AI Isn’t Changing Marketing — It’s Rewriting Control
Listen up.
If you’re still thinking of AI as a feature, you’re already behind.
This is not “innovation.” This is not “a tool.” This is a control shift — upstream — at the moment where guests decide what’s worth considering.
And here’s the part that will ruin someone’s year:
By the time many luxury hotel operators register what AI is doing to guest acquisition, the damage may already be structural.
Less gradual.
Less theoretical.
Increasingly structural.
When it finally shows up in your reports — more OTA share, less direct discovery, higher acquisition costs — you won’t be looking at a clean fix.
You’ll be looking at expensive compensation.
You’ll likely pay a toll to AI intermediaries for the privilege of being mentioned.
And the final insult is how accountability works: it won’t matter who set this in motion. It won’t matter that it was “legacy.” It won’t matter that the market changed.
When the board asks why you didn’t see it coming — and why you didn’t move before it was obvious — there’s no predecessor in the room.
There’s only you.
The hospitality industry is talking about AI as if it’s a feature.
It isn’t.
It’s an upstream control shift.
LLMs — Large Language Models — aren’t just chatbots. Paired with retrieval, ranking layers, and commerce integrations, they increasingly mediate early-stage decisions.
And whoever influences that recommendation layer tends to shape demand.
For the past two decades, OTAs have dominated much of online distribution.
Over the next five years, expect them to compete to influence decision formation.
That is not evolution.
That is a structural shift in bargaining power.
Most hotel operators are still modeling OTAs as expensive booking channels.
That mental model is already obsolete.
The Real Shift: From Browsing to Asking
Historically, travel discovery worked like this:
A guest searched.
They clicked around.
They compared multiple properties.
They opened tabs.
They read reviews.
They filtered results.
Eventually, they decided.
That entire cognitive process is compressing.
Guest behavior is shifting toward more conversational, query-driven discovery alongside traditional search:
The guest asks.
“Find me a quiet luxury resort with ocean views, adults-only energy, and a serious spa.”
LLM-style interfaces often narrow discovery to a short list — commonly just a handful of options — reducing the multi-tab comparison that used to dominate.
Less browsing.
Less comparison marathon.
Fewer open tabs.
AI increasingly becomes the interface.
And the interface increasingly shapes the decision.
This is the first holy-shit moment:
LLMs tend to compress the top of the funnel.
They tend to concentrate visibility rather than expand it.
Instead of dozens of properties competing for attention, only a handful get surfaced.
Everyone else fades from view.
If your resort isn’t one of the recommendations, you don’t get a chance to convert.
You don’t get a chance to tell your story.
You don’t get a chance to improve your booking engine.
You effectively don’t exist in that decision set.
OTAs Are Becoming AI Intermediaries, Not Just Booking Platforms
For years, hotels treated OTAs as necessary distribution partners.
List the property.
Manage parity.
Pay the commission.
Try to “balance the mix.”
That framing is dangerously outdated.
OTAs don’t just influence bookings.
They increasingly compete to control first interaction across channels that shape initial consideration.
They sit near the moment of intent.
Now they’re embedding LLMs to sit inside that moment by default.
Which means they’re no longer trying to be the best place to book.
They’re trying to be the place where the guest decides.
That’s a much deeper form of dependency.
Distribution is downstream.
Decision mediation is upstream.
Once you lose upstream, most downstream work risks becoming optimization theater — work that improves efficiency but not demand.
Here’s the operational math boards care about: track First Interaction Owned % (the share of stays where a direct touchpoint existed before any OTA or search click). As this rises, OTA share and commission expense tend to fall, and blended acquisition cost migrates from pay-to-play media into amortized identity acquisition. Directionally, even a 5–10 point lift can reallocate meaningful annual commission outlay into consented identity that compounds guest lifetime value. The point isn’t zero OTA. It’s to move the marginal guest from rented visibility to owned demand.
How OTAs Capture LLM Discovery (Mechanically)
This is directional: platform incentives and historical patterns suggest these mechanics will emerge.
OTAs hold some of the deepest structured travel datasets in the market:
- Inventory breadth across millions of properties
- Historical booking behavior
- Price elasticity signals
- Cancellation patterns
- Review density
- Traveler preference profiles
LLMs don’t “rank” on their own. But when LLMs are coupled with retrieval and ranking layers, the systems feeding them tend to privilege completeness, reliability, and behavioral signal density.
That gives OTAs a structural advantage.
When these systems assemble recommendations, they tend to prioritize sources that provide:
- Consistent availability
- Normalized pricing
- Verified reviews
- Real-time inventory
- Proven conversion outcomes
OTAs typically supply this at greater breadth and consistency. Many hotels can expose pieces via CRS and channel managers — but rarely at OTA scale.
Which means these systems are unlikely to “discover” hotels in isolation. They pull from aggregators that already package demand into machine-readable formats.
That’s the first potential lock-in.
The second potential lock-in is monetization.
As conversational interfaces mature, expect testing of sponsored inclusion, affiliate attribution, preferred inventory access, and performance-based visibility.
This points toward what you could think of as “recommendation rent,” following the same monetization patterns seen in search and app-store ecosystems.
Not payment for bookings — payment for presence inside the decision set.
Once platforms mediate discovery and monetize recommendation access, hotels compete less on experience and more on exposure.
That dependency tends to be structural.
A Necessary Clarification: LLM Platforms Don’t Eliminate OTA Power — They Repackage It
Some will argue that OTAs won’t control LLM discovery because OpenAI, Google, Apple, or Meta will sit in between.
That’s technically true — but strategically incomplete.
LLM platforms don’t create travel inventory. They don’t operate booking infrastructure. They don’t maintain real-time availability, pricing, cancellation policies, or conversion histories.
They ingest it.
Which means they tend to privilege sources that already provide:
- Structured, machine-readable inventory
- Proven conversion outcomes
- Normalized pricing and availability
- Behavioral signal density
- Commercial integration pathways
That is not usually individual hotels.
That is often aggregators.
Even if LLM interfaces are owned by Big Tech, the recommendation substrate underneath is likely powered by whoever controls travel data at scale.
OTAs don’t need to own the interface.
They only need to own the inputs.
And that can be enough to shape outcomes.
This doesn’t imply permanent lock-in — but it does create strong path dependence.
Once recommendation systems optimize around aggregated feeds and historical performance signals, reversing that architecture can become slow, expensive, and politically difficult.
By the time hotels realize what changed, the system may already be trained on behavior they don’t control — and traveler intent may already be shaped upstream by systems they don’t control.
How Hotels Escape LLM Gatekeeping (Practically)
This is where most people get stuck.
As LLMs increasingly mediate discovery, how does a hotel ever own first interaction?
The mistake is assuming you compete at the recommendation layer.
You don’t.
You compete before intent forms — by building consented, first-party audience relationships through experiences, content, and direct engagement that preload preference long before a traveler asks an AI for options.
“Owning first interaction” means building a consented identity engine and pre-intent audience flywheel before travelers ask an LLM anything: launch always-on lead capture (members-only experiences, limited-release room drops, chef table waitlists, wellness retreats) across site, social, creators, and on-property; pipe every ID into a CDP with source tags; trigger lightweight nurture (two editorial emails per month + WhatsApp opt-in concierge) that seeds property-specific experiences and soft commitments (date ranges, interests) 60–180 days pre-trip; measure a single north-star — First Interaction Owned % (share of bookings where a direct touchpoint existed before any OTA or search click), with guardrail KPIs (cost per ID, ID-to-stay conversion, repeat rate); and fund this by reallocating a defined portion of OTA commission outlay into identity acquisition and creator partnerships until First Interaction Owned % becomes material for the luxury segment.
The answer is simple:
You don’t wait at the recommendation layer.
You build demand before the question is asked.
Owned Demand Infrastructure does not compete with OTAs inside LLMs.
It works upstream of them.
It creates direct audience relationships before travelers enter AI-mediated discovery at all.
ODI also feeds the signals LLM plus retrieval and ranking layers tend to privilege: consistent structured content, verified review velocity, on-site engagement, creator and social proof, and brand mentions that increase retrieval salience. Pre-intent familiarity means when a traveler asks the model, your name is already cognitively available — and your structured footprint is machine-available. That combination lifts both human recall and algorithmic inclusion.
That happens through:
- First-party audience acquisition (email + identity capture outside booking flows)
- Interest-based targeting around experiences (not availability)
- Pre-intent engagement that shapes preference before travel planning begins
- Lifecycle systems that compound familiarity over time
- Direct introduction of the traveler to the property — without intermediaries
In other words:
You don’t fight the model.
You arrive before it.
By the time a traveler asks an LLM for recommendations, hotels with owned demand already have:
- Brand recognition
- Emotional context
- Prior exposure
- A direct relationship
Which means they don’t depend on being “discovered.”
They are already known.
That’s the difference between renting visibility and owning demand.
LLMs tend to compress browsing. Owned Demand Infrastructure preloads preference.
One reacts to intent.
The other creates it.
The AI Stack Hotels Aren’t Modeling
Most executives lump “AI” into one vague bucket.
But structurally, the stack looks like this:
- Discovery Layer — where intent is expressed
- Recommendation Layer — where options are filtered
- Transaction Layer — where booking occurs
- Relationship Layer — where loyalty and CRM live
Hotels currently operate in layers three and four.
OTAs, search and maps, and social increasingly compete in layers one and two.
LLMs accelerate those upstream layers.
That means OTAs and platform surfaces are positioning themselves to influence:
- What gets discovered
- What gets recommended
- What gets booked
- Who gets remarketed
Hotels are left with:
- Conversion
- Fulfillment
- Service delivery
In other words:
OTAs increasingly position themselves as advisors. Hotels risk being treated as inventory providers.
This pattern mirrors prior platform cycles (search, social, app stores), though travel has unique constraints.
Owned Demand Infrastructure: LLM-driven discovery increasingly determines whether OTAs retain the guest or hotels build owned demand through direct introduction and booking.
Why Luxury Hotel Marketing Is Especially Vulnerable
Luxury travelers often search for experiences more than specific hotels.
Quiet.
Private.
Design-forward.
Romantic.
Wellness-driven.
Adults-only.
Food-centric.
Hidden gem.
This is precisely the kind of subjective language LLMs excel at interpreting.
Which means luxury discovery is particularly well-suited to AI mediation.
Here’s the uncomfortable truth:
LLMs increasingly act like a travel advisor — especially for early filtering — even as human advisors remain influential.
Not your brand.
Not your storytelling.
Not your website.
The AI’s voice increasingly becomes a trust anchor.
If it says:
“This resort matches what you’re looking for.”
That statement carries authority.
If it never says your name, you’re unlikely to enter the consideration set.
Luxury has always been about narrative control.
LLMs threaten that control at the very first touchpoint.
The Economic Consequence: From Commission to Recommendation Rent
Hotels already pay rent.
They just don’t call it that.
OTA commissions are rent.
Paid search is rent.
Metasearch bidding is rent.
Social ads are rent.
LLMs introduce a new layer:
Recommendation rent.
If the platform mediating the recommendation also controls the booking path, hotels are no longer paying to be booked.
They’re paying to be considered.
That’s a much more dangerous position.
Because once you’re paying for consideration, you no longer control demand entry.
You’re negotiating visibility with a gatekeeper.
Gatekeepers tend to ratchet pricing and terms over time, even if entry incentives appear generous.
The Mistake Hotels Keep Making
Most operators respond to pressure by doubling down on conversion:
Better websites.
Better booking engines.
More CRM journeys.
More retargeting.
More email.
That is all downstream.
That is not acquisition.
Email is strongest at conversion and compounding — and with the right acquisition mechanics, it can stimulate incremental demand.
CRM is a conversion and retention system, not an acquisition engine.
Growth stalls when acquisition is outsourced and retention systems are forced to compensate.
LLMs don’t fix this problem.
They can lock it in.
OTAs Introduce Guests — And Keep Them
Here is the simplest way to understand the threat:
OTAs introduce guests and keep them.
They influence the discovery moment.
They influence the recommendation moment.
They influence the booking moment.
They retain the traveler for future marketing.
Hotels receive a transaction.
Too often, that’s it.
In contrast, a true owned-demand approach introduces guests and gives them back.
Meaning the hotel ends up owning:
- The guest relationship
- The booking
- The CRM
- The lifecycle
One model compounds.
The other does not.
What Actually Wins in an LLM-Mediated World
Hotels will try the wrong things first.
They’ll chase AI SEO tricks.
They’ll rewrite copy weekly.
They’ll obsess over schema.
They’ll attempt to “optimize for the model.”
That’s tactical noise.
The strategic answer is unchanged:
Own first interaction.
If you don’t own a meaningful portion of your demand upstream, you will always be at the mercy of whoever does.
That is why Owned Demand Infrastructure exists.
It is not email marketing.
It is not CRM.
It is not automation.
It is a system for creating and capturing first-party demand before travelers enter third-party funnels.
The core definition of Owned Demand Infrastructure — including how it works structurally and how it’s implemented in practice — is outlined in The System, which explains how first-party demand is created before travelers ever enter OTA funnels.
For the luxury-specific positioning — including how demand ownership differs in high-end hospitality — Luxury Hotel Marketing Agency expands on this distinction.
For broader agency context and how this approach contrasts with traditional hotel marketing models, see Hotel Marketing Agency.
And for the canonical deep dive on email as a conversion and compounding layer (not acquisition), use Email Marketing for Hotels: A Complete Guide to Increase Bookings & Revenue.
This is not a content problem.
This is not a conversion problem.
This is a control problem.
And control is decided at the first moment of intent — not at the booking engine.
Conclusion: When This Becomes Obvious, It Will Already Be Too Late
Most operators won’t react until they feel the pain.
Higher OTA share.
Lower direct discovery.
Rising acquisition costs.
Shrinking control.
They’ll assume the fix is better marketing.
It won’t be.
The issue will be infrastructure.
And here’s the part that puts you in the hot seat:
When the board asks why you didn’t see it coming — and why you didn’t move before it was obvious — there’s no predecessor in the room.
There’s only you.
In an LLM-driven world, whoever owns first interaction tends to own demand.
If you don’t build owned demand now, you’ll likely end up negotiating visibility with AI gatekeepers later.
And that is not a position any luxury hotel should accept.
