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AI will make travel planning faster, but it is unlikely to make human judgment irrelevant. The most credible near-term model is a partnership: software searches, summarizes and reshapes options quickly, while travelers, advisors, creators and local experts add context, relationships, empathy and accountability. John Baumgartner, founder and CEO of HipTraveler, makes this argument in his March 25, 2026 thought-leadership article, writing that “The future of AI in travel isn’t artificial at all. It’s deeply, stubbornly human.” That is a forecast, not proof that every future system must include a person. Current surveys do show meaningful use of AI for trip planning, alongside stronger reported preferences for human or blended recommendations than for AI alone.
What does a human future for AI in travel actually mean?
“Human” does not mean rejecting automation or returning to phone-only bookings. It means designing AI around a traveler’s real intent and circumstances rather than treating popularity, clicks or average ratings as a complete picture of what someone should do.
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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsBaumgartner argues that generalized signals tend to produce familiar suggestions: the same highly ranked attractions, restaurants and itineraries that appear to work for the largest number of people. A human-informed system can ask why a person is traveling, what trade-offs they accept, which experiences felt meaningful before, and what constraints are non-negotiable. A trusted advisor or knowledgeable local can also recognize details that are difficult to encode, such as a neighborhood’s atmosphere after dark, a supplier’s reliability during disruptions, or whether an apparently suitable activity fits a family’s energy and accessibility needs.
The argument is best understood as “AI plus human expertise.” AI contributes speed and breadth; people contribute interpretation and responsibility. Neither Baumgartner’s article nor the available survey evidence proves that human involvement will be inevitable in every future travel product.
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How is AI changing travel planning today?
AI is already useful for the information-heavy parts of a trip. It can scan many sources, summarize differences, turn a rough wish into a draft itinerary and revise that plan when dates, budgets or interests change. Those capabilities reduce the time spent gathering options, especially for travelers starting with an open-ended question.
Where AI is strongest
- Search and synthesis: It can organize large amounts of destination, transport and activity information into a shorter list.
- Rapid iteration: A traveler can ask for a slower pace, a lower budget, fewer transfers or a different interest profile and receive a revised outline quickly.
- Constraint checking: In a well-designed tool, dates, opening hours, travel times and stated preferences can be considered together instead of in separate searches.
- Always-on assistance: A digital concierge can answer routine questions outside an advisor’s working hours.
Why a fast answer can still be a poor recommendation
Speed does not guarantee relevance. Systems trained or ranked around aggregate behavior may favor what is popular, heavily marketed or frequently mentioned rather than what suits a particular traveler. A polished itinerary can also conceal uncertainty: a source may be outdated, a venue may have changed its policy, or a transfer may be unrealistic for someone with mobility limitations. AI can state an incorrect detail confidently, so important facts still require verification.
What do current surveys say about AI trip planning?
Several surveys indicate growing interest, but their figures measure different things and should not be combined into one adoption rate.
| Measure | Reported result | What it represents |
|---|---|---|
| Used AI to help plan a trip | 24% | All travelers surveyed in Global Rescue’s Summer 2025 Traveler Safety and Sentiment Survey, released July 21, 2025 |
| AI users who used it for itinerary planning | 75% | A use case among respondents who had used AI, not all travelers |
| AI users who used it for general research | 71% | Another use case among AI users; respondents could report more than one use |
| Preferred a blend of AI and human recommendations | 50% | Preference reported in the Global Rescue release |
| Preferred human recommendations | 45% | Preference reported in the Global Rescue release |
| Preferred AI alone | 4% | Preference reported in the Global Rescue release; the published categories total 99% |
The Global Rescue results describe one survey population and one field period. They show reported behavior and attitudes, not a laboratory test of which method produces better holidays. Dan Richards, CEO of The Global Rescue Companies and a member of the U.S. Department of Commerce’s Travel and Tourism Advisory Board, said, “But adoption still depends on trust and reliability, especially in high-stakes situations.”
A separate set of Longwoods International findings, relayed by the Ohio Travel Association, uses two different questions. The share saying they were likely or very likely to use AI in trip planning rose from 34% in August 2024 to 40% in June 2025. The share reporting that they had actually used AI for trip planning in the previous six months rose from 19% to 25% over those same field points. “Likely to use” is an intention measure; “used in the previous six months” is a reported behavior measure. The association page relays Longwoods’ findings rather than claiming to have conducted the survey itself.
Why do personal context and trust matter?
Travel choices are unusually dependent on circumstances that are hard to infer from ratings. A person may choose a less famous museum because it is calm, a longer rail route because the journey is part of the experience, or a particular guide because a friend trusts that operator. Those preferences may not be visible in public popularity data.
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Intent is more than a destination
“A week in Italy” could mean a food-focused trip, a low-walking anniversary, a photography project, a family visit or a first-time solo journey. Human conversation can reveal the purpose and emotional stakes behind the destination. AI can help structure those answers, but a person remains useful when the traveler is unsure how to express them or when priorities conflict.
Local knowledge includes relationships
The Adventure Travel Trade Association’s commentary on AI, advisors and local expertise identifies destination knowledge, supplier relationships and operational experience as human strengths. A specialist may know which local partner responds during a disruption, how seasonal conditions affect an excursion, or which alternative is genuinely available when a popular option sells out. This is industry commentary, not a controlled comparison proving that every advisor outperforms software.
High-stakes decisions need a reachable counterpart
Missed connections, medical issues, severe weather and border changes can turn a planning question into an urgent operational problem. A system may provide information, but travelers often need someone who can interpret the situation, contact a supplier and take responsibility for a recommendation. The survey responses about trust and emergency use indicate concern in this area; they do not establish the actual accuracy of any particular AI tool.
Will AI replace travel agents and advisors?
Replacement is the wrong default assumption. AI can absorb repetitive research, while advisors can focus on judgment, relationships and exception handling. The balance will vary by trip complexity, traveler confidence and the consequences of getting a decision wrong.
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| Planning model | Likely advantage | Typical weakness | Best fit |
|---|---|---|---|
| AI-only | Fast searching, summarizing and itinerary drafts at any hour | May miss unstated preferences, current local conditions or accountability when plans fail | Simple, low-stakes trips where the traveler will verify details |
| Human-led | Personal context, specialist knowledge, supplier relationships and a reachable person | Slower to assemble broad options and may cost more or depend on availability | Complex, time-sensitive, specialist or high-consequence travel |
| Blended | AI handles information volume while a person checks fit, feasibility and trade-offs | Requires clear handoffs and the traveler must know which facts were verified | Most travelers who want efficiency without giving up judgment |
This framework describes capabilities, not guaranteed outcomes. An inexperienced advisor can give poor advice, and a carefully designed AI system can be genuinely helpful. The relevant question is which risks and decisions a particular trip contains.
How can I use AI and human advice together?
A blended workflow keeps automation in the tasks it handles well and assigns judgment to a person at the points where context matters most.
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- Define the trip in plain language. State dates, travelers, budget, pace, accessibility needs, purpose and what you want to avoid. Include constraints that a ranking system would not know.
- Ask AI for a set of options, not a final verdict. Request alternatives with reasons, estimated travel times, assumptions and a list of facts that need checking.
- Check primary details. Confirm operating dates, entry rules, cancellation terms, transport schedules and accessibility directly with official providers or authorities.
- Bring in a relevant human specialist. Share the draft with a local expert, travel advisor, trusted creator or experienced friend who understands the destination or activity.
- Expose the trade-offs. Ask the person to challenge the plan: what is too rushed, fragile, seasonal, expensive or mismatched with the traveler’s real goal?
- Keep a disruption plan. Record contact details, booking references, alternatives and the person responsible for changes if weather, illness or supplier failure interrupts the trip.
This process avoids asking AI to invent confidence and avoids asking a human to perform every search manually.
What is an AI concierge, and what can it realistically do?
A 2024 conceptual paper by Stephanie Q. Liu and co-authors in the Journal of Service Management defines the idea of an AI concierge and considers possible roles across the customer journey. It is a conceptual contribution, not a validation study of a particular commercial assistant and not evidence of measured traveler outcomes.
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In practical terms, an AI concierge could help before, during and after a trip: collect preferences, suggest options, answer routine questions, coordinate information and adapt a plan as circumstances change. The value depends on the quality of its data, its ability to show uncertainty, the freshness of time-sensitive information and the availability of escalation to a person. Calling a system a concierge does not by itself give it local knowledge, booking authority or emergency responsibility.
What does the evidence establish—and what does it not?
The sources answer different questions, so their authority should not be blended.
- Baumgartner’s article: an opinion and forecast from a travel-technology founder about why human-informed context should shape future systems.
- Global Rescue’s release: survey results from its Summer 2025 Traveler Safety and Sentiment Survey about reported use and preferences.
- Ohio Travel Association’s page: a relay of Longwoods International findings from August 2024 and June 2025, with separate intention and recent-use measures.
- Adventure Travel Trade Association commentary: an industry perspective on the value of destination expertise, relationships and operational experience.
- Liu and colleagues’ paper: conceptual academic work describing AI-concierge roles, without testing a specific product.
Together, they support a careful conclusion: AI use and interest are present and increasing in the cited surveys, while trust, context and specialist knowledge remain important reasons to involve people. They do not prove that humans will always be required, that AI will replace all advisors, or that one planning method consistently produces better travel.
How should I decide between AI-only, human-led and blended planning?
Choose according to the consequences of error, not novelty.
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- Use AI as a primary research aid when the route is flexible, bookings are refundable, the activity is low risk and you are comfortable verifying every important detail.
- Use a human-led approach when the trip involves remote environments, complex logistics, multiple suppliers, accessibility requirements, expensive nonrefundable commitments or a serious need for support during disruption.
- Use a blended approach when you want AI’s speed but need a second perspective on cultural fit, pacing, local conditions, specialist activities or the consequences of a mistake.
Before accepting an AI-generated itinerary, ask: Which assumptions did it make? Which facts are time-sensitive? Who can help if a supplier fails? What information would change the recommendation? If you cannot answer those questions, the plan is not finished.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What problems can arise when AI plans a trip?
Confidently wrong details
Opening hours, routes, visa rules and seasonal services change. Treat every time-sensitive statement as a prompt to verify, not as a booking instruction.
Popularity mistaken for suitability
Highly rated or frequently mentioned options may be crowded, inaccessible, expensive or inconsistent with the trip’s purpose. Ask for less-obvious alternatives and explain the preference they serve.
Hidden commercial or data incentives
A recommendation may reflect availability, ranking logic or commercial relationships that are not obvious to the traveler. Look for transparent explanations and compare with independent or official information.
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When something goes wrong, a chatbot may not be able to contact a supplier or make a binding change. Keep human contact details and booking records outside the AI conversation.
What will the next generation of travel AI look like?
Baumgartner’s forecast points toward systems that learn from trusted human perspectives rather than relying only on generalized popularity. That could mean advisors supervising recommendations, local contributors adding structured context, creators explaining the “why” behind a place, and travelers controlling the preferences and sources that shape their results.
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The most useful systems will likely make uncertainty visible, preserve the traveler’s intent, explain trade-offs and offer an easy route to a person. They may automate more of the search and coordination, but the human contribution will remain valuable wherever meaning, trust, local judgment or responsibility matters. That is a plausible direction, not a guarantee about every product or every future trip.
What should travelers do now?
Use AI to widen and organize your options, then use human knowledge to test whether those options fit your actual life. Verify volatile facts with official providers, ask a specialist to challenge complex plans, and keep a reachable contact for disruption. The goal is not to choose between technology and people; it is to assign each the work it can do responsibly.
Frequently Asked Questions
Can AI book an entire vacation without a travel advisor?
Some tools can assemble or even transact parts of a trip, but capability varies by service and destination. You still need to confirm terms, availability, identity requirements and who is responsible when a booking changes or fails.
How can I tell whether an AI itinerary is trustworthy?
Ask the tool to list assumptions, dates checked and uncertain items, then verify those items with official transport, venue or government sources. A trustworthy workflow makes verification and escalation easier rather than presenting every statement as certain.
Is human travel advice only useful for luxury or adventure trips?
No. Human input can help with ordinary trips when travelers have accessibility needs, conflicting priorities, little planning time or low tolerance for disruption. The value comes from context and accountability, not from the price of the vacation.
Why do survey percentages about AI travel use differ?
The cited surveys asked different questions of different respondent groups at different times. For example, “likely to use” measures intention, while reported use in the previous six months measures behavior, so the percentages should not be treated as one trend line.
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