Airports are becoming increasingly smart, connected and data-driven, with AI and advanced decision-support tools reshaping how operations are managed across the ecosystem. These developments were explored during the SESAR Walking Tour on Airport operations – the intelligent airport at Airspace World 2026, guided by Ramon Raposo, SESAR Deployment Manager. Through a series of demonstrations and validation results, participants discovered how innovation is improving punctuality, optimising capacity and enhancing the efficiency of airport operations from surface movements to network coordination.

Smarter turnaround and surface operations through automation

A key operational challenge at airports is how to improve punctuality and efficiency while managing increasingly complex ground movements. At the ENAC/DSNA stand, George Mykoniatis, ENAC, presented the ASTAIR project, which addresses this challenge by introducing automated guidance for aircraft and towing vehicles from pushback to runway line-up, and from runway vacated to gate arrival.

The solution combines A-CDM and A-SMGCS environments with AI-based trajectory prediction, regularly forecasting and deconflicting vehicle movements over a 20-minute horizon. Clearances are transmitted electronically to vehicles, supporting more precise and coordinated surface operations. The demonstration of human–automation AI teaming HMIs illustrated how supervisors can manage operational events and oversee automated processes in real time, improving safety and reducing delays on the airport surface.

Network-wide intelligence and airport collaboration

Beyond individual airport operations, another challenge lies in improving coordination across the wider airport network. At the Indra stand, Juan Francisco García López, Indra, presented the FASTNet project, focusing on how data-driven collaboration between airports can improve overall network performance.

The demonstrations highlighted two complementary solutions. The first showed how airport-to-airport coordination can help reduce air traffic flow capacity management (ATFCM) regulations and delay by improving operational predictability across connected airports. The second demonstrated how AI supports strategic and pre-tactical decision-making by consolidating and validating operational data, while also generating predictions based on stakeholder requirements. Together, these capabilities illustrate how shared intelligence can improve punctuality and optimise capacity at network level.

AI-powered airport decision support and situational awareness

As airports become more automated, a further challenge is ensuring that AI systems can effectively support operational decision-making in real time. At the Indra stand, Jorge Mínguez and Juan Francisco García López presented the JARVIS project, showcasing digital assistants designed for airport operations, air traffic control and flight deck support.

The demonstrations included recorded validation exercises showing AI detection of operational events such as taxiway incursions, foreign object debris (FOD) and wildlife hazards. These events were analysed in real time, with AI-generated alerts transmitted to both controllers and airport operations centres. Additional demonstrations showed AI applied to turnaround operations, highlighting its potential to predict passenger flows, detect anomalies and support mitigation actions. These results confirm the potential of Human–AI teaming in reducing workload, improving situational awareness and supporting more proactive airport operations, while also contributing to ongoing work on certification and explainability with EASA.

AI support for arrival sequencing and terminal operations

Optimising arrival flows remains a critical factor for airport efficiency, particularly in high-density terminal areas. At the INECO stand, Rita Bañón, INECO, and Ian Crook, ISA, presented the ORCI project, which uses AI-based decision support to improve arrival aircraft spacing and sequencing.

Based on historical radar data and real-time vectoring inputs, the system predicts spacing between consecutive arrivals with high accuracy, achieving a mean absolute error of around 0.45 NM. The demonstration allowed participants to interact directly with the platform, simulating controller decision-making in realistic TMA scenarios, such as Barcelona and Lisbon.

The hands-on experience showed how ORCI can support controllers in managing arrivals more efficiently, increasing runway throughput while maintaining safety and operational robustness in complex traffic conditions.

Integrated airport data and collaborative operations

Further improving airport efficiency requires better integration of operational data across stakeholders. At the ANS CR stand, Martin Kacur, Prague Airport, presented the BEACON deployment project, and the tools enabling real-time airport collaboration, improved data sharing, and integration with the broader air traffic management network.

Concluding at the ENAV stand, Marco Pellegrino and Fabrizio Tartarino, Aeroporti di Roma,  presented the EXOPAN project, which focuses on the deployment of an extended airport operations plan to support more data-driven and predictive airport management. Together, both deployment projects highlighted how closer airport–network collaboration, combined with improved use of operational data and forecasting, is central to delivering more efficient, resilient and coordinated airport operations across Europe.

Read more

Read about capacity and demand planning in the European ATM Master Plan

More about the 2026 SESAR Walking Tours