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Destination Discourse · July 16 · 52 min

90: Why Would AI Ever Trust Your DMO's Content?

In this episode of Destination Discourse, Stuart Butler and Adam Stoker tackle a question most DMOs would rather avoid: why should AI ever trust your content over anyone else's? Stuart's thesis - DMOs have grown addicted to equitable treatment of every stakeholder, from alphabetized hotel lists to identical exposure for every attraction, even when real-world demand isn't equal. The conversation opens with Stu's News: Meta's new AI-powered search inside Facebook, now synthesizing answers instead of pointing to profiles, plus the controversy over Meta's "Muse" image tool training on public photos - both signals of how fast AI is reshaping the search landscape DMOs operate in. Stuart's example: if Ripley's Aquarium pulls 5x the visitation of Ripley's Believe It or Not, why promote both the same? He argues DMOs need a firewall between promotional and editorial content, like old-school newspapers. Adam pushes back: the fix isn't softer language, it's stakeholder education - clear performance criteria (a review-score threshold, say 4.2+) and the courage to tell underperforming members they won't be featured until the experience improves. They also flag a measurement problem: referral traffic to stakeholder sites, the metric most DMOs lean on, is heading toward zero as bookings move inside closed AI ecosystems. Bottom Line: LLMs don't reward promoters, they reward trust - and no DMO is entitled to it.

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show notes

In this episode of Destination Discourse, Stuart Butler and Adam Stoker tackle a question most DMOs would rather avoid: why should AI ever trust your content over anyone else's? Stuart's thesis - DMOs have grown addicted to equitable treatment of every stakeholder, from alphabetized hotel lists to identical exposure for every attraction, even when real-world demand isn't equal.

The conversation opens with Stu's News: Meta's new AI-powered search inside Facebook, now synthesizing answers instead of pointing to profiles, plus the controversy over Meta's "Muse" image tool training on public photos - both signals of how fast AI is reshaping the search landscape DMOs operate in.

Stuart's example: if Ripley's Aquarium pulls 5x the visitation of Ripley's Believe It or Not, why promote both the same? He argues DMOs need a firewall between promotional and editorial content, like old-school newspapers. Adam pushes back: the fix isn't softer language, it's stakeholder education - clear performance criteria (a review-score threshold, say 4.2+) and the courage to tell underperforming members they won't be featured until the experience improves.

They also flag a measurement problem: referral traffic to stakeholder sites, the metric most DMOs lean on, is heading toward zero as bookings move inside closed AI ecosystems.

Bottom Line: LLMs don't reward promoters, they reward trust - and no DMO is entitled to it.