For over a decade, my life revolved around the traditional search ecosystem. As a travel blogger and content creator, I built multiple successful travel and recipe sites. We didn’t write from a distance; everything we published was based on our actual boots-on-the-ground experiences.
This lifestyle allowed us to travel the world, partner with tourism boards, and build deep relationships with chefs and winemakers across Europe. If you wanted to know where to find the best plate of pasta or an authentic local market, you came to experts like us. We spent days crafting single, high-quality blog posts packed with real-world nuances.
Then, around 2022 and 2023, the ground began to shift beneath our feet.
Why Did We Sell Our Decade-Old Travel Business?
We started noticing that our high-authority travel sites were being outranked on legacy search engines by massive content farms. These platforms were hiring cheap, low-cost writers to churn out generic articles based on aggregated internet data. The content lacked soul, and more importantly, it lacked real experience.
When ChatGPT first launched in early 2023, I put it to the test. I asked it to plan an itinerary for Bologna, Italy—a city I have visited a dozen times and literally wrote a book about.
That early iteration of AI made some massive, glaring errors. It recommended “popping into” a restaurant for dinner that happened to be the number one restaurant in the world, located in a different city entirely, with a year-long waitlist. It suggested grabbing a midnight scoop of gelato at a local shop I love, which actually closes its doors at 9:00 PM.
The limitations of AI search were obvious back then. But as an entrepreneur and business consultant, I saw the writing on the wall. I knew there was no way to compete long-term against an engine that could spit out 100 blog posts in an hour while we spent days validating a single itinerary. We put our travel blogs up for sale and shifted our focus entirely into AI business strategy.
Fast forward three years. The technology has evolved, and so has my approach to using it.
How Do Travelers Actually Search for Information Today?
Recently, we planned a two-week trip to Europe. We managed to secure frequent flyer miles to and from Amsterdam, but we didn’t want to spend the entire two weeks in the Netherlands. Because Amsterdam is a major hub, we could easily fly anywhere in Europe for the nine or ten open nights of our trip.
We already know Spain and Italy like the back of our hands. We’ve lived in Spain, we’ve lived in Ireland, and we’ve spent significant time in Portugal. Our initial instinct was to return to what was comfortable and familiar—places where we already knew exactly where to eat, stay, and look around without needing to do any heavy research.
Instead, we decided to challenge Gemini and Perplexity to give us an alternative.
We didn’t just type in a lazy, single-line prompt like “plan a 10-day trip to Europe.” Instead, we treated the AI as a high-level travel consultant. We walked through over a hundred queries and iterative discussion points:
- We shared our specific travel history and our old travel blog to establish our preferences.
- We detailed where we had lived and what we typically look for in a vacation.
- We explained that we are entrepreneurs running two businesses simultaneously while traveling. We needed comfortable accommodations, reliable internet, and a slower pace—not a chaotic schedule where we changed hotels every night.
- We specified that since we live in landlocked Colorado, we wanted access to fresh, non-frozen coastal seafood and water views.
What Did the AI Recommend?
Based on our conversation, both Gemini and Perplexity agreed on a cohesive route: fly from Amsterdam to Bordeaux (a wine city we loved and had visited once before), then take a regional train north along the coast to the historic port town of La Rochelle, and finally finish the journey in Nantes.
We used the LLMs to handle every variable of the execution:
- Finding specific hotels that met our business needs
- Identifying local food markets and wine-tasting spots
- Mapping out walking itineraries through historical districts
- Recommending a hidden day-trip destination outside of Bordeaux we had never heard of
- Analyzing historical spring weather data to help us pack for coastal rain
We didn’t let the AI dictate our vacation blindly. We pushed back, adjusted parameters, and co-created the trip. In the end, it built a tailored 10-day French itinerary.
How Successful Was the AI-Generated Itinerary?
As a former professional travel writer, I am a tough critic. But the real-world results of this experiment were undeniable:
- Accommodations: We stayed in three hotels recommended by Gemini. Every single one met our criteria, offered great internet, and caused zero issues.
- Logistics: We booked our train transfers seamlessly through platforms we’ve used for a decade, exactly as the AI mapped out.
- Dining: The restaurant and market recommendations had an 80% to 90% success rate.
- Discoveries: The small day-trip town outside Bordeaux was a spectacular highlight we never would have discovered through a standard Google search.
Out of the three main destinations, Nantes was the only outlier. While interesting, it skewing heavily toward a young university demographic and wasn’t quite our style. But overall? The trip was an absolute success. La Rochelle was so beautiful we actually found ourselves looking at local real estate listings.
Could we have found this information using traditional search engines, checking TripAdvisor, and reading dozens of travel blogs? Yes. But it would have required hours of manual distillation. The LLMs did it for us in minutes.
What Are the Business Implications of the New AI Search?
This shift in consumer behavior is not ideal news for traditional travel writers, bloggers, or legacy publishers. But more importantly, it is a warning sign for every business owner.
Consumers are no longer just looking at a list of blue links on a search page and doing the sorting work themselves. They are having nuanced, multi-turn conversations with AI platforms to make buying decisions. They are providing deep context about their lives, their needs, and their frustrations, and expecting the AI to synthesize the perfect recommendation.
If your business, your services, or your brand authority are not visible to these language models, you are effectively invisible to the modern consumer.
Adapting to the AI-Driven Marketplace
I let AI plan my trip to France, and I would do it again without hesitation. The efficiency, personalization, and accuracy of modern LLMs have fundamentally altered how I look for information as a consumer.
As business owners, leaders, and consultants, we have to recognize that our target audiences are shifting their habits right now. The businesses that adapt their digital strategies to optimize for both human readers and AI models will capture the market. Those waiting for things to go back to the old way will simply be left off the itinerary.
Key Takeaways for Business Owners
- Contextual Search is King: Users are providing highly specific parameters (e.g., “reliable Wi-Fi for video calls,” “coastal seafood locations”) rather than broad keywords.
- Zero-Click Distillation: Customers want answers, not websites. If an AI can summarize your offering accurately inside the chat interface, the consumer saves time.
- The Power of Real Experience: While AI can synthesize data perfectly, it still relies on the digital footprint of real-world experiences. Your brand needs to be talked about in a way that AI models can digest and trust.
FAQ About AI Search and Content Strategy
LLMs analyze vast datasets, user reviews, structured data, and authoritative web content to find options that match the highly specific context of a user’s prompt. They look for consistent, verified information that proves a business matches the user’s explicit needs.
No, but traditional SEO has changed. Ranking for a single keyword is no longer enough. Your digital presence must now optimize for “LLM Visibility”—ensuring your website copy, product descriptions, and brand narrative use clear, direct, and unambiguous language that AI systems can easily parse, categorize, and recommend.
Focus on clarity over cleverness. Clearly state what your business does, who it serves, and the exact problems it solves. Use clear formatting, answer direct questions naturally in your content, and ensure your brand is mentioned across reputable, authoritative platforms that AI models use for training data.
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