Airports using AI aircraft turnarounds are saving millions and cutting departure delays by 25%
November 4, 2025
Airports and airlines adopting artificial intelligence to manage aircraft turnarounds are realising major operational and financial gains, according to Assaia’s 2025 Turnaround Report.
The study examined more than 450,000 AI-enabled turnarounds at 15 airports across Europe and North America between April 2024 and March 2025, providing one of the clearest pictures yet of how data-driven ground handling is reshaping airside performance.
The results are striking. Across the sample group, median departure delays were cut by 25%, from four minutes to three. Average delays stabilised at 11 minutes despite record traffic levels, while overall gate efficiency improved by 5%, allowing roughly one additional flight per day for every 20 stands.
Narrowbody aircraft showed the sharpest improvement, turning in 78 minutes on average and completing 4.75 turns per stand each day.
Medium-sized airports gained the most from AI oversight, reducing stand downtime by 11 minutes, effectively freeing 44 extra minutes of gate capacity daily.
“I’m proud that our technology has helped partners like Alaska Airlines, Berlin Brandenburg Airport, and
JFKIAT unlock tangible gains in efficiency and service quality,” said Christiaan Hen, CEO of Assaia. “But we’re only just getting started.”
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Money on the table with AI-powered aircraft turnarounds
The financial implications are significant: in Europe, Assaia-enabled airports achieved departure delays six minutes shorter than the regional average, saving nearly $600 per turnaround, or more than $70 million annually for a large hub. In North America, one minute less delay per flight translates into about $100 in savings per turnaround.
Looking ahead, Assaia estimates that if the industry consistently achieved the so-called “perfect turn” — a fully optimised sequence of ground operations — it could unlock up to $900 million in annual benefits for a major airline and between $300 million and $500 million for a large international airport by 2035.
“As global air traffic hits record highs and infrastructure expansion lags behind demand, AI has become essential for increasing capacity and profitability,” said Hen. “It allows the industry to move from reactive operations to predictive, optimised performance — the most scalable lever airports and airlines have today.”
How AI improves turnaround performance in practice
Turnaround operations – the period between landing and taking off again – are a complex choreography involving dozens of subprocesses. According to industry research, ground operations are among the largest contributors to delay after air traffic control impacts.
The International Air Transport Association highlights that while safety remains paramount, digitalisation and innovation in ground support equipment and processes are key to faster turnarounds. Assaia’s case studies show that reducing turnaround time by five minutes at an airport handling 25 million passengers can generate about $11 million in additional annual revenue.
Assaia, a Swiss-based specialist in AI and computer-vision systems for airports, developed the ApronAI platform to bring real-time transparency to the turnaround process. Using cameras positioned around the stand, aerobridge and apron, the software analyses live video and operational data to track every milestone, from chocks on to pushback, and predict the exact moment an aircraft will be ready to depart.
By capturing real-time events via video and sensors, time-stamping actions such as door open, bridge left, cones removed, stand clear, and feeding the data into analytics, the system can identify surface delays before they cascade.
The platform also supports alerts when tasks slip, visual dashboards for ground-handlers and airlines, and integration into collaborative decision-making (A-CDM) workflows. At Munich Airport, for example, the system is tasked with predicting milestone delays and helping operations teams intervene proactively.
By reducing cycle times and improving stand utilisation, airports can turn constrained infrastructure into additional capacity. If each stand is freed up for a few additional minutes, that may open the door to an extra flight per day per 20 stands. In a world where runway and gate capacity expansion is slow and costly, this represents a major lever.
The business case for AI aircraft turnarounds
With global air traffic rising but airport infrastructure upgrade lagging, the ability to extract more value from existing assets is critical. Assaia’s forecast that by 2035 a large airline might realise $900 million in annual gains and a major hub $300-500 million underscores the scale of opportunity.
The business case rests on three pillars: cost avoidance (less delay cost, fewer disruption knock-on effects), revenue enhancement (more flights, better asset use), and passenger experience (higher on-time performance, loyalty).
In tight capacity environments, shorter turnarounds improve gate and aircraft utilisation, which drives top-line revenue; airlines gain more departures per aircraft; airports gain more flights per gate.
In the competitive low-cost carrier space, where every minute contributes to aircraft use and unit cost, turnaround efficiency is a strategic differentiator. For legacy carriers and large hubs facing congestion, AI-driven turnarounds may be one of the few remaining ways to increase throughput without new infrastructure.
In short, smarter ground operations mean more flights, lower costs and higher revenue — all from existing assets.
