According to fresh industry benchmark data, 72 percent of destination marketing professionals feel ill-equipped to adopt AI tools and platforms. Three-quarters say AI is not a strategic priority within their organizations. Meanwhile, more than half are already using AI for data analysis, and two-thirds are using it for content creation.

Read that again. Most DMOs are actively using AI while simultaneously telling themselves it isn’t a priority and they don’t know what they’re doing. That is not a technology problem. That is a leadership posture problem — and it’s one worth naming directly.

The Difference Between Using a Tool and Having a Strategy

There is a meaningful difference between a team member who has figured out how to generate first drafts in ChatGPT and an organization that has made a deliberate strategic decision about where AI creates competitive advantage. Most DMOs are in the first category. That’s fine as a starting point. It becomes a problem when it’s the ceiling.

When AI is just a productivity shortcut for individual staff members, the organization captures incremental efficiency gains. When AI is a strategic capability — integrated into visitor intelligence platforms, used to model attribution, applied to audience segmentation and campaign personalization — the gains compound. The organizations that figure that out now will build data infrastructure and internal capability that is genuinely difficult for slower-moving peers to replicate.

The gap between “using AI for content” and “AI as a strategic priority” is not a technology gap. It’s a decision about whether leadership is willing to invest in capability building, and whether they’re willing to have hard conversations about resource allocation, staff training, and vendor partnerships.

Why Most DMOs Default to Tactical AI Use

There are structural reasons why DMOs end up here. Destination organizations are often under-resourced relative to their mandates. Staff bandwidth is consumed by campaigns, partner relations, board reporting, and operational work. Strategic capability investments — the kind that take 12 to 18 months to pay off — are chronically deprioritized in favor of this quarter’s deliverables.

Technology vendors haven’t helped much either. The DMO tech ecosystem has been flooded with AI-adjacent product claims, many of which amount to AI-assisted content generation with a destination marketing wrapper. That noise makes it harder for practitioners to distinguish between tools that genuinely build organizational intelligence and tools that just make it slightly faster to write Instagram captions.

The result is an industry that adopted AI at the edges — where it was easiest and lowest-risk — without ever asking the harder question of what AI-enabled destination marketing actually looks like at the strategic level.

What a Strategic Approach Actually Requires

It starts with a deliberate question: where in our operation would AI create the most durable competitive advantage? The answer is almost never content creation. Content generation is table stakes — every competitor has the same tools. The places where AI creates defensible advantage are in data: first-party visitor data aggregation, behavioral modeling, attribution across the conversion funnel, and predictive modeling for seasonal demand.

Getting there requires three things most DMOs don’t currently have in alignment: a data infrastructure that aggregates visitor signals across channels, staff capability to work with that data or vendor partners who genuinely can, and leadership willingness to report on AI-driven outcomes rather than AI activity.

That last one matters more than it might seem. Organizations report on what leadership cares about. If the CEO and board are asking “how many posts did we generate with AI this week,” the team optimizes for production volume. If leadership is asking “what did our visitor intelligence tell us about conversion rates this month and how did we act on it,” the organization builds toward that.

The Window Is Real

One of the persistent myths about technology adoption cycles is that there’s always time to catch up. Sometimes that’s true. Sometimes the organizations that build capability early establish a compounding advantage that latecomers can’t replicate — not because the tools become unavailable, but because the institutional knowledge, the data accumulation, and the operational integration take years to build.

Destination marketing is not a fast-moving industry. That cuts both ways. The good news is that most DMOs are at similar stages of AI maturity, so the gap to close is not yet enormous. The risk is that the organizations — and the vendors serving them — that decide now to treat AI as infrastructure rather than as a productivity shortcut will look very different from their peers in three years. That divergence has already started.

The 72 percent figure is not alarming because it means most DMOs are behind. It’s alarming because most of those organizations are also not doing anything about it. Feeling unprepared is a data point. Choosing to stay unprepared is a strategy — and not a good one.