Schafer Newman coauthored this article

Key takeaways:

• AI travel commerce is changing distribution by moving influence upstream, before travelers reach a supplier’s website, app or booking path.
• Travel suppliers can protect offer control by making dynamic merchandising logic accessible to AI on their terms, with clear data and commercial guardrails.
• Travel and hospitality leaders should define their travel distribution strategy before intermediaries shape the transaction layer and capture customer data, economics and relationships.

AI is reshaping how travel decisions are made, not just how products are searched. Discovery, comparison and booking are increasingly collapsing into a single AI-mediated interaction before a traveler reaches a supplier’s website or app. The point of influence is moving upstream, bringing the foundations of travel distribution with it.

For decades, travel brands competed by driving traffic into owned channels and optimizing conversion within them. Many have made real progress as airlines and hotels clawed back direct bookings from online travel agencies (OTA) and other intermediaries. But that model assumes the moment of decision happens inside the brand’s environment. AI is disrupting that assumption by shaping the consideration set itself, determining which options are surfaced, how they are compared and how value is perceived.

In this environment, visibility alone is not the strategic question. The real issues are control and ownership, including whether a supplier’s offer is presented in a way that preserves its value, whether that offer is flattened into a commodity comparison and which player owns the transaction.

Three strategic moves will define the winners:

• Make dynamic merchandising logic accessible to AI on your terms
• Control how offers are described and framed across AI touch points
• Shape the transaction layer before intermediaries do

The real battle in travel is offer control, not visibility

The risk is familiar. When platforms control demand, they capture disproportionate value. In travel, that dynamic played out through global distribution systems (GDS), OTAs and metasearch. AI-enabled tools are emerging as the next layer in that evolution, shaping visibility and preference formation before a traveler reaches a supplier’s channel.

Optimizing for generative and answer engines matters because strong brand awareness does not automatically carry into AI-mediated travel journeys. Suppliers need their content and data structured in ways to help large language models find, understand and accurately represent their offers. Beyond visibility, suppliers must know whether AI agents can compare and recommend those offers in a way that preserves their value or flattens them into a commodity comparison.

Today’s intermediaries simplify travel products to enable comparison, reducing complex offers to schedules and prices. AI can do the opposite. It can interpret nuance, weigh context and present offers with more depth than a traditional comparison grid.

When a traveler shares loyalty status, trip purpose or personal preferences with an AI agent, the supplier can use that context to return a more relevant offer. That might mean an upgrade path based on loyalty tier, a bundled fare matched to the trip profile or a personalized ancillary recommendation. The strategic point is to connect traveler context to supplier-controlled merchandising logic so the offer becomes more relevant, not easier to flatten into a standard comparison.

But this cuts both ways. When suppliers do not provide structured, rich content or cannot dynamically respond to traveler context, AI systems default to whatever data is available. The result is predictable. Complex products get standardized. Premium cabins, loyalty benefits and bundled offers collapse into interchangeable options. Someone else defines how the product is described.

The answer is not to open data to every AI platform. It is to make merchandising intelligence accessible on the supplier’s terms, with clear guardrails around how offers are represented, what context is shared and under what commercial arrangements. The suppliers who get this right will not just appear in AI-mediated journeys. They will shape how their products are understood.

Where travel suppliers still have leverage

To understand where advantage exists, it helps to unpack the emerging architecture of AI-mediated travel.

As Cory Garner, a leading voice in airline distribution strategy, has framed it, an AI travel platform consists of four core components:

• The large language model layer, which powers the conversational interface
• A user memory layer, which captures the traveler’s preferences, history and context
• Travel business logic, including pricing, inventory and merchandising rules
• Transactable content, including real-time availability and fulfillment capability

The first layer is increasingly competitive and interchangeable. The second is owned by the platform. The last two, business logic and transactable content, are controlled by suppliers. They are also the hardest to replicate.

The implication is clear. Supplier leverage sits in the offer intelligence powering the AI experience, including the real-time pricing, inventory and merchandising logic Garner’s last two layers represent.

An AI system can know a traveler’s preferences. Only the supplier can translate that context into a relevant, transactable offer.

When traveler context lives outside the supplier’s ecosystem in an AI agent that remembers preferences across brands, loyalty becomes part of the same offer intelligence problem. Traditional loyalty mechanics lose some of their hold as switching becomes easier, and loyalty shifts from accumulation to relevance through the quality of the offer, the recognition built into it and the supplier’s ability to act on context in the moment. Leaders need to understand how AI is reshaping loyalty as travel decisions move outside the channels they control.

3 moves to protect travel distribution strategy

Suppliers who treat AI-mediated commerce as a data-sharing exercise will get commoditized, just as many did in earlier distribution shifts. The mechanisms are different, but the outcome can look familiar: Someone else controls the customer path, the offer framing and the economics of the transaction. Suppliers who treat the shift as an offer orchestration challenge will be better positioned to define the next era of travel commerce.

But being intentional also means being selective. At the Aviation Festival Americas in June 2026, Glenn Hollister, VP of sales strategy at United Airlines, said, “We’ve got to be super careful not to give away the keys to the kingdom as we figure out how to adapt to and use AI.” Airlines still control proprietary inventory, operational and loyalty data that outside AI systems cannot access unless airlines choose to share it. As Hollister noted, “That data is what creates our ability to shape the way AI plays out in retailing.” Making merchandising intelligence accessible to AI does not mean making it freely available to everyone.

Three strategic moves matter:

1. Make dynamic merchandising logic accessible to AI on your terms. Structured data is table stakes. The real challenge is exposing the offer engine: The real-time decisioning about who gets what bundle, at what price, with what loyalty recognition and in what context. Static content can be scraped, normalized and flattened by anyone. Dynamic merchandising logic cannot. It lives inside the supplier’s systems, changes constantly and requires real-time access to inventory and pricing. If that complexity is not translated into machine-readable form, AI systems will default to simplified comparisons. But translating complexity does not mean giving it away. It means establishing partnerships with AI platforms where access is granted on terms that protect the supplier’s competitive position.
2. Invest in how your offers are described and framed, not just what they contain. A redesigned premium economy cabin or differentiated loyalty experience does not just need to show up when travelers compare options through AI-enabled tools. It needs to be described in a way that captures its value. This is the real meaning of owning the offer: controlling not just the product and price, but the narrative around it. As travelers use AI-enabled tools to compare options, suppliers need to know whether their brands and offers show up accurately and whether their value survives the comparison. Optimizing for generative and answer engines can help, but discoverability is only the first step. The content behind the recommendation still needs to be rich, structured and curated so the full value of the offer comes through, not just the parts easiest to compare.
3. Shape the transaction layer before it is shaped for you. AI platforms are already testing how far they can move from discovery into transaction, and the operating details are still messy. But the incentive is clear. The more of the journey platforms keep inside their own experience, the more influence they have over the sale, the customer relationship and the data created along the way. Suppliers need to define their role in AI-mediated journeys before those choices are made for them.

OTAs are not waiting. If they become the default transaction layer in AI-mediated commerce, suppliers pay intermediary fees, lose access to customer data and cede the relationship, undoing years of direct distribution investment.

The window to prevent that outcome is now. Suppliers should work directly with AI platforms to ensure that when a traveler books through an AI-mediated journey, the supplier, not an intermediary, processes the transaction, owns the customer relationship and captures the data. The same direct distribution strategies airlines have spent years and billions building need to extend into the AI channel before someone else fills the gap.

Emerging standards like the Model Context Protocol (MCP) matter as plumbing because they standardize how AI systems connect to supplier content. But MCP is agnostic to what it carries. The strategic lever is not the protocol. It is the quality and depth of what travels through it.

Where suppliers should start before AI sets the default booking path

These shifts are already underway. Suppliers should start by answering three practical questions:

• How do their products appear in AI-driven journeys today?
• Where is their merchandising intelligence still inaccessible to AI systems?
• What transaction principles need to be defined before external platforms determine how bookings flow?

What suppliers should avoid as AI reshapes travel

The common pitfalls are practical: treating AI as a marketing problem rather than a commercial one. This is a distribution shift, not a campaign. Other mistakes include confusing a branded AI experience with a distribution strategy, opening data without commercial guardrails and underestimating the complexity of travel commerce. A chatbot is not a distribution strategy. The GDS era shows what happens when distribution access is scaled without sufficient control over pricing, content and commercial terms—the economics and leverage gradually shift toward intermediaries. Suppliers who understand travel commerce complexity, and can translate it into machine-readable intelligence, have more leverage than they think.

AI is becoming the decision-shaping layer in travel. Suppliers hold an irreplaceable piece of the puzzle in the offer itself and the real-time intelligence behind it. Suppliers who make that intelligence indispensable to AI platforms, wherever those platforms live, are best positioned to capture the advantage. Those who simply feed data and hope for the best will again find themselves competing on price in someone else’s ecosystem.