Most travelers using ChatGPT for trip planning are not asking it to "plan my vacation." They are asking it to build a day-by-day itinerary, compare flight and hotel options, and suggest restaurants or activities that match a specific mood, budget, or travel style. Roughly 40% to 54% of travelers now use AI chatbots somewhere in their trip planning process, and adoption is climbing fast, with year-over-year growth reported between 64% and 124% depending on the age group surveyed. Simaia studies this exact behavior professionally, not for travel brands, but because the same query patterns, the same trust signals, and the same citation logic that shape how ChatGPT answers "best 5-day Japan itinerary" also shape how it answers "best HR outsourcing provider in Vietnam." Understanding one means understanding the other.

TL;DR

• Travelers mostly use ChatGPT for itinerary building, flight and hotel comparisons, and personalized recommendations, not one-shot "plan my whole trip" prompts [famileetravel.com][stardrift.ai].

• Different AI tools get used for different jobs: ChatGPT for creative itinerary ideas, Gemini and Google AI Overview for real-time logistics, Claude for budget detail, Perplexity for sourced fact-checking.

• AI chatbots lean heavily on OTAs, aggregators, and review platforms like Booking.com, Expedia, Tripadvisor, Viator, and Trustpilot when answering travel questions.

• Up to 35% of travel booking conversions are now influenced by an AI chatbot recommendation somewhere in the decision path.

• The same mechanics that get a hotel or airline cited in a ChatGPT travel answer are the mechanics B2B brands need to get cited in buyer-research answers, which is the discipline known as generative engine optimization.

About the Author: This article is written by the Simaia team, which runs AI search audits across ChatGPT, Gemini, Claude, Perplexity, and Google AI Overview for B2B clients and has directly tracked how these models select, cite, and rank sources across dozens of query categories, travel included, as a proxy for consumer-facing AI search behavior.

What Are People Actually Typing Into ChatGPT for Trip Planning?

The real prompts are narrower and more functional than the "plan my dream vacation" framing suggests. The most common travel planning queries submitted to AI chatbots fall into three buckets: building a day-by-day itinerary, searching for flights and accommodation within a budget or date range, and asking for personalized recommendations on restaurants, neighborhoods, or activities [yeti.co][famileetravel.com]. A typical sequence looks less like a single magic prompt and more like a conversation: "5 days in Lisbon, mid-range budget, traveling with a toddler" followed by "now cut that to fit a $150/day food budget" followed by "which of these neighborhoods is walkable to the train station."

This matters because it shows AI trip planning is iterative, not transactional. People treat ChatGPT less like a search engine and more like a research assistant they can push back on. Family travelers in particular use this back-and-forth to refine constraints that Google search results cannot easily absorb, like a five-year-old's nap schedule or a shared strategy for interest gaps within a group [famileetravel.com]. A step-by-step trip request works because it forces the model to hold context across multiple constraints at once, something a static list of blog results was never built to do.

How Does ChatGPT Travel Planning Actually Compare to Google Search?

ChatGPT and Google Search are not solving the same problem, which is the core reason "chatgpt vs google search" comparisons often miss the point. Google Search returns a ranked list of pages and lets the traveler do the synthesis. ChatGPT does the synthesis first and returns a single narrative answer, pulling in flight patterns, seasonal notes, and neighborhood trade-offs into one response. Traveler head-to-head tests have found the chatbot genuinely useful for narrowing down a shortlist of destinations or activities but weaker on specificity, sometimes recommending restaurants that have closed or itineraries that ignore actual travel times between stops [cntraveler.com].

That gap is worth taking seriously rather than glossing over. A model trained on general web text has no live inventory feed, so it can describe a great walking route through a city without knowing which listed hotel on that route is fully booked. Practical use tends to land in a hybrid pattern: travelers use ChatGPT to generate the shortlist and the structure, then verify and book through an OTA, review site, or map tool [cnn.com][stardrift.ai]. That is also why up to 35% of travel booking conversions now trace back to an AI chatbot recommendation somewhere in the path, even though the actual transaction usually still happens elsewhere [stardrift.ai]. The chatbot is doing the thinking; the booking platform is closing the loop.

Do Different AI Models Get Used for Different Parts of Trip Planning?

Yes, and the split is consistent enough to be a genuine pattern rather than anecdote. Search behavior and query intent diverge sharply by model:

This division exists because each model's underlying strength lines up with a different traveler need. Gemini and Google AI Overview are tied more closely to live search infrastructure, so they handle time-sensitive questions like current flight pricing better. Claude tends to produce more careful, structured reasoning, which suits multi-line budget math. Perplexity's whole product is built around citing sources inline, which is why travelers turn to it when they want to verify a claim rather than just generate one.

The practical takeaway: no single AI tool is "the" travel planning tool. Travelers are already building a personal stack, and any brand hoping to be recommended inside these answers needs to show up correctly across all of them, not just the one with the biggest headlines.

Which Sources Do AI Chatbots Actually Trust for Travel Answers?

Building on the model-by-model breakdown above, the next natural question is where these models get their information in the first place. AI chatbots most frequently cite online travel agencies and aggregators such as Booking.com, Expedia, Tripadvisor, and Viator, alongside trusted editorial travel publications and review platforms like Trustpilot. This is not random. These platforms combine three things models weight heavily: structured, frequently updated data, large volumes of user-generated reviews, and consistent citation by other reputable sources across the web.

That pattern is the exact mechanism behind generative engine optimization, often shortened to GEO. Where traditional SEO optimizes a page to rank in a list of ten blue links, GEO optimizes content and its distribution across the web so an AI model chooses to cite or summarize it directly inside a generated answer. The "geo vs seo" distinction is not cosmetic. SEO rewards keyword relevance and backlink volume on your own domain. GEO rewards being the source a model trusts enough to quote, which often depends on how consistently a brand is discussed and reviewed on third-party platforms it does not own.

This is precisely the mechanism Simaia builds strategy around, just outside the travel sector. In a healthcare SaaS case, Simaia grew a client's AI search visibility from 0% to 45% within 2.5 months, giving that brand 45% share of its niche's traffic across major LLMs, using the same principle that gets Tripadvisor cited over a random hotel's own website: being the source models trust because it shows up consistently in the right third-party places.

What Does This Mean for Any Brand, Not Just Travel Companies?

Stepping back from travel specifically, the underlying lesson generalizes to any B2B company being researched by a buyer instead of a tourist. AI answer engine optimization is the practice of making sure a brand is present, accurate, and cited in the answers AI models give to category-relevant questions, whether that question is "best hotel in Porto" or "best manufacturing supplier for injection-molded parts in Southeast Asia." The mechanics are the same: structured data, third-party validation, and consistent citation across the sources a given model already trusts.

An AI search audit is how you find out where you currently stand in that answer. Simaia runs this audit across ChatGPT, Gemini, Claude, Perplexity, and Google AI Overview, testing a set of real buyer-style prompts to see exactly where a brand appears, where competitors appear instead, and which third-party sources are driving those citations. For a global textile manufacturer client, that process fed directly into AI-powered content marketing and distribution: 90 LLM-formatted blog posts published in the first month, a press release picked up by USA Today, and AI bot visits to the site growing 3.5 times year-over-year, from 741 to 2,546 hits. Inbound leads went from one every two months to five per month within two months. That is AI referral traffic converting into a pipeline, not just visibility for its own sake.

Frequently Asked Questions

Can ChatGPT actually book a flight or hotel for me?
No. ChatGPT can research, compare, and structure options, but it does not currently execute live bookings. Travelers still complete the transaction on an airline, hotel, or OTA site [stardrift.ai].

Is ChatGPT more accurate than Google for finding a specific restaurant or hotel?
Not necessarily. ChatGPT is strong at narrowing a shortlist and building structure, but it can surface outdated details like closed venues, since it lacks a live inventory feed [cntraveler.com].

What is generative engine optimization in plain terms?
It is the practice of shaping content and its distribution so AI models cite it directly in generated answers, rather than just ranking it in a search results list.

How is GEO different from traditional SEO?
SEO optimizes for ranking position on a results page. GEO optimizes for being the trusted source a model quotes or summarizes inside its answer, which depends heavily on third-party citation and validation, not just on-page keywords.

Do all AI models pull from the same sources?
No. Gemini and Google AI Overview lean on real-time search data, Perplexity emphasizes inline-cited sources, and ChatGPT and Claude draw more on trained knowledge plus browsing, which is why answers can differ meaningfully by platform.

How would a B2B company know if it's showing up in AI search results?
An AI search audit run across the major models with category-specific prompts is the direct way to see this, rather than guessing from Google rankings alone.

Does AI referral traffic actually convert into real business?
Yes, when the visitor is properly identified. In Simaia's Australian healthcare SaaS case, a high-value inbound visitor arriving through AI search was de-anonymized and handed to the client's sales team as an actionable lead.

About Simaia

Simaia is an agentic marketing team built for B2B companies that want to be found by buyers using ChatGPT, Gemini, Claude, Perplexity, and Google AI Overview. It runs the strategy side, including AI search audits and competitor gap analysis, and the execution side, including LLM-formatted content, press placement, and lead identification, as one done-for-you service rather than a dashboard clients have to operate themselves. Simaia is built specifically for founders, sales leaders, and marketing teams across APAC who are losing ground to competitors already showing up in AI-generated answers. Its clients have seen measurable shifts, including a jump from 0% to 45% AI search visibility in 2.5 months and a 10x increase in monthly inbound leads within two months.

If your buyers are already asking ChatGPT and Gemini who the best provider in your category is, the question worth answering is whether your company shows up in that answer at all. Get in touch with Simaia to find out.

References

1. ChatGPT: The Ultimate Guide to Vacation Planning | by Rudy Mutter | Emerging Technologies | Yeti LLC (yeti.co)

2. What happened when CNN Travel challenged ChatGPT to ... (cnn.com)

3. Family Travel Hacks: 5 ChatGPT Prompts for Travel Planning (famileetravel.com)

4. I Let ChatGPT Plan My Vacation-Here's What It Got Right and Oh-So Wrong | Condé Nast Traveler (cntraveler.com)

5. Can You Use ChatGPT for Travel Planning? (stardrift.ai)