Ask ChatGPT to plan three days in Cape wine country for two people who like Chenin Blanc and quiet places to stay, and you will get an answer. Nine recommendations. Named estates. Booking suggestions. Restaurant notes. In roughly eight seconds.
If the destination marketing organisation that should have coordinated this trip appears in that answer, it does so as one citation among many, ranked on its data, not its brand. If it does not appear, the traveller never knew it existed.
This is the quiet disappearance happening across the destination marketing sector right now. Visitor numbers hold. Brand surveys look fine. Partner conversations turn strange. And the destination's share of AI-generated recommendations, the emerging answer layer that now mediates a substantial fraction of all travel discovery, may be zero.
The DMO has not been displaced. It has been disintermediated. Travellers simply stopped walking past.
The numbers behind the shift
The data is unambiguous. Between 2024 and 2025, zero-click searches rose from 56 to 69 per cent. Google AI Overviews appear in roughly 60 per cent of U.S. searches. ChatGPT alone serves more than 800 million weekly users, a substantial and growing share of them asking travel questions. Gartner projects that 25 per cent of organic search traffic will have shifted to AI chatbots by the end of 2026.
According to the 2026 Accenture and Skift analysis, over 61 per cent of travellers now use AI tools for some portion of their trip planning - inspiration, itinerary, increasingly booking. Among travellers under 35, the number climbs to 40 per cent using AI actively for travel decisions. Noble Studios' tracking shows visitors arriving through AI-driven searches are approximately 4.5 times more valuable than those from traditional organic search - they are not browsers, they are buyers who have already compared and decided.
For a DMO operating on a three-year strategy written in 2023, this is the ground moving under the institution. The website, carefully designed and brand-consistent, still receives traffic. But the composition of that traffic is changing in ways the annual plan does not have the vocabulary for. Growth in AI-referred visitors is real but small. Citations in ChatGPT and Perplexity answers, when anyone thinks to check, often do not appear. The brand is strong. The machine-readability is close to zero.
The DMOs already leading
The counter-pattern is visible in half a dozen destinations that stopped treating AI as a marketing problem and started treating it as an operating question. Four examples tell the story.
Visit Tampa Bay
Patrick Harrison, Chief Marketing Officer of Visit Tampa Bay, deployed a Satisfi Labs conversational AI agent integrated with the destination's CRM and content systems. Within the first stretch of operation, the platform handled more than 6,500 visitor questions. Forty-five per cent of those conversations happened outside business hours - nearly half of all visitor engagement the organisation had been missing through its call-centre-only service model.
"Don't wait. We should have done it two years ago. Just the fact that 45 per cent of calls are outside of business hours - think of the money you're losing by not being able to answer those questions."
The deeper shift is structural, not tactical. The AI agent pulls dynamically from the destination's content management system, hands off intelligently to partner wineries, hotels and attractions via a chat-in-chat architecture, and collects intent data the organisation never previously had access to. Visit Tampa Bay is no longer running a marketing website with a contact form. It is operating a distributed visitor-intelligence layer in which the DMO is the coordinator and the partners are the endpoints.
Visit Mesa
At Visit Mesa, the Arizona CVB, the AI transition is being led from the top. As Destinations International reported in its 2026 sector survey, the CEO's position is that AI is not a tool the team may adopt. It is part of how the team works. Every role has at least one AI-related objective embedded in its performance plan. Learning is not optional.
"Buy-in started at the top. Our CEO set the expectation that AI is part of how we work."
Paid media has been repositioned in the same spirit. Paid clicks, Yordi notes, tell a smaller part of the story now. Visit Mesa has shifted from buying traffic to funding momentum - using PPC to capture high-intent demand and move travellers from curiosity to a plan. The chatbot rollout is tied directly to visitor experience in the physical destination, with QR codes on signage and partner touchpoints opening the AI agent instantly. The organisation's measurement framework and its operational framework have been reshaped around AI-native behaviour, not bolted on.
Visit Colorado Springs
Visit Colorado Springs deployed the GuideGeek conversational AI assistant and saw more than 6,000 messages from 3,000 unique users within the first few months, with no significant promotional push behind the launch. What the team surfaced is a behaviour pattern every destination will recognise: travellers want to ask follow-up questions, want personalised recommendations, and want to move from inspiration to itinerary in one conversation.
The institutional machinery of a traditional DMO - static pages, downloadable PDFs, generic FAQs - cannot deliver this. The AI agent can. The team has also adapted measurement. PPC performance is no longer evaluated on click-through rate alone; conversions are being redefined to emphasise engagement quality rather than traffic volume. A DMO that measures differently operates differently.
NYC Tourism + Conventions
New York City Tourism + Conventions has taken the content architecture problem head-on. The team has introduced structured Article Summary modules on high-traffic destination pages - short, link-rich, answer-capsule formats written for AI citation rather than human browsing. They track LLM impressions and referrals as a first-class metric, alongside the traditional web analytics layer.
The assumption underlying this shift, that AI systems and not human users are increasingly the first readers of DMO content, is treated as operating reality, not speculation.
Outside North America, the transition is being coordinated through the AI Opener for Destinations programme run by GROUP NAO, a peer learning network now spanning more than 300 destination professionals across 120+ participating organisations. The 2026 cohort includes Atout France, Austria Tourism, Amsterdam Partners, Failte Ireland, Helsinki & Partners, Copenhagen Capacity, Graz Tourismus, Innovation Norway, Innsbruck Tourismus, Tourism Ireland, Visit Estonia, Tourism Oslo, and VisitScotland. Their survey of participating DMOs found that 99 per cent of tourism professionals have now tried AI tools, and more than half use them weekly.
What unites these organisations is not the specific technology they have chosen. It is the reframe underneath the technology: each has stopped asking "how do we market our destination better?" and started asking "how do we organise our destination for a world in which AI systems are the first audience and human travellers are the second?"
What they share: three capabilities
Visibility makes the destination findable. Coordination makes it coherent. Intelligence makes it smart. No traditional DMO toolkit covers all three.
The category shift
The DMOs already leading have quietly stopped describing themselves as marketing organisations. What replaces the DMO is not a different marketing body. It is a different kind of institution - one whose core function is the maintenance, enrichment and distribution of the intelligence layer that the destination and its partners now depend on.
We call this the Destination Intelligence Organisation, or DIO.
A DIO does four things a DMO historically did not. It operates the structured data fabric that makes the destination legible to AI systems and partners alike. It runs the partner intelligence functions - dashboards, benchmarking, demand signals - that give member operators decisions-ready data they could not produce alone. It coordinates AI readiness across the ecosystem, treating the destination as a network to be raised collectively rather than a brand to be promoted individually. And it continues to carry the destination brand, but now as the public expression of the underlying data and coordination work, not as its substitute.
Traditional DMO vs Destination Intelligence Organisation
Destination Intelligence Organisation: Organise the destination.
Destination Intelligence Organisation: AI systems, partners, travellers.
Destination Intelligence Organisation: Shared ecosystem intelligence.
Destination Intelligence Organisation: Coordinate and enable.
Destination Intelligence Organisation: Economic contribution, member value.
Destination Intelligence Organisation: The public expression of the product.
The distinction is not semantic. A DMO markets a destination. A DIO organises a destination so that AI systems, partners and visitors can interact with it coherently. The first is an output business. The second is an infrastructure business. The first can be replaced by a search engine. The second cannot.
The economic case sits where the jobs are
The DIO argument is not abstract. It translates into jobs and local economic activity through a specific mechanism.
An AI-mediated discovery economy rewards destinations whose structured data is rich enough for AI to cite, and whose ecosystem coordination is tight enough that the citations land on experiences travellers can actually book. Day-visit-to-overnight-stay conversion improves, because AI-generated itineraries anchor multi-day experiences on destinations they can cite with confidence. Foreign high-value segment capture improves, because international travellers lean more heavily on AI than domestic ones. Member retention improves, because wine estates, accommodation operators and experience providers experience the DMO as useful - a source of intelligence and visibility - rather than as an annual membership invoice.
Every additional rand or dollar of tourism economic contribution supports jobs through the standard tourism multiplier. At the one-job-per-R200,000 rate used by WESGRO and Tourism KZN for Cape-region wine tourism, the differential between a stalled DMO and a compounding DIO is measured not in hundreds of jobs but in thousands over a three-year horizon. For destinations operating under municipal jobs targets, and most mature wine regions are, this is the argument that carries board and political weight. AI is the mechanism. Jobs are the outcome.
The DMOs that organise first, become visible first.
The DMOs that wait become the control group.
How to begin
For DMO leaders reading this and recognising their own organisation in the pattern, the question is not whether to move but how. The DMOs already leading share a common starting sequence - deliberately modest, deliberately sequenced, deliberately team-involving.
-
Begin with the audit, not the technology.
An AI readiness audit - eight dimensions, evidence-based, including uncomfortable findings - creates the permission structure within which strategic reframing becomes possible. Skipping the audit and going straight to "let's deploy a chatbot" produces tactical wins that do not survive a board conversation.
-
Sharpen the identity before the technology.
The DMOs that frame AI transformation as a technology adoption problem struggle. The DMOs that frame it as an identity question - what are we becoming; what function do we serve - make faster and better decisions. Technology follows identity clarity. It cannot substitute for it.
-
Right-size from the first conversation.
The largest failure mode in DMO AI transformation is choosing a shape the organisation cannot resource. Affordability is not a constraint to satisfy at the end of a strategy process. It is a design principle that should run through every choice. A programme right-sized for the organisation's real capacity will be executed. One that stretches further will not.
-
Integrate brand and website with the transformation, not alongside it.
The classical DMO impulse, when faced with a digital age pressure, is to commission a brand refresh. The impulse is not wrong - the brand probably does need refreshing - but running brand refresh as a separate marketing project alongside the AI strategy produces both at half value. The integration, the new website built on the data layer and the refreshed brand carrying the Intelligence Hub thesis, is what makes both investments compound rather than depreciate.
-
Build with the team, not for the team.
A small admin team holds operational knowledge no strategist can replicate. Which partners are genuinely engaged. What data actually flows today. Where the friction lives. The transformations that extract this knowledge early and involve the team in shaping the output consistently outperform those that deliver a finished strategy to be executed. The team becomes the transformation's internal champion, not its delivery vehicle.
What comes next
The sector conversation about AI in destination marketing has moved quickly. Two years ago it was about content creation. A year ago it was about chatbots. Today it is about the category shift itself - whether an organisation is still a DMO or is quietly becoming a DIO. The distinction will define which destinations carry their heritage into the next decade and which become footnotes in the answer someone else's AI system delivers.
For the destinations that begin the transition deliberately - with an audit, a reframe, a right-sized programme, and a team brought along - the reward is compound. Brand intact. Relevance renewed. Jobs created. Partners retained. Authority in the AI search layer owned, not rented.
For the destinations that wait, the cost accumulates quietly. By the time it shows up in visitor numbers or partner defection, the gap to the leading pack is too wide to close with a campaign. The quiet disappearance continues.
The category shift is the work. The rest is decoration.
Green Everest works with DMOs moving through this transition. If you are recognising the pattern in your own organisation, the first conversation is straightforward. Not a pitch. A discovery. We would rather help you ask the right questions than sell you the wrong answers.
Dr Danie Maritz is Founder and CEO of Green Everest Strategic AI Consultancy, advising South African SMEs and industry bodies on AI transformation. He holds a DCom in organisational psychology and was previously a Partner at Deloitte. Green Everest's current DMO and tourism-sector engagements span regional destination bodies, municipal tourism platforms, and wine industry federations.
To continue the conversation, visit greeneverest.co.za or contact danie@greeneverest.co.za.