How to check and fix what AI says about your hotel

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What does AI say about your hotel, and why does it matter?

SiteMinder’s Changing Traveller Report found that 80% of travellers now want AI assistance at some stage of their booking journey. Part of this is using ChatGPT, Gemini, Perplexity and Copilot to research, discuss, and choose accommodation. 

What an AI says about your hotel depends on what you say about yourself and how well you have set up your content on your website, OTA listings, social media, and other public platforms. 

While a traditional search engine returns dozens of blue links and lets the traveller sort them, an AI assistant does the sorting itself, narrowing to a handful of named properties and, crucially, describing each one in a sentence or two based on the original query. 

Being described accurately and being bookable are two separate achievements. Being described accurately is the owned-media layer, which you can start auditing immediately. Read our full blog for the wider picture of how AI is reshaping hotel discovery. Being bookable is the live-inventory layer, the plumbing that lets an assistant retrieve your real rates and put a guest on a path to a reservation, which we covered in how AI books hotels. 

This blog will provide a guide to auditing what AI currently says about your hotel, understanding why it gets things wrong, and fixing your content so that guests get the right information.

How do AI assistants decide which hotels to recommend?

When a traveller asks for hotel recommendations, an assistant synthesises an answer from several layers at once: 

• Knowledge baked into the model during training
• Live retrieval from the web at the moment of the query
• Third-party signals such as OTA listings, directories and review platforms
• Structured data it can parse cleanly from your own pages

The important thing to understand is that when information about your property is thin or contradictory, the assistant fills the gap with its best guess. The problem is that a plausible-sounding guess about your cancellation policy or your distance from the beach might satisfy the guest at the time, but it could lead to disappointment and disgruntlement down the line. 

An analysis of more than 131,000 properties across 30 countries found that only around 16% of global hotel supply appeared consistently across ChatGPT, Google’s AI and Perplexity. The rest are either invisible or being described from a shallow pool of data.

Two other factors at play include the detail that each assistant also reads a different pool of sources, so appearing prominently in one is no guarantee of appearing in another, and a strong Google ranking no longer travels with you automatically since AI tools draw upon so much more than SEO content to surface responses.

From described by AI to bookable through AI

Getting your content right makes AI describe you accurately. SiteMinder puts your live rates and real availability into the assistants themselves, so travellers can go from a recommendation to a confirmed reservation.

Learn more

How can you check what AI currently says about your hotel?

Before changing anything about your website or content, you first need to run a structured audit of what AI assistants say about you right now, and record it so you have a baseline to measure against once the fixes are done. 

1. Ask the biggest AI assistants, not just the one you use: Run your queries through ChatGPT, Gemini, Perplexity and Copilot at a minimum. Each draws on different logic, so you need to treat them as four separate audits. You’ll even find that Google’s Gemini may differ from Google AI Mode.
2. Run brand queries first: Ask “What can you tell me about [your hotel name] in [your city]?” and “What are the room types and amenities at [your hotel name]?” This tests what the assistant thinks it already knows about you or how well it can access your content. Any invented details will show up here.
3. Send general queries the way a guest actually would: Ask “Recommend a family-friendly hotel near [landmark] under [budget]” or “Best boutique hotels in [neighbourhood] for a couples’ weekend.” This tests whether you appear at all when the traveller isn’t already looking for you, which is more valuable.
4. Record when you appear and how you are described: For every answer, note whether the assistant named you, where you placed in the list, which competitors appeared alongside you, and whether the details it gave are correct. Flag anything wrong or missing as something to investigate.
5. Note which sources the answer cites: Most assistants will show or can be asked to reveal how they sourced the information they provide. If an outdated listing or a third-party page is feeding a wrong detail, you know exactly what to correct. 
6. Repeat the audit on another day: Testing something once generally doesn’t prove anything. Results that are repeated tell a much stronger story and will give you a clearer picture about where to focus.

When you’re finished you’ll have a documented snapshot of your machine-generated reputation, ready to reference when you’ve made updates to your online presence. 

Why does AI get hotel information wrong?

AI ‘hallucinates’ or gets things wrong because it finds gaps where it can’t directly solve the user’s query, or it finds outdated information. Here are the most common reasons:

• Thin or missing data: If your own site says little about your rooms, policies and setting in plain, extractable language, the AI has nothing solid to go off and improvises instead.
• Stale information lingering on the web: This might be an old renovation announcement, a restaurant that closed, or a price from a season that has passed.
• Conflicting details across your listings: When your website, your OTA profiles and social media pages each state a slightly different check-in time or room count, the assistant has to pick, and it may not pick the accurate one each time.
• Weak entity presence: If you’ve never claimed and optimised a profile like your Google Business Profile, the web has never clearly established that “[your hotel name]” is a specific, real, singular place with a fixed set of attributes. As a result the AI model struggles to anchor its answer to you at all.
• No structured website data: Without machine-readable markup telling an AI assistant exactly what it is looking at, your best content can be misread or skipped.
• Blocked crawlers: If your site refuses the bots that feed the assistants, your most accurate source of truth, your own website, is invisible to the very systems describing you.

How can you fix and improve what AI says about your hotel?

The audit you perform will surface a few specific details to fix, but there are a number of factors in your control which you can optimise including your website, your public listings, your reviews, your markup, and more. Here’s your starting point:

• Add structured data to your own site: Implement schema markup (specialised code that uses machine-readable vocabulary such as categories) so assistants can parse your rooms, location, amenities and policies as unambiguous facts rather than guessing. This is the single clearest way to hand a machine what it needs to know.
• Make your brand consistent across the web: Your name, address, phone and core facts should match across your Google Business Profile, the major directories, and Wikidata. Consistency is what tells the model you are one real establishment.
• Treat reviews as a signal, not just social proof: Assistants read review platforms heavily, and the language guests use to describe you feeds directly into how you are described by AI tools. Encourage reviews, respond to them, and watch for the recurring phrases that AI might be picking up.
• Write content that answers real guest questions: Publish clear, self-contained answers to the questions guests actually ask. An FAQ section on your website is the perfect way to do this.
• Open the door to AI crawlers: Check your robots.txt and confirm you are allowing the retrieval bots that power AI answers. Consider an llms.txt to point assistants at your best pages. A site that blocks these bots has erased its most authoritative source.
• Double down on consistency: Make your website, your OTA listings and your social profiles tell one consistent story about pricing, policies, and amenities, so there is nothing for the assistant to have to choose between.

There are also distribution pillars that help you get shortlisted by AI, which you can learn about in how AI travel agents shortlist hotels.

How do you keep your hotel accurate in AI over time?

The way AI tools are trained and learn is always changing, just like search algorithms are always changing. So you can’t treat this exercise as a ‘one and done’.

Establish a rhythm of re-running your audit on a regular cadence. Every few months is recommended as this is manageable from a time and effort perspective, and allows enough change to happen to make it worthwhile. Each pass compares against the baseline you recorded and tells you, in a few minutes, whether the machine’s account of you still matches reality.

Run an extra check after anything that changes the facts such as a renovation, a rebrand, or a major repricing, so you can ensure that the AI assistants aren’t describing a version of your hotel that no longer exists. 

What’s the difference between being found by AI and being bookable through AI?

Everything above gets your hotel found and described accurately, and it does so through media you own and control. It’s something many properties neglect and is half the battle if you get it right.

Being bookable through AI; putting your live rates and real availability directly into the assistants so a conversation can become a confirmed reservation, is an infrastructure challenge rather than a content one. This is where SiteMinder’s AI distribution comes in, and the mechanics of how a live rate travels into an AI answer and back out as a booking are laid out in how AI books hotels. Think of it as the difference between an assistant knowing you exist and describing you well, and an assistant being able to sell a room on your behalf. You ideally want both. 

Frequently asked questions about your hotel’s AI visibility

Can you control what ChatGPT says about your hotel?

Not directly but you can strongly influence it. You can’t dictate ChatGPT’s exact wording the way you can edit your own website, but you can shape the evidence it draws upon such as accurate structured data, a consistent brand presence online, positive reviews and crawler access. 

Do AI assistants read your Google reviews?

Yes. Review platforms, Google’s included, are among the sources assistants lean on most when describing and recommending hotels, partly because reviews are recent, specific and written in the language real guests use. 

Is AI visibility the same as SEO?

They overlap but they are not the same. Traditional SEO optimises for a ranked list of links on a search results page; AI visibility, sometimes called AEO or GEO, optimises for being read, understood and accurately described by an assistant that returns a synthesised answer rather than a list. Many SEO fundamentals still help, like clean crawlable pages and good content, but a strong search ranking no longer guarantees you appear in AI answers.

Which AI assistants matter most for hotels to check?

For most properties the priority set is ChatGPT, Gemini, Perplexity and Copilot, with Google’s AI surfaces close behind given their reach. Because each reads a different pool of sources, you cannot treat them interchangeably; a clean answer in ChatGPT tells you nothing about what Perplexity might be saying. Check all four at minimum, and weight your attention toward whichever your own guest data suggests your travellers are actually using.