AI Search and Destination Discovery: 15 FAQs for DMOs

February 2026.

Travel planning is shifting. Visitors are no longer typing queries into Google and clicking through ten blue
links. They’re asking ChatGPT, Gemini, Perplexity and Copilot to plan their trip, and getting a complete answer
without ever visiting your website.

For DMOs and tourism operators, this raises urgent, practical questions. Here are 15 of them, answered.

Q1. How do AI tools interpret destination websites, and how should DMOs restructure their content?

Large language models don’t browse your website the way a human does. They don’t admire your hero image or follow your navigation. They read your text, strip out the formatting, and try to extract facts.

What AI tools look for:

• Clear, factual statements (“The Great Barrier Reef is accessible from the Town of 1770 via Lady Musgrave
  Experience, departing daily at 7am”)
• Structured headings that signal topic hierarchy (H1 = destination, H2 = experience category, H3 = specific
  operator)
• Consistent naming across pages (if you call it “Agnes Water” on one page and “the Discovery Coast” on another,
  the AI may treat these as separate places) What confuses AI tools:
• Emotive copy with no factual anchors (“Where the reef meets the rainforest and dreams come alive”)
• PDFs, image-only content, and JavaScript-rendered pages that crawlers can’t read
• Buried practical information (opening hours three clicks deep, pricing only in a booking widget) What to do: Restructure every page so it leads with a clear, factual summary paragraph before the storytelling
  begins. The AI gets its facts from the first paragraph. The human gets the emotional connection from the rest.

Q2. What is “Answer Engine Optimisation” and what does it look like for destinations?

Traditional SEO optimised for ranking. AEO optimises for being the answer.

When someone asks an AI assistant “What should I do in the Whitsundays for three days?”, the AI doesn’t return a list of links. It builds an itinerary. Your goal is to be the operator or destination it names.

AEO principles for tourism:

• Answer the question directly. If your page is about snorkelling, the first sentence should say where, when, how long, and how much. Not “Discover the magic of the underwater world.”
• Use the questions visitors actually ask. Structure content around real queries: “Is the reef suitable for
  non-swimmers?”, “Can I do a day trip from Bundaberg?”
• Provide complete information. AI prefers sources that answer follow-up questions without needing another search. Include logistics, pricing, seasonal notes, and accessibility on every experience page. The destinations that win at AEO are the ones that make the AI’s job easy. If your content is clear, complete and well-structured, the AI has no reason to look elsewhere.

Q3. What signals do AI tools use to prioritise certain operators over others?

When an AI recommends “where to eat in Noosa”, it draws from multiple sources, weighted roughly as follows:

High weight:

• Google Business Profile completeness and accuracy
• Volume and recency of Google reviews
• Consistency of business information across the web (name, address, phone, hours)
• Presence on authoritative tourism websites (destination website, state tourism body, ATDW) Medium weight:
• TripAdvisor and Booking.com reviews and ratings
• Mentions in editorial content (blog posts, travel guides, news articles)
• Structured data and schema markup on the operator’s own website Lower weight (but growing):
• Social media presence and engagement
• User-generated content mentioning the business
• Direct mentions in other AI conversations (a feedback loop that’s just beginning) DMOs can help by running operator workshops. Most operators don’t know their Google Business Profile is their most
  important digital asset.

Q4. How important is structured data and schema markup?

Very. But not in the way most people think.

Schema markup doesn’t directly make AI recommend you. What it does is make your information machine-readable, so AI tools can extract facts accurately rather than guessing.

Priority schema types for tourism:

• TouristAttraction for experiences and points of interest
• LocalBusiness for operators (with openingHours, priceRange, address)
• Event for festivals, markets, seasonal activities (with dates)
• FAQPage for common visitor questions (AI tools love this format)
• BreadcrumbList to help AI understand your site hierarchy The consistency rule: Schema markup is only useful if it matches what’s on the page, what’s on your Google
  Business Profile, and what’s on ATDW. If your website says you close at 5pm, your GBP says 6pm, and ATDW says 4pm, the AI may give up and not recommend you at all.

Q5. If travellers stop visiting destination websites, what’s the website’s role?

Your website isn’t dying. Its role is changing. It’s shifting from being the primary discovery channel to being
the authoritative source that AI tools reference.

The visitor may never see your website, but ChatGPT or other LLMs (Large Language Models) did. And it used your content to recommend your destination.

The new roles of the destination website:

1. AI training ground. Your website is where AI tools learn about your destination. Every page is a training
   document.
2. Verification source. When AI tools cross-reference information, your website is the authoritative source for
   your region.
3. Conversion endpoint. Visitors who arrive via AI referral tend to be further down the funnel. They’ve already
   decided to visit. Your website needs to convert, not convince.
4. Content hub for operators. Your operator listings feed into AI recommendations. Keep them current. New success metrics:

• AI citation rate (how often AI tools reference your content)
• Answer accuracy (are AI tools getting your destination right?)
• Conversion rate per visit (fewer visits, but higher intent)
• Distributed reach (website + embed widgets + AI citations = total reach) Stop measuring total traffic as your primary KPI. Measure influence instead.

Q6. How can operators ensure AI directs travellers to their direct booking channel rather than OTAs?

This is the million-dollar question. AI tools currently favour OTAs because OTAs have better structured data, more reviews, and more consistent information.

What operators can do:

• Have a bookable website. If yours says “call to book” or “enquire now”, the AI can’t recommend a direct booking. You need real-time availability and online booking.
• Use booking schema markup. Add offers and potentialAction schema so AI tools know this is a bookable product.
• Keep pricing on your website. AI tools can’t recommend your direct channel if the price is only visible inside a booking widget the crawler can’t read.
• Build review volume on Google. The more reviews on your GBP, the more likely AI tools are to reference your primary listing rather than an OTA aggregation.
• Claim and optimise ATDW. Australia’s official tourism database feeds into Google and AI tools. Incomplete ATDW = invisible to the ecosystem.

Q7. Are AI tools using social content for recommendations, and how should destinations respond?

Yes, but not in the way social marketers expect.

AI tools are increasingly ingesting public social media content, particularly:

• TikTok and YouTube for “hidden gem” and “things to do” recommendations
• Instagram for visual verification (AI can now interpret images and associate them with locations)
• Reddit for authentic, unfiltered travel advice (a major source for AI travel recommendations) What this means for your social strategy:
• Use location tags and full place names in captions, not just hashtags. “Snorkelling at Lady Musgrave Island,
  Town of 1770″ is more useful to AI than “#1770life #reefdays”
• Include practical information in captions. Duration, pricing, seasonal availability. The emotive caption with
  zero facts is invisible to AI.
• Create list-style content that AI tools can parse: “5 free things to do in Agnes Water”
• Encourage operators to do the same. User-generated content from operators and their visitors contributes to the
  AI training data pool.

Q8. How can destinations balance emotive storytelling with machine-readable content?

You don’t have to choose. You layer.

The “Facts First, Story Second” structure:

Snorkelling at Lady Musgrave Island

Lady Musgrave Island is a coral cay on the southern Great Barrier Reef, accessible by boat from the Town of 1770. Day trips run daily from October to May, departing at 7am. Includes snorkelling, glass-bottom boat tours, and island walks. Suitable for non-swimmers (pontoon available). From $250 per adult.

The moment you slip beneath the surface, the reef unfolds like a living tapestry. Turtles glide past with an
unhurried grace that makes you forget you have a return boat to catch…

AI tools extract from the factual lead. Humans read the story. Both audiences are served.

Test: If you deleted all your storytelling and only the facts remained, would an AI still know what the experience
is, where it is, when it operates, and how much it costs? If not, add more facts.

Q9. What are the top 3 things DMOs can tell operators to do today?

1. Complete your Google Business Profile. Completely. Not just name, address, phone. Fill in every field: categories, attributes (wheelchair accessible, outdoor seating, pet-friendly), business description, products/services. Keep opening hours current. Respond to every review. Add photos monthly. This is your most important digital asset in the AI era.
2. Put real answers on your website. Write a genuine FAQ page that answers the questions your visitors actually ask. Not marketing fluff. Real questions: “Can I bring my dog?”, “Is there shade?”, “What happens if it rains?”, “How far is the car park from the entrance?” These are the questions AI tools get asked, and your answers become the AI’s answers.
3. Be consistent everywhere. Your business name, address, phone number, opening hours, and pricing must be identical on your website, Google Business Profile, ATDW, TripAdvisor, Facebook, and any other listing. Inconsistency is the number one reason AI
   tools skip over businesses. If the AI isn’t sure which information is correct, it won’t recommend you.

Q10. How critical are Google Business Profiles and review content?

Google Business Profiles are the single most important data source for AI-driven tourism recommendations. Full
stop.

Google’s own AI products (Gemini, Search Generative Experience) pull directly from GBP data. Other AI tools
(ChatGPT, Perplexity, Copilot) also scrape or reference Google’s knowledge graph, which is built primarily from
GBP data.

What matters most:

• Completeness — every field filled
• Accuracy — hours, location, contact details all correct
• Categories — primary and secondary categories properly set
• Attributes — accessibility, amenities, payment methods
• Review volume and recency — not just star rating
• Review responses — AI tools can read owner responses
• Photos — AI can now interpret images and associate them with experience quality The review content matters as much as the rating. When a reviewer writes “amazing snorkelling, saw three turtles,
  the crew were fantastic and the lunch was surprisingly good”, the AI extracts: snorkelling quality (high),
  wildlife (turtles), service quality (high), food quality (good). These become the attributes the AI uses when
  matching the experience to a visitor’s query.

Q11. How much weight do AI systems place on reviews when recommending destinations?

Substantial. Reviews are one of the few sources of authentic, unfiltered information that AI tools trust.

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What AI extracts from reviews:

• Specific experiences mentioned (activities, food quality, scenery)
• Sentiment about specific aspects (not just overall rating)
• Recency signals (recent reviews weighted higher)
• Response patterns (businesses that respond are seen as active and reliable)
• Complaint patterns (repeated complaints about the same issue = red flag) Help operators understand that reviews are no longer just social proof for website visitors. They’re training data
  for AI. A business with 500 detailed Google reviews will be recommended by AI far more than a business with 5,
  regardless of how beautiful their website is.

Q12. If AI reduces website traffic but still influences visitation, how should destinations rethink measurement?

The old funnel (website visits, enquiries, bookings) is breaking. A visitor might plan their entire trip via
ChatGPT, never visit your website, but still come to your destination and spend money.

New measurement framework:

1. Distributed Reach: Measure total reach across all channels: website visits + chatbot conversations + embed widget interactions + AI
   citations.
2. AI Accuracy Score: Monthly, query AI tools about your destination. Measure factual accuracy, business coverage, and competitor
   positioning.
3. Conversion Quality: Fewer visitors, but higher intent. Track conversion rate per session (should be increasing), average booking value, and time from first visit to booking (should be decreasing).
4. Influence Attribution

• Survey visitors: “How did you plan your trip?” Add AI tools as an option
• Track referrer data (AI platforms have distinct referral signatures)
• Correlate AI citation rate with visitation trends Accept that you can’t measure everything. The visitor who planned via ChatGPT and booked via phone may never
  appear in your digital analytics. That’s okay. Measure what you can, and use proxies for the rest.

Q13. What content formats are most effectively interpreted by AI tools?

Excellent for AI:

• FAQ pages: question-and-answer format maps directly to how users query AI
• Structured itineraries: “Day 1: …, Day 2: …” is easily parsed and recombined
• Categorised lists: “Top 10 family-friendly activities” with name, description, price, location
• Comparison tables: tour options, accommodation tiers, seasonal availability grids
• “How to” guides: “How to get to Lady Musgrave Island” with step-by-step logistics
• Long-form editorial with clear subheadings
• Operator profiles with structured information blocks
• Seasonal guides with specific dates and conditions
• Accessibility guides with specific detail Poor for AI:
• Image-heavy pages with minimal text
• Video-only content (transcripts help)
• Interactive maps without text-based location data
• Content locked behind forms, logins or JavaScript widgets
• PDF brochures (invisible to most AI crawlers) The optimal page structure: Factual summary paragraph, structured details (table or list), FAQ section (3-5 real questions), storytelling and imagery, schema markup throughout.

Q14. How can destinations monitor and correct misinformation that AI tools present about their region?

AI tools confidently present outdated or fabricated information. A restaurant that closed two years ago gets
recommended. A hiking trail gets the wrong difficulty rating. A town gets placed in the wrong state.

Monitoring:

1. Regular AI audits. Monthly, query ChatGPT, Gemini, Perplexity and Copilot with your top 20 visitor questions. Log the responses. Flag inaccuracies.
2. Track patterns. Are certain businesses consistently misrepresented? This tells you where your source data is weak.
3. Identify the root cause. AI misinformation usually traces back to: outdated website content, inconsistent data across platforms, missing information (AI fills gaps with guesses), or thin web presence. Correction:
   You can’t email ChatGPT and ask for a correction. But you can fix the sources:

• Update your website content (AI tools re-crawl regularly)
• Fix Google Business Profile data
• Update ATDW listings
• Publish a definitive, fact-rich page that becomes the authoritative source
• Ensure all platforms agree on the same facts Consider building your own AI concierge that uses verified local data. This gives you control over accuracy and
  lets you offer a trusted alternative to generic AI tools.

Q15. What will the destination website of 2028 look like, and what’s your advice for DMOs redesigning now?

The destination website is evolving from a brochure into a data platform.

What stays: Beautiful imagery and storytelling, operator listings, event calendars, blog content.

What changes:

AI-first information architecture. Every page structured for machine reading first, human browsing second.

Embedded AI concierge. Visitors ask questions and get personalised answers from your own AI, grounded in verified data.

Real-time data layers. Weather, tides, events, business hours, availability. Surfaced dynamically, not buried in static pages.

API-first design. Your website becomes one consumer of your data. Others include AI platforms, partner websites, state tourism bodies, and national platforms.

Structured data everywhere. Schema markup as a core part of the CMS workflow, not an afterthought.

Advice for DMOs redesigning now:

1. Don’t build a brochure. Build a content platform with structured data at its core.
2. CMS matters more than design. Choose a CMS that makes it easy to maintain structured, up-to-date operator and experience data. A beautiful website with outdated content will be ignored by AI.
3. Build for multiple outputs. Your content should feed your AI concierge, email templates, social content, and external AI platforms. One source of truth, many channels.
4. Invest in FAQ content. Comprehensive, question-based content for every experience category. This is the format AI tools consume most effectively.
5. Plan for embeddability. Your chatbot, event calendar, and operator directory should all be embeddable on
   partner websites. Your reach should extend beyond your own domain.
6. Budget for maintenance, not just launch. A website that’s accurate in 2028 is more valuable than a stunning website that’s outdated by 2029.

Conclusion

AI isn’t replacing destination marketing. It’s replacing the discovery layer. Visitors still want to visit your
region, eat at your restaurants, and snorkel your reefs. They’re just finding you differently.

The good news: most of this work is practical, achievable, and within your control. Complete Google Business
Profiles. Structured website content. Consistent data. Regular AI audits. Operator education.

The destinations that act now will have a significant head start. Because once AI tools learn your destination
well, that knowledge compounds. Every accurate recommendation leads to more visitor reviews, which leads to more training data, which leads to more accurate recommendations.

The flywheel works in your favour. But only if you start it spinning.