The power of artificial intelligence (AI) is limitless. Today, much of our economy is driven either exclusively or in part by AI applications. Across all industrial sectors, from banking to education, AI is changing how we do business and how we live our lives. The aviation sector takes no exception to this rule.

For decades, airlines and air traffic control centers have been incorporating AI to create safer skies. Training simulations, management databases, support systems, and even piloting are becoming artificially intelligent.

In recent years, AI technologies have only gathered speed. Soon enough, the entire aviation industry will be revolutionized by the power of AI. It is not a matter of “if”, but “when”. Already, companies such as Boeing and Fly Emirates are conducting high-level research on how to fully incorporate AI into the cockpit. Once this is achieved, nothing will be the same.

Want to find out more about what AI is, and how it is affecting the aviation industry? In this article, we’ll break down everything there is to know about this growing phenomenon. Read on to get brought up to speed on all things AI, and to find out what’s to come in the world of aviation.

AI 101

What is AI? Although many of us have a basic understanding of what AI is, few have a complete grasp of the subject. Artificial intelligence (AI), also referred to as “machine intelligence”, refers to the general capacity for intelligence demonstrated by machines.

Scientists and researchers use the term “AI” to refer to a device that perceives its environment and responds in a way that maximizes the likelihood of achieving its goals. In other words, AI is the ability for machines to act intelligently in a way that mimics that of human beings and other intelligent life forms. AI gives machines the ability to problem solve and to learn.

A (Brief) History of AI

With the advent of modern computing the mid-20th century, the field of AI research began. In the 1950s, AI research laboratories and workshops began popping up in universities across Europe and the United States. At first, AI scientists created basic programs that taught computers how to play games like chess and checkers.

Eventually, computers became significantly more powerful. This allowed for more complex and innovative AI applications. By the 1990s, companies like IBM were creating computers that exhibited a unique form of super intelligence. In 1997, IBM’s Deep Blue computer defeated the reigning world chess champion, Garry Kasparov.

By the turn of the millennium, AI expanded rapidly. It is now used to replace many jobs and occupations that were once manned by human beings. Today, everything from medical diagnoses to drafting legal briefs are now done by AI-enabled systems. With the recent rise in deep neural networks and cloud computing, AI is now undergoing another wave of expansion.

Boeing’s AI Simulations

Beginning in 2015, U.S. aviation giant Boeing started experimenting with AI to devise a jet that can entirely fly itself. In a widely-circulated article published by Wired Magazine, it was revealed that Boeing’s research and development division was building “autonomous aviation” software. In time, the software is intended to use AI to fly a commercial jet without the use of a pilot.

While there are no reports yet about the program’s testing, we can expect to see it in-flight over the next few years. When it is finally released, it is reasonable to believe that this Boeing project will replace the current autopilot systems that are in most aircraft already.


A flight management system (FMS) is a type of computer that is built into all modern aircraft. These computers perform several critically important tasks that the aircraft needs to do while in flight. The FMS comprises the role of a few artificial crew members. For example, the work that the FMS does replaces the need for multiple engineers and navigators during the flight.

The FMS is one of the main applications of AI in aircraft. And every year, FMS systems are upgraded and improved upon so that fewer operations are expected to be performed by humans. The FMS use many sensors and other pieces of avionics equipment to make thousands of calculations per second. These calculations help safely guide and track the plane.

The pilot and co-pilot interact with the FMS through a display unit in the plane’s cockpit. From there, they can program instructions into the FMS. Once those instructions are given, they can sit back and simply monitor its progress. In the years ahead, FMS systems will be fully autonomous and will have the power to operate without a pilot’s input.

Asiana Airlines

If you are wondering exactly how intelligent aviation AI is becoming, look no further than Asiana Airlines. Formerly known as Seoul Airlines, Asiana is a South Korean airline that operates on a global scale. It is one of the two major international airlines in the Republic of Korea, and it has garnered a reputation as a key innovator in the civil aviation industry.

Asiana Airlines owns and operates one of the most technically sophisticated FMS computers in the world. The FMS and autopilot AI is so intelligent that they are trusted even more than Asiana Airlines pilots. In fact, Asiana Airlines even prohibits pilots, captains, and first officers from manually flying aircraft above 3,000 feet. Instead, only their AI systems are permitted.

Military AI Systems

In a 2017 article written by the Indian Defence Review, numerous military applications of AI aviation are discussed. For example, a U.S. Department of Defense-funded DARPA project named “Aircrew Labor In-cockpit Automation System” (ALIAS) is currently under development. This project seeks to replicate human activity in a cockpit, and eventually replace pilot input.

Militaries have the unique budget capacity to spend big money on AI research. Since artificial intelligence-related work is costly in terms of energy output and human labor, big government departments such as the U.S. Department of Defense are usually at the forefront of research efforts. Air forces around the world are working to implement AI technology in their fleet.

In military hospitals, AI is also being employed to interpret MRI results and read millions of data signatures per second. This can save lives on the battlefield as well as at home. 

When Aviation AI Goes Wrong

The story of Air France Flight 447 is not for the faint of heart. In July 2009, Flight 447 tragically crashed into the Atlantic Ocean, killing all 228 souls aboard. The plane was departing from Rio de Janeiro, Brazil and was headed for Paris, France when it stalled mid-flight.

Flight 447 will be remembered as a major failure in aviation artificial intelligence. This is because investigators believe that the flight entered an aerodynamic stall after the autopilot AI malfunctioned. The autopilot caused the stall to occur because it pointed the plane’s nose too high, and the pilots were caught off guard.

The aftermath of Flight 447 saw a fierce debate about the use of AI and autopilot programs in commercial aircraft. Today, many efforts are being made to improve AI quality to make sure that accidents will never happen again. However, by and large, autopilot programs are still far safer and more trustworthy than human pilots.

Revamping Assembly

According to an interview with Tomas Lopez, the Head of Data Analysis at Airbus, the European aeronautics giant is heavily invested in AI technology. Primarily, AI and machine learning are being designed to speed up the aircraft manufacturing process and to reduce the risk of errors. However, in practice, Airbus is investing in many different AI programs across all departments.

In real time, AI programs are now collecting critical information from all the factories and assembly lines that are part of Airbus’s supply chain. As a result, errors can be fixed and recorded as they happen. This is intended to remove the possibility of human error and reduce excess operating costs.

Improving the Customer Experience

In the same interview with Tomas Lopez, he explains that Airbus is also collecting big data from their passengers. Specifically, Airbus is collecting social media data from their passengers to gain better insight into their preferences. In effect, this will improve the passenger experience as Airbus will have a better understanding of their passenger’s wants and needs.

Lopez also spoke about the various other AI initiatives that Airbus is currently working on. For example, Airbus is investing in AI applications for their aerospace and defense sectors. In particular, Airbus is using machine learning to automate border surveillance and the “monitoring of human welfare through biosensors.” This project is designed to reduce operating costs, which will translate into lower fare prices for passengers.

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