This sponsored content was created in collaboration with a Skift partner.
AI has started to move from the edges of travel businesses into core workflows. The challenge now is one of execution, taking systems that perform well in controlled settings and making them dependable inside the complex machinery of booking, servicing, payments, and disruption management.
As AI begins to take a more active role in those workflows, questions of integration, oversight, and accountability become harder to separate from questions of performance. Travel companies will need to prove these tools can work consistently at scale, deliver clear business value, and earn enough trust to shape decisions that directly affect travelers.
At the 2026 Skift Data + AI Summit Europe in London, Benjamin Cany, vice president, product and business strategy, AI Delivery Hub at Amadeus, joined Sania Lali, branded content editor at Skift, to discuss what changes when AI moves from pilots into production, and why the shift from search to action raises the stakes for travel companies.
What It Takes to Put AI Into Production in Travel
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The conversation explored how the industry’s AI priorities are changing as travel companies move beyond testing and begin connecting AI to real booking, servicing, and operational workflows.
Key takeaways included:
- Production requires much more than a capable AI model. Travel companies need to start with a clear customer or business problem, then build around the integration, context, governance, monitoring, and adoption required to make the technology work in a live environment.
- The shift from search to action changes the equation. AI assistants increasingly need to connect with live availability, pricing, loyalty, payment, servicing, and fulfillment systems if they are going to move beyond recommendations and complete real travel tasks.
- Trust becomes more important as AI gets closer to booking. Cany discussed the need for clear oversight, accountability, transparency, and escalation as AI begins to influence or take customer-facing actions.
- The strongest AI use cases are grounded in outcomes. Rather than pursuing AI for its own sake, the focus should be on solving a defined problem inside an existing workflow and creating measurable value for travelers or travel professionals.
- Travel companies should design for production from the beginning. That means starting with a focused challenge, learning from real usage, and putting the foundations for trust, integration, and scale in place early.
The biggest takeaway was that AI in travel is moving into an operational test. As these systems take on a larger role in customer-facing decisions, companies will have to prove that they can make AI work inside the complexity of the existing travel ecosystem. That means stronger integration, clearer oversight, and more focus on measurable outcomes.
Getting that right will decide which AI applications can move beyond experimentation and become part of the machinery of travel.
To find out more about Amadeus, visit amadeus.com/ai
This content was created collaboratively by Amadeus and Skift Studio.