When AI Becomes the Travel Agent

How AI assistants are moving beyond search and into decision-making

The interface is changing, not the traveler

Travelers still follow the same journey they always have: discover, evaluate, and book. What has changed is the interface through which those decisions are made.

Physical travel agents gave way to online travel agencies. OTAs then built a highly profitable relationship with search engines. Now, both search and OTAs are being challenged by AI assistants.

For the first time, a single interface may accompany travelers throughout the entire journey: from discovery, to consideration, to transaction. Unlike previous interfaces, it is conversational and no longer tied to a website, an app, or even a screen.

For hotels, this represents both a risk and an opportunity. The question is no longer whether AI will participate in the travel funnel. It is how much of the funnel it will eventually own.

Discovery is being compressed

AI assistants have dramatically reduced the effort required to discover travel options.

What once required multiple searches, websites, reviews, and comparisons can now begin inside a single conversation. Travelers can explore destinations, compare neighborhoods, and build shortlists in minutes.

This does not mean traditional search disappears overnight. Most travelers still turn to search engines, OTAs, or hotel websites when making serious decisions.

But that is precisely the point. AI assistants have already proven they can handle discovery. If they gain access to structured hotel data, availability, rates, policies, and booking capabilities, travelers will have fewer reasons to leave the conversation.

And once discovery is compressed, the next logical step is consideration.

The economics of discovery are changing, too

For more than two decades, discovery was not simply a stage in the travel funnel. It was an entire economy.

Search engines, OTAs, metasearch platforms, and hotel brands invested heavily in visibility because discovery generated attention and attention generated revenue.

AI assistants are beginning to challenge that model. As travelers increasingly discover destinations and hotels through conversational interfaces, some traffic historically generated during discovery may never reach traditional search engines or websites.

Yet today’s AI funnel remains incomplete. Many travelers discover through AI but still return elsewhere to compare options, validate information, or make a booking decision.

Discovery is increasingly occurring within AI assistants, while consideration still largely occurs elsewhere. That is about to change.

Building the consideration layer

Discovery and consideration are often treated as part of the same journey. In reality, they are very different problems. Discovery can tolerate approximations. Travelers looking for inspiration do not expect perfect answers.

Consideration is very different from discovery. This is where travelers compare hotels, evaluate trade-offs, and make decisions. They want exact information about cancellation policies, room categories, loyalty benefits, availability, and pricing. Consideration depends on accurate, structured, and up-to-date information.

Historically, travelers found that information on hotel websites, OTAs, and review platforms. AI assistants could summarize it, but not reliably access it directly from the source.

That is beginning to change, and the solution may be a new piece in the hotel stack: AI connectors. They are tools and emerging standards that connect assistants directly to supplier systems, enabling them to retrieve information, answer questions, and eventually perform actions.

OpenAI, Anthropic, and Google are pursuing different approaches, but the objective is the same: helping travelers make decisions without leaving the conversation.

Another important trend is that assistants are increasingly moving towards automatic discovery of tools and connectors. Expecting users to manually find, install, and activate thousands of travel-related integrations is unlikely to scale. Instead, platforms are experimenting with ways for assistants to discover and invoke relevant capabilities when needed.

Different approaches are emerging, but the direction is similar: reducing friction between the traveler’s question and the supplier’s data or services.

If assistants succeed in solving consideration, they may become the first interface capable of accompanying travelers throughout the entire funnel up to the transaction stage. Agentic booking is the final step.

Remember that travel agents are not valuable because they list options and redirect customers elsewhere. They are valuable because they help a traveler decide and ultimately facilitate the reservation. AI travel agents will emerge soon, and the question will be whether travelers will feel comfortable using them.

From visibility to representation

For most of the digital era, the challenge was visibility. If a hotel appeared in search results, the user clicked through to a website where the hotel controlled the presentation, comparison process, and transaction.

AI assistants introduce a different dynamic. Visibility still matters a lot. Hotels that are never mentioned cannot be chosen. But visibility alone is no longer enough. Hotels also need to be represented.

A traditional website is designed for humans. AI assistants need information they can understand, compare, and act upon programmatically. Room attributes, policies, amenities, rates, availability, and booking capabilities increasingly need to exist in structured formats.

Through connectors, APIs, and standards such as MCP, suppliers are beginning to expose not only content but also agentic capabilities directly to AI systems.

If consideration is solved inside AI assistants, we may be witnessing one of the biggest shifts in digital distribution since the arrival of search itself.

This does not mean hotel websites disappear. But their role may change. They may no longer be the default place where every traveler compares, asks questions, and resolves uncertainty. Part of that process may move into the assistant itself.

What is still missing

Much of the technology required to support AI-driven travel experiences is already emerging. Assistants are improving at discovery. Structured data is improving consideration. Transactional and agentic capabilities are emerging.

What remains unclear is the economic model that will sustain this ecosystem. Search succeeded not only because it offered a better interface, but also because it created a marketplace that aligned users, suppliers, and platforms.

The AI ecosystem has not reached that stage yet. This challenge goes beyond advertising. It also extends to representation. How will visibility be monetized? How will suppliers participate in recommendation and representation? A sustainable economic model will eventually emerge. Technology is being built, but the marketplace is still being designed.

The adoption gap

Even if the technology and the economic model emerge, adoption will not be immediate or uniform.

Travel is a high-stakes purchase. Travelers may use AI assistants for inspiration, shortlisting, and comparison long before they fully trust them to complete a booking. Many will still want to validate photos, reviews, policies, and prices before committing. For many travelers, planning is part of the experience.

There is also an unresolved question of responsibility. When a reservation fails, a flight is canceled, or a traveler needs support during the trip, who owns the problem? Until that is clear, many users will remain cautious about delegating the entire journey to an assistant.

Hotels will face their own friction. Many still operate with fragmented systems, inconsistent data, and manual processes. For them, AI distribution will not simply be another marketing channel. It will require operational readiness.

This does not change the direction of travel. But it does mean the transition will be uneven. Some use cases, segments, and hotels will move faster than others.

What hotels should do now?

The greatest mistake hotels can make is waiting for certainty. And, unfortunately, many are in that position. It is true that no one knows which standards, platforms, or business models will dominate. But the capabilities required to participate are already becoming clear.

Hotels need to centralize their knowledge, structure it so AI systems can consume it at scale, and expose operational capabilities as machine-accessible tools.

Availability checks, quotations, reservations, cancellations, modifications, loyalty validation, and guest services increasingly need to be accessible programmatically. Hotels have to move all their core competencies to agentic capabilities.

Hotels should also think beyond direct integrations. Much as online distribution evolved through aggregators and technology platforms, AI distribution is likely to develop similar layers.

This may not look like an urgent revenue project today. For many hotels, proving short-term ROI will be difficult. But that is exactly why it should be treated as strategic infrastructure rather than campaign investment.

Most hotels built websites, booking engines, SEO capabilities, and connectivity because the internet changed the distribution landscape. Many reacted late, giving OTAs room to grow and strengthen their position. AI distribution may follow the same pattern, and hotels should not give OTAs the same advantage again.

Conclusion

Travelers will continue to discover, evaluate, and book. The funnel itself is not changing. What is changing is the interface through which those decisions happen.

Discovery is already moving into AI assistants. The consideration layer is now being built, and that may trigger transactions to eventually follow.

The question is no longer whether AI will influence the funnel. It is whether they will be ready to participate in the decisions that happen inside it. After all, isn’t that what travel agents have always done?