Artificial intelligence is no longer content to simply answer our questions: it is becoming a player in everyday tasks. In the travel industry, this evolution is reflected in the emergence of “agentic booking”,<\/strong> i.e. intelligent agents capable of planning and booking stays from end to end. This transformation, which will begin in 2024 and accelerate in 2025, promises to shake up the entire tourism ecosystem, from search engines to online agencies. This in-depth article (approx. 2,000 words) explains what agentic booking is, describes the innovations that will follow, analyzes the impacts for industry players and offers ways to prepare for this new era. <\/p>\n \n Whereas generative AI, popularized by ChatGPT, simply produces text or images on command,agentic AI<\/strong> takes things a step further: it makes decisions and acts autonomously<\/strong>. These agents exploit long-term memories, multipath reasoning and external tools (APIs, search engines) to accomplish complex tasks. In short, agentic AI moves from an advisory role to a proactive, autonomous posture. <\/p>\n Generative AI is limited to answering questions (“How do I book a flight to Barcelona?”) or suggesting choices. An agent is objective-centric<\/strong>: it understands that we want a stay in Barcelona in June, searches for the best flight options, suggests a suitable hotel and finalizes the booking, adapting to unforeseen circumstances. These agents can even orchestrate a range of tools, monitor weather conditions, reschedule in the event of delays and optimize costs. It is this ability to “act” that is driving the growth of agentic booking. <\/p>\n The term agentic booking<\/strong> refers to the application of agentic AI to the booking process: an agent no longer simply displays results, but completes the transaction<\/strong>. This evolution responds to two observations: <\/p>\n Increasing friction in the booking process.<\/strong> A traveler may touch hundreds of pages over several weeks to book a hotel; this complexity discourages and generates attrition. Consumers demand more fluid, personalized experiences. <\/p>\n<\/li>\n AI maturity.<\/strong> Major platforms (Google, Booking.com, Expedia) and start-ups (Perplexity, SkyLink) are testing agents capable of booking a flight or hotel in a matter of seconds. Agentic AI is thus becoming a concrete tool rather than a futuristic vision. <\/p>\n<\/li>\n<\/ul>\n Online travel agencies (OTAs) have built their success on aggregating millions of offers and comparing rates. Agentic booking threatens this model. Reports explain that with agentic AI, “travelers no longer enter keywords but formulate intentions” (“Plan a weekend at the beach in April”) and receive a complete itinerary without visiting third-party sites. OTAs’ loyalty programs risk becoming invisible if data is not exposed via APIs. Specialists believe that loyalty could shift from the platforms to the AI assistant itself, capable of memorizing user preferences. <\/p>\n The market experienced a boom in 2025, with the deployment of several agentic booking solutions. Here are the main ones: <\/p>\n In October 2025, Booking.com unveiled its first agentic innovations for the general public. Smart Messenger<\/strong> and Auto-Reply<\/strong> automate communication between partners and customers. Smart Messenger compiles property and booking information to offer suggestions and respond autonomously. Auto-Reply enables hoteliers to define personalized responses to common questions, providing instant answers. These agents learn continuously and adapt their answers based on previous interactions. Tests have shown an increase in partner satisfaction compared with previous messaging tools. <\/p>\n Booking.com also offers AI Trip Support<\/strong>, a 24\/7 assistant capable of answering customer queries and making booking changes. For example, a traveler may ask whether a hotel has parking facilities; the tool retrieves the information and provides an immediate response. For more complex requests, the agent transfers to a human advisor, providing full context. <\/p>\n With AI Voice Support<\/strong>, the passenger can interact by voice (“I wish to cancel my reservation”), and the agent retrieves the reservation details and performs the necessary actions. This service, available in several languages (English, German, Italian and Spanish tests), reduces processing times. <\/p>\n For car rentals, the AI Rental Helper<\/strong> answers questions about pick-up, payment terms and insurance. The Flight Search Summaries<\/strong> module simplifies flight comparisons by highlighting trade-offs (number of stopovers, price, travel time). This feature is available in English and will be extended to other languages in 2026. <\/p>\n In November 2025, Google extended its AI Mode<\/strong> (experimented with via Search Labs) to include agentic booking capabilities. The user describes what they’re looking for (for example, dinner for three on Friday night) and the AI assistant explores multiple platforms (OpenTable, Resy, Ticketmaster, etc.) to suggest available options. The results are displayed in the form of a list, and the user finalizes the reservation via the partner of his choice. Google has clarified that this functionality is not limited to restaurants; it now includes event tickets and wellness appointments, and plans to integrate flights and hotels. <\/p>\n Julie Farago, vice-president of travel engineering at Google, explains that the aim is to enable users to book flights and hotels directly in AI Mode, while working with partners such as Booking.com, Expedia, Marriott and IHG. Google insists that it will not become an OTA; transactions will remain managed by partners, and users will retain the ability to choose their preferred partner. Caution is advised, as air and hotel bookings are less frequent and more sensitive purchases. <\/p>\n Start-ups also contribute to innovation. In a demonstration reported by the press, a journalist asked Perplexity’s Comet<\/strong> agent to book a Southwest flight; the agent selected the fare, filled in the personal information and finalized the purchase in a matter of minutes. All the user had to do was confirm before the transaction. Other companies, such as Hopper with its Assist<\/strong> tool, automate disruption management; the agent contacts the traveler by e-mail after a cancellation and proposes new options via chat or voice. Specialized solutions such as SkyLink<\/strong> target business travellers, comparing thousands of options in line with company policy and favoring less expensive flights. <\/p>\n At the same time, Sabre, Kayak, Expedia and ChatGPT are developing or integrating conversational agents capable of booking or modifying travel. This craze illustrates the race not to lose customer relationships to digital giants. <\/p>\n Agentic booking applies to many phases of travel: before, during and after. Specialist reports detail ten key use cases: <\/p>\n Proactive disruption management.<\/strong> Delays and cancellations need no longer cause uncertainty. Agents detect disruptions in real time, reschedule flights, notify customers and offer compensation or hotel vouchers. <\/p>\n<\/li>\n Hyper-customized planning.<\/strong> Thanks to the analysis of preferences, history and behavior, the agent proposes adapted and evolving itineraries. This real-time personalization strengthens commitment and loyalty. <\/p>\n<\/li>\n Dynamic pricing and revenue optimization.<\/strong> Agents monitor demand, competitor rates and trends to adjust room, flight or package prices, maximizing sales without sacrificing demand.<\/p>\n<\/li>\n Autonomous commitment to loyalty programs.<\/strong> Agents suggest targeted offers and detect inactive customers to re-engage them.<\/p>\n<\/li>\n Instant customer support.<\/strong> Virtual concierges answer questions and perform tasks (gate searches, restaurant recommendations, reservation changes) 24 hours a day.<\/p>\n<\/li>\n Operational efficiency.<\/strong> In the hotel sector, agentic AI optimizes housekeeping, room service and maintenance according to demand and forecasts. It also manages inventory (minibars, amenity kits) to minimize shortages and waste. <\/p>\n<\/li>\n Safety monitoring and compliance.<\/strong> By analyzing sensor and log data, AI detects violations of health standards and sends out alerts.<\/p>\n<\/li>\n Demand-driven inventory management.<\/strong> By forecasting consumption, AI triggers just-in-time replenishments.<\/p>\n<\/li>\n Autonomous upselling throughout your stay.<\/strong> Contextual offers (lounge passes, massages, excursions) appear at the right moment, boosting revenue without appearing intrusive.<\/p>\n<\/li>\n Multi-channel marketing orchestration.<\/strong> Agentic AI optimizes the sending of campaigns (e-mails, push notifications) according to customer behavior and context.<\/p>\n<\/li>\n<\/ul>\n Analysts point out that these agents are transforming contact centers: AI collects data, suggests the best action, frees up the human agent for high value-added tasks and improves the customer experience. Agentic AI thus becomes an “experience engine” that coordinates conversational and generative. <\/p>\n Despite the media hype, agentic AI is still in its infancy. Only a few percent of the travel companies surveyed are making widespread use of agentic AI, while a much higher proportion are experimenting with generative AI. However, AI as a whole is spreading: more and more major travel companies are mentioning AI in their annual reports, and venture capital investment targeting AI-enabled travel start-ups is rising sharply. <\/p>\n Of the executives surveyed, a quarter see a reduction in costs, around a third faster decision-making and more than half an increase in productivity thanks to AI. These figures encompass all types of AI, but illustrate the economic potential. Customers are also showing growing interest in AI assistants for reservations and personalized activity recommendations. <\/p>\n Travelers remain wary. Less than 2% of respondents to some studies say they are willing to let an autonomous agent book and modify their trip without human supervision. Hallucinations of generative models and booking errors fuel this caution. Adoption will therefore depend on trust<\/strong>, transparency of algorithms and respect for privacy. <\/p>\n The rise of autonomous agents is reshuffling the deck:<\/p>\n Potential disintermediation.<\/strong> If users go through an agent to search and book, they no longer have to visit OTA sites. Examples show that an agent can make a booking on an airline without going through an intermediary platform. OTAs risk losing their role as showcases and comparators. <\/p>\n<\/li>\n Loss of visibility and loyalty.<\/strong> Loyalty could shift from the platform to the AI assistant. Loyalty programs will need to integrate with the agent ecosystem (via API) to remain relevant. <\/p>\n<\/li>\n New business models.<\/strong> Google has explained that it has no intention of becoming a travel retailer, and that it would prefer to focus on partnerships. Its revenue model could be based on advertising or remuneration for agent visibility, but these points remain unclear. <\/p>\n<\/li>\n<\/ul>\n For suppliers, agentic booking represents an opportunity:<\/p>\n Direct access to the customer.<\/strong> Agents act as a qualification engine. Hotels that adopt agentic AI will see their conversion data improve thanks to micro-moments converted via targeted suggestions. AI becomes a vector for emotion-based recommendations, for example matching a room to a work of art that matches the customer’s taste. <\/p>\n<\/li>\n Equality for small operators.<\/strong> Medium-sized hotels without a dedicated concierge can offer personalized service thanks to conversational agents. Agentic AI creates a “memory infrastructure” that recalls customer preferences and improves retention. <\/p>\n<\/li>\n Operational management.<\/strong> Agentic AI can optimize room allocation according to preferences and loyalty levels, schedule predictive maintenance, assign housekeeping tasks and optimize the catering offer. In air travel, AI helps with dynamic pricing, load optimization and reward personalization. <\/p>\n<\/li>\n<\/ul>\n Human agents fear becoming obsolete. Some experts warn that agentic AI could make traditional travel agents “functionally obsolete” for the majority of customers. However, AI has shortcomings: it lacks real-life experiences, doesn’t visit hotels and can’t offer authentic recommendations derived from a stay. Advisors can therefore differentiate themselves by focusing on: <\/p>\n Personal experience.<\/strong> Showcase their local knowledge of destinations and establishments.<\/p>\n<\/li>\n Creating complex, emotional journeys.<\/strong> AI can optimize a cruise or a trip to Disney, but it’s no substitute for human creativity when it comes to orchestrating a unique itinerary or handling special requests.<\/p>\n<\/li>\n Human relations.<\/strong> Some customers seek human contact for reassurance, especially when it comes to large expenses. Advisors can become curators<\/strong>, while AI takes care of administrative tasks. <\/p>\n<\/li>\n<\/ul>\n Companies wishing to deploy reservation agents must follow a few basic rules:<\/p>\n Choose high-value use cases<\/strong>: start with scenarios where the impact is obvious (disruption management, rebooking optimization) to demonstrate the return on investment.<\/p>\n<\/li>\n Ensure data quality and integration<\/strong>: AI needs real-time data from multiple sources (CRM, booking engines, flight\/hotel databases). Wrong data will lead to wrong decisions and a loss of trust. <\/p>\n<\/li>\n Keeping a human in the loop<\/strong>: the agent must be able to hand over to human staff when situations go out of hand or a check is needed. This control prevents critical errors and enables the AI to be adjusted with human feedback. <\/p>\n<\/li>\n Ensuring explicability and transparency<\/strong>: customers need to understand why they are receiving a particular recommendation or upgrade. Transparent AI builds trust and facilitates regulatory compliance. <\/p>\n<\/li>\n Pilot, measure and iterate<\/strong>: large-scale deployment without prior testing is risky. Pilots enable you to adjust the agent, measure impact and reduce risks. <\/p>\n<\/li>\n<\/ul>\n Too much autonomy too fast<\/strong>: giving AI too much decision-making power can lead to serious mistakes (booking a closed hotel or choosing an unavailable flight). Human supervision and safeguards are essential. <\/p>\n<\/li>\n Ignoring compliance<\/strong>: personal data and payments are subject to regulations (RGPD, CCPA). Non-compliance leads to fines and loss of reputation. <\/p>\n<\/li>\n Thinking that AI is a one-off installation<\/strong>: agents require constant updating. Without monitoring, they can drift away from the company’s objective and produce biased recommendations. <\/p>\n<\/li>\n Rely on a single data source<\/strong>: limiting the agent to internal data (reservation history) omits external signals such as weather or local events.<\/p>\n<\/li>\n<\/ul>\n Because agents make decisions, they must be transparent and fair. Transparency<\/strong> means explaining the rules or data that have led to a recommendation (for example, an upgrade). Lack of explicability can generate suspicion or violate regulations. Algorithmic biases<\/strong> must be detected (preference for certain companies, unintentional discrimination). Human control and regular audits are essential. <\/p>\n Agents handle sensitive data (travel habits, means of payment). Any leakage could be catastrophic. Companies need to invest in encryption, access management and data minimization. Initiatives are emerging, notably around secure protocols for payment management. <\/p>\n Consumers fear errors or abuse.Opt-in<\/strong> mechanisms, human verification options and ongoing education on how agents work are needed. <\/p>\n The travel industry is highly fragmented, with heterogeneous systems and siloed data, which hinders AI adoption. Companies need to modernize their infrastructure, embrace the cloud and implement real-time data pipelines. <\/p>\n The next step will be anticipation. Agentic AI will be able to propose a wellness stay after detecting months of stress in the traveler’s diary. Offers will become proactive and tailor-made. <\/p>\n Agents will have to communicate between different platforms (airlines, hotels, transport). Retailers are already working on interoperability frameworks. The aim is for a single agent to manage the entire trip, coordinating tickets, accommodation and activities. <\/p>\n Interaction with AI will diversify: immersive screens, in-flight voice commands or intelligent mirrors in the hotel room. Interfaces will become natural and integrated into the physical environment. <\/p>\n Regulators will begin to frame agentic AI, particularly in terms of pricing transparency, data protection and liability in the event of error. Companies will have to adopt governance frameworks andresponsible AI<\/strong> principles. <\/p>\n The 2026 playbook for travel companies offers :<\/p>\n make their inventories accessible via APIs and standard data schemas;<\/p>\n<\/li>\n expose their loyalty programs and personalization data to agents ;<\/p>\n<\/li>\n produce conversational content and build knowledge graphs to answer questions in natural language;<\/p>\n<\/li>\n move to API-based attribution models, as booking paths will be made within agents;<\/p>\n<\/li>\n experiment with their own agents or co-create assistants to keep control of customer relations.<\/p>\n<\/li>\n<\/ul>\n Agentic booking is no longer a theoretical concept: by 2025, it has already been deployed for restaurant, event ticket and vehicle reservations, and projects targeting flights and hotels are underway. This evolution is redefining the relationship between travelers, platforms and suppliers. It promises smoother, more personalized experiences, but raises questions of trust, governance and the redistribution of value. To prepare, companies need to : <\/p>\n understand the potential and limitations of agents ;<\/p>\n<\/li>\n enhance the quality and interoperability of their data ;<\/p>\n<\/li>\n adopt responsible AI practices (explicability, human supervision, compliance);<\/p>\n<\/li>\n rethinking customer loyalty and experience through partnerships with AI platforms.<\/p>\n<\/li>\n<\/ul>\n By adopting a proactive and thoughtful approach, travel professionals can turn the challenge of agentic booking into an opportunity and offer travelers a new way of discovering the world.<\/p>\n","protected":false},"excerpt":{"rendered":" The rise of “agentic booking”: when AI takes over travel bookings Artificial intelligence is no longer content to simply answer our questions: it is becoming a player in everyday tasks. In the travel industry, this evolution is reflected in the emergence of “agentic booking”, i.e. intelligent agents capable of planning and booking stays from end […]<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[78],"tags":[],"class_list":["post-4853","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence"],"acf":[],"yoast_head":"\n1. What is agentic AI?<\/h2>\n
Difference with generative AI<\/h3>\n
2. The emergence of the agentic booking concept<\/h2>\n
\n
An upheaval in the online agency (OTA) model<\/h3>\n
3. Innovations in 2025: concrete examples<\/h2>\n
3.1 Booking.com: Smart Messenger and Auto-Reply<\/h3>\n
3.2 AI Trip Support and AI Voice Support<\/h3>\n
3.3 AI Rental Helper and Flight Search Summaries<\/h3>\n
3.4 Google AI Mode: from planning to booking<\/h3>\n
3.5 Start-ups and competitors : Perplexity, Hopper, SkyLink and others<\/h3>\n
4. Use cases and benefits of agentic booking<\/h2>\n
\n
5. Adoption statistics and market status<\/h2>\n
Gradual adoption<\/h3>\n
Observed benefits<\/h3>\n
Consumer reservations<\/h3>\n
6. Impact on travel professionals<\/h2>\n
6.1 OTAs and reservation platforms<\/h3>\n
\n
6.2 Hoteliers and airlines<\/h3>\n
\n
6.3 Traditional travel consultants and agencies<\/h3>\n
\n
7. Best practices and pitfalls to avoid during implementation<\/h2>\n
7.1 What to do<\/h3>\n
\n
7.2 What not to do<\/h3>\n
\n
8. Ethical issues and challenges<\/h2>\n
8.1 Transparency and bias<\/h3>\n
8.2 Data security and privacy<\/h3>\n
8.3 Social acceptability<\/h3>\n
8.4 Data fragmentation<\/h3>\n
9. Future prospects<\/h2>\n
9.1 From reactive assistance to anticipation<\/h3>\n
9.2 Interconnected ecosystems<\/h3>\n
9.3 Multi-modal interfaces and spatial computing<\/h3>\n
9.4 Responsible adoption and regulation<\/h3>\n
9.5 Opening up data and building partnerships<\/h3>\n
\n
10. Conclusion<\/h2>\n
\n