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Oliver Giles for AVEM Insight

Do you remember the first time you used the internet or the first time you made a call on a mobile phone? Those of us with a ’19’ prefixing our birth year will have undoubtedly lived that moment when we were picked up by a tidal surge of technology and carried forward into the next age. Chances are that many of us have had that moment recently with AI. AI is infiltrating every aspect of our lives – but how is it affecting the aviation industry?

The Power of AI

ChatGPT is a large language model trained by OpenAI for natural language processing tasks such as conversation, question-answering, and language generation. To labour a point, that last sentence was generated by ChatGPT on being asked to explain itself! After half an hour or so of messing about asking it to write Shakespeare in the style of Jeremy Clarkson, I realised that this was my ‘tidal surge’ moment, my world has moved from ‘pre’ to ‘post’ AI, and I’m not sure I’m all that comfortable with it. In messing with this chatbot, it is painfully easy to see how this technology holds a power that will change every aspect of our lives. Currently, our exposure to AI is quite limited, yet the pace of development has led to calls for pauses in development in a vain attempt to rein in its disruptive effects. The way this technology will utterly bend, shape and perhaps break what we know now may be terrifying for many. AI cannot be thought of in terms of other recent technological leaps; it is a humanity-defining moment where our species has unleashed a power that must be thought of alongside the discovery of farming, the invention of the printing press, and the industrial revolution.

AI is already on a relentless path to reshape many industries worldwide, and the aviation sector is no exception. The marriage of AI and aviation promises a future where air travel is safer, more efficient, and more environmentally friendly.

Let’s delve into the potential applications of AI in aviation, with examples and case studies that showcase the possibilities on the horizon.

Transforming Air Traffic Management

One of the most promising areas where AI is making a significant impact is air traffic management. Ensuring the safe and efficient movement of aircraft in the skies has always been a top priority for the aviation industry. With the ever-growing demand for air travel, AI can play a crucial role in optimising air traffic management and reducing congestion.

NASA’s Airspace Technology Demonstration 3 (ATD-3) project is a prime example of AI’s potential. The project focuses on developing and demonstrating new technologies that can significantly improve the efficiency of the National Airspace System (NAS) in the United States. ATD-3 utilises AI and machine learning algorithms to analyse flight data and develop more efficient flight routes and schedules. The system is designed to optimise air traffic flow, reduce delays, and minimise the environmental impact of aviation.

The Dawn of Autonomous Aircraft

The concept of autonomous aircraft has been a hot topic in recent years. Although fully autonomous passenger planes are still a long way off, AI-driven advancements in drone technology and unmanned aerial vehicles (UAVs) are paving the way for a future where autonomous flight is a reality.

Boeing’s MQ-25 Stingray is an excellent example of how AI is enabling autonomous flight. The Stingray is an unmanned aerial refuelling aircraft developed for the U.S. Navy. It is designed to autonomously take off and land on an aircraft carrier, identify and track target aircraft, and refuel them mid-air. The use of AI in the Stingray’s navigation and refuelling systems showcases the potential of autonomous aircraft technology in both military and commercial aviation.

Revolutionising Aircraft Maintenance with AI-Driven Analytics

In the aviation industry, ensuring the safety and reliability of aircraft is paramount. Predictive maintenance powered by AI has the potential to revolutionise aircraft maintenance by identifying potential issues before they become critical, reducing downtime and maintenance costs. Rolls-Royce’s IntelligentEngine initiative is a prime example of AI-driven predictive maintenance. The program uses AI, advanced analytics, and the Industrial Internet of Things (IIoT) to monitor and analyse data from thousands of sensors installed in aircraft engines. By continuously monitoring this data, the IntelligentEngine system can detect early signs of wear or potential failure, allowing maintenance teams to address issues proactively, minimise downtime, and reduce the risk of catastrophic failures.

Enhancing the Passenger Experience

AI can also enhance the passenger experience, from streamlining the check-in process to providing personalised in-flight entertainment. As airlines seek to attract and retain customers in an increasingly competitive market, AI-driven innovations in passenger experience will become essential.

Dutch airline KLM has been a pioneer in utilising AI to improve the passenger experience. KLM’s chatbot, “BlueBot” (BB), leverages AI and natural language processing to assist passengers with booking flights, selecting seats, and answering questions about luggage, check-in times, and more. By automating routine customer service tasks, BB enables KLM to provide swift, personalised assistance to its passengers, saving time and resources.

AI for a Greener Aviation Industry

The aviation industry has been under increasing pressure to reduce its carbon footprint and become more environmentally sustainable. AI can contribute significantly to these efforts by optimising flight routes, reducing fuel consumption, and improving operational efficiency.

Airbus has been working on its Advanced Inspection Drone project, which uses AI-powered drone technology to inspect aircraft for defects and damage. The drones are equipped with advanced sensors and AI algorithms that can quickly and accurately detect structural issues, allowing maintenance teams to address them promptly. This streamlined process reduces the time and resources required for manual inspections and contributes to fuel savings and lower emissions, as aircraft are returned to service more quickly.

Moreover, AI-powered route optimisation tools can help airlines minimise fuel consumption by identifying the most efficient flight paths, considering weather conditions, air traffic, and fuel prices. These tools can significantly reduce emissions and costs associated with fuel consumption, contributing to a more sustainable aviation industry.

Similarly, AI is now even being used to consider how the natural world interacts with aviation. Predictive wildlife risk services will soon enable greater visibility of a previously ‘uncontrollable’ risk, with specific consideration given to reducing not just the cost of aircraft repairs, but also wildlife species conservation. Providing this as a 3rd party service via API increases the attractiveness as it can be seamlessly integrated into existing business solutions, reducing the barrier to industry engagement.

The Ethical Considerations of AI in Aviation

As AI continues to advance and reshape the aviation industry, it’s essential to consider the ethical implications of these new technologies. Issues such as data privacy, security, and the potential loss of jobs due to automation must be addressed to ensure a responsible and inclusive transition toward an AI-driven future.

For instance, as AI systems gather and analyse vast amounts of data to improve aviation operations, it is crucial to ensure that this data is handled responsibly and securely to protect passengers’ privacy. Additionally, as AI and automation become more prevalent, the industry must invest in re-skilling and up-skilling programs to help workers adapt to the changing landscape and find new opportunities within the sector.


The story of AI in the aviation industry will no doubt be one of a relentless drive for more efficiency and streamlining of business in the name of achieving greater productivity. AI does promise to deliver vast improvements in air traffic management, maintenance, passenger experience, and – perhaps most importantly – sustainability. Undoubtedly these improvements will be positive, but the promise of doing ‘less with more’ is intrinsically connected with profitability. Across the world, in one form or another the term ‘race to the bottom’ has been used about the aviation industry’s relentless drive to increase efficiency, with sometimes questionable decisions and testing the boundaries of acceptability. It could be that AI soon opens the floodgates for airline executives to turn to this new technology with such fervor that the years of hard-won experience by industry professionals are swept aside. It is down to us all as responsible professionals to embrace the opportunities presented by AI while addressing the ethical challenges and ensuring a responsible and safe transition to this next age in aviation.