How AI Quietly Became the Backbone of Today’s Aviation Industry

Every traveler has experienced it at least once: you’re waiting at your gate when an announcement is made saying, “The flight has been delayed due to mechanical issues”. While this is a frustrating, yet surprisingly frequent scene at airports around the world, arguably the most popular new technology is actively reducing delays and cancellations of this nature, namely, AI.

The aforementioned is an example of what Delta’s APEX system is used for. APEX (Advanced Predictive Engine) monitors real-time engine health and optimizes maintenance timing; between 2010 and 2018, it helped reduce annual maintenance-related cancellations from 5,600 to only 55, according to Airways Magazine. Not only are such systems reducing travel disruptions, but also in other cleverly-integrated ways making travel for passengers easier: AI travel assistants help passengers without the need for a help desk, and fares are also dynamically priced using AI.

In other words, AI is now a practical tool transforming not only aircraft maintenance but also pricing, passenger support, and airport operations.

Where, Why, and How Is AI Used?

Aside from maintenance scheduling and AI assistants, AI is used in various ways in the airline industry. Airlines are deploying AI technology across various operational domains to reduce expenses, boost revenue, and improve operational safety. The following are some examples of AI integration by airlines:

• Predictive Maintenance: AI schedules maintenance by using machine learning to monitor engine health, scheduling maintenance accordingly.
• Ground Operations: Crowd flow management and turnaround optimization can improve ground operation efficiency. A digital twin model of an airport can also model ramp operations such as baggage loading, refueling, and cleaning in real time.
• Route Optimization: AI dynamically adjusts flight paths based on the weather and air traffic congestion, saving fuel and time.
• Revenue Management: AI can simulate millions of pricing scenarios in milliseconds, taking into account holidays, competitive fares, and real-time demand factors with ease, thus maximizing revenue for airlines.
• Customer Experience: AI assistants and chatbots eliminate the need for passengers to visit a physical help desk. Handling high volumes of passenger inquiries in this way simultaneously means less burden on ground staff.
• Sustainability: AI optimizes engine wash scheduling and APU idling during turnarounds, which also allows a reduction in CO2 emissions. Route Optimization also means that a flight will burn less fuel, reducing an airline’s carbon footprint.

Another factor worth taking into account is how the airline industry makes a profit: thin profit margins and a tightening shortage of skilled workers, combined with increasing wages, mean airlines need to find a better way to optimize operating expenses; precisely where AI comes into play. In 2024, American Airlines operated at 17.6 cents per seat mile while earning only 16.9 cents per available seat mile in airfare only (although the total revenue per seat mile, including ancillary fares, was 18.51 cents). Fuel and maintenance account for nearly 40 percent of total operating expenses, making airlines turn to AI to find fractional efficiencies that translate into millions of dollars in annual savings when added up.

This financial pressure is further burdened by a global workforce shortage of roughly 32,000 professionals, including a wave of approximately 4,300 pilot retirements expected every year through 2042 in the United States. Therefore, AI is viewed as an essential tool for survival, enabling airlines to enhance capabilities while improving reliability.

Implementation of dynamic AI-driven pricing is projected to improve airline revenue by an average of 10%. Fetcherr, Delta’s AI pricing agent partner, claims that its GenAI pricing system increased revenue by 6% to 9%, with Virgin Atlantic reportedly already seeing an impact while testing it against its legacy pricing process.

How Are Passengers Affected?

Passengers can benefit from reliable flight operations, as optimized fleet management means a substantially reduced chance of delays and even cancellations. Waiting times at the airport are also inherently reduced as a result of improved crowd flow management. Eco-conscious travelers can fly with peace of mind knowing that their flight is flying an optimized route, reducing fuel consumption and CO2 emissions. Food waste due to over-catering is minimized thanks to deep-learning of meal selections by passengers.

Ticket prices are also affected by AI; automated revenue management prices tickets using real-time data. While this might be beneficial for passengers on heavily competitive routes with several airlines offering service, routes with significant demand where a single airline has a monopoly might see increased fares due to low competition.

As previously discussed, passengers are also able to utilize AI themselves in the form of a Digital Concierge service offered by AI assistants and chatbots; this eliminates the need for passengers to physically visit a help desk and wait in line to ask a simple question. AI can tend to the needs of passengers requiring assistance with flight rebooking, airport wayfinding, and passenger requirements such as forms of identification.

How AI Is Already Reshaping Aviation Operations

Aside from Delta’s previously discussed APEX system, Delta also makes use of Fetcherr’s generative pricing engine for dynamic pricing by AI. A Delta Concierge was also introduced: a generative AI assistant to help passengers requiring assistance.

American Airlines has been rolling out its Smart Gating system, which uses AI to optimize aircraft ground movements. This system reduces on-ground time and improves gate utilization, reducing delays. American has also developed an AI-assisted solution for passengers struggling with missed connections; the tool allows passengers to rebook themselves instantly, giving flight suggestions tailored to each passenger’s situation, like urgency and travel preference. Also, at Dallas-Fort Worth and Charlotte Douglas, another AI system suggests outbound flights that can be briefly delayed to wait for delayed inbound passengers.

Air Canada has taken an in-house approach to AI, allowing the airline to maintain tighter control over the tech and its data assets. This reflects the belief that gaining the competitive edge in using AI technology comes from proprietary data and custom-built AI models tailored to the airline’s demands. The airline is also able to rely less on third-party solutions and gain self-sufficiency in the space as a result of this.

Alaska Airlines has partnered with several AI startups, employing an open-minded stance in the AI game. One such startup is Air Space Intelligence (ASI), an AI route optimizer that saved the airline 480,000 gallons of jet fuel and reduced 4,600 tons of CO2 emissions in six months. Alaska also uses ASI’s Odysee tool for resilient schedule building for optimized deployment of aircraft on high-value routes and fewer delays. The airline also works with Pattern Labs to use a digital twin model to optimize its ramp operations, such as baggage loading, refueling, and cleaning.

Korean Air had gone through a major overhaul of its contact center operations, shifting to a cloud-based infrastructure for advanced AI integration of its customer support operations. Service agents now have access to generative AI tools that draft complex responses, taking much less time than traditional responses from customer service agents. The company reported that agents now save 5-7 minutes in hold times alone, along with being able to offer speed and intelligence at the first point of contact with customers, especially for those in high-stress moments.

Lufthansa Technik uses AI-powered drone inspections for fuselage and engine checks, reducing the time needed for a manual inspection. Lufthansa’s Tray Tracker uses computer vision to scan meal trays after flights for analysis of passengers’ consumption patterns for future production of airline meals. This helps prevent excessive catering of meals that will likely be left over, contributing to the airline’s sustainability. The airline is also developing a digital twin for optimized maintenance scheduling, ultimately reducing CO2 emissions over its fleet.

Turkish Airlines has implemented photo-recognition to track baggage for travelers. This system allows for less staffing, optimized cargo space, and accurate prediction of baggage demand on future flights. It is especially used for managing luggage on connecting flights, as AI can identify individual bags based on size, color, texture, and other unique characteristics.

IAG, the parent company of British Airways, Iberia, Aer Lingus, LEVEL, and Vueling, developed an engine optimization system powered by AI that runs millions of scenarios considering regulatory requirements, parts availability, labor constraints, and operational continuity to find optimal maintenance windows for each aircraft. British Airways also reportedly saved up to 100,000 tons of fuel by using AI-powered flight planning.

The Bottom Line

The rapid development of AI technology has started influencing airlines; flight operations are being optimized for best efficiency, AI assistants are helping passengers, and machine learning is used to reduce the waste of resources such as fuel and catering. While the introduction of AI into the airline industry was rather necessary for airlines to maximize profit, it also benefits travelers in many ways, such as fewer delays and receiving better assistance. With the ever-increasing implementation of AI into air travel, airlines and passengers together can expect a more seamless flight with fewer disruptions at possibly lower costs, ultimately benefiting all parties involved.