Tourism in the Age of AI: Competing for Preference, Not Just Visitors

Travel today is a connected and data-enriched experience. On a recent family trip, a simple car ride became an opportunity to learn about the social, political, and economic context of our destination by chatting with ChatGPT. It felt like having a private guide with us, one capable of drawing from vast knowledge with precision and patience.

This personal example reflects a broader reality: artificial intelligence is already transforming how travelers dream, choose, book, experience, and remember their trips. For a country like Portugal, where tourism holds significant strategic value, AI represents an opportunity to compete more effectively on a global stage. Not through higher volume, but through smarter relevance, personalization, and operational intelligence.

Winning traveler preference requires precision, context, and empathy. When designed and applied responsibly, AI elevates all three.

This insight explores how AI can support every stage of the traveler’s journey, creating value for airlines, hotels, destination management organizations, and public tourism entities.

Dreaming and Planning: Relevance That Inspires

Choosing a destination has become a fragmented process. Travelers navigate dozens of platforms, opinions, and sources before making a decision, creating an environment where attention is scarce and relevance matters more than ever.

AI-driven recommendation systems help organizations anticipate traveler preferences by identifying behavioral patterns, clustering similar users, and tailoring suggestions based on browsing habits, booking history, and content interaction.

Projects that optimize segmentation and recommendations have demonstrated conversion gains ranging from 16 to 61%, in comparison with less analytical approaches.

For airlines, tour operators, hotel chains, and tourism platforms, this translates into higher conversion rates and lower acquisition costs. It also enables a more inspiring and personalized experience at a moment when travelers are still imagining what their trip could be.

Booking and Confirmation: Meeting Expectations of Instantaneity

Speed has become a crucial component of the tourism experience. In an age of on-demand information, a quote request that takes several days can jeopardize a sale.

AI-powered sales agents now enable organizations to respond quickly without compromising personalization. These systems understand the context behind each request, check availability constraints, and generate complete, tailored proposals in minutes.

‍Our project experience indicates that this approach can reduce the manual workload of commercial teams by roughly 50%.

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The result is not only faster response times, but also more focus on negotiation, loyalty building, and value creation. When supported by proprietary data and strong governance, these agentic systems strengthen the commercial relationship by giving professionals more time to engage meaningfully with customers.

The Travel Experience: Anticipating Flows and Coordinating Operations

Much of the traveler’s satisfaction depends on what they do not directly see: congestion management, waiting times, mobility fluidity, and the predictability of services.

Predictive models that combine mobility data, weather forecasts, reservation trends, and arrival patterns help tourism boards and operators anticipate peaks in demand and allocate resources accordingly. These models create the foundations for evidence-based decision-making, allowing public entities to balance tourism promotion with sustainability.

For private operators, they support operational efficiency by aligning supply with expected demand, reducing environmental impact, and enhancing the visitor experience in ways that are both visible and invisible to the traveler.

Remembering the Trip: Closing the Loop at the Right Moment

The end of a trip is often the beginning of the next. When done thoughtfully, post-travel communication can significantly increase the likelihood of repeat visits.

AI-driven timing models help organizations send the right message at the right moment, taking into account travel history, preferences, and seasonal calendars. Whether during end-of-year planning or after a contextually meaningful interval, communication that aligns with natural decision cycles performs better.

In practice, our experience shows up to 27% more successful contacts and 23% higher sales effectiveness when predictive timing is used.

This leads to more sustainable, relevant, and impactful tourism marketing at scale.

Competing for Preference

The tourism sector faces real pressures: rising operating costs, labor shortages, demand volatility, and increasingly demanding consumers. AI is not a shortcut, nor a standalone solution. It is an intelligence infrastructure that must be built with purpose, quality data, and clear governance.

Portugal, however, begins with a natural advantage. Travelers actively want to visit the country. The tourism offering is diverse, culturally rich, and geographically varied. The national ecosystem for technological innovation is growing.

The next step lies in transforming scattered data into actionable insight, and applying that insight across the value chain, from boutique hotels to national tourism groups. The global competition in tourism is no longer solely about attracting visitors. It is about earning their preference.

Those who understand what truly motivates, delights, and surprises travelers will lead this new frontier. Artificial intelligence is the lever that can help Portugal secure that advantage, while preserving what has always made the country exceptional: its heritage, its hospitality, and its human touch.

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