Your Hotel's 2027 AI Strategy: Four Questions to Answer Before Budget Season

Prepared by Gourmet Marketing, a hotel marketing agency offering SEO, content marketing, social media, and website development for hotels, restaurants, and boutique properties.

Sometime in the next few weeks, you'll open last year's marketing budget, nudge a few numbers, and call it 2027 planning. Almost every property does it this way. It feels responsible.

The problem isn't the spreadsheet. It's that the spreadsheet assumes one search environment, and there are now several. Each one sources information about your property differently, and each rewards different work. AI overviews, Google's AI mode, ChatGPT, Perplexity, and now agentic booking are not a single channel called "AI." Budgeting for them as one line is how properties end up funding, for the third year running, activity that stopped paying for itself.

If you want the underlying shift in plain terms before you go further, start with our breakdown of what AI search means for hotel discovery. Everything below assumes that change is already priced into your market, because it is.

So this isn't a budget template. It's a diagnostic: four questions to work through before you allocate a dollar. Answer them honestly, and the allocation mostly writes itself.

Start here: the five-minute test

Before you read another paragraph, open ChatGPT and Google's AI Mode side by side. Ask each one the question a guest in your segment would actually ask. Try "boutique hotels in Charleston walking distance to King Street", or "family-friendly resorts near Scottsdale with a kids' club", or "where to stay in Nashville for a conference at Music City Center." Unbranded. No property names.

Then check three things:

1. Do you appear at all?
2. If you appear, is the description accurate? Right positioning, right amenities, right distances, current F&B.
3. Do the two engines give you the same answer? They almost certainly won't.

That last point is the one that lands. In research published by Tharro, covering 695 unbranded hotel searches across the Algarve, Mallorca and Rhodes run through both ChatGPT and Google's AI Mode, ChatGPT named 3,151 distinct hotels and AI Mode named 1,286, with only 691 properties appearing on both lists. An 18% overlap. Being recommended by one engine tells you almost nothing about whether you're recommended by the other.

Five minutes, no cost, and you'll know more about your 2027 problem than any dashboard will tell you. If you want a structured version of this exercise, we've written a longer walkthrough on how to get found by AI assistants, not just Google.

1. Are you treating "AI" as one channel when it's five?

The old chain was clean: rankings drive traffic, traffic drives bookings, so fund rankings. That chain is now broken in places. But the useful insight isn't "AI ate our clicks." It's that each engine builds its shortlist from a different source set, so the work required to appear in each is different. Our breakdown of AEO vs. SEO for hotels covers where the two disciplines diverge.

The Tharro research found that nearly half of the hotels recommended by AI didn't appear in Google's organic results for the same query at all. Strong rankings help. Properties ranking in Google's top three were named around 66% of the time, versus 27% for those below position 20. But ranking is neither necessary nor sufficient.

More importantly for how you spend: a hotel's own website was cited as the source less than 10% of the time but 37% of the time for properties ranking in Google's top ten. It's important to highlight that if they are ranking in the top 10, their AI appearance increases. Most citations went to OTAs, Tripadvisor, and editorial guides. Google's AI Mode leans on Maps-style prominence and proximity signals. ChatGPT leans on editorial lists and travel guides. Feefo's study of 250 travel queries found the same divergence on the review side, with Perplexity referencing first-party reviews in 100% of its travel responses, ChatGPT in 58%, and Gemini in 56%.

Practically, that's five different jobs:

• AI Overviews and AI Mode. Google Business Profile completeness, category and attribute accuracy, Maps prominence, local review volume, and proximity language that matches how guests describe your location. This is local SEO for hotels doing double duty, and it's the same signal set that drives performance on Google Hotel Finder.
• ChatGPT. Presence in editorial round-ups, destination guides, and "best of" lists. Digital PR is an AI visibility tactic now, not a vanity one.
• Perplexity. Review depth and recency above almost everything else.
• OTA and review-platform listings. These are what actually gets cited. Your Booking.com and Tripadvisor content is training data for how AI describes you, whether you like that or not.
• Agentic booking. The newest layer, and the one most likely to catch properties unprepared. On August 7, 2026, Google confirmed to Skift that agentic hotel booking is live in a limited U.S. test inside AI Mode, with Booking, Expedia, Marriott, Wyndham and IHG among the early partners. An agent doesn't respond to your hero video or your brand story. It reads structured rate, policy and availability data, which is why a site designed for human guests may not be legible to an agent at all.

Note who's on that early partner list: OTAs and chains. If agentic booking scales before independents are machine-readable, the channel re-intermediates you at exactly the moment you were trying to go direct. That's a 2027 problem you can act on in 2026.

Naming the mechanism behind "be consistent"

"Consistency" is a value, not a task. Here's the task list, the version you can hand to a web vendor or agency and hold them to. The reasoning behind it sits in our piece on semantic SEO for hotels.

• Structured data. Hotel schema on the property page, with amenityFeature, checkinTime and checkoutTime, priceRange, geo coordinates, and sameAs pointing to your Google Business Profile, OTA listings and social profiles. FAQPage schema on question-led content. Room or HotelRoom schema on room type pages.
• Entity and NAP alignment. Property name, address and phone identical, character for character, across your site, GBP, Booking.com, Expedia, Tripadvisor, and your CRS. "St." versus "Street" is a different entity to a machine.
• Amenity parity. The amenity list on your website, your GBP attributes and your OTA extranets should match. Where they diverge, the OTA version usually wins, because that's what gets cited.
• Location language. Describe distances the way guests ask about them ("eight-minute walk to the riverfront", "two blocks from the convention center"), not in miles from a landmark nobody names.
• Machine-readable rates and policies. Cancellation terms, deposit rules, pet and parking policies stated as structured content rather than buried in a PDF or an image.

Ask your vendor which of these are live today. If the answer is vague, that's your first line item.

2. Does your review program have an owner, or just good intentions?

Ask what your property spends, in money and staff hours, on generating and responding to reviews. For most independents, the honest answer is "whatever's left after everything else."

That allocation made sense when reviews were a trust signal guests read late in the funnel. It makes considerably less sense now that machines read them first. Feefo's research found 71% of AI travel responses drew on first-party customer reviews as a source. The Tharro data adds an uncomfortable wrinkle: review volume and star class predicted AI recommendations more strongly than guest rating did. Established, upper-tier properties with moderate scores and a lot of reviews were surfaced ahead of smaller, better-rated properties with fewer.

Read that again if you run a 9.2 boutique with 180 reviews competing against an 8.4 with 3,000. Rating alone isn't the asset. Volume, recency and descriptive richness are. We've covered the same mechanic on the restaurant side in how AI uses reviews to rank hospitality businesses, and the logic transfers cleanly.

The recurring phrases in your feedback, the rooftop bar, the ten-minute walk to the convention center, the front desk that remembered a birthday, are the raw material AI uses to describe you to travelers who will never appear in your traffic reports. Which makes reviews a visibility channel, and visibility channels get real lines: a named owner, a systematic post-stay ask across more than one platform, and response time managed like ad copy rather than like admin. The service-recovery side of this is worth its own attention, and we've covered it in five ways to build guest trust and loyalty.

3. Do you know which channels produce stayed revenue, and do you have a second scorecard for the work that can't be attributed?

Here's the question that should gate every media dollar you approve: of last year's campaigns, which produced guests who booked, arrived and stayed?

Most operators can't answer it cleanly, and the gap is bigger than it looks. Commonly cited industry figures put hotel booking-engine abandonment around 80%. Run the arithmetic properly: a property doing $500,000 in completed direct revenue at an 80% abandonment rate had roughly $2.5 million in booking sessions start, meaning about $2 million entered the funnel and left without converting.

Now, before that number gets turned into a slide: you know as well as anyone that a booking-engine session is not a lost sale. A large share of those sessions are rate shoppers, calendar browsers, returning guests checking a date, and people parity-checking you against a Booking.com tab in the next window. Treating $2 million as evaporated revenue is the abandoned-cart fallacy, and it isn't a claim worth making.

The real point is narrower and more useful. That's $2 million of demand that entered your funnel and went unmeasured. You don't currently know how much was genuine intent lost to a slow rate load, a forced account creation, or a deposit policy that surprised someone at step three, and how much was never bookable in the first place. Until you can separate those, you're allocating on session counts, which is the least informative number in your reporting. Our look at how AI revenue tools read demand before you do covers what modern tooling can actually surface here, and the hotel data playbook covers the data structure underneath it.

Paid media is where this bites hardest and where the fix is fastest. Most properties are carrying spend that looks fine on sessions and poor on stayed revenue. We've catalogued five ways hotels waste Google Ads budget, and the brand versus non-brand balance is usually the single largest misallocation. Before you set 2027 targets, check them against realistic Google Ads ROAS benchmarks for hotels.

Reconciling this with everything above

There's a tension between this section and section 1, and it's worth naming rather than leaving the reader to find it.

Section 1 argues that AI-influenced discovery is largely invisible to your analytics. This section argues for funding what you can tie to completed bookings. Applied literally, the second rule defunds everything the first one recommends.

The resolution is that these are two scorecards for two different jobs:

• Demand capture, meaning paid search, metasearch, retargeting, and the booking engine itself, is governed by attribution. Judge it on completed, stayed revenue. Be ruthless here.
• Demand creation and visibility, meaning review programs, structured data, editorial placement, and content, cannot be judged by last click, because last click is structurally incapable of seeing it. Judge it on leading indicators instead: branded search volume, direct traffic share, citation and mention presence in AI answers, review velocity and recency, and share of AI shortlists for your core unbranded queries.

Applying attribution logic to visibility work isn't discipline. It's a measurement error that happens to feel like discipline.

That reframe also settles the question of content. Blog and guide content rarely wins on last-click conversion, and it never did. But it now does two jobs it wasn't credited for previously: it's a primary source for editorial-leaning engines like ChatGPT, and it assists conversions attributed elsewhere. We have clients whose guide content both generates direct revenue and demonstrably appears in AI answers about their market. The practical version of this is understanding what guests are actually searching at 2am and answering it on-site. Judge that work on assisted conversions and citation presence, not last-click bookings, and the picture changes entirely.

4. Is there a funded line aimed squarely at the commission tax?

OTA commissions for independents run roughly 18% to 30% all-in once you include preferred-partner boosts, sponsored placement and payment fees, and the true cost of OTA advertising programs is higher again than the headline rate suggests. That band hasn't moved much in years, and that's the point. The commission rate isn't the story. Your mix is. The rate has been stable. What changes annually is the share of business flowing through it.

The second cost is less visible on the P&L. Cloudbeds' 2026 State of Independent Hotels report, drawn from its client base, found 21.8% of OTA bookings cancelled in 2025 against 10.6% of direct bookings, a little over double. So a share of that commission is buying reservations that never become stays, while degrading the reliability of your pace report.

Every operator says they want to reduce OTA dependency. Almost no plan contains a funded line that says so. "Shift five points of share from OTA to direct" is a fundable objective, but only if the tactics are ones you actually control.

Which is worth being blunt about: if you're on SynXis, Mews, Cloudbeds or a similar platform, "fix your booking engine UX" is not advice you can act on. You don't own that interface. Here's what you do own:

• Vendor choice and version. Most engines have newer templates or configurations that materially outperform what you were provisioned with three years ago. Ask what you're running and what's available. Our comparison of booking engines for independent hotels is a starting point for that conversation.
• The configurable path. Steps enabled, whether guest account creation is forced, whether the rate calendar loads before or after the guest picks dates, and how many upsell interstitials sit between selection and payment. The principles are in our hotel website conversion strategy guide.
• Rate presentation. Where taxes and fees appear, whether the member or direct rate is visible before checkout, and how the direct-booking benefit is stated on the rate line rather than buried in a banner. What guests look for when booking online covers the decision cues that matter.
• Abandonment remarketing. Booking-engine abandonment triggers, and whether they're actually switched on and integrated with your CRM. Many are provisioned and never activated.
• Metasearch presence. Google Hotel Ads and Trivago are where high-intent guests compare your rate against the OTA. Absent there, parity is theoretical. See what metasearch advertising is and how it works.

Pick the mix that fits your property. But put a number and an owner on it, because a goal without a line item is a wish.

What this looks like when you open the spreadsheet

You won't get a universal allocation out of this, and anyone selling you one is guessing. But the four questions imply a direction of travel that's defensible in front of an owner or asset manager, and if you need help making that case, elevating the boardroom conversation is its own skill.

Fund measurement first. It's the only line that compounds, because it makes every other line smarter. It doesn't create demand. It typically reveals enough misallocated spend to pay for itself in the first quarter.

Add a visibility line that didn't exist before, covering structured data, listing and entity consistency, editorial placement, and a properly resourced review program. Judge it on leading indicators, not last click.

Benchmark your direct-booking line against what OTA commissions cost you last year. For most independents that's one of the largest marketing-adjacent numbers on the books, and it deserves proportional counter-investment.

Split "AI" into the engines that actually matter for your market, and accept that they need different work, including making your property legible to agents that book without a human ever seeing your site.

And be equally deliberate about what you cut. Rankings-only SEO, session-count reporting, and any channel whose case rests on traffic rather than stayed revenue. Our assessment of where AI is genuinely delivering for hotels and where it's stalling is the difference between a plan built on strategy and one built on vendor buzzwords.

The hotels that outperform in 2027 won't be the ones that spent more. They'll be the ones that stopped paying for a discovery environment that no longer exists. Budget season is your one clean shot at that reset. But the strategy has to come first, and it starts with those five minutes in ChatGPT.

Frequently Asked Questions

Should hotels cut SEO spend now that AI answers more searches?

No, but the work has to change. Rankings correlate with AI recommendations without guaranteeing them, and a hotel's own site is cited as a source in AI answers less than 10% of the time, but 37% of the time for properties in Google's top ten. Ranking doesn't guarantee you're recommended — it reliably buys you a say in how you're described. Below the top ten, your summary gets built from OTA listings, TripAdvisor, and editorial guides. So SEO isn't the shrinking asset; rankings-only SEO is, because ranking now has to be paired with entity consistency, third-party presence, and review signals to earn what you pay for it. Our guide to hotel SEO strategies for direct bookings covers what still earns its place.

Which AI engine should we prioritize?

It depends on how your guests search. Google's AI Mode and AI Overviews reward Maps-style prominence, complete Google Business Profiles and local review volume, the material we cover in AI, local SEO and hotel visibility. ChatGPT leans on editorial guides and round-ups. Perplexity weights reviews most heavily. Run the five-minute test on your top three unbranded queries and prioritize where you're least visible relative to your comp set.

Do we need to do anything about agentic booking yet?

It's in limited testing rather than full rollout, so this isn't an emergency. But the preparation work overlaps almost entirely with what you should be doing anyway: structured rates, machine-readable policies, accurate availability, and clean entity data. Running through a commerce-readiness checklist is the fastest way to see where you stand.

What's the highest-leverage addition to a 2027 plan?

Measurement that connects channels to stayed revenue rather than sessions, paired with a second, separate scorecard of leading indicators for visibility work that attribution structurally can't see. One without the other gets you either false confidence or a defunded visibility program.

How much should direct booking initiatives get?

Benchmark against last year's OTA commission outflow, then factor in the cancellation differential, since OTA cancellations run a little over double direct. The real cost of the channel is higher than the commission line suggests, and the counter-investment should reflect that.