The Travel Distribution Funnel Is Fragmenting Across AI
At Skift Global Forum, travel tech leaders discuss how AI agents, direct traffic, and answer-engine optimization are reshaping bookings.
Stock photo for illustration only, not from the actual event
- Travel executives note that AI is fracturing and breaking apart the traditional travel distribution funnel.
- Booking Holdings reports LLM referral traffic drives under 1 percent of room nights while mid-60 percent come direct.
- Expedia highlights answer-engine optimization as its fastest-growing channel, partnering with Google and OpenAI.
- Uber runs hotel bookings at break-even because it no longer depends on Google for traffic acquisition.
Discussions at the recent Skift Global Forum highlighted how the conventional framework of the travel industry is splitting into distinct segments. Artificial intelligence is actively fragmenting travel distribution across multiple starting points, rather than simply swapping Google out for a brand-new gatekeeper. Following conversations with Uber CEO Dara Khosrowshahi, Sierra CEO Bret Taylor, Booking Holdings CEO Glenn Fogel, Expedia Group CEO Ariane Gorin, and Airbnb CEO Brian Chesky, it became evident that determining who actually owns the customer is far more complex than a neat diagram suggests.
Throughout the online travel era, a traveler typically demonstrated intent by typing into a search box. Google often captured this intent before travel companies did, leaving airlines, hotels, and online travel agencies to compete for clicks and handle downstream bookings. Although this journey was never as streamlined as diagrams depicted, spotting intent early held immense value, prompting travel companies to invest billions to capture that attention.
Stock photo for illustration only, not from the actual event
Ever since ChatGPT emerged, the prevailing promise has been a shift in this sequence. Travelers can now state their desires directly to an assistant instead of repeatedly declaring identical intents across various search engines and booking sites, forcing industry giants to reevaluate their strategies.
Source: Skift
According to Booking Holdings CEO Glenn Fogel, large language model referrals still drive less than 1 percent of room nights, with roughly the mid-60 percent of transactions occurring directly, arguing that trust remains the ultimate scarce asset. Conversely, Airbnb CEO Brian Chesky noted that ChatGPT has functioned as a more efficient version of Google, funneling traffic straight to Airbnb while predicting a future filled with numerous homepages and agents.
The diverging viewpoints among top travel executives illustrate a profound transition in online travel distribution. As companies embrace answer-engine optimization and embed inventory, payments, and servicing directly into third-party interfaces, the traditional boundaries of online travel agencies and metasearch platforms are dissolving. This decentralization means future travel planning may happen across conversational AI surfaces where traditional website funnels no longer serve as the primary gatekeepers.
Expedia Group CEO Ariane Gorin shared that answer-engine optimization represents the company's fastest-growing channel. She explained that Expedia has stepped away from pursuing a single end-to-end agent, opting instead to collaborate with Google, OpenAI, Anthropic, and Meta while embedding its inventory, payment processing, and customer service tools into external product ecosystems.
Meanwhile, Uber CEO Dara Khosrowshahi stated that the majority of traffic for both Uber and Uber Eats arrives directly. This direct reach allows the company to operate hotel bookings at approximately break-even to bolster the Uber One membership ecosystem without relying heavily on Google traffic. Sierra CEO Bret Taylor provided a historical perspective, emphasizing that Google's front-door position never fully converted into travel commerce because the ultimate last mile—genuine inventory, reliable payments, secured reservations, and service recovery—remains the deciding factor for who gets paid.
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