Key Takeaways

- Travelers are open to using AI for inspiration and planning, but booking and support require a higher level of trust.

- Travel AI needs more than model intelligence: reliable services, transparent handoffs, recovery when plans change, and clear accountability.

- Existing service providers can give AI access to real-world delivery experience, but new AI platforms still have to earn trust through outcomes.

AI can compare destinations, suggest hotels, and organize a multi-city itinerary in seconds. These capabilities make travel planning faster and easier.

But a plan is not yet a journey.

Once a traveler needs to pay, confirm that a service is available, change a booking, or recover from a disruption, the standard changes. A useful answer is no longer enough. The service also has to work — and support must be available when it does not.

That is where travel AI meets its trust gap.

Travelers welcome AI for planning, but hesitate at booking

An Expedia Group study conducted by YouGov surveyed more than 5,700 adults across the United States, United Kingdom, and India in March 2026. It found that 53% were comfortable letting AI suggest travel options, while 40% used or would use AI to help build itineraries.

At the point of booking, however, behavior changed. Sixty-eight percent preferred to book through a trusted travel brand rather than an AI chatbot or agent, even when AI booking was available. Two-thirds said they would not trust an AI assistant to purchase or book something on their behalf.

This does not mean travelers are rejecting AI. It means they distinguish between low-risk assistance and high-consequence execution.

An itinerary can be regenerated. A payment error, unavailable hotel, missed transfer, or poorly handled cancellation has a real cost. As AI moves closer to these moments, trust becomes part of the product — not a layer that can be added after the technology is built.

Travel trust is a delivery system

Trust in travel is often described as a brand attribute. In practice, it is produced by a chain of operating conditions.

Reliable supply. The hotel, transfer, activity, or local service being recommended must exist, be available, and be capable of delivering what was promised.

Transparent handoffs. Travelers need to understand when they are interacting with an AI platform, a booking provider, or the company that will deliver the service. The more complex the journey, the more important those boundaries become.

Recovery when plans change. Flights are delayed. Meetings run long. Weather changes. A service becomes unavailable. A system becomes trustworthy when it can help the traveler understand what changed and find a workable next step.

Clear accountability. When something goes wrong, the traveler needs more than another generated response. They need a party that can access the relevant information, communicate clearly, and help resolve the issue.

The hardest part of travel AI may therefore be less about generating a better itinerary and more about connecting intelligence to a service system that can deliver and recover in the real world.

The industry is already testing that broader model. In its Q1 2026 Management Review, Amadeus described testing an agentic AI solution for airline call centers that could support multilingual conversations, change bookings, review alternatives, complete payments, and update an order. The example shows how much infrastructure sits between a conversation and dependable execution.

Offline service providers are part of the opportunity

AI innovation is often framed as removing existing intermediaries. Travel may require a different model.

Hotels, transportation providers, local activity operators, and concierge services already know how to deliver parts of a journey. Many also have existing customers, practical operating knowledge, and service relationships built through repeated delivery. A model cannot create those capabilities on its own.

AI can still add value by interpreting traveler intent, organizing a realistic plan, and helping users navigate complex choices. But the final outcome depends on the organizations and people delivering the service.

The opportunity is therefore not simply to place AI on one side and established providers on the other. It is to explore how digital intelligence and real-world delivery capabilities can work together.

For new AI travel platforms, that distinction matters. A capable model does not make a new brand trusted overnight, and trust cannot be automatically transferred from experience in another business. It has to be earned in the travel context through transparent connections, reliable service, and repeated outcomes.

From travel planning to AI for Service

This is one reason Guardforce AI is exploring a travel AI direction that connects digital understanding and planning with existing offline service resources.

Within Guardforce AI's broader transition toward AI-driven solutions, DVGO serves as a travel use case for exploring that connection. The objective is not to treat itinerary generation as the finish line or assume that AI should replace the full service chain. It is to examine how AI can understand traveler intent, organize a workable plan, and connect that plan to services capable of delivering in the real world.

This direction still has to be built and validated. Connecting services does not by itself prove that trust has been achieved. But it establishes a more realistic standard for useful travel AI.

The next travel AI advantage will begin after the answer is generated: when a plan connects to reliable service, responsibility is clear, and support remains available when reality changes.

Travel AI will not replace trust. It will have to earn it — one reliable connection and one real-world outcome at a time.

Data Sources

- Expedia Group, Expedia Group Reveals “The AI Trust Gap”: Travelers Embrace AI for Planning but Rely on Trusted Brands to Book, April 14, 2026:

- Amadeus IT Group, Q1 2026 Management Review, May 8, 2026, pp. 5–8: