Rick Posey on Navigating AI Blind Spots and Protecting Brand Perception in Modern Hospitality

2026-09-25 09:53 Insights Expert Column

Key Takeaways
Shift from Ranking to Recommendation: Traditional SEO focuses on SERP placement, but AI discovery evaluates contextual relevance, determining whether your hotel is actively recommended when a traveler asks a nuanced question.
The Source-of-Truth Gap: Over 80% of brand mentions in AI outputs are synthesized from third-party channels. Inconsistent entity data across OTAs, review platforms, and local directories directly distorts your property's narrative.
Auditing AI Share of Model: Hoteliers must measure "fact health" and competitive AI visibility to ensure generative models accurately convey distinct property attributes rather than defaulting to generic competitor profiles.

AI is already deciding how travelers see your hotel. Is it getting you right? As AI becomes part of the hotel discovery journey, visibility isn’t enough. Hotels need to know what AI is saying about them, and who it’s sending their way.

Everyone has been asking, “Are we in AI search?” But that’s not the only question we should ask. More importantly: “What version of your hotel is AI search presenting?”

AI is already shaping first impressions and influencing the shortlist before guests reach your website. WIth 91% of global travelers using ChatGPT, Gemini, Claude and other AI tools to help them plan trips, they’re not just searching for hotels. They’re asking AI for specific recommendations.

If AI misunderstands your hotel’s strengths, you may never be considered, even if your property is the better fit. Visibility alone won’t win the booking. You need to be identifiable to the right audiences, with accurate data backing up the AI search narrative.

Being Recommended Is Not the Same as Ranking

There’s an important distinction between ranking and recommending. Ranking is about appearing in a list; the holy grail of traditional SEO. Recommendation is about whether AI names your hotel when a traveler asks for advice. You can rank highly and never get recommended. You can rank much lower and still be recommended regularly. AI isn't just deciding whether to mention your hotel. It’s describing it, comparing it, and framing it for the traveler.

A guest might ask AI to recommend hotels for a romantic getaway, or support guests with specific itineraries. They might then ask which of those properties has the best restaurants, the best location, the best spa, or the best access to local attractions. Every answer shapes the next question, and every answer can influence the eventual booking decision.

How AI Constructively Defines Your Brand

Generative AI does not consume website content the way a human marketer reads it. It synthesizes information from multiple sources to build an understanding of your hotel. Your website is one part of that picture. Google Business Profile, Bing Places, reviews, press coverage, third-party mentions, and other sources can all contribute to how AI understands your property.

Where information is vague, inconsistent, or absent, the model faces a confidence deficit. This introduces immediate commercial risk:

Generic Language vs. Structured Facts: Describing a property as "conveniently located near top attractions" gives an AI engine virtually nothing to parse. A specific data point, such as "a 12-minute walk from the Metropolitan Museum of Art" provides an actionable, indexable attribute.
Entity Inconsistencies: A property listed as The Great Hotel on its direct site but Great Hotel & Suites on a secondary platform creates entity ambiguity, lowering the AI’s confidence score in connecting those references.
Outdated Information: If dining hours, amenity lists, or renovation statuses have changed on site but older references persist elsewhere online, AI engines risk surfacing inaccurate facts at the exact moment of booking consideration.

If AI doesn’t understand what makes your hotel distinctive, it may recommend a competitor that communicates those attributes more clearly. These can look like small inconsistencies. But small inaccuracies can become commercial risks.

The Foundations of AI Trust

To establish an authoritative presence within AI recommendations, hotels must cultivate digital signals that LLMs prioritize:

Structured, Specific Content: Replace vague promotional copy with explicit, factual attributes that directly answer complex travel intent.
Robust Schema and Technical Architecture: Implement comprehensive structured data (Schema markup) to explicitly communicate entity types, amenities, and operational facts.
Unified Entity Data: Consistent entity data across your website, business listings and third-party platforms makes it easier for AI to connect the different references to the same property.
Active Information Hygiene: Continuously update property facts across the web to prevent legacy data from polluting generative outputs.
Third-Party Validation: Optimize off-page presence, recognizing that upwards of 85% of brand mentions in AI responses originate from non-owned sources, including press and review aggregators.
Substance Over Buzzwords: Detailed descriptions are more important than marketing clichés, because AI needs specific attributes it can connect to the nuanced questions travelers are asking.

This isn't about gaming AI, but giving it a clearer, more consistent understanding of your hotel. If you leave gaps in that understanding, something else will fill them. Hotels that ignore this are essentially allowing the web to own the narrative about what their hotel is about.

A New Paradigm for Hotel Marketers

The go-to metrics for hotel marketers center on questions around rankings and traffic. These aren't disappearing. But AI is introducing a new layer of questions that hotels need to start asking:

Are we showing up in the AI conversations that matter to our strategy?
Who is being recommended alongside us?
What facts is AI using about our hotel, are they accurate and how are they repeated?
Where is AI's understanding of our property drifting from our own source of truth?
What do we need to change or clarify to strengthen our visibility?

These are marketing and technical questions with commercial implications. If AI consistently describes your hotel as a family-friendly resort when your focus is luxury couples, you’ll bypass your target market. If it fails to mention the feature that differentiates you from your competitors, you’ll lose out. If a competitor repeatedly appears alongside you, and AI gives them the attribute a traveler is looking for, you won’t be the top choice.

One of the challenges with this is that hotels can't simply look at their own website and know what AI thinks. They need visibility into their AI visibility. That’s why Cendyn Wayfinder is becoming a central part of the process for hoteliers. Bringing together measures such as AI readiness, fact health, and competitive benchmark (share of models), it gives hotels greater awareness of how they are appearing across AI conversations, and where gaps may exist.

From Visibility to Understanding

The industry shift is real, and the guest journey is changing. Travelers can now move from a broad question to choosing a hotel without ever following the traditional search journey hotels have spent two decades optimizing for.

That changes what visibility means. Hotels are no longer just competing to be found. They’re competing to be understood. Since AI processes information rather than experiencing a hotel, the nuances that feel obvious to a human marketer can easily get lost. The details need to be clear. The data needs to be consistent. The story needs to stack up across the digital ecosystem.

This is where Wayfinder can help. Built into Cendyn CMS, it gives hotels visibility into how AI platforms are representing their property, bringing together measures such as AI readiness, fact health, and how often they appear in AI recommendations. That gives hotel teams a clearer view of what AI is getting right, what it isn’t, and where action can make a difference.

Hotels that take control of how AI understands their property will be the ones that successfully Find, Book, and Grow in this new era. Being visible is only half the battle. The real advantage is making sure AI gets your hotel right.

About Rick Posey

Rick Posey serves as Vice President, AI at Cendyn. Drawing on executive leadership roles at iCIMS, Sabre Hospitality Solutions, and Preferred Hotels & Resorts, he brings extensive expertise across artificial intelligence, digital strategy, enterprise product management, eCommerce, and web analytics. His intersectional knowledge of hospitality operations and emerging technology drives AI innovations that empower hotel brands to scale commercial performance, optimize digital distribution, and deliver personalized guest journeys.

About Cendyn

Cendyn is a global hospitality cloud-based technology company that enables hotels to drive revenue, maximize profitability, and create deeper connections with guests through its integrated solutions. Serving hoteliers for nearly 30 years, Cendyn drives commercial success for hotels through its Find, Book, Grow promise: find the right guests, drive them to book direct, and grow loyalty and revenue across the spectrum of digital guest interactions.

Cendyn has over 35,000 customers worldwide in more than 150 countries generating more than $20 billion in annual hotel revenue. The company supports its growing customer base from locations across the globe, including the United States, France, the United Kingdom, Singapore, Bangkok, and India. To find out more, visit cendyn.com

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