls — and each contributes differently to how AI understands and recommends hotels.
Open-access publications, including Forbes Travel Guide, Country & Town House, Afar and CN Traveller Middle East, are fully legible to AI systems. Their content can be read, interpreted and reused directly, helping generative engines understand what a hotel is, how it is positioned and why it matters.
Structured hotel platforms play an equally important role. Curated networks such as Mr & Mrs Smith and Leading Hotels of the World provide clearly defined, factual property profiles — consistent naming, verified attributes and standardised descriptions. AI systems love these because the information is structured, factual and consistent.
As a result, these platforms often exert disproportionate influence. They don’t simply describe hotels. They help define them within the information layer AI systems rely on when generating recommendations.
Soft paywalled publications, including Condé Nast Traveller, Travel + Leisure and National Geographic Traveller, operate metered or subscription models while still allowing partial access to AI models. Here the editorial is influential because it combines accessibility with institutional authority. Even when full articles are restricted, their structure, metadata and wider citation footprint help reinforce how AI systems interpret a hotel’s credibility.
Hard paywalled publications, such as the Financial Times, The Wall Street Journal and business travel platforms such as Skift, contribute a different but equally important signal. Their strict subscription models reflect rigorous editorial standards, fact-checking and institutional credibility — qualities generative systems are designed to prioritise.
AI systems do not rely solely on unrestricted access to full articles. They also interpret headlines, summaries, metadata, and the wider network of citations surrounding authoritative publications. Coverage in these environments helps establish a hotel as a verified, recognised entity — reinforcing its credibility within the information ecosystem generative models use to form recommendations.
In this way, hard paywalled publications shape not just what travellers read, but how AI systems understand which hotels are trustworthy enough to recommend.
Together, these layers form the knowledge infrastructure generative systems rely on. Open-access coverage helps AI understand a hotel’s identity. Soft paywalled editorial reinforces its credibility and context. Hard paywalled publications strengthen their authority.
Hotels that appear consistently across all three environments are more likely to be recognised, trusted, and recommended when travellers ask AI for recommendations on where to stay.
The future of hotel discovery
Each transition in travel discovery has redrawn the map. Guidebooks defined the routes of the Grand Tour. Travel agents and concierge networks shaped the movements of the 20th century. Search engines reordered the landscape again, determining which hotels travellers encountered first.
Generative systems are now beginning to do the same, marking the beginning of a deeper shift. Until now, travellers have used tools to inform their decisions. Increasingly, those tools are beginning to act on their own behalf. AI systems are evolving from guides into agents — systems capable not only of recommending hotels, but selecting and booking them in accordance with a traveller’s preferences, history and intent. As Maria Sze observes: “AI is the new concierge — hotels need to tell it their story before someone else’s becomes the default.”
The map of travel discovery is being redrawn once again. What follows next will not be a return to open exploration, but a new geography defined by recognition, trust and inclusion within the systems travellers increasingly rely on to navigate the world. For hotels, the implication is clear: visibility must be engineered not just for search engines, but for the AI systems increasingly shaping travel decisions.
Glossary
The key terms shaping how travellers discover hotels through AI
| Term | Definition |
|---|---|
| AI answer interfaces | Answer-based search features, including Google’s AI Overviews, that generate summaries and hotel recommendations within search results. |
| Entity | A hotel, brand or destination that AI systems can clearly identify, understand and reference. |
| Large language models (LLMs) | Including ChatGPT and Claude, LLMs are artificial intelligence systems that generate human-like responses to traveller questions. |
| AI search platforms | Search tools such as Perplexity, that produce direct hotel recommendations instead of traditional lists of links. |
| Generative EngineOptimisation (GEO) | The practice of ensuring a hotel’s digital presence is clear, consistent, and authoritative so that AI systems recognise and recommend it in generated answers. |
| Structured data | Standardised hotel information that helps AI systems interpret facts such as location, amenities and brand identity. |
| Authority signals | Trusted references, including editorial coverage and verified platform listings, that help AI systems assess a hotel’s credibility. |
| Knowledge platforms | Structured travel platforms, such as Mr & Mrs Smith and Leading Hotels of the World, that provide reliable hotel data used by AI systems. |
| Reputation layer | The network of trusted references, editorial coverage and platform listings that AI systems rely on to evaluate and recommend hotels. |
| Citation | The inclusion of a hotel within an AI-generated answer or recommendation. |
