Artificial intelligence is already reshaping how travellers discover, plan, book and experience destinations. For tourism SMEs, this pace of change presents a particular challenge. While many recognise that AI is relevant to their future, without a clear strategic framework, the risk is either moving too quickly into tools that don’t fit existing organisational culture or dismissing AI entirely as too complex for their needs. Both responses lead to missed opportunities.

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The breadth of available AI applications is itself part of the problem. From content generation and conversational interfaces to dynamic pricing and predictive analytics, AI can feel overwhelming for organisations with limited time, capacity and technical expertise. To succeed, businesses need to answer the question of “which AI applications address our specific challenges and opportunities?” This requires expert, evidence-based guidance to help businesses identify which AI applications actually solve their specific problems and offer the best opportunities.

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That is the thinking behind Destination Intelligence, a strategic guidance report Smålands Turism commissioned to the Digital Tourism Think Tank (DTTT). Drawing on the DTTT’s extensive knowledge of AI developments across the tourism sector, the research sets out a practical direction for driving forward AI-enabled efficiencies tailored to the realities of a regional tourism economy. In doing so, it provides the clarity and confidence that tourism organisations need to move from ambition to action. This was achieved by mapping the evolving AI landscape across interconnected themes, with each supported by practical case study examples, alongside a curated overview of tools that tourism businesses can begin exploring immediately.

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A New Operating Environment

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Developing an AI strategy must begin with a clear understanding of how AI has been rapidly embedded into the mainstream platforms that underpin the entire visitor journey. This is transforming how tourism products are surfaced, evaluated and booked. At the same time, accessible open tools have dramatically lowered the barriers to entry, enabling smaller businesses to compete with larger players in terms of creativity, responsiveness and reach.

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For rural and regional destinations, this shift is particularly significant. AI presents a timely opportunity to address long-standing structural challenges that many tourism SMEs face, from limited digital capacity to seasonal fluctuations and stretched resources. Applied thoughtfully, it can extend capacity, strengthen competitiveness, support innovation and build resilience. Unlike previous phases of digital transformation, many of today’s AI tools are modular, intuitive and lightweight, designed to plug into existing workflows without requiring large-scale investment.

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Understanding what is genuinely changing, and at what pace, matters enormously for organisations deciding where to focus. This is where the DTTT’s continuous monitoring of the AI landscape adds particular value, separating the transformative from the incremental to help destinations prioritise with confidence.

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Where AI Makes a Real Difference

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Most tourism businesses recognise the growing relevance of AI, yet the struggle is often in translating the overarching trend into tangible operational improvements. Such a knowledge gap is crucial for businesses to overcome for AI to make a meaningful difference in the execution of daily tasks.

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Taking a challenge-first approach, effectively using AI starts with the real, everyday pressures that small tourism businesses face. Time-consuming repetitive enquiries from guests. Language barriers with international visitors. Pricing decisions based on instinct rather than demand signals. These are familiar pressures across the sector, and for many of them, AI already offers surprisingly effective and accessible responses.

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What becomes clear is that successful AI adoption is about matching the right technology to a specific need. Some applications are simple yet remarkably effective; others require more considered implementation. The difference between basic use of tools, such as ChatGPT, and the more sophisticated prompting techniques that unlock real productivity gains is significant, and closing that skills gap is where strategic guidance makes the greatest difference.

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The New Visitor Journey

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It is important to recognise that operational efficiency is only part of the picture. AI is also fundamentally changing the relationship between travellers and destinations. That shift has profound implications for how tourism businesses attract and engage visitors.

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Large language models now serve as interactive trip companions from the very first moment of curiosity, creating entirely new models of discovery that are conversational, contextual and continuously adaptive. A traveller might search for quiet places in Sweden with forests, local food and cycling trails, and receive a recommendation for a region they had never previously considered. With this, destination discovery becomes a conversation, with visitors actively shaping their journey instead of passively searching. Such interactions are founded upon AI models synthesising impressions, reviews, sensory language and emotional tone into cohesive suggestions.

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For destinations with genuine depth of character, this is where authentic competitive advantage becomes essential. Rich, distinctive content rooted in real places, traditions and experiences is precisely what AI systems draw upon to construct meaningful recommendations. As a result, the traditional marketing funnel of awareness, consideration and booking is giving way to something far more fluid. This means rethinking how content is structured, distributed and optimised, helping individual businesses and the destination as a whole surface more effectively across AI-mediated channels.

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However, this visibility increasingly depends on the digital infrastructure that sits behind it: connected booking systems, well-structured data and the technical foundations that allow AI to access, interpret and recommend what a destination has to offer. Getting this right is a strategic investment in long-term competitiveness.

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Collective Destination Intelligence

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Building the institutional capacity to coordinate, govern and sustain AI adoption across a destination ecosystem is arguably more consequential than boosting visibility and operational efficiency. Succeeding with AI adoption requires designing systems that learn, adapt and align continuously, bringing together data, values, people and decisions to create a destination ecosystem that is both adaptive and grounded. Given the deeply local and interpersonal micro-enterprise relationships, trust is extremely essential, meaning that AI should not be introduced as a top-down solution. Instead, it must be framed as a collective capability, one that is transparent, inclusive and demonstrates clear and practical value.

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This transition to increased AI uptake involves creating the conditions for ethical, shared use of intelligence that benefits all destination stakeholders. When businesses, DMOs and local authorities share intelligence and coordinate around common goals, interventions become more timely, better targeted and more impactful. This means moving away from acting in silos towards building the governance structures, data frameworks and partnerships that make this kind of collaborative intelligence work. AI is a capability, and like any capability, it must be shaped, steered and embedded within a destination’s identity and values.