How the World’s 10 Largest Airlines Are Using AI to Soar Ahead (According to Flightradar24)

Ever wondered how airlines use artificial intelligence? After all, human pilots are still flying the planes and when you go to the airport, you can still check in with a printed boarding pass. We asked ourselves the same question and decided to dig into what one can find online about how aviation industry heavyweights use AI. You’ll be just as surprised as us, what we found out!

SITA, a company specializing in providing IT and telecom services to the aviation industry, regularly publishes a Meet the Megatrends report. In 2024 it examined 12 emerging technological, societal, traveler and economic trends that will significantly influence the travel landscape by 2033. The surprise? Only 3% of airlines said they had no plans to invest in AI technologies! This means, there must be more out there than meets the eye.

One thing we didn’t look at are airport operations, so don’t expect topics like AI-powered baggage tracking systems or crowd management and airport security to be covered. It’s really about getting into the knitty-gritty of how each of the ten biggest airlines in the world uses AI for customers and in their operations: a collection of sort of publicly available AI use cases.

American Airlines (AA/AAL)

American Airlines uses AI to enhance customer service and operations. Machine learning powers rebooking options and schedule forecasting, while the ASAPP platform automates over 50% of customer inquiries. Future plans include Generative AI for improved self-service.

Operationally, AI helps estimate crew needs, predict block times, and forecast baggage volumes. Since 2021, Smart Gating technology has cut taxi time by 17 hours daily, saving 1.4 million gallons of fuel annually. In collaboration with Google Research and others, the airline also developed an AI solution to predict and reduce aviation contrails, mitigating their climate impact.

United Airlines (UA/UAL)

United Airlines uses AI to improve customer satisfaction and operations. Their Every Flight Has a Story initiative leverages generative AI to provide context-rich delay explanations, boosting satisfaction by 6%. The In the Moment Caretool uses AI to recommend real-time compensation options, enhancing both customer and employee experiences.

In customer support, AI assists human agents through a GenAI-powered copilot that identifies contact opportunities and provides relevant information. Operationally, the Connection Saver AI minimizes delay impacts by analyzing real-time data to determine which flights to hold and alert passengers. Other AI-driven tools include a GenAI app for shift changes, LLMs for procurement, and another LLM for manager-employee communications. 

Lufthansa (LH/DLH)

Lufthansa Group leverages AI to enhance travel planning, sustainability, punctuality, and customer interactions. AI-driven initiatives include a concierge-style service for personalized travel suggestions and IBM Watson-powered customer support handling 100,000+ queries annually.

Eurowings Holidays launched Holly, an AI travel advisor, enabling instant package bookings based on personal preferences. Business travelers benefit from Swifty, an AI assistant integrated with Expedia for faster bookings. The George chatbot, launched in 2024, assists prospective pilots on the European Flight Academy website.

Lufthansa’s Customer Insight Hub utilizes AI for sentiment analysis and feedback classification. AI also optimizes airline operations, including automating NOTAM processing, enhancing pilot support via voice/chat interfaces, and streamlining disruption management through Google Cloud’s Operations Decision Support Suite (OPSD).

Lufthansa Technik, in collaboration with Microsoft, employs AI to revolutionize aircraft maintenance by extracting insights from vast unstructured data, boosting efficiency and innovation.

Delta Air Lines (DL/DAL)

Delta Air Lines leverages AI across customer service, entertainment, HR, and pricing. International travelers access the AI-powered guidance through Delta Concierge in the Fly Delta app which debuted in 2025 and currently works toward integrating with traveling services such as Uber for easy trip management. The future in-flight entertainment system scheduled for 2026 delivery will use customer viewing behavior to generate personalized content recommendations.

Deliverance of customer support occurs because AI operates a call system driven by NLP technology to automate standard questions and queries. AI-based training tools along with reinforcement learning systems help HR departments at Delta to improve job descriptions. The generative AI pricing engine of the company demonstrates robust price optimization through early positive results while simultaneously helping to determine fare rates effectively.

Southwest Airlines (WN/SWA)

Southwest Airlines utilizes AI across customer service, marketing, maintenance, and flight operations.

Its Southwest Bot chatbot uses NLP to handle customer inquiries, reducing wait times and staffing costs. AI-driven customer segmentation and personalization enable targeted promotions and flight recommendations. NLP also analyzes traveler feedback to improve services.

In maintenance, an AI tool with AIXI automates technician reports, reducing manual work. AI also analyzes historical flight data to identify anomalies, enhance safety, and optimize in-flight decisions. Additionally, Southwest had the highest percentage (8.7%) of AI-generated reviews among U.S. airlines, according to a 2024 study by Originality.ai.

FedEx (FX/FDX)

FedEx leverages AI across logistics, automation, and customer service.Its machine-learning models improve delivery time estimates by analyzing 16 million daily shipments, while generative AI enhances customer interactions and predicts shipment codes. The FedEx Surround analytics system, developed with Microsoft, provides real-time tracking and predictive insights for high-value deliveries.

Automation efforts include the Roxo same-day delivery robot, the DoraSorter intelligent sorting robot in China, and Dexterity AI-powered robotic loaders. FedEx has tested autonomous vehicles with Neolix, Aurora’s self-driving trucks, and Elroy Air’s Chaparral autonomous cargo aircraft.

AI also powers customer service through the Nina virtual assistant, handling millions of inquiries globally. In 2025, FedEx launched the Shipment Eligibility Orchestrator, an evolving AI model optimizing package routing, prioritizing healthcare shipments, and automating key logistics decisions.

Ryanair (FR/RYR)

Ryanair leverages AI across customer support, operations, and maintenance. Its chatbot, built with Amazon Lex and SageMaker, handles over 500,000 conversations monthly in seven languages, with human agents stepping in as needed. A voice-controlled chatbot for booking is also in development. AI-powered inventory forecasting, nicknamed the “panini predictor”, optimizes in-flight food and beverage stock based on demand patterns.

For operations, Ryanair uses Optifly to automate and optimize flight schedules, increasing seat capacity by 38%. Predictive maintenance, powered by AWS, analyzes millions of flight data points to foresee mechanical issues up to four days in advance. AI-driven aircraft allocation optimizes fleet efficiency, saving millions annually.

Ryanair also employs machine learning on the New Relic Digital Intelligence Platform to monitor system performance, quickly diagnose issues, and streamline operations across the company.

Air China (CA/CCA)

The implementation of AI allows Air China to enhance their flight scheduling while improving fuel efficiency and resulting in reduced expenses alongside environmental impact. Real-time flight information together with customized travel advice comes from AI-powered virtual assistants and chatbots provided by the airline to its customers. The airline depends on AI-based predictive maintenance which tracks aircraft health to stop mechanical failures thus enhancing safety measures.

Turkish Airlines (TK/THY)

The IT subsidiary of Turkish Airlines named Turkish Technology leads efforts to digitalize the airline through technological advancements in order to deliver better passenger experiences by 2033. AI serves as the backbone for delivering personalized marketing services and revenue management operations and dynamic pricing operations as well as customer support platforms

Their data science team develops AI-driven solutions, including custom LLMs for document Q&A, Passenger Name Record (PNR) analysis, and optimization models for resource allocation and pricing. AI-powered tools like TK Assistant and Boti on WhatsApp assist with flight searches, check-ins, and travel queries. A creative AI campaign, Fly by Sign, used Instagram chatbots to provide personalized travel recommendations based on users’ star signs, offering promo codes for discounted tickets.

IndiGo (6E/IGO)

IndiGo, India’s leading airline, utilizes AI to enhance customer experience and operations. Its WhatsApp AI chatbot, 6Eskai, built with Microsoft and GPT-4, simplifies bookings, check-ins, seat selection, and flight status inquiries. It supports 10+ languages, mimics human behavior, and adds humor for engaging interactions.

The airline’s website chatbot, Dottie, assists with common queries like flight changes and cancellations, with live agents available if needed. IndiGo’s app integrates AI for personalized hotel and taxi booking recommendations. For operations, IndiGo leverages Skywise for predictive maintenance and an AI-powered risk management platform to analyze security threats, ensuring safer air travel.

Takeaways 

The world’s top airlines heavily invest in building their own AI and data science teams, while also partnering with external experts to develop or acquire AI solutions. Their strategy focuses on developing internal capabilities and buying technology when needed. Most airlines have also migrated to cloud-based environments for better data management and analysis.

AI use cases in airline operations are more varied and complex compared to customer support, with chatbots and virtual assistants being the most common application. Operational AI is more challenging due to the diverse systems and data formats involved. Airlines likely have many more AI projects in development or testing that aren’t publicly disclosed, with some potentially failing or being too small to publicize. This represents only the visible part of their AI efforts.