Walk into almost any DMO in 2026 and ask the team to map their AI footprint. You will hear a list. The CRM has an AI scoring layer. The website has an AI chatbot. The content team uses ChatGPT. The video editor uses an AI subtitle tool. The PR team uses an AI press list builder. Marketing uses AI-generated subject lines in email. The board recently approved a pilot with a vendor for AI-driven media buying.

That is not an AI strategy. That is a stack of disconnected AI tools, each one solving for the problem of whatever team bought it. None of them talk to each other. None of them share underlying data. And none of them produce a coordinated visitor experience or a coordinated internal workflow. By the end of 2026, that gap is going to start showing up in measurable performance — both on visitor-facing metrics and on internal cost.

The fragmentation problem is bigger than any single tool

The vendor world has been making this worse, not better. Every DMO platform — Simpleview, Sojern, Zartico, Satisfi, Madden, GuideGeek, the new wave of agentic startups — has shipped its own AI features over the last 18 months. Each is excellent in isolation. None are integrated by default.

And the recent push toward “agentic” deployments raises the integration stakes. Satisfi Labs’ new Agentic City Program with Experience Columbus is a useful preview: every DMO partner gets its own agent, sourcing answers dynamically from each location’s website, and over time those agents can connect back to Experience Columbus and to each other. That is one network. The DMO running it now has to figure out how that network connects to the CRM, the email system, the visitor data warehouse, and the campaign attribution stack.

If your AI tools cannot exchange data, you do not have leverage. You have a parts bin.

What an actual AI strategy looks like for a DMO

There are five layers, and they have to be designed together — not procured in sequence by individual teams.

Layer 1: Data foundation. First-party data needs to live in one canonical place — visitor data, partner data, sales data, content metadata, behavioral signals. Without this, every AI tool downstream is making decisions on a partial picture of the destination.

Layer 2: Visitor-facing AI. Chatbots, agents, content recommendations, itinerary builders. These tools have to read from the same data foundation. A visitor asking your chatbot a question and a visitor receiving an email a week later should not feel like they are talking to two different organizations.

Layer 3: Internal productivity AI. Content drafting, brief generation, SEO research, design ideation, video editing. This is where most DMO teams have started — and where the per-employee productivity gains can hit 20–30% if rolled out with consistent training.

Layer 4: Decision support AI. AI that helps leadership make resource allocation, partner prioritization, and campaign-mix decisions. This is the layer most DMOs haven’t even started — and the one with the highest strategic ROI. Sojern’s 2026 State of Destination Marketing report ranks measuring economic impact as the top DMO priority right now, and AI-assisted decision-making is the only realistic way smaller DMOs will get there with the staff they have.

Layer 5: Governance and policy. Where you allow AI to make autonomous decisions, where you require human review, what data can be fed to vendors, what your stance is on disclosed AI-generated content. If this layer is missing, the other four create legal and brand risk that compounds over time.

The CEO question to ask this quarter

Pull every team lead together and ask: “For every AI tool we use, who else in the org has access to its outputs?” If the honest answer is “nobody else” for more than half the tools, the org is operating with AI at the team level, not the institutional level.

That is the gap that will compound. The DMOs that close it in 2026 will compound benefits — better visitor experience, lower per-campaign cost, faster content cycles, smarter board-level decisions. The DMOs that don’t will spend the next two years quietly paying for tools that never quite produce the lift the vendor demoed.

AI strategy is not a procurement decision. It is a leadership decision about how the org wants to operate. The window to make that call deliberately — rather than have it made for you by the vendor with the biggest sales team — is now.

Photo by Vitaly Gariev on Unsplash