Conversational AI for Booking & Support: Handles complex queries (e.g., multi-city rebooking) via natural language processing (NLP).

Voice-Enabled Assistants: Integrates with smart speakers (e.g., Alexa) for hands-free flight updates or check-ins.

Omnichannel Support: Integrates customer interactions across call centers, chatbots, email, and social media for seamless service.

AI-Powered Recommendations: Pega Decisioning uses real-time data (past bookings, loyalty status, preferences) to offer personalized upsells (e.g., seat upgrades, lounge access).

Dynamic Pricing & Offers: Airlines use Pega to tailor promotions based on customer behavior, increasing ancillary revenue.

Loyalty Program Optimization: Enhances frequent flyer programs by predicting customer needs and rewarding engagement.

Automated Ticketing & Issue Resolution: Pega’s case management helps airlines handle customer inquiries, complaints, and disruptions (e.g., flight delays, cancellations) by automating workflows and suggesting resolutions.

Omnichannel Support: Integrates customer interactions across call centers, chatbots, email, and social media for seamless service.

Self-Service Portals: Passengers can rebook flights, request refunds, or manage loyalty points via AI-powered self-service options.

Crew & Staff Management: Automates crew scheduling, fatigue management, and compliance with regulations.

Baggage Claim Automation: Streamlines lost/delayed baggage claims by tracking cases and automating compensation processes.

Regulatory Compliance: Ensures adherence to aviation regulations (e.g., EU261 compensation rules) through automated policy enforcement.

Automated Survey Generation: Sends personalized post-flight feedback requests via preferred channels.

Social Media Sentiment Analysis: Monitors passenger sentiment on Twitter/Instagram to address complaints proactively.

AI-Generated Messages: Sends tailored post-flight emails based on trip details (e.g., "Hope you enjoyed your business class flight to Paris!").

Proactive Aircraft Maintenance: Uses IoT and AI to predict engine failures or part malfunctions before they occur, reducing unplanned downtime.

Automated Work Orders: Generates maintenance requests automatically based on real-time sensor data from aircraft.

Component Lifespan Forecasting: Uses machine learning to predict when parts (e.g., landing gear, hydraulic pumps) will fail based on historical wear-and-tear data.

Fuel Optimization: Analyzes routes, payload, and weather to suggest fuel-efficient flight paths.

Proactive Aircraft Maintenance: Uses IoT and AI to predict engine failures or part malfunctions before they occur, reducing unplanned downtime.

Weather Disruption Response: AI recommends optimal reroutes or alternate airports during storms.

Dynamic Pricing Strategies: Uses AI to adjust fares based on demand, competitor pricing, and customer profiles.

Fraud Prevention: Detects fraudulent bookings or loyalty point redemptions using predictive analytics.

AI-Priced Fare Classes: Pega analyzes demand signals (searches, bookings, competitor prices) and adjusts fare buckets (Y/B/M classes) dynamically.

AI-Based Crew Pairing: Optimizes crew schedules while considering legal rest periods, qualifications, and cost efficiency.

Automated Fatigue Monitoring: Ensures compliance with aviation labor laws by tracking crew duty hours and suggesting adjustments.

Cost-Efficient Reserve Crew Management: Uses historical no-show rates, weather, and events (e.g., sports finals) to calculate optimal reserve crew numbers.