AI and the Aviation Industry: A Turbulent Journey

If there is a global industry poised to benefit due to the nature of its industrial manufacturing processes and live operations, it is undoubtedly the airline industry.

As news of Boeing whistleblowers raising security issues dominates headlines, sided with viral videos of serious aviation security incidents transcending — such as the blowout of an Alaskan Airline Boeing window mid-flight — experts wonder how advanced the digital transformation of the airline industry is and why it isn’t embracing artificial intelligence (AI) and automation faster.

From aeroplane design to factory floors and AI in flight, monitoring, and safety, we are going to explore how artificial intelligence is expected to take flight in the near future – and the blockers currently in the way.

Table of Contents Table of Contents

1. Key Takeaways
2. AI Investment Hits Aviation, Airlines and Airports
3. AI and Automation in Manufacturing, Maintenance, Repairs, and Security
4. Disrupting Innovations in Aerospace: From 3D Printing Manufacturing to GenAI Autopilot
5. Next-Gen AI Autopilot Technology
6. The Bottom Line

Show Full Guide

Table of Contents

1. Key Takeaways
2. AI Investment Hits Aviation, Airlines and Airports
3. AI and Automation in Manufacturing, Maintenance, Repairs, and Security
Show Full Guide
4. Disrupting Innovations in Aerospace: From 3D Printing Manufacturing to GenAI Autopilot
5. Next-Gen AI Autopilot Technology
6. The Bottom Line

AI Investment Hits Aviation, Airlines and Airports

The Global Airline Industry Market is expected to be worth around $1,193.2 billion by 2033, a substantial growth from $647.7 billion in 2023.

The Air Transport IT Insights 2023 of Société Internationale de Télécommunications Aéronautiques (SITA) — a leading company specializing in air transport communications and information technology — found that airports and airlines saw IT spending increase year on year into 2023.

Investments reached an estimated $10.8 billion and $34.5 billion, respectively, with over two-thirds of airport and airline Chief Information Officers (CIOs) expecting continued growth into 2024.

CIOs are now looking to supplement passenger processing tech with innovative solutions on the operations side, boost efficiency, protect operations against disruption, and streamline processes by embracing IT solutions.

The Risks of AI are Augmented in Aviation

However, unlike other industries, in aviation, the risks of AI are much more significant. This has been identified as one of the reasons why AI and automation, which is becoming a norm in many industries today, lag behind in airline companies and aerospace manufacturers.

IBM warns that the industry should take cautious first steps when approaching and rolling out AI solutions. The European Union Aviation Safety Agency’s (EASA) second version of its AI Roadmap, already addresses a comprehensive plan for the integration of AI in aviation.

IBM says a big focus is placed on safety, security, AI assurance, human factors, and ethical considerations.

“Such measures indicate that the industry is aware of AI’s risks, which include bias in the data used by machine learning systems to train AI models that can skew recommendations or analyze… (and) generative AI (which) can sometimes identify patterns or objects in data that are nonexistent or inaccurate — a phenomenon known as a hallucination.”

AI and Automation in Manufacturing, Maintenance, Repairs, and Security

Predictive maintenance in aviation is one of the top trends in development. Predictive maintenance leverages Internet of Things (IoT) and AI to predict and prevent aircraft maintenance issues, reducing downtime and operational costs. Experts say that predictive maintenance systems could also automate repairs, driving security.

Furthermore, robotics, automation, and AI have already proven to be effective in creating digital twins and managing production lines.

Product development leaders turn to digital twins to accelerate product development processes and improve outcomes while reducing costs. This is the reason why the digital-twin technologies market is expected to grow 60% annually over the next five years, reaching $73.5 billion by 2027.

Ricky Gomulka, owner of JetLevel Aviation, told Techopedia that AI’s role in aviation is increasingly pivotal, particularly in predictive maintenance.

“By analyzing vast data sets from engine performance to minor electrical anomalies AI can forecast potential failures before they occur, enhancing safety and minimizing aircraft downtime.”

Gomulka said that looking ahead, AI could extend to real-time, in-flight diagnostics and adjustments, possibly through automated systems that respond instantly to operational data, thus reducing human error and improving efficiency.

Jarred Knecht, President and CEO of Promark Electronics (a leading wire harness and cable assembly manufacturer for OEMs) and KonnectAi — divisions of Electrical Components International — also spoke to Techopedia about the issue.

“AI technology in machine maintenance and in predictive maintenance of equipment will continue to grow, as will AI quality and traceability products, and other tools which are quick and cost-effective to implement.”

“AI will also be used in business development activities that will be especially helpful for airline manufacturers, such as how we prepare presentations, communicate, and create content for both technical and non-technical audiences,” Knecht said.

“Every aspect of manufacturing can and will involve AI sooner rather than later. Today, airline manufacturers can pick their starting point and dip their feet in AI adoption that will be simple to use and understand.”

The Costs of Delaying Innovation and Investment

Using digital twins, predictive maintenance, and automated manufacturing companies can identify issues before they become a problem within the entire supply chain while presenting detailed reports of where the problem began and how it can be solved.

Knecht from Promark Electronics said new AI-driven technologies could change security in the industry, and spoke about the recent Boeing incidents, — now being investigated by the U.S. Department of Justice.

“With Boeing’s 737 MAX bolt crisis, for example, mitigation would involve finding not only the exact issue with the door and bolt but the exact batch where the defective part came from. Mitigation would also involve tracking if the door and bolts were made by an OEM, subcontractor, or another supplier.”

Knecht warned that manufacturers across industries are sometimes using traditional business processes, such as physical records, yet still need to accurately track their supply chains through all levels.

Knecht spoke about AI visual inspection tools that enable manufacturers to respond to demand pressures by increasing the efficiency of their inspection processes.

“AI tools can drastically reduce inspection time and virtually eliminate manufacturing errors,” Knecht said.

“As manufacturers face labor shortages or the retirement of experienced workers, AI visual inspection can put the equivalent of hundreds of years of inspection experience to work, even as manufacturers contend with talent pool challenges.”

“In addition to ensuring quality from the production line, manufacturers looking to avoid becoming a part of the next Boeing-like crisis should ensure they are modernizing their tracking and recordkeeping processes.”

Disrupting Innovations in Aerospace: From 3D Printing Manufacturing to GenAI Autopilot

Questioned about the significant AI innovations in aerospace, Gomulka spoke about AI-enhanced 3D printing and AI-driven digital twin technology.

“These advancements allow for more precise components and faster production while lowering costs,” Gomulka said.

“Digital twins simulate aircraft systems and operations in real-time, enabling engineers to predict outcomes under various scenarios without physical trials, significantly accelerating R&D.”

Next-Gen AI Autopilot Technology

Another area is autopilot technology. While autopilot has been widely integrated into commercial and passenger aircraft for decades, the emergence of new and more powerful machine learning models and AI technologies is expected to drive further autopilot advancements.

“The evolution of autopilot technology with generative AI is focused on enhancing existing algorithms to better handle complex, unpredictable situations encountered during flight,” Gomulka explained.

New Gen AI autopilot systems involve not only refining the software for better decision-making but also integrating more robust fail-safes and redundancy protocols to prevent accidents linked to automation complexities. Another area where AI innovations are making strides is Ground Control.

“Particularly in optimizing flight paths, managing airspace traffic more efficiently, and reducing communication delays. AI systems are being developed to handle routine communications tasks, freeing up human controllers for more critical decision-making processes.”

The Bottom Line

The aviation industry stands at a juncture. While significant potential exists for AI to revolutionize safety, efficiency, and profitability, delays in adoption threaten to leave airlines behind.

While the industry is still economically recovering from the impacts of pandemic-era shutdowns, from potential security incidents to lagging behind competitors, the costs of not investing in R&D and innovation are real and dangerous.

Conversely, embracing AI offers a clear path to growth, with advancements in predictive maintenance, 3D printing, and autopilot poised to transform the sector.

The question remains: Will the aviation industry overcome its hesitation and take flight with AI, or will it remain grounded by outdated processes?