Generative AI is increasingly becoming part of travel search, information organization, and itinerary planning processes, but 'using AI' and 'delegating travel decisions to AI' remain two distinct issues. This analysis primarily draws on YouGov survey data of U.S. travelers from 2024 and 2025, supplemented by Booking.com's The Global AI Sentiment Report and Accenture's The Travel Industry's New Trip for industry context. It's important to define the research boundaries upfront: the existing YouGov data measures consumer comfort with AI travel planning and the AI features they have used or considered using; it does not directly survey users' willingness to let AI automatically book hotels, purchase flights, or complete payments. Therefore, this report focuses on the potential 'trust-authorization gap' between informational assistance and transactional execution, rather than calculating a hypothetical AI autonomous booking acceptance rate.
Research Background
Travel is becoming one of the earliest scenarios where generative AI enters complex consumer decision-making processes. Booking.com's 2025 global AI survey shows that consumers have begun incorporating AI into travel planning but retain significant reservations regarding AI trust, independent decision-making, and control. Accenture's 2024 travel industry research also notes that the travel consumption journey—from inspiration discovery, information search, planning to booking—naturally spans multiple websites, platforms, and decision steps, positioning generative AI to consolidate information and streamline processes. The issue is that technological capability to cover more processes does not automatically mean consumers will grant more permissions. YouGov's 2024–2025 U.S. traveler surveys provide a valuable observation window: as AI travel tools proliferate, consumer attitudes have not followed a simple linear upward trajectory.
Increased AI Travel Tools Did Not Correspondingly Raise Overall Comfort Levels
Overall comfort levels among U.S. travelers regarding AI travel planning declined slightly between 2024 and 2025. According to YouGov's survey results published in August 2025, 32% of U.S. travelers felt comfortable using AI for travel planning in 2024, a figure that dropped to 30% in 2025. Concurrently, 40% of respondents in 2025 explicitly stated they are uncomfortable with it. YouGov conducted these two survey rounds in April 2024 and July 2025, targeting U.S. consumers who had traveled in the past 24 months or planned to travel in the next 12 months.
This change warrants distinguishing between two variables. One is whether AI travel tools are becoming more accessible; the other is whether users have consequently developed higher levels of trust. The former primarily reflects product supply and feature coverage, while the latter is influenced by factors such as information accuracy, sense of control, user experience, and decision risk. The shift from 32% to 30% is modest, but combined with the 40% discomfort rate, it's clear the U.S. market remains significantly divided, rather than naturally progressing towards widespread acceptance as AI features become more common.
Industry research from Booking.com and Accenture reveals a similar structural phenomenon: AI is playing a greater role in travel search, planning, and service processes, yet consumers still differentiate between tasks suitable for AI assistance and those requiring human judgment. In other words, tool penetration and trust levels cannot be directly equated.
Younger People Are Not Necessarily More Willing to Delegate Travel Planning to AI
The changes across age demographics are more pronounced than the overall figures. According to YouGov's 2024–2025 surveys, the share of U.S. travelers aged 18–24 comfortable with AI travel planning dropped from 47% to 34%, a decline of 13 percentage points. The 25–34 age group saw a decrease from 47% to 38%. Conversely, the 35–44 age group increased from 37% to 41%, and those over 55 rose from 16% to 20%.
This indicates that the simple assumption—'younger users interact with AI more, so they will maintain higher acceptance of travel AI'—is not supported by the 2025 U.S. travel market data. Younger users may still be frequent users of AI products, but high-frequency engagement and sustained trust are not synonymous. As user experience accumulates, consumers may shift from 'willingness to try new tools' to evaluating 'whether this tool can reliably solve real travel problems.'
On the other hand, increased comfort among middle-aged groups cannot be directly interpreted as age causing trust growth. The current data only indicates that different age cohorts experienced attitude shifts in different directions between the two surveys. Whether the actual drivers are product experience, accuracy, usage frequency, travel complexity, or other variables requires further research to determine.
| Age Group | 2024 Comfort Level | 2025 Comfort Level | Change |
|---|---|---|---|
| 18–24 years | 47% | 34% | Down 13 pts |
| 25–34 years | 47% | 38% | Down 9 pts |
| 35–44 years | 37% | 41% | Up 4 pts |
| 55+ years | 16% | 20% | Up 4 pts |
Source: YouGov, U.S. Traveler Surveys, April 2024 & July 2025.
Consumers Prefer AI for Information Handling Over Ceding Entire Travel Decisions
Looking at specific features, current consumer acceptance of travel AI is primarily concentrated in information processing and decision-support roles. According to YouGov's 2025 survey, 28% of U.S. travelers have used or would consider using AI to analyze reviews and ratings, 26% would consider AI for personalized travel recommendations based on interests or preferences, and another 26% have used or would consider using language translation tools. Additionally, 23% of respondents explicitly stated they do not want to use any AI tools when planning travel.
While review summarization, recommendations, and translation are distinct features, they share a common trait: AI primarily helps users reduce information processing costs, while the choice remains firmly with the user. AI can summarize numerous hotel reviews, narrow destination options based on preferences, or handle unfamiliar languages, but consumers can still review the output, compare options, and decide whether to adopt the suggestions.
This provides a foundation for observing the 'trust-authorization gap.' If a user is willing to let AI analyze 200 reviews, it doesn't necessarily follow that they would also let AI directly purchase a non-refundable flight based on that analysis. In the former case, errors typically leave room for re-evaluation and correction; the latter could directly involve finances, time, cancellation policies, and liability.
| AI Travel Use Case | % Used or Would Consider (2025) | Primary Role |
|---|---|---|
| Analyze reviews & ratings | 28% | Organize info, aid comparison |
| Personalized travel recommendations | 26% | Narrow destination & product choices |
| Language translation | 26% | Reduce cross-language communication costs |
| Prefer no AI in travel planning | 23% | Maintain traditional planning methods |
Source: YouGov, U.S. Traveler Survey, July 2025. Importantly, these figures do not measure willingness to authorize automatic hotel booking, payment, or flight purchases, and therefore cannot be used to claim consumers reject AI autonomous booking.
The Next Variable for Travel AI: How Far Users Are Willing to Grant It Authority
Synthesizing the data above, the challenge for travel AI is not solely about functional capabilities. In 2025, only 30% of U.S. travelers felt comfortable with AI travel planning, and 40% felt uncomfortable, yet specific auxiliary functions like review analysis, personalized recommendations, and translation show usage or consideration rates between 26%–28%. Users aren't simply 'accepting' or 'rejecting' AI; they are drawing different boundaries across different tasks.
During the search, organization, comparison, and recommendation phases, users can verify information anytime and ignore AI suggestions, keeping a clear sense of control. As travel AI extends into booking decisions, payments, cancellations, changes, and itinerary management, the nature of the tasks changes. Errors are no longer just incorrect answers; they could result in actual bookings, financial loss, missed flights, or subsequent customer service issues. Consequently, the threshold for granting authorization may differ significantly.
Therefore, the conclusions supportable by current public data are: consumers retain significant reservations about AI travel planning, and the information-processing functions they are more willing to accept are primarily concentrated in decision-support roles. As for how much willingness to delegate drops when moving from itinerary planning to autonomous transactions, there remains a lack of specific data to directly calculate this gap. This data gap itself warrants continued monitoring by travel platforms, AI products, and brands.
The next phase for travel AI isn't just answering 'what can it do for users,' but also 'how far are users willing to let it go.'
Trend Observations / Industry Implications
Firstly, the competitive dimension of travel AI is extending from 'can it generate itineraries' to 'which decision layer can it participate in.' Generating itineraries, summarizing reviews, and recommending destinations are becoming increasingly common capabilities. As these information-layer features become widespread, the variables truly impacting user experience will shift towards execution permissions, information verification, and the user's ability to take back control at any point.
Secondly, AI trust cannot be simply inferred from age. In the 2024–2025 U.S. data, comfort levels dropped for the 18–34 age groups but rose for those 35–44 and 55+. This suggests demographic attributes can be an observational dimension but are insufficient to directly predict user authorization levels for AI. For travel businesses, segmenting users solely based on 'younger people like AI' may fail to explain real travel decision-making behaviors.
Thirdly, different stages of the travel journey may present different authorization thresholds. Tasks like inspiration discovery, translation, and review summarization generally have high reversibility, allowing users to check other sources. However, once entering flight and hotel booking, payment, order modification, cancellation, and changes, the financial costs, time investments, and liability concerns increase. Future measurements of travel AI usage should consider breaking down levels such as 'information trust,' 'recommendation adoption,' 'booking authorization,' and 'transaction authorization,' rather than relying on a single overall AI acceptance metric.
The more rigorous industry assessment at this stage remains: AI has entered the travel planning process, consumers show clear demand for certain auxiliary functions, but whether a larger authorization gap exists between planning and autonomous transactions—and its exact magnitude—still requires survey data focused on transaction behaviors to verify.
Research Implications
For travel brands focused on GEO abroad, it's no longer enough to monitor just whether the brand is mentioned by AI; it's also crucial to observe at which stage of the travel decision journey the brand appears. The travel user journey can be segmented into 'inspiration discovery → information comparison → itinerary planning → product filtering → booking decision → transaction execution → itinerary management.' Brands should then observe how AI platforms like ChatGPT, Gemini, Google AI Mode, Perplexity, and Google AI Overview present brand names, hotels or travel products, pricing conditions, cancellation policies, third-party reviews, and destination information across these stages.
For example, a brand might frequently appear in AI answers for 'where to stay in Tokyo' but rarely surface in queries closer to booking decisions, such as 'family-friendly hotels with free cancellation.' Or, AI might identify the brand's product information but fail to consistently present cancellation terms, pricing rules, or service scope. From an effectiveness monitoring and data analysis perspective, these differences reflect the brand's position within the AI travel decision chain more accurately than simply counting brand mentions.
Whether travel AI will further take on transactional execution remains to be seen. For brands, the more pragmatic question is continuously assessing which stages consumers start relying on AI, and whether their own information can be accurately identified, compared, and presented during those stages.
As travel search extends from traditional results to AI recommendations and answer interfaces, brands need to monitor not just search rankings, but also whether they enter the AI decision scenarios consumers actually use. Check your real-world visibility across 6 major AI engines in just 1 minute with aipogeo, and further observe how your brand appears across different platforms.
Related Questions
Are U.S. consumers willing to use AI for travel planning in 2025?
According to a YouGov 2025 survey, 30% of U.S. travelers feel comfortable using AI for travel planning, while 40% feel uncomfortable. The data indicates a clearly divided market, and the increase in AI tools cannot be directly interpreted as widespread acceptance.
Are younger people more willing to use AI travel tools than older demographics?
It's not that simple. YouGov data shows comfort levels decreased for the 18–24 and 25–34 age groups between 2024 and 2025, while increasing for the 35–44 and 55+ groups. The relationship between age and AI trust is not a simple linear one.
Which travel tasks are consumers currently most willing to let AI handle?
In the 2025 U.S. survey, review and rating analysis stood at 28%, while personalized travel recommendations and language translation were both at 26%. These features primarily help consumers organize information and aid decision-making.
Does a user's willingness to use AI for itinerary planning imply they'd let AI auto-complete bookings?
No, that inference cannot be made. Existing YouGov data does not directly survey acceptance rates for automatic hotel booking, flight purchases, or payments. It can only confirm attitudes towards using AI for planning and certain auxiliary functions; it cannot calculate autonomous transaction authorization rates.
What roles might ChatGPT, Gemini, and Perplexity play in travel decisions?
Different AI products can be involved in destination search, information comparison, itinerary planning, and recommendations, but their specific presentation varies based on product features and the nature of the query. For brands, it's more appropriate to observe them continuously across user decision stages rather than assuming a single role for any one platform.
How should travel brands monitor their visibility in AI travel search and recommendations?
Brands can segment query scenarios according to inspiration discovery, information comparison, itinerary planning, product filtering, booking decisions, transaction execution, and itinerary management. Then, monitor the presence of brand names, product details, pricing, policy information, and third-party reviews across different AI platforms, and track changes over time.