AI in Aviation
The most recent AI trends and innovations in the aviation sector related include revenue management, air safety and airplane maintenance, feedback analysis, messaging, contact and workflow automation, mrew Management, fuel efficiency optimization, in-flight sales and food supply, operations improvement and optimization, use of virtual assistants, passenger identification, baggage screening and generative product design.
We started the search by looking for recent trends and innovations when it comes to AI technology in the aviation industry. We also looked into different companies that use these innovations and trends. We found the related information in reputable sites such as Datafloq, Future Travel Experience, Social Hospitality, Techopedia, and Forbes. Additionally, we focused more on the industrial applications of these trends and innovations. We concentrated on service processes, operations, maintenance, and product designs of airlines. We also found that the trends and innovations we found were becoming quite popular in the industry because of the recent surge of the AI industry. All information was synthesized and summarized in the research brief below.
Introduction to the AI Market
Artificial intelligence is one of the leading markets in the aviation industry, with an average annual growth of 45.16%. In 2014, the market was valued at $34 million. The value grew to $104 million in 2017 and is predicted to reach $714 million in 2022. Additionally, AI is part of the top ten leading trends in airlines and airports in 2019. Various airlines and airports are now using AI-powered products such as chatbots and virtual assistants. While some airports use Virtual Reality (VR) to create immersive experiences in both the terminal and in-flight. One example of the use of VR in airports is from Iberia, in where the airport uses a “motion sickness-free” VR in-flight entertainment system (IFE) in both its premium lounge in the Madrid Airport and some selected onboard flights. Other airlines using and testing the product are Etihad and Emirates and Alaska Airlines. Etihad and Emirates tested the VR headsets in their lounges, while Alaska Airlines partnered with Skylights to test VR IFE.
AI Trends and Innovations in the Aviation Industry
Service Manufacturing Processes and Operations
AI has ten trending uses in aviation service manufacturing processes and operations. These are revenue management, feedback analysis, messaging, crew management, operations improvement, passenger identification, baggage screening, fuel efficiency optimization, in-flight sales and food supply, and virtual assistants.
AI is used in managing the revenue of individual airlines. AI does this by analyzing flight destinations and adjusting ticket prices through the results of the analyzation. The technology also looks for the best distribution channels and manage customers’ seats. This keeps airlines competitive and customer-friendly. An example of this would be Easyjet, who uses AI to improve their pricing strategy and to manage their inventory. Overall, its impact can be seen in improved pricing and inventory.
Another use of AI is through feedback analysis. Much like revenue, AI can also analyze feedback from customers. This provides the airlines with a list of services to improve on. One of the innovations in this platform is found in the PureStrategy platform in where they use an Automated Neural Intelligence Engine (ANIE) to provide data review, categorization, visualization, and sentiment analysis to airlines. The platform also makes sure that customers have an easy time finding, booking, and paying for their flights. The overall impact of this in the industry is the improvement of on-brand services.
AI is also improving both messaging and workflow in the aviation industry. AI is enhancing communication between passengers and the airline by providing a smooth channel to communicate in certain situations such as flight delay and baggage loss. It overall improves the speed of customer queries. An example of this would be the Coseer program made by Arbot Solutions. The program speeds and simplifies both customer service and employee workflow through the use of algorithms that processes natural language or unstructured texts. Additionally, Southwest uses leverages on this trend by optimizing the interaction between contact center agents and travelers. It also helps streamline existing employee workflow.
AI manages airline crews by managing their flight route, licensing and qualifying individual crew members, choosing the aircraft type and fuel usage, monitoring airplane maintenance schedules, suggesting training requirements, advising work regulations, and assigning and tracking vacations and days off schedule for pilots and flight crew. An example of this would be from Jeppesen, who uses the Crew Rostering Solution to provide predicted and real-time fatigue analytics of their crew members. Overall, it improves workflow, scheduling, and staff management.
AI also optimizes and improves airline operations. An example of this would be from Delta Airlines. The airlines use AI to improve overall customer service and to predict aircraft maintenance. Specifically, for customer service, the airlines use AI technology such as bag tracking technology and self-service bag checking machines. When it comes to analytics, the airline uses the SmartSignal predictive analytics software, BitStew, and Asset Performance Management (APM). These technological innovations are meant to analyze and provide insights to airlines, notably to support maintenance engineers so they can work proactively. The overall impact of this trend in the airline industry is optimizing and improving current operations and maintaining costs of providing innovative customer service.
AI is also used to identify passengers and help with the check-in operations in the airport. For example, Delta Airlines uses advanced AI ticketing kiosks and online check-in with the use of the Fly Delta mobile app. The overall impact of this trend in the industry is efficiently identifying passengers and improving check-in services.
Baggage screening is also another process that AI controls within the industry. For example, American Airlines created the Team Avatar app so passengers may quickly screen their baggage. The app allows passengers to determine the size of their baggage and to know if their baggage could carry extra costs. This trend helps the industry by facilitating and speeding baggage screening.
AI systems also help optimize aircraft fuel efficiency. AI does this by analyzing flight data, which includes identifying route distance and altitude, aircraft type and weight, and the in-flight weather. Southwest is airlines capitalizing on this trend by partnering with GE Aviation and using their flight analytics system to improve the fuel consumption of their fleet of 700 Boeing 737s. The overall impact of this trend is the optimization and monitoring of fuel supply based on distance.
AI also monitors in-flight sales and food supply by defining how many snacks and drinks they must onboard. EasyJet is capitalizing on this trend by using AI to determine if in-flight meals would be enough for all passengers onboard. It does this by analyzing attributes such as weather, types of passengers expected to be on board, and the time of the year. The trend overall improves food supply services in the aviation industry.
Lastly, AI-based virtual assistants help the aviation industry by improving overall productivity and efficiency of their pilots. It does this by reducing repetitive tasks, such as changing radio channels, reading wind forecasts, and providing position information on request. Garmin (US) capitalizes on this trend by using AI-enabled audio panels which help their pilots.
Safety and Maintenance
AI predictive analytics reduce unplanned maintenance and delayed flights in the aviation industry. It does this by managing and analyzing data from aircraft health monitoring sensors. For example, AirTran uses the AI platform known as SynapseMX to manage and utilize both historical and real-time data to better improve and speed up technical decisions within the airline.
The airline industry uses AI to efficiently requisition materials and identifies manufacturing methods for their products. On top of this, AI also helps in calculating cost constraints found within these products. From this analysis, AI can then explore all possible alterations for the product, and then it could design various alternatives from it. AI also uses machine learning to see which design works and which does not. It improves overall product design in the industry.