Tourism & The Impact of AI Search: How Discovery, Content and Trust are Reshaping the Sector

AI Search Optimisation for Tourism: Is Your Destination Ready?

Tourism has always been shaped by information. Guidebooks, travel agents, brochures, blogs, and social media have each influenced how people choose where to go and what to do. But today, a new force is reshaping the sector at pace: AI-powered search. What began as simple recommendation engines has evolved into intelligent systems capable of understanding intent, predicting preferences, and generating personalised travel guidance in seconds.

The result is a tourism landscape that is more dynamic, more competitive, and more traveller‑centric than ever before – and increasingly shaped by AI-driven discovery, multi‑channel planning, machine‑readable content formats, and trust as a defining constraint.

From Search to Discovery: A New Traveller Behaviour

Traditional search engines relied heavily on keywords. Travellers typed “best hotels in Barcelona” or “things to do in Tokyo,” sifted through pages of results, and manually pieced together itineraries. AI search has flipped this model. Instead of forcing travellers to hunt for information, AI anticipates what they need and delivers it proactively.

AI is not yet the first touchpoint – but it is the new validator

Despite rapid adoption, AI tools are rarely the first platform travellers use when searching for holiday information. In the UK, only 7% begin with an AI chatbot, compared with 44% who start with search engines (Mintel, Travel and AI – UK, 2026; Mintel, Consumers and Online Search Habits – UK, 2026).

Marketing implication: SEO is no longer enough

Brands must now optimise for AI-generated answers through Answer Engine Optimisation (AEO) and Generative Engine Optimisation (GEO), or risk becoming less visible. Search is no longer only about ranking in conventional results; it is also about creating content that AI systems can interpret, trust and use when curating personalised answers.

AEO focuses on structuring content so answer engines can respond directly to a user’s question, while GEO focuses on helping generative AI systems find, interpret and cite a brand accurately. Together, they extend traditional SEO rather than replacing it.

How to optimise for AI-generated answers

Earned media is one of the most influential drivers of brand visibility in AI-generated responses, as AI systems tend to place significant weight on trusted third-party validation and authoritative sources. Research suggests that trusted media, where claims are independently reviewed and verified by journalists and editors, can play a substantial role in shaping how large language models assess brand reputation and authority.

However, earned media alone is not enough. Successful AI Overview, AEO (Answer Engine Optimisation) and GEO (Generative Engine Optimisation) strategies also rely on high-quality owned content, strong technical SEO foundations, clear site structure, structured data, and consistent brand signals across the web. AI platforms need to be able to discover, understand and trust your content before it can be surfaced in responses.

Alongside media coverage, third-party review sites such as Trustpilot, peer communities and forums such as Reddit, industry rankings, aggregators, and independent recommendations can all influence AI-generated answers. Proprietary research is particularly valuable, with original data, white papers and primary research often cited because they provide unique, authoritative information that AI systems can reference.

To maximise visibility in AI-generated search experiences, organisations should take a balanced approach that combines earned media, authoritative content creation, technical optimisation and reputation management. The brands most likely to appear in AI-generated answers are those that are not only discoverable, but consistently recognised and validated by trusted sources across the wider digital ecosystem.

This generational split challenges the idea of a single, linear customer journey. Instead, tourism brands must build multi-channel content ecosystems that serve:

• search-led planners

• social-led inspiration seekers

• AI-led comparison users

One-size-fits-all media plans no longer work. Channel strategy must be audience-specific, behaviour-specific, and format-specific.

Content for Humans and Machines

Destination marketing organisations have long relied on storytelling, imagery, and promotional campaigns. But AI search is changing the rules of engagement.

Among UK consumers who use AI for travel planning, 42% have used it for personalised accommodation recommendations (Mintel, Travel and AI – UK, 2026). This reinforces the value of AI-curated product discovery – and the need for brands to ensure their data is accurate, structured, and up to date.

To appear in AI-driven recommendations, brands must create content that is structured, machine-readable, credible and consistent across platforms. This includes clear headings, bullet points, FAQs, schema markup, rich metadata, accurate geolocation and up-to-date event information.

Travel brands are increasingly advised to produce AI-ready content that chatbots and LLMs can easily interpret (Mintel, Loyalty in Travel – UK, 2026). As AI search becomes habitual, brands must become trusted, data-driven sources that models can reliably extract and recommend (Mintel, Consumers and AI – UK, 2026).

Destinations that invest in digital clarity are rewarded with higher visibility. Those that don’t risk becoming invisible.

Hyper-Personalisation and Agentic Booking – Opportunities Limited by Trust

AI thrives on personalisation. By analysing behaviour, preferences, past trips, and subtle cues in language, AI can tailor recommendations with remarkable precision.

A traveller who frequently books boutique hotels and food-focused experiences will see different suggestions than someone who prefers adventure travel or budget-friendly options. AI adjusts recommendations based on:

• budget

• travel style

• accessibility needs

• sustainability preferences

• time constraints

• group size

• weather patterns

• seasonal events

This level of personalisation was once the domain of high-end travel agents. Now it’s available to anyone with a smartphone.

However trust remains the limiting factor

Consumers perceive general AI chatbots as more inaccurate (13%) than friends or family (4%) (Mintel, Travel and AI – UK, 2026). In travel, errors carry serious consequences – missed flights, incorrect opening hours, or misleading safety information.

As a result, 41% of travellers prefer brands that guarantee human customer service (Mintel, Travel and AI – UK, 2026). AI should augment, not replace, human reassurance.

The brands that thrive will be those that blend automation with human expertise.

A More Intelligent Future for Tourism

AI search is still evolving. In the coming years, we can expect:

• real-time crowd prediction

• AI-guided tours using augmented reality

• personalised sustainability scoring

• emotion-aware travel recommendations

• AI-powered translation

• predictive booking tools

The tourism brands best placed to benefit will treat AI search as part of a wider discovery ecosystem, not as a standalone channel. They will make their information easy for machines to interpret, earn validation from trusted sources, and retain human support where travellers need reassurance.