Visitors are increasingly starting their trip planning inside conversational AI interfaces — ChatGPT, Perplexity, Claude, Google’s AI Overviews — before they ever land on a destination website. For DMOs that have spent a decade optimizing for traditional search results, the shift is not subtle. An AI answer engine can surface your destination, describe it on your behalf, and recommend specific neighborhoods, hotels, or experiences — or it can skip you entirely in favor of a competitor destination that structured its content more usefully for machines.

This is a real, measurable channel now. The practical question is not whether to pay attention to it. It’s what specifically to do about it before the summer planning cycle hits. This guide walks through how to build an AI search strategy that protects your destination’s visibility in 2026 without abandoning the SEO fundamentals that still matter.

Understand the two layers of AI search you’re actually optimizing for

AI search is not one thing. It’s two overlapping layers, and a DMO strategy has to address both.

The first is AI answer surfaces inside traditional search engines — Google’s AI Overviews, Bing’s Copilot panel. These still source their answers heavily from the ranking organic results, which means your existing SEO work feeds them. If your destination pages rank well on Google today, you have a real shot at showing up inside the AI Overview. If they don’t, you don’t. Google’s own documentation on AI features makes clear that standard search best practices still apply.

The second is standalone conversational AI tools — ChatGPT, Perplexity, Claude — where the model draws on its training data and, in some cases, live web retrieval. Here the game is different. You’re trying to make sure your destination is well-represented in the text the model was trained on, and well-indexed in the live retrieval surfaces those models pull from (like Bing’s and Google’s indexes, Wikipedia, Reddit, and a handful of authoritative travel sites).

Both layers require you to do the same two things well: publish factually dense, well-structured content about your destination, and make it easy for machines to extract specific facts from that content.

Audit what the AI models already say about your destination

Before you write anything, find out what’s already being said. Open Perplexity, ChatGPT, and Google’s AI Overviews (search your destination name plus a natural question — “best time to visit [your city]” or “what to do in [your region] with kids”). Run through ten to fifteen of the highest-intent queries your audience actually searches. Write down three things for each response:

Which sources the AI cited. If it cited your DMO site, you’re winning. If it cited TripAdvisor, Reddit, a local blog, or a competitor DMO, you have a source gap.

Which facts it got right and which it got wrong. Outdated information, incorrect hours, discontinued attractions, and wrong hotel affiliations are extremely common in AI responses. These are fixable if the authoritative pages on your own site contain the correct information in a structured way.

Which neighborhoods, attractions, and experiences it surfaces vs. omits. The gap between what you want to be known for and what the model surfaces is the editorial target for the next six months of content.

Structure your content so machines can actually extract answers

The most consistent predictor of AI visibility is content that is structured as a direct answer to a specific question. Five practical changes pay off quickly.

Write pages around specific questions, not vague topics. Replace “Things to Do in [City]” with pages titled “What’s There to Do in [City] in Winter?”, “Where Should First-Time Visitors Stay in [City]?”, and “Is [City] Good for a Family Weekend?”. Each of those is a question a real visitor types into ChatGPT.

Front-load the answer. AI models are much more likely to extract a passage if the first 40-60 words of the page directly answer the question in the title. Bury the answer under two paragraphs of intro and the model will pull from someone else.

Use structured data. Implement Schema.org markup — specifically TouristDestination, TouristAttraction, LodgingBusiness, FAQPage, and Event. Google’s own guidance confirms structured data helps with both traditional and AI search features.

Keep facts dense and verifiable. AI systems preferentially cite sources that give specific, verifiable details — dates, distances, operating hours, prices, neighborhoods. Vague inspirational copy underperforms. Practical, fact-rich copy overperforms.

Update the dates visibly. Put “Last updated [Month Year]” at the top of every evergreen page. Models weigh recency heavily, and DMOs with the freshest visible date stamps are surfacing more often than those without.

Build off-site authority that AI models actually weight

AI models do not only pull from your site. They pull from Wikipedia, Reddit, TripAdvisor, Google Maps, YouTube, and a handful of authoritative travel publications. If your destination is thin on any of those, your AI visibility suffers.

Concrete moves:

Own your Wikipedia page. Most destinations have one; most destinations are not actively maintaining it. Make sure it’s factually current, properly sourced, and reflects the attractions and events you want discoverable. Wikipedia is one of the most heavily-weighted sources across every major AI model.

Claim and maintain your Google Business Profile and TripAdvisor listings for the DMO itself and for the major attractions your destination owns or supports. These feed both traditional and AI search.

Seed accurate content on Reddit. Not spam — authentic, helpful answers from people who actually know the destination. Subreddits like r/travel, r/solotravel, and city-specific subreddits are disproportionately cited by AI models. A single well-written thread about your destination’s best shoulder-season hikes can be extracted by a model years later.

Invest in YouTube. Video transcripts are increasingly being used as retrieval sources by AI search. A clean, searchable YouTube channel with titles and descriptions that match real visitor questions is as important as a clean website.

Measure what you can, and accept that some of it will be imprecise

AI search measurement is not as clean as traditional organic-search reporting, and no vendor has solved this perfectly yet. What you can measure:

Referral traffic from AI surfaces. ChatGPT, Perplexity, and Google AI Overview referrers show up in analytics. They are usually small but growing. Track the trend, not the absolute number.

Branded query volume. If your AI strategy is working, branded searches for your destination should increase over time as more users discover you through AI answers.

Manual audit frequency. Set a calendar reminder to re-run the same 10-15 AI queries every 60 days. Changes in which sources the AI cites and which facts it reports are your best qualitative signal that the strategy is working — or that a competitor destination has moved faster.

Direct bookings from emerging channels. If your partner hotels and tour operators start reporting unusual referral patterns or “I saw you on ChatGPT” comments in booking notes, capture those anecdotes. They’re directionally valuable even when they aren’t statistically clean.

AI search is not going to replace traditional destination marketing. But it is already reshaping the top of the funnel in ways that punish DMOs that treat it as a 2028 problem. The DMOs that are investing quietly now — auditing, restructuring, and seeding — are the ones that will still be discoverable when their competitors notice the shift.

Photo by Planet Volumes on Unsplash