The financial markets have seen remarkable growth and success in recent years, driven largely by the adoption of advanced technology infrastructure and automation. In the world of high-frequency trading, speed and efficiency are essential, and the transition from manual to electronic trading systems has been crucial in meeting these demands.
By enabling faster and more efficient trading, electronic systems have increased liquidity, tightened bid-ask spreads, and lowered trading costs, all of which have helped to drive growth and profitability in the capital markets. The benefits of automation and advanced technology infrastructure extend beyond just the financial markets, with other industries, such as the airline industry, beginning to explore their potential.
However, the airline industry is still grappling with outdated systems that are not equipped to handle the volume of data and volatility inherent in the industry. Recent events, such as the COVID-19 pandemic, the Southwest Airlines computer outage and Lufthansa IT failure, have exposed the industry’s limitations. Thus the capabilities of the financial markets’ systems provide a valuable example for the airline industry to follow.
The financial markets have developed robust technology infrastructure, utilizing state of the art technology available at every period, including advanced machine learning algorithms and AI, which enable high-frequency trading and automated trading. These systems can process vast amounts of data with hundreds of millions of actions per second and operate on millisecond timescales, all without crashing. By implementing cross-industry technologies like ML algorithms and AI, airlines, even though lagging decades behind financial markets, can modernize their infrastructure and move towards more efficient and stable systems, enabling them to make smarter decisions based on real-time data and predictive analytics.
The potential benefits are significant. By leveraging third-party vendors, airlines can streamline and optimize their operational processes, resulting in cost savings of up to 10-20%. Furthermore, according to a recent ‘Precedence Research’ report, the implementation of AI in the airline industry is projected to grow at a CAGR of 35.38% from 2022 to 2030, offering a significant growth opportunity for airlines to enhance their operations and improve the passenger experience.
The benefits of implementing new technology and infrastructure upgrades extend beyond operational efficiency and increased profitability. By modernizing their systems, airlines can also enhance the passenger experience. For instance, airlines can leverage data analytics to personalize the travel experience for each passenger, offering customized services and recommendations based on their preferences. Additionally, AI-powered chatbots and virtual assistants can help passengers navigate the booking and check-in process, reducing wait times and improving overall satisfaction.
While the airline industry faces several challenges in modernizing its technology and infrastructure, cloud-based systems that offer remote control and easy onboarding, along with third-party vendors, can provide a flexible and scalable solution for airlines to optimize their operations while reducing operational risk.
According to a report by Allied Market Research, the aviation analytics market was valued at $2.78 billion in 2020 and is projected to reach $8.21 billion in 2030, registering a CAGR of 11.72%.
In conclusion, the aviation industry can modernize their technology and infrastructure with cross-industry technologies like ML algorithms and AI, as well as by collaborating with third-party tech enablers. This can enhance operational efficiency, reduce delays, improve the passenger experience, and increase profitability. By adopting these innovative strategies, airlines can make smarter decisions based on real-time data, leading to higher revenue and stability. This will give them a competitive edge in the industry and enable them to stay ahead of the curve.
Article by Dr. Uri Yerushalmi, Co-Founder and Chief AI at Fetcherr, Former CEO and Head of AI for a major algo trading firm. Three decades of experience in software development and AI.