When the passenger experience runs smoothly, an airport can seem like a remarkably well-oiled machine.
Check-in and bag drop are seamless, the wait for security is a matter of moments, lounge entry is secured with biometric recognition, and boarding is swift.
For passengers, it can feel effortless. But that apparent simplicity is the result of a vast and carefully coordinated operation.
Behind the scenes, numerous pieces of a complex jigsaw have to fit into place, all at the right moment.
In reality, airports are tremendously complex operational environments and creating the experiences passengers increasingly expect is a complex task. We believe AI can play a transformative role in that process.
A large, international airport may maintain up to half a million assets, managing thousands of flights and tens of thousands of passengers every day.
Working at this scale requires the airport, airlines, ground handlers, refuelling providers, catering firms, government stakeholders and many more organisations to cooperate.
If we are successful in creating an environment where each can contribute to the success of the greater whole, tremendous benefits can be unlocked.
What limits digital cooperation today?
Today, as many readers will understand, the smooth operation of an airport can quickly become complicated when the systems behind the scenes fail to work together.
Fragmented visibility, limited data sharing, and manual processes can create barriers to cooperation, preventing airports from achieving their full operational potential.
Obstacles to intelligent decision-making include fragmented operational systems, with large airports running hundreds of different operational applications, many of which are unconnected.
Elsewhere, limited data sharing means stakeholders often do not have the tools, governance frameworks, or mindset needed to exchange the information that can provide a common operational view.
Without that shared picture, even the most carefully coordinated operation can be held back by gaps in information.
Finally, legacy protocols and manual processes mean it is still common for data to be exchanged using Type B and Type Y teletype messages – expensive, outdated protocols that date back to the 1960s.
The time is ripe, then, for a new generation of transformative technology to help us address these barriers and create new opportunities to maximize the benefits of cooperation.
Agentic AI in airport operations
Agentic AI has the potential to help, transforming how airports and their stakeholders operate. The technology is remarkably powerful, and we believe it is ready to make a meaningful impact.
When supported by the right data foundation, agentic AI enables airport stakeholders to access the information they need quickly and securely, helping to make decisions with greater speed.
It can also deliver proactive, intelligent, and context-rich recommendations based on a comprehensive operational picture, helping teams make decisions that are not only faster, but better informed.
For airport teams used to working with inaccurate data scattered across disconnected systems, and relying on manual radio calls to verify information, the potential impact of AI is substantial.
Embedding a proactive intelligence layer
For example, imagine a terminal manager being able to ask an AI agent, via a chat session on their mobile, “Why is check-in slow this morning?”
The agent pulls the relevant information from multiple systems across the airport, including the Airport Operational Database (AODB), analyses the data, and identifies a problem with the baggage system. It then explains that six flights are at risk of delay.
This represents a significant improvement on the process we see today, where an analyst needs to run a query to produce a data visualisation, which the airport manager must then interpret.
With AI assistance, we are looking at a dramatically faster route to insight, with information presented in a way that is easy for everyone to understand.
The next step is for the agent to offer proactive insight. What if AI could continuously monitor the operational environment, identify current and emerging bottlenecks, and alert staff to them before they become bigger problems?
What if that alert could go beyond simply describing the issue to recommending the most effective way to resolve it?
This is where the technology stands today and we are working with customers to embed AI agents directly into operational workflows.
Establishing a data foundation
How can we build these opportunities? The value an airport derives from AI will depend directly on the scale, reliability, and quality of the data available. Data readiness is therefore a critical foundation for successful AI projects.
For airports, this starts with bringing together data generated by passenger, operational, and flight-related systems, making it consistent, structured and ready to support a team of AI agents.
This means building the necessary data pipelines, improving data quality, transforming data, and putting effective governance in place.
It is clear that AI agents will become increasingly embedded across airport operations. We see the airport operations centre (APOC) evolving into an environment where coordinated teams of AI agents continuously support day-to-day operations.
Each agent could be responsible for a particular operational area, such as disruption management, baggage journeys, or passenger-flow optimization. They would monitor live conditions, identify emerging issues, and alert the appropriate teams before problems escalate.
As more AI agents come into use, the ability to coordinate and govern them becomes increasingly important.
Take flight disruption as an example. Individual agents could provide insight into aircraft, crew, and gate availability, as well as passengers with connections that need to be managed.
But how do we bring these different inputs together to identify the best solution while considering the wider objectives and regulatory responsibilities of both the airline and airport?
The answer lies in orchestration, supported by clear guardrails grounded in the airport’s rules and business logic.
As a platform provider to our airport and airline customers, this is the role Amadeus aspires to play.
We connect AI agents to the data and business logic embedded in the industry’s underlying systems, giving the intelligence layer the context it needs to tackle even the most complex operational challenges.
Overcoming structural weaknesses
For too long, the aviation industry has worked around fundamental limitations in its technology architecture. Operational systems remain disconnected.
Data does not flow freely between airports and airlines. Decision-making takes time as information is gathered, consolidated, and analysed.
Today, skilled people fill these gaps with manual workarounds, doing what they can within a fragmented operating environment.
But, built on a robust data foundation, agentic AI has the potential to address these limitations.
It is also readily accessible, with AI agents available on smartphones and tablets to answer questions, issue proactive alerts, and deliver intelligent recommendations drawing on the full operational picture.
Adding an intelligence layer enables airport stakeholders to establish a shared view of the situation, uncover insights more quickly, and make better decisions that enhance operational performance.
Agentic AI is opening a new era for airports where they can move from reacting to today’s challenges to anticipating tomorrow’s opportunities – creating more connected operations and better journeys for all.
