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Generative AI: Transforming data insights into aviation magic
Historically, aviation has been a cornerstone of technological innovation. While generative AI has seen widespread adoption in customer support, predictive maintenance, and pricing, its integration into operational processes remains slower.
by Niha Shaikh, VP of Product, Cirium Journey
“Any sufficiently advanced technology is indistinguishable from magic”.
This quote from Arthur C. Clarke rings truer than ever as we experience unprecedented technological advancements. The world we live in today feels almost magical with everything at our fingertips. Gone are the days when a phone call would disrupt your internet connection. Technology is at the heart of everything and with the renewed interest in Artificial Intelligence (AI) due to the rise of generative AI, things have never been so magical!
Historically, aviation has been a cornerstone of technological innovation, setting the pace for advancements across various domains. We’ve seen the aircraft design evolve from the Wright Flyer to the modern-day jets and witnessed the advancements in avionics, including GPS navigation and autopilot systems that profoundly improved flight safety and operational efficiency. As e-commerce gained traction, the first airline ticket was sold online in 1995. 4 years later, you could check-in online and get your boarding pass. The passenger experience became much more seamless with AI chatbots, multiple booking options and various conveniences. However, as these foundational technologies matured, the pace of innovation in aviation began to slow down compared to the rapid advancements seen in mainstream technology.
And not all sectors of aviation equally reaped the benefits of new tech. The operational side is still fraught with challenges.
The logistics of moving goods and people from point A to point B with good performance consistently is extremely challenging as the operational landscape is ever-changing with lots of variables. Working on gut feel is no longer viable given that the global travel and economic landscape is changing rapidly. It is far too time-consuming to look for the needles (useful insights) in a haystack (mountains of data). Airlines and Airports often miss key pieces of context that often contribute to a lack of situational awareness eventually leading to operational inefficiencies. Often, the operations teams struggle to gauge their performance accurately as they lack comparative information from similar days or situations, making it hard to understand their performance within a broader context. The time and effort required to consistently perform a deep multi-layer analysis is often cost-prohibitive. This is compounded with by long feedback loops that make it incredibly challenging to understand the cause and effect of actions taken and decisions made over time.
In recent years, we have seen a resurgence in aviation innovation with the digital transformation movement that began during the pandemic.
It continued to gain momentum and was further boosted with the advent of generative AI which lends itself well to the type of use cases that call for dynamic problem solving. This is much needed and timely considering the change in passenger expectations, increasing focus on greener travel and the ever-rising demand. The need for efficiency, and cost reduction, whilst delivering an enhanced passenger experience has never been greater.
The market for AI-driven decision support tools in aviation is expanding, with airlines, airports, and service providers actively seeking solutions to optimize operations with most major airlines investing heavily in data science and analytics teams, striving to put data at the heart of key organisational decisions. The AI in aviation market was valued at $686.4M in 2022 and is projected to register a CAGR of over 20% each year between 2023 and 2032 (Wadhwani, 2023). The “Generative AI and Aviation” report by the International Air Transport Association (IATA) showcases that over 40% of its members are interested in leveraging GAI for disruption management-related use cases. While generative AI has seen widespread adoption in customer support, predictive maintenance, and pricing, its integration into operational processes remains slower. How do we unlock the efficiencies in the actual logistics of moving people and goods around?
Closer collaboration between airlines, airports and technology providers is even more crucial to unlock the data silos where every actor in the system holds a different piece of the overall puzzle. Data sharing, organisation and contextualisation will be key to unlocking the unearned gains and unmet potential in the wider ecosystem. A robust foundation of comprehensive data is needed to support predictive and prescriptive analytics that can truly enhance operations across the ecosystem.
It has always been said that Data is the new fuel, but Generative AI might just be that brand new engine that harnesses its power and propels the industry to another new era of rapid innovation and seamless experience for the passengers. In another decade or so, the experience of flying could be magical again!
Bibliography
*Wadhwani, P. (2023, August). Artificial Intelligence in Aviation Market Size. Retrieved from Global Market Insights : https://www.gminsights.com/industry-analysis/artificial-intelligence-in-aviation-market
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