Destinations International Leaders Jane Cunningham and Eleonora Steenken Reveal AI, GEO and Trusted Data Are Reshaping the Future of Tourism

Travel And Tour World interviewed Jane and Eleanora, two of the most dyanmic leaders focusing on technological advancements.

Jane Cunningham, Director of European Engagement at Destinations International

With over two decades of experience in the global meetings industry, Jane has worked for a range of hotels, convention centres, destination marketing organisations, and convention bureaus. She is now building a platform of valuable knowledge sharing in the form of Destinations International’s European Membership programme, a global community dedicated to advancing the destination organisation and convention bureaux sector. The programme provides valuable opportunities for industry connection as well as access to a wealth of innovative resources. Jane is based in Stockholm, Sweden and loves life in the Nordics and the spirit of Scotland.

Eleanora Steenken, Head of Marketing, Innovation, and Strategy at Tourism Marketing Baden-Württemberg

Eleonora is Head of Marketing, Innovation & Strategy at Tourism Marketing GmbH Baden-Württemberg, with more than 13 years of experience in the tourism sector. She has extensive leadership expertise and specialises in strategic management, digital transformation, innovation and organisational change.

In her current role, Eleonora develops and delivers future-focused strategies, leads transformation initiatives, and drives sustainable organisational growth. Working at the intersection of policy, market dynamics and societal change, she helps position Baden-Württemberg as a forward-thinking and resilient tourism destination.

As AI models frequently generate fake landmarks or outdated travel data, how can Destination Marketing Organisations (DMOs) practically position themselves as the ultimate “truth-checkers” for travellers?

AI has increasingly become the go-to tool for destination searches, with 52% of UK (56% US) travellers using AI for planning or booking at least one trip in the past year. The days of relying on a single high-quality photo or an old social media post to attract visitors are gone; DMOs must embrace the use of AI as a search engine, and in order to appear near the top of the list, they must maintain a continuous stream of fresh, authoritative tourism data.

DMOs can help travellers, tech platforms, and AI systems easily distinguish reliable information from outdated or fabricated content. They can position themselves as trusted reference points by providing a central, verified source of information on attractions, events, routes, accommodation, and local services. By maintaining clear accountability for keeping information updated, especially around real-time facts like correct opening times and seasonal closures, DMOs can project trustworthiness in this new age of AI search.

With the transition from SEO to Generative Engine Optimisation (GEO), what immediate steps should destinations take to restructure their content infrastructure so AI itineraries actually surface them?

Traditional search engines used to work by indexing isolated keywords, but AI models look for context, intent, and answers to complete questions. To ensure destinations are featured in AI-generated itineraries, we must make our content accessible far beyond our own websites. 

First, tourism information needs to be stored within a consistent data structure, enriched with useful context, and updated directly at the source. This data must be prepared so generative AI can easily identify, interpret, and access it through direct feeds or interfaces. 

Second, content should be presented in bite-sized chunks to make it easier for AI systems to capture and process. Using clear subheadings for short sections provides excellent structural guidance for machines. Finally, move away from general statements and focus on specific, concrete content that offers real added value. Write answers to real questions using natural, everyday language. Instead of just labelling an asset as a “historic castle,” provide concrete guidance that addresses the target audience’s needs, such as: “Where can families find a sustainable lunch spot within walking distance of the castle?”

Smaller and mid-sized regions risk being digitally erased by AI due to a thin data footprint. How can these smaller destinations build the algorithm clout needed to compete with major urban hubs?

If there isn’t a sufficient digital footprint for a small town or rural area online, AI models simply will not know it exists. Smaller destinations cannot compete with major urban hubs on marketing budgets, but they can compete insofar digital visibility in the AI era depends on the quality and structure of available data. With this knowledge, we can make sure these hidden gems are detected.

Smaller destinations can build significant algorithmic clout through a shared data infrastructure. Participating in a statewide or shared database gives regional providers immediate access to the same digital standards and global distribution channels as major cities. A smaller region’s chances of being recommended increase dramatically when local attractions, events, and services are represented comprehensively and linked to relevant themes, locations, and target groups. It is crucial to showcase unique local characteristics; when content is peppered with deep local insights and authentic quotes from the community, even a small destination can perform exceptionally well in AI search systems.

AI itineraries risk homogenising travel by pushing the same top-tier sites to everyone. How can DMOs leverage their local expertise to infuse diverse, authentic experiences into standardised AI recommendations?

If left alone, AI programs naturally default to the most popular, crowded spots because they have the most reviews online, creating a real risk of “copy-paste” trips that cause overcrowding. Tourism boards can actively stop this from happening by sharing our deep knowledge in a way that technology can easily grasp. 

By adding hand-picked local favourites, regional stories, and hidden gems into our online systems alongside major attractions, we give AI the variety it currently lacks. When we include straightforward details about the best seasons to visit, accessibility features, or smart ways to combine different activities, the algorithm learns to generate much better, more balanced recommendations. This keeps unique local character alive online and ensures that the money spent by tourists reaches independent businesses and more people across the whole community.

Drawing from your work bridging North American and European memberships, are you seeing distinct differences in how these two regions are adapting to AI integration in tourism?

The two regions are adapting in different ways. In North America, destinations are adopting AI to improve marketing and deliver more personalised visitor experiences. Tools such as chatbots and automated advertising are already supporting this shift.

In Europe, the emphasis is different. Destinations are using AI to support sustainable tourism while meeting evolving data privacy requirements. Many DMOs are also exploring data systems to better understand visitor flows and manage tourism’s impact on local communities.

At Destinations International, we bring these approaches together. We help tourism boards apply AI in ways that support both innovation and responsible destination management.