The OTAs (online travel agencies) built their empires by aggregating travel options and making it easy to compare and book. By owning the demand funnel and investing billions in search marketing, they achieved vertical dominance, especially when regulators scrutinised Google’s monopoly. That model is about to be disrupted. Generative and agentic AI systems now interpret intent, anticipate needs, and complete actions. Instead of keying dates and sorting through hundreds of listings, travellers can tell an AI assistant, “Plan me a three‑night beach break next month,” and receive a personalised, end‑to‑end itinerary and booking. This shift threatens to strip OTAs of discovery, loyalty and visibility and will reshape how travel brands connect with customers.
What is agentic booking?
Agentic AI refers to systems that not only generate content or answers but take actions on behalf of the user, such as booking hotels, flights or activities. In an experiment, ChatGPT’s Agent Mode planned a Paris trip by searching Expedia, comparing options and finalising the booking without the user ever visiting Expedia’s site. For consumers, this means less time on comparison sites and more personalised itineraries; for OTAs, it means losing the ability to influence travellers through lists, filters and upsells.
How agentic AI shifts the value exchange
- Choice vs. certainty – OTAs win by offering choice, but AI agents thrive by narrowing choices to a small set of recommendations. When a generative engine surfaces only two hotel options, users don’t browse dozens of OTA results. Shorter dwell time can be misread by search algorithms as lower relevance, further reducing OTA visibility.
- Loyalty moves from platform to AI – Expedia Rewards, Booking Genius and similar programmes drive retention. But travellers may become loyal to their AI assistant rather than the OTA. If loyalty points and preferences aren’t exposed via API to the agent, the programme becomes invisible.
- Search becomes conversation – In the new search layer, queries sound like goals (“find me a boutique hotel with a rooftop pool near Barcelona beach”) rather than keywords. Generative AI interprets intent, predicts needs, and manages bookings, dining reservations and tickets. OTAs no longer compete for a top ranking on a results page but for inclusion in an AI’s short list.
Market responses
- Integration over confrontation – Expedia’s collaboration with OpenAI and Booking’s Kayak.ai test conversational search. OTAs are embedding AI to protect their customer base and experimenting with co‑developed agents. The success of these partnerships hinges on access to inventory and user data; without it, general AI platforms will fill the void.
- AI‑ready data – Generative agents need structured data to answer questions and book. OTAs and suppliers must invest in schema markup, robust APIs and clean data feeds so that AI can read and action their inventory.
- Agentic analytics – Because journeys may start and end inside an AI interface, traditional web‑based analytics will not capture the customer path. Tracking needs to shift to API‑based attribution models and partnerships with AI platforms to access conversion reporting.
- Re‑definition of “direct” – In a world where an AI books for the traveller, the system owns the relationship. OTAs risk being relegated to invisible fulfilment pipelines. They must compete on intelligence, data quality and frictionless integration to remain part of the conversation.
Opportunities for travel brands and hoteliers
Hotels, airlines and destination management companies hold the inventory, so they can benefit from this shift if they move quickly. Agentic AI acts like a qualification engine, delivering ready‑to‑convert customers. Brands that surface their inventory to AI agents can capture demand without paying steep OTA commissions and can nurture direct relationships with travellers before, during and after the trip.
Actionable playbook for 2026
1. Make your inventory AI‑accessible
- Standardise data – Implement schema markup (e.g., Hotel, Flight schemas) and maintain real‑time availability/pricing feeds. Structured data enables AI models to parse attributes such as location, amenities and cancellation policies, making your properties candidates for inclusion in recommendations.
- Open APIs – Provide secure booking APIs that allow agents to complete reservations end‑to‑end. Without reliable APIs, AI systems may recommend competitors that offer seamless booking capabilities.
- Maintain rich content – High‑quality images, descriptions and reviews remain vital. AI models use this content to justify recommendations and summarise highlights for users.
2. Expose loyalty and personalisation through partnerships
- Integrate rewards – Work with AI platforms to expose your loyalty programme via API so that points and perks are visible to the agent. When a traveller asks for “hotels where I can use my points,” you want your brand in the shortlist.
- Feed preference data – Share anonymised booking history, guest profiles and contextual data to help AI match travellers with your products. The more the agent knows about your ideal customer, the more relevant its recommendations will be.
3. Invest in conversational content and knowledge graphs
- Answer real questions – Generate content that responds to natural‑language queries (e.g., “Which beachfront resorts in Bali are family‑friendly and close to surfing lessons?”). This increases the likelihood that your information will be pulled into AI overviews and assistants.
- Develop a knowledge graph – Map relationships among destinations, attributes, experiences and customer intents. Knowledge graphs help both your internal AI and external agents understand your brand and cross‑sell opportunities.
4. Prepare for agentic analytics and attribution
- Adopt API‑based tracking – Traditional cookie‑driven analytics will not capture bookings made within AI agents. Work with AI platforms and booking engines to implement API hooks that return conversion data and post‑booking actions.
- Model lifetime value – Because agentic journeys compress browsing and booking, focus on lifetime value rather than one‑off transactions. Use first‑party data to model repeat behaviour and cross‑product uptake.
5. Experiment with your own agents
- White‑label or build – Consider launching your own travel concierge powered by generative AI. For example, airlines could create a trip‑planning assistant that offers flight + hotel packages, seat upgrades and ancillary services.
- Co‑create – Partner with reputable AI platforms to build co‑branded assistants embedded on your site or in messaging channels. This helps retain control over the customer relationship while leveraging best‑in‑class AI capabilities.
Key take‑aways for CMOs
- Agentic AI is reshaping discovery and booking – It compresses the funnel from inspiration to transaction, bypassing many traditional OTA touchpoints.
- Data is your competitive moat – Structured inventory, clean APIs and contextual content determine whether you appear in generative recommendations.
- Loyalty and personalisation must be portable – Ensure your rewards programme and customer insights travel with your guests via AI agents.
- Direct relationships are up for grabs – In the agentic era, the “direct” channel may be owned by the assistant. Brands must build alliances with AI providers and invest in their own conversational experiences to stay close to the customer.
- Experiment now – The next two years will set new leaders. Those who test agentic integrations early, measure outcomes and refine strategies will own the future.
Conclusion
Agentic AI is not a distant future—it is already booking hotel rooms and recommending flights. While OTAs may still dominate today’s search results, the shift from lists to conversations is accelerating. CMOs who prepare their data, integrate loyalty programmes, invest in conversational content and forge partnerships with AI providers will thrive. Those who cling to the old model risk becoming invisible. The playbook above offers a roadmap to keep your brand found in the age of AI‑powered travel.
