AI is quickly becoming a game changer for the aviation industry. Global air traffic has surpassed pre-pandemic levels, and industry revenues and profits are at record highs. Key players such as airports, airlines, travel aggregators and global distribution systems are collecting vast quantities of data that’s both rich with possibilities and complex to manage. AI has the potential to transform customer experience, improve safety and security, drive operational efficiency, boost profitability and much more, but businesses need a robust AI strategy and data governance approach to capitalize on that potential.
While the aviation industry is experiencing record demand and revenues, it continues to face numerous challenges, from geopolitical instability to rising fuel and operational costs, supply chain disruptions, talent shortages and IT infrastructure strain. AI is introducing new opportunities and helping aviation companies manage these challenges alongside sustainable growth.
The aviation market is vast, involving many connected participants across the globe. Some of these ecosystem players, such as travel agents, reservation systems, airport retailers and digital payments systems, interface with consumers. Others operate behind the scenes, manufacturing equipment and providing technology and services to enable air travel. In the age of AI, collaboration between aviation companies is becoming more crucial than ever. To be AI-ready, these organizations need to be able to connect with each other and exchange data securely, in real time, to further their mutual goals. This collaboration and data exchange will be key to unlocking AI’s potential in aviation.
Every day, we’re seeing new AI use cases arise in the industry, and the future of aviation will undoubtedly be transformed by AI across operations, customer experience, security and many other domains.
3 use cases for AI in the aviation industry
Collectively, the aviation ecosystem supports billions of passengers every year. Delivering great customer experiences is a top priority across the market, as is sustainability. The industry collects huge volumes of data from diverse sources including aircraft sensors, flight operations, airport video feeds, weather forecasts, passengers and supply chains. Managing and integrating all this data has become complex but will be essential to AI success. Aviation companies also need the right infrastructure in the right locations to support real-time data analysis and insights.
Let’s look at three ways AI is already being used in aviation:
Predictive maintenance
Unexpected maintenance problems on aircraft or airport equipment can cause operational delays for airlines and airports alike. Being able to better anticipate these maintenance issues can prevent unscheduled downtime and travel interruptions. With AI-powered predictive maintenance, companies can monitor aircraft, baggage handling systems, HVAC units and other equipment to track patterns and forecast repairs.
Predictive maintenance requires low-latency data processing in data centers positioned near the data source. By doing AI inference at the edge, airports can process real-time data from equipment like baggage handling systems with ultra-low latency to enable faster predictions and more proactive maintenance.
Passenger flow management
Have you ever wondered how airports manage the complex flow of traffic inside? They collect real-time data from sensors, video cameras and flight schedules that can be integrated and processed using AI. With the help of AI, they can forecast passenger traffic patterns and possible congestion points, and then use that information to optimize traffic and improve airport efficiency.
Real-time analytics for passenger flow management requires the seamless integration of AI systems with airport data sources. As with predictive maintenance, deploying AI workloads close to the data source ensures faster responses during peak travel times and enables dynamic staffing adjustments to keep passenger traffic flowing and improve customer experiences.
AI-driven safety and security
AI can be used to enhance aviation security in several ways:
- Streamlining passenger screening processes with biometric verification systems
- Detecting prohibited items faster when they go through X-ray and CT scanners
- Monitoring access points with real-time video surveillance to identify unusual behavior and potential threats quickly
- Automating more aspects of threat detection
Because AI-powered security systems often involve sensitive passenger data, it’s crucial that AI systems are designed to protect data privacy and ensure regulatory compliance.
Vueling Airlines wanted to use emerging technologies such as AI, sensors, and facial and voice recognition to enrich customer service delivery. Using Equinix Managed Services and interconnection solutions, they were able to deliver more dependable service and enhance customer experience with scheduling flexibility and up-to-the-minute information alerts.
Read the Case StudyChallenges and opportunities for the aviation industry
The examples above are just a few among many emerging use cases for AI in the aviation industry. Many others are either in development or already in use, such as dynamic pricing, customer service automation, fuel efficiency optimization and personalized passenger services. No doubt, there will be many more to come.
As companies begin to explore new opportunities with AI, they should identify the use cases that make sense for their business and run a pilot program. Trial and error are inevitable, but experienced AI partners and service providers can help. As organizations build an AI strategy, they’ll need to tackle challenges around costs, performance, regulatory compliance and skills shortages, as well as the sustainable and responsible use of AI. They should also plan on providing education to address cultural resistance to AI and help employees see it as a tool rather than a threat to their jobs.
Partnering for AI success
When it comes to deploying high-performance AI infrastructure, external infrastructure and service providers can help companies in the aviation industry get a head start. Putting AI infrastructure in the right edge locations, near the data source, is crucial to enable low-latency connectivity for real-time analytics and AI-driven decision-making. With a global presence in 76 metros across 36 countries, Equinix high-performance data centers can help aviation companies around the world deploy repeatable AI solutions wherever they are, while maintaining compliance with regional regulations. As the data volume of AI workloads grows, companies can easily scale their operations.
Deploying AI infrastructure where the richest aviation and AI ecosystems already exist empowers collaboration and value exchange between industry participants, which is essential for AI success. Inside Equinix, aviation companies can connect directly to thousands of clouds, network service providers and AI solution providers already on our platform. That’s why companies like SunExpress joined Equinix, for secure, low-latency connectivity to aviation ecosystem partners and cloud environments. Equinix helped SunExpress improve flight operations efficiency and provide more dependable service. Air Canada, likewise, chose Equinix to build a “digital backbone” that keeps their passengers, partners and governments connected for the best end-user experience possible.
By leveraging Equinix’s global platform, airports, airlines and other aviation companies can unlock the full potential of AI to enhance operational efficiency, improve passenger experiences and ensure safety.
To learn more about the role of high-performance data centers to power AI-driven innovation, download our white paper The engine of AI powering innovation at scale.
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