The power of AI during times of airline disruption
By Phil Cole, Civil Aviation Business Manager, Aerogility.
From strikes and airspace congestion to war and emerging technical issues, ‘airline disruption’ was a common theme over the summer months, negatively impacting passenger experiences and airline reputations.
As a result, it’s never been more important to be able to plan for uncertainty and respond with confidence when confronted with the unexpected.
It’s here that AI technology comes into play. Sophisticated model-based solutions allow airlines to simulate different scenarios, evaluate the impact of disruptive events and develop robust contingency plans accordingly. Here, we explore how that looks in practice.
The power of predictive forecasting
With airlines currently required to respond to the unexpected, model-based AI has a crucial role to play.
With these AI solutions in place, users can anticipate and prepare for the unexpected by asking the system hypothetical questions.
Airlines can work out the likely impact of certain teams going on strike, or specific airports suffering significant delays, for example.
During times of uncertainty, it’s also important that airlines gain complete transparency when seeking to understand the effect of future disruption using these AI solutions.
Importantly, Aerogility’s model-based approach means forecasts are generated from real-world models of a whole operation — an enterprise digital twin — which ensure insights gained from the forecasts are explicable, transparent and trustworthy.
Aerogility uses model-based AI to create detailed simulations and offers airlines confidence in their decision making during even the most uncertain environments.
Through the power of simulation software, it’s possible test a real-world phenomenon and play this out over a given period to determine ultimate outcomes.
This software has been designed to interpret the outcome of repeated interactions, recognizing that small events within complex systems can lead to large consequences.
For example, just a few key employees going on strike could result in multiple aircraft being grounded. This means a complex system is inherently difficult to understand just from knowledge of its starting state, which is why simulation is typically the best way to predict unforeseen circumstances.
This ability to project future consequences is key to reducing operational risk. It enables airlines to take proportionate action if a forecast demonstrates that aircraft could become unavailable in a given scenario.
Optimized operations amidst airline disruption
It’s this ability to confidently pre-empt disruption that ensures airlines can harness the power of AI to enhance fleet management, minimize delays and prevent cancellations.
This is even more crucial during peak holiday seasons and times of uncertainty, offering improved operational efficiency and customer satisfaction.
Through faster, better-informed strategic and operational decisions, airlines can use AI to manage complex tasks and succeed in disrupted environments by anticipating the unexpected and proactively planning to meet customer expectations.