AI Is Deciding Which Hotels Get Considered — Hospitality Revenue Leaders Need a Budget Response

This shift represents a fundamental crisis of visibility. For independent hotels and regional brands that lack the massive brand recognition and multi-billion-dollar loyalty programs of global giants like Marriott or Hilton, the stakes are existential. If a property is not surfaced during the initial AI-driven discovery phase—where travelers ask open-ended questions like "Where should I stay in Maui for a sustainable, luxury honeymoon?"—it may never be considered at all. Recent research conducted by Curacity in partnership with Cornell University highlights the severity of this gap, revealing that a staggering 94% of hotels are currently invisible in AI-generated search results. This invisibility creates a "demand vacuum" where the direct channel has nothing to capture because the demand was never generated in the first place.

As discovery migrates to these sophisticated generative engines, the hospitality sector is facing an urgent need to reorganize its commercial structures. What was once a siloed marketing task—optimizing for keywords—has transformed into a complex commercial challenge involving revenue management, distribution, business intelligence, and content strategy. To navigate this new landscape, industry leaders are questioning the traditional division of labor within their organizations.

Jenna Villalobos, Senior Vice President and Chief Revenue Officer at Outrigger Hospitality Group, notes that the question of "who owns visibility" is one that many organizations have yet to formally answer. At Outrigger, visibility is treated as a shared responsibility across various departments, yet it remains fragmented by channel. The product and analytics teams typically handle search engine optimization (SEO) and technical LLM visibility, while the revenue team manages relationships with OTAs and third-party distributors. This fragmentation can lead to a lack of a cohesive commercial objective. Villalobos suggests that the path forward involves formalizing visibility ownership within analytics teams, as they are best positioned to pull the necessary data and identify where the property is missing out on early-funnel opportunities.

Lance Burton, Vice President of Marketing at Remington Hotels, echoes this sentiment, emphasizing the cross-functional nature of modern discovery. Managing a diverse portfolio of properties requires a "quarterback" to lead the effort, a role that often falls to the marketing department. However, Burton argues that technical setup, content relevance, guest reviews, and the physical guest experience are all interconnected drivers of visibility. In an AI-driven world, a hotel’s "digital twin"—the data and narrative that exist about it online—must be robust and consistent across all platforms to be picked up by generative engines.

The necessity for this cross-functional collaboration is driven by the fact that AI discovery is not just about keywords; it is about context and storytelling. Traditional search engines looked for specific terms, but LLMs look for relationships and sentiment. They scan the web for editorial reviews, social media mentions, and travel blogs to synthesize a recommendation. This means that a hotel’s presence in high-authority, third-party editorial environments is now more valuable than ever.

Outrigger Hospitality Group has responded to this shift by emphasizing "upper-funnel" investment. By working with platforms like Curacity, Outrigger places its brand story into trusted third-party editorial content. This strategy aims to influence travelers during the inspiration phase, often before they have even finalized their destination. Villalobos points out that for an independent brand, this type of authentic storytelling is crucial for building a "base" of demand. As AI-generated content becomes more ubiquitous, travelers are increasingly seeking out authentic, human-vetted recommendations. By securing placements in reputable travel publications, hotels provide the high-quality "training data" that AI engines use to form their suggestions.

The financial implications of this shift are profound. Commercial leaders are now debating whether to move significant portions of their budgets away from traditional "demand capture" channels—like paid search and OTA commissions—and toward "demand creation" activities. This debate is fueled by alarming data regarding the decline of traditional search traffic. Analysis from SparkToro indicates that 68% of U.S. Google searches now end without a single click to an external website. This "zero-click" phenomenon is largely driven by AI Overviews, which provide the user with all the information they need directly on the search results page. For hotel brands, this means that even if they rank well, the likelihood of a user clicking through to their website is shrinking. In fact, the presence of an AI Overview can cut click-through rates (CTR) by approximately 60%.

In this environment, spending more money on traditional SEO or PPC (pay-per-click) may yield diminishing returns. Instead, the case for moving dollars "upstream" becomes a matter of necessity. If the AI is going to answer the traveler’s question without a click, the hotel must ensure it is the answer the AI provides. This requires a new discipline known as Generative Engine Optimization (GEO). Unlike SEO, which focuses on technical site structure and keywords, GEO focuses on the brand’s broader digital footprint, including its presence in the news, its reputation on social media, and its inclusion in authoritative lists and articles.

However, shifting budgets to the upper funnel presents a significant measurement problem. The hospitality industry has long been addicted to "last-click" attribution—a model that gives all the credit for a booking to the last link a traveler clicked. This model naturally favors OTAs and branded search, but it completely ignores the weeks or months of research and inspiration that led to that final click. Villalobos argues that travelers do not make decisions in a vacuum; they encounter a brand in multiple places before booking.

The challenge for commercial leaders like Burton and Villalobos is to convince hotel owners and stakeholders that long-tail investments in AI visibility are worth the cost. Owners typically demand immediate, measurable ROI, which is difficult to provide for upper-funnel activities. Burton notes that optimizing for AI visibility is a "long-tail effort," much like traditional SEO, and should be viewed as a long-term capital investment in the brand’s future relevance rather than a quick-fix marketing tactic.

Looking toward 2027, the hospitality industry is at a crossroads. Commercial budgets being drafted today will determine which brands survive the transition to an AI-first search environment. Forward-thinking companies are already testing new approaches, such as Curacity’s VISTA, which focuses on building visibility within the editorial sources that inform AI recommendations. By investing in these channels now, brands can gain a competitive advantage in understanding how early-journey discovery translates into long-term commercial performance.

The risk of inaction is high. Brands that remain focused solely on downstream, bottom-of-the-funnel channels risk fighting over a shrinking pool of demand that has already been filtered through AI gatekeepers. As AI continues to push discovery earlier in the journey, the definition of a successful hotel brand is changing. It is no longer enough to be the best option at the point of purchase; a hotel must be the most prominent and recommended option at the point of inspiration. This requires a total reimagining of the commercial organization—one where data, narrative, and distribution are seamlessly integrated to ensure the brand remains visible in a world where the "search" is over before the "click" even happens.