The way travelers find and book hotels is changing fast. Here’s what it says you need to know about AI-powered discovery.

Not long ago, planning a vacation followed a predictable sequence: Open a search engine, type in “hotels in Charleston” or “best resorts in Cabo,” and sift through dozens of results, review aggregators, and booking sites until something clicked. The research was exhausting, and according to OAG’s “Travel 2045” report, it has become staggeringly so: In 2024, travelers visited an average of 141 webpages before completing a booking, up from 38 in 2013. In the U.S., that number spiked to 277 pages per trip. 

That burden is now being rapidly outsourced to AI, and the numbers confirm just how fast. Traffic to U.S. travel, leisure, and hospitality websites from generative AI sources increased by 1,700% between July 2024 and February 2025. And on the consumer side, nearly one-third of U.S. travelers use AI tools to plan or experience trips. 

The implications for hotels, resorts, vacation rentals, and destination marketers are profound. Understanding how travelers now search, explore, and decide today is a competitive necessity. 

Is AI Really Changing How Travelers Search for Hotels?

Traditional travel search was built on keywords. A traveler’s intent got compressed into a short phrase, and search engines returned a ranked list of links. Discovery was linear: search → click → read → compare → book. Travel brands competed for a position in that list by optimizing title tags and bidding on Google Ads. 

That model is starting to lose ground. Search engines, once dominant, dropped from 51% of travel research behavior in late 2024 to 36% by the second half of 2025, while generative AI platforms increased from 6% to 15% of traveler research activity in the same period. 

What’s replacing keyword search is conversational exploration. Travelers are increasingly turning to ChatGPT, Google AI Overviews, Perplexity, and other assistants to have a back-and-forth dialogue about where they want to go, what kind of experience they want, and what fits their budget and timeline. Instead of 10 blue links, they get a curated synthesis. Instead of scanning review snippets, they receive tailored recommendations with contextual rationale. For frequent AI users (those using generative AI tools at least weekly), generative AI has already become the top channel for travel discovery, surpassing both online travel agencies (OTAs) and social media. So if you’re lacking AI search visibility, you’re missing out.

How Does AI Interpret What Travelers Actually Want?

AI search tools are remarkably good at interpreting nuanced, natural-language queries. When a traveler types, “Romantic weekend getaway within 3 hours of Atlanta that isn’t too touristy,” an AI assistant goes beyond matching keywords to infer the full intent: proximity, atmosphere, authenticity, and occasion. 

This means long-tail intent is now discoverable in ways it never was through traditional SEO. A boutique inn that might never rank on Page 1 for “Georgia hotels” might be perfectly positioned to appear in an AI response for “cozy mountain cabin retreats in North Georgia under $300.” 

The data backs up just how richly travelers are using AI across the planning journey. Among travelers who have used AI for trip planning, the top use cases include researching specific destinations (60%), finding and booking flights (51%), booking hotels or vacation rentals (46%), getting initial destination ideas and inspiration (46%), and discovering local experiences and activities (42%). This isn’t single-task behavior; it’s end-to-end trip building conducted through conversation. 

Are AI-Referred Visitors More Valuable Than Traditional Search Traffic?

Here’s what makes the AI shift particularly important for hospitality marketers: The travelers arriving from AI sources aren’t casual browsers. Consumers who arrive at travel sites from generative AI sources show 36% longer visits, 7% more pages per visit, and a 44% lower bounce rate compared to non-AI traffic sources. 

These are high-intent visitors who have already done significant research before ever clicking through to a property website. The implication is significant: When AI sends a traveler to your site, they often already have a favorable impression, and the job shifts from capturing attention to converting intent. 

That said, the conversion picture is still evolving. In February 2025, traffic from generative AI sources was 9% less likely to convert than non-AI sources, though that gap has narrowed considerably from 43% in July 2024, suggesting travelers are becoming more comfortable completing bookings directly after an AI-powered interaction. 

Which Hospitality Brands Will Win in an AI-First Discovery Era?

The hospitality industry has always rewarded differentiation. The most successful properties have always been those that could articulate, clearly and compellingly, what makes the experience they offer irreplaceable. AI doesn’t change this fundamental truth. It amplifies it. 

In an AI-mediated discovery environment, clarity of positioning is a competitive advantage. The boutique hotel that knows exactly who it serves and communicates that consistently across every digital touchpoint will be surfaced more reliably by AI tools than a larger property with a more generic presence. The resort that has built genuine authority in travel media, earned authentic rave reviews, and structured its digital content with precision will see its story reflected faithfully in AI-generated recommendations. 

Travelers are already searching differently. The question for every hospitality marketer is whether their brand is visible in the places those travelers are now looking and whether the story being told about their property, by AI or otherwise, is how they want to be seen by the world.  

Published by Intero Digital:

AI features are changing how customers find you on Google, but the path to visibility might be simpler than industry hype suggests.

Google recently published something marketers have been waiting for: an official guide on how to optimize websites for generative AI features in Google Search, including AI Overviews and AI Mode. After months of speculation, competing frameworks, and a lot of noise from the industry, we finally have Google’s own playbook. 

If you’ve been doing SEO well, you’re on the right track, but the details matter, and a few widely circulated “optimization tactics” are explicitly called out as unnecessary. Let’s dig into what Google actually said and what you should do about it. 

Is SEO Still Relevant in an AI Search World?

Absolutely. Google is direct on this point. Its generative AI features are built on top of the same core ranking and quality systems that have always powered Google Search. That means the work you’ve put into building a technically sound, authoritative, helpful website isn’t wasted. It’s the foundation for AI visibility, too. 

But there are a couple of underlying mechanisms are worth understanding: 

Retrieval-augmented generation (RAG): When Google’s AI generates a response, it doesn’t just pull from its training data. It uses core Search ranking systems to retrieve fresh, relevant pages from the index and grounds its answer in that content with clickable citations. If your content ranks well, it has a real shot at being cited in AI search. 

Query fan-out: AI Search doesn’t just interpret one query. It generates a cluster of related sub-queries behind the scenes to build a fuller answer. If someone asks, “How do I fix a lawn full of weeds?” the system might be pulling results for herbicide comparisons, chemical-free options, and weed prevention simultaneously. Your content doesn’t need to match the exact phrasing of the original query to be contextually relevant. 

AEO vs. GEO vs. SEO: What’s the Difference?

The industry has spawned two new acronyms: AEO (answer engine optimization) and GEO (generative engine optimization). Google’s official position is that these aren’t distinct disciplines. They’re SEO applied to a new context. Optimizing for generative AI search is optimizing for the search experience, full stop. 

This framing matters strategically. It means you shouldn’t be building a separate “AI track” for your search strategy. The same principles (quality, authority, technical soundness, and user focus) apply across the board. 

Debunking the Biggest AI SEO Myths

Perhaps the most valuable part of Google’s guide is what it tells you to ignore. As generative AI search exploded, so did the ecosystem of tactics claiming to be the key to AI visibility. Google addressed several of them directly in its documentation: 

• LLMS.txt files

Google’s original guidance downplayed llms.txt, and for traditional AI Overviews and AI Mode visibility, that still holds. No special file is required to appear in AI search results.

However, that’s not the full story. Google has since published an official llms.txt page on the Chrome Developers site, framing it as an “emerging convention” for agentic browsing. Their own documentation notes that without the file, AI agents may spend more time crawling your site to understand its structure and primary content. It remains optional (Lighthouse marks it N/A rather than an error if it’s missing), but if your audience includes users interacting through AI agents, it’s worth adding. Place an llms.txt file in your root directory with a concise Markdown summary of your site’s purpose and key links.

• ‘Chunking’ content

Some practitioners have advised breaking content into small, discrete chunks to help AI systems process it. Google says this isn’t necessary. Their systems can understand nuance across a full-length page and surface the relevant section for a given query. So what does that mean for you? Write pages at whatever length makes sense for your audience and the subject matter, not for algorithmic chunking. 

• Rewriting content to match AI query patterns

There’s been advice circulating about writing specifically to address “fan-out queries,” essentially creating pages for every possible variation of how someone might search. Google explicitly cautions against this. Their systems understand synonyms, context, and intent without exact keyword matches, and creating large volumes of thin, variation-targeted pages actually violates their scaled content abuse spam policy. Don’t do it. 

• Chasing inauthentic mentions

Some guides have recommended engineering brand mentions across blogs, forums, and third-party sites to boost AI visibility. Google’s position is clear: The same spam systems that evaluate traditional Search apply to generative AI features. Manufactured mentions will be caught and filtered. Earned mentions, through genuinely useful content and real brand presence, are what count. 

• Over-indexing on structured data for AI

Structured data remains valuable for rich results in traditional Search, and you should continue using it for that purpose. But Google confirms there’s no special schema markup that’s required (or particularly beneficial) for AI features. Don’t let structured data become a distraction from content quality. 

How to Optimize for AI Search: What Google Says

1. Create non-commodity content.

This is Google’s loudest message, and it deserves the most attention from content teams. 

Google draws a meaningful distinction between commodity and non-commodity content. Commodity content (think “7 Tips for First-Time Homebuyers”) is generic, widely available, and could have been written by anyone (or any AI). Non-commodity content brings something genuinely original to the table: personal experience, expert depth, proprietary insight, or a perspective that couldn’t easily be replicated. 

The example Google offers is telling: A post like “Why We Waived the Inspection and Saved Money: A Look Inside the Sewer Line” is specific, experiential, and hard to replicate. It has a real author with a real story. That’s the direction your content strategy needs to move in. 

What this means in practice:

• Audit your existing content library for commodity pieces that could be elevated with firsthand experience, original data, or expert commentary. 
• Prioritize content types that are inherently non-commodity: case studies, original research, interviews with subject matter experts, and content that documents what your team actually does and knows. 
• Stop producing volume for volume’s sake. More pages don’t equal more quality, and Google’s systems have gotten significantly better at identifying the difference.

 

2. Write for humans; structure for readability.

Google’s guidance here is refreshingly simple: Organize content for your human audience. Use clear paragraphs, logical sections, and descriptive headings that help people navigate. Don’t contort your content structure around AI systems. They’re sophisticated enough to understand pages that are written for real readers. 

This extends to multimedia. Images and video aren’t just nice to have. They create additional entry points for your site to appear in AI-generated responses. If you’re already following image and video SEO best practices, you’re already ahead. 

3. Maintain a technically sound website.

Technical SEO isn’t going away. Google is explicit: To appear in generative AI features, a page must be indexed and eligible to show with a snippet. If your content can’t be crawled and indexed, it simply won’t be considered. 

Key technical areas to prioritize: 

• Crawlability: Make sure your content is publicly accessible and not inadvertently blocked. For large, frequently updated sites, review your crawl budget.
• Page experience: Fast load times, mobile-friendliness, and clear visual hierarchy all matter not only for rankings, but also for the users who arrive from AI-generated citations.
• JavaScript: Google can process JavaScript content, but it adds complexity. Follow JavaScript SEO best practices carefully if your site relies heavily on JavaScript frameworks.
• Duplicate content: Reduce duplication where you can. It wastes crawl resources and creates a poor user experience.
• Search Console: Verify your site and use it actively to surface technical issues before they turn into visibility problems.

 

4. Optimize your local and e-commerce presence.

Generative AI responses increasingly surface product listings and local business information directly. If you’re in retail or have a local presence, this is an opportunity you can’t ignore. 

Make sure your Google Business Profile is complete and accurate. For product-based businesses, Google Merchant Center feeds are a direct path to product visibility inside AI responses. Google also mentions Business Agent, a relatively new conversational feature that lets customers ask questions about your brand directly within Search results. Think of it as a chat interface tied to your brand profile, designed to handle pre-purchase and service inquiries without requiring users to visit your site first. If you serve customers who do a lot of research before converting, it might be worth exploring. 

What Are AI Agents, and How Do They Affect Your Website?

This section of Google’s guide is forward-looking, and it’s worth paying attention even if the technology is still maturing. 

AI agents are autonomous systems that take actions on behalf of users, like booking reservations or comparing products. They are beginning to interact with websites directly. Browser agents may analyze your site’s visual rendering, DOM structure, and accessibility tree to gather what they need. 

What does this mean? Semantic HTML and accessibility practices aren’t just good for screen readers. They also increasingly determine how well AI agents can interact with your site. If your content is locked behind inaccessible JavaScript, cluttered DOM structures, or poor visual hierarchy, you may be invisible to the next generation of AI agents, regardless of how well your content ranks. It’s also worth adding an llms.txt file to your root directory. Google has officially documented it as an emerging convention for agentic browsing, noting that without it, agents may spend more time crawling your site to understand its structure and primary content. It won’t affect traditional search visibility, but it’s a low-effort step that may meaningfully improve how AI agents interpret and interact with your site.

Keep an eye on emerging protocols like the Universal Commerce Protocol (UCP), an open standard currently in development that would allow AI agents to interact with websites in a structured, reliable way (like requesting product data, checking availability, initiating transactions, and more) without having to scrape or interpret pages visually. It’s early-stage, but if it gains adoption, it could significantly change how AI agents interact with e-commerce and service-based sites. 

Your Quick-Start Checklist for AI Search Optimization

Based on Google’s guidance, here’s how to translate all of this into a simple working road map you can put into action: 

Immediate priorities:

• Audit your content for commodity vs. non-commodity quality. Flag anything that’s generic and could be elevated. 
• Verify your site in Search Console and check for crawl errors, indexing issues, and page experience signals. 
• Review your Google Business Profile and Merchant Center feeds, if applicable.

 

Short-term (next quarter):

• Develop a content strategy centered on original research, subject matter expertise, and firsthand experience. 
• Make sure images and videos are properly optimized and accessible. Alt text, structured metadata, and file quality all matter. 
• Review your JavaScript implementation if your site is JavaScript-heavy.
• Add an llms.txt file to your root directory with a concise Markdown summary of your site’s purpose and key links. It’s optional, but Google has officially recognized it as a useful signal for AI agents navigating your site.

Ongoing:

• Resist the urge to go all in on chasing emerging AI-specific tactics that haven’t been validated. Google’s guide is a reminder that fundamentals compound over time. 
• Monitor AI Search visibility through Search Console alongside traditional ranking metrics. 
• Start thinking about accessibility and semantic HTML not only as a compliance issue, but also as an AI-readiness issue.

 

What the Industry Is Getting Wrong About Google’s Guide

Google’s guide didn’t land without debate, of course. Leigh McKenzie, who leads organic and agentic search at Semrush, put it well in a recent LinkedIn post: The reaction is split into two predictable camps. One group has concluded that nothing has changed. It’s all just SEO. The other has declared that AI search is an entirely new discipline and Google is downplaying the shift. McKenzie’s take is that both camps are wrong. 

He’s right. And the nuance matters when it comes to how your team allocates resources. 

Google’s guide is accurate about what it covers: Ranking in Google Search, including AI Overviews and AI Mode, still runs on the same foundational signals it always has. But Google’s guide is also, by definition, limited to Google’s products. It doesn’t account for how brand visibility works across the broader discovery ecosystem. 

McKenzie’s argument is that the scope of what “search” means to a business has fundamentally expanded. The most clarifying reframe he offers: Search isn’t just a channel. It’s a brand visibility function. That distinction has real teeth. A channel is something you allocate budget to and measure in isolation. A brand visibility function is something that touches PR, communications, customer experience, community, and content strategy all at once. It changes how you make the case for headcount. It changes what your SEO team’s job description looks like. And it changes what success metrics you bring to leadership. 

In practice, that means closer alignment with PR, communications, and community engagement. It means investing in third-party platforms that matter to your audience, like YouTube, Reddit, industry publications, or wherever else your customers are actually forming opinions. It means your SEO function needs a seat at the table for brand strategy conversations that it probably hasn’t been a part of before. 

If your organization still thinks of SEO as a traffic channel with its own budget line, this is the moment to push for a different conversation. 

None of that contradicts Google’s guide. It extends it. The fundamentals Google describes are the floor, not the ceiling. 

Google’s official AI optimization guide is, at its core, a reaffirmation of principles that good SEOs have always believed: Build real things for real people, make them technically accessible, and don’t try to game the system with shortcuts. 

What’s new is the context. AI Overviews and AI Mode are reshaping how answers are delivered and how traffic flows. Sites with unique expertise, strong technical foundations, and genuine authority are positioned to benefit from those changes. Sites built around volume, keyword manipulation, or shallow content are increasingly exposed. 

The question for your team isn’t “How do we optimize for AI?” It’s “How do we become the kind of source that AI systems want to cite?” That’s a content strategy question, a brand-building question, and ultimately a business quality question. And if you aren’t already, it’s one worth taking seriously right now.