AI in the Sky

AI in the Sky

The first-ever commercial use of in-flight AI is proving to be a major success story for Alaska Airlines — both in terms of efficiency and future sustainability

Here’s an interesting finding: 85% of the total AI projects being implemented in a corporate setup fail to bring intended results to businesses. While most organisations report failures in their AI projects, almost a quarter of them report about a 50% failure rate. Of the projects that did not fail outright, 31% did not meet their objectives, 49% were late and 43% exceeded their initial budgets. In fact, a study by Capgemini even found that only about 27% of the data projects being implemented are considered successful.

Given the evidently high failure rates of AI adoption in corporate setups, questions regarding the efficacy of said adoption seem more obvious than anything else. Yet, most organisations worldwide are still experimenting with AI and looking to find use-cases suitable for their work. Success stories are thus going to be crucial going forward.

Enter: Alaska Airlines

The idea of using Artificial Intelligence to completely overhaul an existing flight-operation system is a prospect, rather daunting to say the least. According to Alaska Airlines’ Flight Operations Strategy and Innovation Director, Pasha Saleh: “Since the idea was highly conceptual, we didn’t want to oversell it to management. Instead, we got Airspace Intelligence, our AI vendor, to visit our network centers so they could observe the problems and build that into their development process. This was well before the trial period, about 2.5 years ago.”

That an airline that operates flights in harsh arctic conditions thence developed an industry-changing platform that became the innovator in flight operation using AI technology should not come as a surprise to many. Of the myriad opportunities to append legacy systems across the airline industry, some of the features that Alaska Airlines stressed on included dynamic mapping, built-in monitoring and predictive abilities.

Dynamic Mapping offers a fully real-time based ‘4D’ map with relevant information such as turbulence reports, weather reports and FAA data feeds all visible on a highly stylised and detailed map. The fourth dimension is time, “with the novel ability to scroll forward eight-plus hours into the future, helping to identify potential issues with weather or congestion.”

In addition to dynamic mapping, built-in monitoring and predictive abilities using AI also analyse aspects such as looking at all scheduled and active flights across the USA, systemically scanning air traffic, continuously (and autonomously) evaluating operational safety, flight planning efficiency and air traffic compliance, among several others. TechRepublic opines, “The predictive modeling is what allows Flyways to “look into the future,” helping inform how the U.S. airspace will evolve in terms of weather, traffic constraints, airspace closures and more.”

Saleh adds: “Finally the system presents recommendations. When it finds a better route around an issue like weather or turbulence, or simply a more efficient route, Flyways provides actionable recommendations to flight dispatchers. These alerts pop up onto the computer screen, and the dispatcher decides whether to accept and implement the recommended solution. In sum: The operations personnel always make the final call. Flyways is constantly learning from this.”

Much like autopilot, the AI systems being implemented are aimed at augmenting human capabilities: with humans always taking the final call in all aspects, be it route planning or flying the aircraft. The efficiency of the AI adoption by Alaska Airlines is a firm step towards more sustainable and efficient air travel for the future, with the organisation reporting as much as 480,000 gallons of fuel being saved in six months, coupled with reduced carbon emissions worth almost 4600 tons as well. It also goes to show that given the right use-case, AI could indeed be life-changing.

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