Rise of AI in travel planning does not signal end of destination marketing

Artificial Intelligence has continued to grow as an all-encompassing go-to for every need, evolving from a search engine to a personal assistant that can help outline a plan for just about anything, with many turning to chatbots as a personal travel agency. Jane Cunningham explores how Destination Marketing Organisations (DMOs) can ensure their location isn’t at risk from being overlooked by these new-age planners.

 

Destination marketing has long relied on a tried-and-true model: inspire travellers, drive them to owned channels, and guide them through the planning process.

That model is on the cusp of being fundamentally disrupted.

 

Artificial intelligence (AI) is increasingly serving as the go-to first touchpoint in travel planning, reshaping not just how trips are booked but also how destinations are discovered.

 

Travellers are no longer browsing and comparing in the traditional sense; they are simply asking, and AI is answering.

 

The Digital Tourism Think Tank has coined the term “delegated discovery” to explain this profound behavioural shift. Travellers are outsourcing initial decision-making to AI systems that curate and filter options before a destination is ever truly considered. At the same time, inspiration itself is moving elsewhere.

 

Social media platforms are now a primary source of travel ideas, shaping where people want to go long before they begin planning. AI then takes over as the planning layer, translating that initial inspiration into curated itineraries, recommendations and decisions.

 

The result is a compressed and fragmented journey, where two of the most critical touchpoints for DMOs inspiration and early-stage planning are increasingly happening outside of owned channels.

 

In practical terms, fewer users reach destination websites during the early stages of travel planning, not because demand is declining, but because the audience is being intercepted upstream.

 

For DMOs, this can present as declining traffic or engagement. However, this is not a demand issue; it is a visibility issue. Audiences still exist, but they engage in AI-driven environments that determine which destinations make it into the consideration set.

 

This has significant implications for how destinations are selected and prioritised. AI systems do not “discover” destinations in human terms. They rely on structured data, consistent signals and trusted sources to generate recommendations.

 

Destinations that lack clear, accurate and machine-readable information, now referred to as Generative Engine Optimisation, or GEO, risk being excluded entirely. In this context, visibility is no longer driven solely by brand strength or marketing investment, but by how effectively a destination can be interpreted and surfaced by algorithms.

 

There is also a broader consequence of this reliance to consider, the risk of increasingly homogenised travel experiences. AI models tend to prioritise destinations that are already well-documented, highly rated or widely referenced. While this improves efficiency for travellers, it can reinforce existing patterns and limit exposure to lesser-known places.

 

The industry must therefore consider what is lost if discovery becomes constrained by data availability rather than genuine personal recommendations and defined cultural experiences.

 

This shift reinforces the critical role DMOs continue to play. While AI is changing how discovery happens, it does not replace the need for authentic storytelling, local insight and the human connections that underpin meaningful travel experiences.

 

Now, in order for smaller destinations to be picked up by these AI algorithms, they must ensure their identity is consistently represented across the data ecosystems that inform AI outputs.

 

To support this transition, organisations such as Destinations International is working with its members to build practical capability. This includes guidance on AI-ready content strategies, frameworks for structured, consistent data management, and policy resources to support responsible, transparent AI adoption. Through research, training and shared case studies, the organisation is helping DMOs understand how to maintain visibility and influence in an increasingly AI-mediated landscape.

 

Adapting to this shift requires both strategic and operational change. Destinations must prioritise content that is not only engaging for human audiences but also accessible to AI systems. This means maintaining accurate, up-to-date information, aligning messaging across platforms and producing authoritative content that can be confidently surfaced in AI-generated responses.

 

At the same time, closer collaboration with the platforms shaping travel discovery is essential. Ensuring that high-quality destination data feeds into these systems is now a core requirement, not a technical detail.

 

The rise of AI in travel planning does not signal the end of destination marketing, but it does redefine where influence is exerted.  

 

DMOs may not always sit at the start of the traveller journey in the same way as before, making it important to maintain visibility within the systems that now influence it.

 

In a landscape defined by “delegated discovery”, being considered is no longer automatic. It must be deliberately built into the data, content and signals that guide AI-driven decisions.

 

Destinations that recognise this shift and act on it will not only retain visibility but also remain competitive in a travel ecosystem increasingly defined by algorithms rather than search.