For DMOs & Visitor Bureaus
AI for DMOs: what actually changes.
Travellers now ask an assistant before they ever reach an official tourism website. That moves the decisive moment upstream of everything a destination marketing organisation currently controls, and makes the readability of your supplier data a marketing question, not an IT one.
of travellers have already used AI to plan or book travel
begin planning without a single destination decided, so what gets recommended shapes what they consider
of tourism rests on SMEs and local businesses, whose visibility decides where the spend flows
say recommendations influence what they ultimately book
The decisive moment moved upstream
A destination’s campaign reaches a traveller who is already considering it. The assistant reaches them before that: when a traveller asks where to go, what is worth doing, or whether somewhere is a good fit, the shortlist is assembled from whatever the model can read. If your suppliers are not readable, the campaign is competing for a place on a list it was never on.
The question comes first
Travellers ask an assistant before they visit an official tourism or government site. The site is now the second stop, and sometimes not a stop at all.
Absence is the failure mode
Being described badly is recoverable. Not being mentioned is not, and nothing in a standard analytics stack reports it.
What the marketing team owns now
Supplier data stops being back-office record-keeping and becomes distribution. The practical shift is that a DMO’s job now includes making sure the ecosystem it represents can answer questions, not only that it can be admired.
From inspiring to answering
A brochure page inspires. A structured record answers. AI-led planning rewards the second and cannot use the first.
From assets to entities
The unit of work becomes the supplier as a machine-resolvable entity with a stable identifier, not the campaign asset that features them.
From reach to representation
The number worth reporting is whether the destination appears, accurately, in the answers travellers are actually given.
What a marketing team can report
A fixed set of realistic traveller prompts, run against the major AI assistants every week and scored on three things: whether the destination is mentioned at all, whether the suppliers named actually exist and are described accurately, and whether the answer is favourable. Tracked against a Day 0 baseline, that is a reportable number rather than a claim. Website analytics cannot substitute for it, because the traveller never reached the website.
Whether you appear at all
The share of traveller questions where the destination is mentioned, which is the number absence hides in.
Whether the detail is right
Whether the suppliers named are real and described accurately, because being mentioned wrongly is its own failure.
The blind spot it closes
A recommendation that excluded your destination leaves no trace in analytics. This is the only place that loss shows up.
Where a destination starts
With a baseline, not a platform. Before committing to a programme, a destination should know what assistants say about it today, which categories are thin, and which cohort of suppliers would most change the answer. That is a scoped piece of work with a document at the end of it, and it is deliberately the first thing we do.
An AI-readiness audit of what exists
Whether an llms.txt exists, whether pages carry structured data, whether robots.txt actually admits AI crawlers, whether entities have stable identifiers, and whether the content answers questions directly.
A Day 0 discoverability baseline
What assistants currently say, captured before any work begins, so the programme is judged against a number rather than a narrative.
A prioritised first cohort
The suppliers whose absence costs the most, agreed with the destination before outreach opens.
Common questions
Answers, in the body of the page.
- How can a DMO use AI effectively?
- The highest-return use of AI for a DMO is not generating more marketing content. It is making the destination’s supplier ecosystem machine-readable so that AI systems can recommend it accurately. That means collecting structured data directly from suppliers, publishing it with schema.org markup and stable identifiers, and measuring how assistants answer traveller questions about the destination before and after. Content generation competes in a surplus; readable supplier data is still scarce.
- Is this the same as SEO for a tourism board?
- This is data work. An AI assistant can only describe your suppliers if it holds structured, current information about them, and for most independent operators that information has never been written down in a machine-readable form anywhere. GOAGENTIC collects it from the suppliers themselves, structures it to an agreed taxonomy, publishes it in the forms assistants read, and measures whether the answers travellers are given actually change.
- What should a DMO measure to know if AI visibility is improving?
- Run a fixed set of realistic traveller prompts against the major assistants on a schedule and score three things: whether the destination is mentioned at all, whether the suppliers named actually exist and are described accurately, and whether the answer is favourable. Tracked week over week against a Day 0 baseline, that is a reportable number. Website analytics cannot substitute for it, because the traveller never reached the website.
- Our suppliers are small and hard to reach. Does this work for them?
- They are the reason the approach exists. Large chains already publish structured data; independent restaurants, guides and cultural operators generally do not, which is precisely why they are missing from AI answers. Reaching them over WhatsApp, email or a phone call in their own language, in short conversations rather than a portal login, is what makes the long tail reachable, and the long tail is what makes a destination distinctive.
Where we start
Find out what AI says about your destination today.
We read your site the way an AI crawler does, six checks and no opinion in any of them, and capture a Day 0 baseline of what assistants currently say. Before any programme is committed to.