The following is a guest post from Tim Major, CEO of hospitality management software company Operto. Opinions are the author’s own.
Travelers aren’t searching for hotels the way they used to. They’re asking questions like “What’s the best boutique hotel near the Javits Center?” or “Where should I go for a quiet weekend in nature?” And increasingly, they’re receiving a confident response containing a short list and no prices.
Search and websites still matter, but discovery is starting earlier, inside generative search. Hotels are no longer just competing for placement. They’re being interpreted by systems they don’t control or see into, which creates a new kind of problem.
Hotels can still see outcomes — traffic, bookings, performance — but the layer where decisions are actually being shaped is becoming harder to access. In response, new systems are starting to emerge to help close that gap.
The behavioral shift: From search results to synthesized answers
Travelers are describing trips in terms of mood, purpose and experience, and artificial intelligence turns that into a shortlist almost instantly. Instead of browsing 10 options, a traveler is handed two or three that already feel right.
"This is where knowing your niche stops being a branding exercise and starts becoming a distribution advantage."
Tim Major
Operto CEO
In the traditional search model, there are signals like rankings, impressions and click-through rates. Hotels could see what was happening and adjust. In the age of AI, that visibility disappears. For the first time, hotels are being judged in a system they can’t observe.
As traveler queries become more specific, vague positioning gets filtered out. There’s less room for broad, catch-all messaging. A hotel that tries to be everything to everyone becomes difficult to place. One that is clearly designed for a specific type of guest becomes much easier to match.
This is where knowing your niche stops being a branding exercise and starts becoming a distribution advantage.
The risk: Losing control of distribution, again
AI has introduced a new kind of intermediary. It doesn’t just redirect demand, it shapes it. If your hotel is mischaracterized, deprioritized or excluded, you don’t just lose traffic, you lose the chance to be considered at all.
The focus shifts from placement to interpretation, which means the job changes too. The challenge is no longer just showing up. Rather, it’s being understood, consistently, across every source these systems draw from, including your website, listings, reviews and structured data.
This isn’t something you can manage periodically. It’s continuous, fragmented and spread across systems you can’t directly access. You’re no longer optimizing a channel you can log into. You’re trying to influence how your hotel is interpreted across environments you can’t see or measure.
There’s no interface for that — no reporting layer or obvious lever to pull. That’s where the gap starts to show.
A new layer: Agentic AI in distribution
If this shift is continuous and systemwide, then periodic optimization isn’t enough. It’s happening too quickly and across too many systems for teams to realistically manage in the way they do today. That’s where a new type of system starts to emerge.
Often referred to as agentic AI, this approach is built around AI agents; systems designed to continuously monitor how a hotel is interpreted across AI platforms and surfaces where that interpretation breaks down. In practice, an AI agent behaves less like a tool and more like a specialist. They build a picture of where a hotel appears, where it doesn’t and how it’s being described across different types of queries.
"If your hotel is mischaracterized, deprioritized or excluded, you don’t just lose traffic, you lose the chance to be considered at all."
Tim Major
Operto CEO
From there, the agents highlight gaps: where positioning is unclear, where signals don’t align and where a property is being overlooked for searches it should be relevant for. They don’t control the platforms themselves, but they give teams a clearer view of how they’re being understood, and what to adjust in response.
What changes when AI manages AI
When you introduce this kind of visibility, distribution starts to shift. Instead of reviewing performance after the fact and trying to infer what happened, you can see how your hotel is being represented as it’s happening, and test how different inputs affect whether you’re included.
That creates a feedback loop that didn’t exist before. And crucially, it happens before the click, not after. Distribution becomes less about reacting to performance and more about actively managing how your hotel is understood.
The next phase of distribution is already underway
This shift is already happening, just without clear metrics — which makes it easy to underestimate. There’s no dashboard showing how often your hotel is being included in AI search or how it’s being described, but that doesn’t mean those decisions aren’t already being shaped.
Discovery is already moving into AI-powered systems that are influencing how travelers choose where to stay. By the time this becomes visible in reporting, your positioning may already be set.
It’s no longer about who ranks highest. It’s about which hotels are understood clearly enough to be included in the first place. Because if you’re not understood there, you’re not part of the decision at all.
