Agentic artificial intelligence (AI) is reshaping the front end of travel. 

Unassisted, travelers often struggle with choice overload, compare too few dimensions, or fixate on headline price. AI agents, by contrast, can normalize trade-offs across fares, ancillaries, and constraints so evaluation stays focused on total value.

These differences fundamentally change how travel options are curated and selected. When discovery and decisions are delegated to machines, transparent, dynamically bundled offers are likely to outperform static, price-led merchandising—especially for complex or high-value trips.

The evolution seems inevitable. In the next wave of agentic AI, booking could take place with minimal or no “human clicks.”

Is the industry ready for this agentic travel future? To find out, we ran two practical tests: one focused on flight discovery and one on flight booking.

Flight discovery test results

For the flight discovery test, we selected three large European full-service carriers (FSCs) and their 10 most relevant markets (aggregated at the country-pair level). Then we prompted three major large language models (LLMs) to book a flight from country or city A to country or city B, using 60 nonbranded prompts.

This test measured two things: which sources LLMs used to search schedules and prices; and which airlines were presented to the user.

In this test, airline websites were accessed directly only about 5% of the time (see Figure 1).

Figure 1

Subsequently, we reviewed how often airlines appeared (on their 10 major passenger flows) in answers produced by the models. All three European FSCs consistently showed up in the top three results when queries involved routes touching their home markets. However, their share of mentions declined noticeably when queries focused on transit flows (see Figure 2).

Figure 2

Moreover, LLMs frequently directed users to an OTA rather than an FSC website—even when an FSC was a “first choice” option.

The implication is clear: LLMs gravitate toward the source with the easiest downstream interaction, and OTAs currently produce cleaner, more structured, and more agent-readable data.

For airlines, this creates a generative engine optimization challenge. Airlines need to rethink how offers are surfaced, structured, and interpreted by LLMs rather than humans. Today, OTAs are clearly winning the discovery step.

Booking test results

Next, we attempted to book travel with several major European and North American airlines, including FSCs and low-cost carriers (LCCs), as well as two major OTAs. We used three tools: OTA action tools/plug-ins, browser‑automation agents, and prompt‑generated airline links.

A booking was considered successful if a tool reached the payment page of an airline or OTA website. Across our attempts, no single tool was able to do so reliably—although OTAs were more successful (see Figure 3).

Figure 3

Some browser agents reached deep into the flow, but only slowly and erratically, and user intervention was frequently required. Browser agents regularly stalled on basic user interface (UI) components such as date pickers or fare selectors, looping for 10 to 20 minutes before abandoning the attempt and redirecting to an OTA or metasearch site. CAPTCHAs, two-factor authentication, identity challenges, ancillary selection, and session time-outs frequently broke the autonomous chain.

These results are unsurprising. These websites were designed for humans, with cybersecurity measures to protect against traditional incursions—not for agentic interactions.

The autonomous booking test surfaced clear winners. OTAs dominated AI-agent-mediated transactions, LCCs benefited from simplicity and price transparency, and FSC performance was highly variable.

To compete in this space, airlines need to quickly adapt their commercial and technical foundations. Otherwise, they risk structural disadvantages as agentic infrastructure matures. For example:

• OTA action tools/plug-ins: These function primarily as search widgets that return lists of flights but offer little support for booking.
• Browser‑automation agents: Autonomous browsing agents could navigate airline and OTA websites but were slow, inconsistent, and error‑prone—often taking 5 to 30 minutes before getting stuck on trivial steps or redirecting to intermediaries.
• Prompt‑generated airline links: LLMs often claimed they could generate links with traveler details prefilled, but consistently failed to do so. At best, they produced static search links.

Where do airlines go from here?

AI agents favor suppliers with structured, machine-readable offers. Intermediaries have moved fastest, building agent-ready data and transaction layers. However, most airlines still operate digital stacks optimized for humans—leaving their offers only partially visible to AI agents and pushing high-intent demand into fragile scraping or manual servicing paths.

The implication is straightforward: To compete in an AI-agent-mediated world, airlines must start optimizing infrastructure rather than interfaces.

Airlines should urgently focus on five priorities:

1. Optimize data for machines, not humans.
   Structured content, stable application programming interfaces, and consistent identifiers matter more than visual user experience. If agents cannot reliably parse and compare offers, they will route demand elsewhere.
2. Control the transaction layer.
   Decide which elements of pricing, payment, and servicing should remain proprietary vs. exposed to avoid being reduced to a commoditized fulfillment pipe.
3. Make agents care where booking happens.
   Differentiated inventory, bundles, or benefits must appeal to AI agents—not just humans—to justify a channel preference.
4. Design for trust, not just access.
   Agents reward transparency, consistency, and fulfillment reliability. Progressive autonomy requires clear rules and predictable outcomes.
5. Choose partners deliberately.
   Early alliances with AI platforms and intermediaries will shape future standards. Airlines that join late risk accepting unfavorable economics and losing control.

At the moment, intermediaries have a clear head start. Airlines can soften that shift or reverse trajectory by acting on the priorities listed here.