AI Search is changing the marketing playbook: How can travel survive?

Every morning, my Linkedin feed is flooded with another batch of "How to win in AI Search" posts. Figuring out how to differentiate genuine, market-shifting signals from the relentless marketing industry noise is hard.

One week a new analysis claims that only 12% of links cited in Gemini appear in Google's top 10 results for the same prompt, and the next week another study alarms of an 86% drop in Reddit citations for ChatGPT. Chasing this rollercoaster is a losing game; sustainable visibility requires ignoring the whiplash and focusing on the structural fundamentals of your content, brand positioning and site structure.

Below, I cut through the noise and boil AI search down to three actionable principles for travel marketers.

The search pie isn't shrinking; it's splitting by 'job'

The assumption baked into the "AI will kill Google" narrative is that people who use ChatGPT have stopped using Google. They haven't. 

According to Similarweb global desktop and mobile data, 95% of ChatGPT users in a given month also use Google. The most recent search report revised Google's daily search volume upward from 9.1 billion to 13.7 billion searches per day.

Let these numbers sink in: On average, the entire world's population runs 1.6 Google searches per person every single day. And Google itself has reported consistent double-digit growth in its core Search business over the last several quarters.

Consumers aren't abandoning traditional search engines; they are dividing tasks. Organic search continues to drive high-volume brand navigation and high intent search, while AI is assigned the heavy cognitive lifting of discovery and complex, multicriteria research and planning.

The travel takeaway

The landscape is splitting into two distinct behaviors: Travelers are increasingly leaning on AI for top-of-funnel discovery and untangling trip planning, but they still turn in a large share to traditional search when they have high intent to book.

Maintaining a rigorous focus on traditional search optimization remains business-critical.

The overall search engine optimization (SEO) traffic might gradually decline over the years to come, but branded and high intent keyword searches remain your best bet to capture the ready-to-convert user today. The hidden bonus? Traditional and AI search share the same plumbing. By perfecting your site map, speed and crawl efficiency, you ensure large language model (LLM) crawlers have the access required to read, index and cite your content.

The visibility blind spot: How AI engines rely on content you don't own

For years, the SEO playbook was largely about your own site: write authoritative content, structure it well, build internal links, and Google will reward the domain. AI models don't play by the same rules. Depending on which report you read, between 51% to 85% of what AI cites about brands is third-party content.

This means building your brand's footprint on external sites matters more than ever. To get selected by AI bots, your offsite content is king. AI models trust community consensus far more than your slick onsite marketing copy.

The travel takeaway

Treat user-generated content (UGC) and video like search content sources. LLMs treat UGC and user forums like Reddit as high-signal environments. Treat community engagement as a long-term investment in brand equity. Engage with brand ambassadors to provide expert, non-promotional advice on relevant subrredits, building a digital footprint of helpfulness. Cooperate with creators to publish how-to videos about pain points addressing your core value proposition. When a brand appears repeatedly in "positive authentic contexts," the AI perceives a real-world consensus.

Use the hub-and-spoke approach to repurpose content. Ensuring that your core value propositions are echoed across the digital ecosystem increases the probability that an LLM will cite your brand as a primary reference. Repurpose successful historical assets ensuring your subject matter expertise is broken down into granular, platform-specific segments that AI can easily ingest. A high-performing blog post regarding "sustainable travel in Iceland" can be deconstructed into an infographic highlighting carbon-offset strategies in Iceland and a series of short-form videos featuring the specific locations mentioned.

Design your content for reach and frequency. When dozens of independent sources confirm the same brand positioning and value proposition, AI treats this repetition as verified fact. Two tactics will help you reach this goal:

1. Mine your internal data to publish something a "proprietary travel demand index" or similar in your business domain on a strict, recurring schedule. Publishing this benchmark regularly is what transforms your brand into the go-to source for other domains. When you produce original, data-backed research that others quote, AI treats your brand as the undeniable industry canon in your specific niche.
2. Strategic timing: Most "best of" lists refresh annually. Time your outreach to coincide with these refreshes to ensure your brand remains in the current training data.

AI search collapses discovery and decision process into a single conversation

LLMs do not simply retrieve facts. They synthesize evidence from multiple sources to answer increasingly complex questions. This distinction fundamentally rewrites the rules of travel SEO and content marketing.

Every time an AI system recommends a travel player, it is executing a chain of reasoning. It weighs trade-offs, evaluates consumer requirements and compares alternatives. Therefore, your content must explicitly answer:

• Who is your product most appropriate for?
• When should your option be chosen over a competitor?
• What specific evidence supports these claims?

The travel takeaway

Shift from standard product specifications to conversational user centric attributes. Traditional travel catalogues classify products using rigid checkboxes (e.g., "Wi-Fi," "pool," "in-flight entertainment"). However, AI conversations are complex, granular and emotional. Map and expanding your product descriptions to reflect how travelers actually speak and tag them with experiential attributes. Instead of simply stating "fully equipped kitchen," explain that families can "save money and easily manage picky eaters with a modern, fully stocked kitchen." By framing basic amenities as tangible solutions to specific traveler concerns, brands provide the undeniable proof of value required to win over the algorithmic gatekeeper.

Mine search and chat data to identify travelers' requests pain points. Travelers use specific constraints and comparison points when narrowing down a trip. Your existing data holds the key to understanding these nuances. Audit your Google Search Console, Google Ads reports, onsite search logs and customer service chat transcripts. Look for repeated constraints and use these insights to proactively inject "best for" scenarios and niche use cases into your product descriptions.

Treat every individual product page as a standalone homepage. AI search doesn't just send traffic; it pre-qualifies buyers. Optimize product pages for high-intent arrivals. A landing page must immediately validate the complex, highly specific query the AI used to send the traveler there. Surface localized trust signals, verified reviews, exact specifications, policies and compatibility to convert a visitor who is ready to buy on arrival.

The hybrid future of traditional and AI search

The buyer’s journey is experiencing its most profound structural shift since the dawn of the Google search bar. While traditional organic and paid search remain the cornerstone for capturing immediate purchase intent, the discovery and research phases are being rewired as we speak.

In May 2026, Google published its "How to use conversational attributes" guide in the Merchant Center. By introducing these six new conversational data points, Google officially gave brands access to its back-end systems to keep enhancing complex, generative AI search experiences.

Visibility in the AI era is a compounding loop where each phase amplifies the next.

1. Technical accessibility, anchored in the technical SEO foundations ensures you are found
2. Shaping and scaling your brand's content on external sites ensures your brand is trusted by the LLMs
3. Reframing your product details into user-centric traveler solutions allows AI to evaluate, compare and recommend your brand in its answers

If you neglect the technical foundation, your content will be invisible for LLMs. If you lack third-party validation, your brand may never be trusted enough to be cited. If your product pages are not addressing the relevant traveler constraints, your product will not be recommended in the AI conversations. When all three phases are executed in sequence, every citation reinforces the last, creating a sustainable advantage in AI search results.

The question you need to ask: Is your current site architecture and content strategy ready to win both search keywords and AI answer's game? Traditional search traffic might be slowly shrinking but is what keeps paying the bills today. Securing AI recommendations guarantees your brand being part of the top-of-funnel conversations and might also become your entry ticket to the future era of agentic commerce.