What AI search actually changes for experience brands

Every attraction operator I have spoken to this year has asked some version of the same question, usually phrased with more alarm than the situation deserves. The honest answer is that AI search is a real change to a narrow part of the funnel, and most of what is being sold as a response to it is noise.

What is actually different about how people find venues now?

The old path was a search, a page of ten blue links, and a click. The new path, for a growing share of queries, is a search, a synthesised answer, and sometimes a click. The synthesis is assembled from pages the engine decided to trust.

That matters more for some queries than others. “Trampoline park near me open on Sunday” gets answered in the interface. Nobody clicks, and nobody needed to. But “is Jumpoline or Funky Island better for a nine-year-old’s birthday” still produces a click, because the parent wants photographs, a party package page and a sense of whether the place is chaos on a weekend.

So the first thing to do is stop treating traffic as one number. Split it. Informational traffic is going to fall and that is fine. Commercial and transactional traffic is the traffic that was ever worth anything, and it is holding up.

How do AI engines decide which sites to cite?

They run a search, read what comes back, and quote the sources that answer the question most directly. That is the entire pipeline, and understanding it dissolves most of the mystique.

Three things follow from it.

The first is that classical SEO still matters, because being in the retrieved set is a precondition for being cited. If you are not findable, you are not citable.

The second is that structure beats prose. Princeton researchers testing generative engine optimisation found that citing sources, adding statistics and including quotations improved visibility in AI answers by roughly 30 to 40% against unoptimised content. Those are not writing-quality improvements. They are extractability improvements.

The third is that off-site presence matters more than most venue operators assume. One 2026 analysis found that distributing content across multiple publications increased AI citations by up to 325% compared with publishing only on your own domain. For a venue, that means local press, parenting publications, event listings and genuine review activity are not brand fluff. They are now part of the same system as your website.

What should a venue website actually do?

Four things, in order of return.

Answer the question in the first paragraph. Each important page should open with a direct forty-to-sixty word answer to the question that page exists for. Not a welcome message, not a brand statement. If your party packages page opens with “Welcome to the most exciting destination in the city”, you have handed the engine nothing to lift. If it opens with what a party costs, how many children it covers, how long it runs and what is included, you have.

Make your entity facts identical everywhere. Your venue name, address, opening hours and category should match exactly across your site, your Google Business Profile, your Instagram bio and every listing site. Engines build confidence about an entity from repetition. Three slightly different versions of your address is three reasons to cite someone else.

Implement the four schema types that matter. LocalBusiness with real hours and price range, FAQPage on the pages that answer questions, Article on anything you publish, and BreadcrumbList so the hierarchy is explicit. We treat these as non-negotiable in the measurement work we do for venues, because the same structured data feeds both reporting and discovery.

Let the crawlers in. Check your robots.txt and your bot-protection rules for GPTBot, ClaudeBot, OAI-SearchBot, PerplexityBot and Google-Extended. A surprising number of venue sites sit behind aggressive bot rules that a developer added years ago and nobody has reviewed. Blocking those agents is the most efficient way to disappear from AI answers.

What can you safely ignore?

Most of the tooling being marketed at you right now.

Start with llms.txt. It was a thoughtful proposal, and the 2026 evidence is unambiguous: one analysis of 515 million AI bot events found 408 requests to the file, Ahrefs found 97% of published files received no requests at all, and Google’s own documentation says it has no effect on Search or AI Overviews. No major lab has committed to reading it in production. If your site generates one automatically, fine. If someone is charging you for it, stop.

Then there is the category of AI visibility monitoring platforms. These are real products solving a real problem, and they are genuinely useful once you have something to monitor. For a single-venue operator publishing four pages a year, paying a monthly subscription to discover that you are not being cited is expensive confirmation of something you already suspect. Build the pages first.

Finally, ignore anyone promising a specific position in an AI answer. Outputs are non-deterministic. The same prompt produces different citations on different days, from different accounts, in different regions. Anyone quoting you a guaranteed placement is describing something that does not exist.

How should you measure any of this?

Separate the two questions, because only one of them is cheap.

Whether AI crawlers are reaching your pages is measurable for free, from your own server or CDN logs, broken down by user agent. If OAI-SearchBot and PerplexityBot are at zero over thirty days, you have a technical problem to fix before you have a content problem to solve.

Whether engines are actually citing you, and for which prompts, is not free. It needs repeated querying of each engine and parsing of the answers, which is what the paid platforms do. The affordable substitute is a fixed list of ten or fifteen prompts that matter to your business, checked manually once a quarter, logged in a spreadsheet with the competitor who got cited instead. It is tedious and it works, and it is the same discipline we apply to creative testing: write the hypothesis down, check it on a schedule, keep the record.

The uncomfortable part is that none of this is a growth channel yet for most venues. It is insurance on a channel that is still forming. Spend accordingly: fix the technical blocks this month, restructure your five most important pages this quarter, and leave the monitoring subscription until there is something worth monitoring.