AI Transformation in the Airline Industry: Technical Perspectives

Karnam, Vikram Sai Prasad (2025) AI Transformation in the Airline Industry: Technical Perspectives. World Journal of Advanced Research and Reviews, 26 (2). pp. 1828-1834. ISSN 2581-9615

Artificial intelligence technologies are transforming airline operations, delivering significant enhancements in operational efficiency, cost reduction, and passenger experience. The aviation sector has witnessed widespread adoption of sophisticated AI applications across critical business functions. From dynamic pricing algorithms that adjust fares based on real-time competitive intelligence to natural language processing systems that enable responsive customer support, these technologies have evolved from experimental prototypes to operational capabilities. Revenue management systems leveraging neural networks and reinforcement learning frameworks have demonstrated forecast accuracy improvements of 14-22%, while customer experience platforms employing sentiment analysis and personalization algorithms have reduced waiting times by up to 80% while maintaining high satisfaction levels. Despite compelling operational benefits, implementation challenges persist around data integration complexity, computational requirements, regulatory compliance, explainability, and model maintenance. Future technological approaches include federated learning, quantum computing applications, neuromorphic computing, and human-AI collaboration frameworks that promise to address current limitations while further extending capabilities across the aviation ecosystem.