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AI visibility for city tourism boards

A quarter of US travellers say they are less likely to visit a destination website with no AI features, while 22% of destination organisations offer AI planning on theirs. For a city board, whose site is often the visitor's first stop, that is a question about the site's role rather than about a feature.

What the data says

Most city boards treat their website as the destination's shop window. The traveller data complicates that. 25% of US travellers say they are less likely to visit a destination website that has no AI features, measured in April 2026 (a stated preference, and the downside counterpart to the 63% who say they would use an AI trip planner on a destination site).

In the same study, 22% of destination organisations offered one. The asymmetry is not really that a feature is missing. It is that the site is increasingly judged against the assistant the visitor has just come from.

City destinations attract the most task-specific questions in this dataset. 60% of US AI users research attractions, restaurants and transport with an assistant (the highest task-level figure available) and 38% of AI users across 33 markets use AI for destination research before a trip.

These are precisely the questions a city board's content has always answered: what to see in three days, where to eat near the station, how the transport card works. The difference is that the answer is now assembled elsewhere from whatever is readable, and official city content competes with aggregators that publish more structured text than it does.

The zero-click worry is overstated for this segment, and there is a figure for it. About half of US travellers who encounter an AI answer inside a search engine still click through to the source websites. Being named in the answer therefore still sends visits, which changes the investment case: a city board is not choosing between AI visibility and its own traffic, it is choosing whether its site is the thing the answer points at. That is a more favourable position than the sector's commentary usually allows.

The sequencing follows from the same numbers. The planner that 63% of US travellers say they would use is a product, with a budget, a vendor and a maintenance burden. The structured, current, specific content that puts the city into the answers those same travellers see first is editorial work the organisation already does, in a different format.

Doing the second well is a precondition for the first being worth building, because an AI planner sitting on stale underlying facts produces confident wrong answers faster than a static page ever did.

Three things to do

  1. 1

    Answer the three-day question in text

    The itinerary, the neighbourhood guide, the transport explainer and the opening-hours page are a city board's most retrievable assets, and they are often published as a downloadable PDF or inside a map widget. Rebuild them as plain, dated, specific HTML text. Explicit minutes, prices and hours outperform atmospheric prose by a wide margin here.

  2. 2

    Fix the facts that go stale weekly

    Museum closing days, seasonal opening, roadworks, event dates, transport card prices. Decide who owns each, give each a visible last-updated date, and delete last year's version rather than leaving it to be retrieved. A city has more fast-moving facts than any other kind of destination.

  3. 3

    Measure by question, not by page

    Run the questions visitors actually ask (three days, with children, in February, near the station, on a budget) and record who is named and cited for each. The gap between where your content is strong and where the engines cite an aggregator instead is your work list, in priority order.

The evidence on this page

Every figure above comes from one of these indicators. Each one links to its publisher, field period and sample, so you can check the reading for yourself.

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