AI for airline industries

By: Vajratiya Vajrobol, International Center for AI and Cyber Security Research and Innovations (CCRI), Asia University, Taiwan,

In the dynamic landscape of the airline industry, Artificial Intelligence (AI) stands as a transformative force, reshaping operations and enhancing various facets of air travel. Among the applications, five key areas emerge as vital in revolutionizing the industry. From predictive maintenance to personalized marketing, AI is not just a technological advancement but a strategic enabler for airlines striving to improve efficiency, reduce costs, and elevate the passenger experience.

1. Predictive Maintenance

At the forefront of AI’s impact on the airline industry is predictive maintenance, a paradigm-shifting application that employs AI algorithms to analyze sensor data and equipment performance. By preemptively identifying maintenance needs, airlines can avert unexpected breakdowns, minimizing downtime and optimizing maintenance schedules. This not only changes into substantial cost savings but also exemplifies AI’s role in elevating operational efficiency and reliability [1].

2. Route Optimization

AI’s influence extends to flight operations through route optimization, a critical component in enhancing efficiency and on-time performance. By examining historical data, weather patterns, and air traffic information, AI algorithms optimize flight routes, mitigating fuel costs and navigating around potential delays. This technological prowess empowers airlines to streamline flight planning and execution, fostering a more efficient and punctual air travel experience [2].

3. Customer Service and Chatbots

AI’s impact on customer service within the airline industry is evident through the deployment of chatbots and virtual assistants. These AI-driven systems provide real-time assistance, handling a myriad of passenger inquiries related to flight details, baggage, and more. Automating routine interactions not only reduces wait times but also enables airlines to offer 24/7 support, exemplifying AI’s role in enhancing overall customer experience and satisfaction [3].

4. Personalized Marketing and Offers

Focusing on airline marketing, AI emerges as a strategic ally, particularly in the creation of personalized campaigns and offers. By delving into customer preferences, travel patterns, and behaviors, AI tailors promotions, fostering increased customer loyalty and maximizing revenue. This personalized approach reflects AI’s capability to elevate the effectiveness of marketing strategies in a highly competitive industry [4].

5. Baggage Handling and Tracking

Airlines leverage AI to transform baggage handling and tracking systems, incorporating technologies like RFID tags and sensors. This integration enables real-time monitoring of luggage, minimizing the occurrence of lost baggage and significantly enhancing overall customer satisfaction. AI’s role in baggage management underscores its contribution to a more streamlined and reliable travel experience for passengers [5].


As the airline industry hurtles towards a future defined by technological innovation, Artificial Intelligence emerges as a linchpin, driving efficiency, reliability, and customer-centricity. From preemptive maintenance to personalized services, the five key applications outlined showcase the transformative power of AI in meeting the evolving needs of airlines. Embracing these advancements positions the industry at the forefront of innovation, promising a future where air travel is not just a journey but an experience shaped by the intelligent integration of technology.


  1. Zeldam, S. G. (2018). Automated failure diagnosis in aviation maintenance using explainable artificial intelligence (XAI) (Master’s thesis, University of Twente).
  2. Kim, J., Justin, C., Mavris, D., & Briceno, S. (2022). Data-driven approach using machine learning for real-time flight path optimization. Journal of Aerospace Information Systems, 19(1), 3-21.
  3. Sarol, S. D., Mohammad, M. F., & Rahman, N. A. A. (2022). Mobile Technology Application in Aviation: Chatbot for Airline Customer Experience. In Technology Application in Aviation, Tourism and Hospitality: Recent Developments and Emerging Issues (pp. 59-72). Singapore: Springer Nature Singapore.
  4. Guerrini, A., Ferri, G., Rocchi, S., Cirelli, M., Piña, V., & Grieszmann, A. (2023). Personalization@ scale in airlines: combining the power of rich customer data, experiential learning, and revenue management. Journal of Revenue and Pricing Management, 22(2), 171-180.
  5. Chabel, S., & Ar-Reyouchi, E. M. (2023, February). Artificial Intelligence: An Effective Protocol for Optimized Baggage Tracking and Reclaim. In Proceedings of Third International Conference on Sustainable Expert Systems: ICSES 2022 (pp. 759-771). Singapore: Springer Nature Singapore.
  6. Poonia, V., Goyal, M. K., Gupta, B. B., Gupta, A. K., Jha, S., & Das, J. (2021). Drought occurrence in different river basins of India and blockchain technology based framework for disaster management. Journal of Cleaner Production312, 127737.
  7. Gupta, B. B., & Sheng, Q. Z. (Eds.). (2019). Machine learning for computer and cyber security: principle, algorithms, and practices. CRC Press.
  8. Singh, A., & Gupta, B. B. (2022). Distributed denial-of-service (DDoS) attacks and defense mechanisms in various web-enabled computing platforms: issues, challenges, and future research directions. International Journal on Semantic Web and Information Systems (IJSWIS)18(1), 1-43.
  9. Almomani, A., Alauthman, M., Shatnawi, M. T., Alweshah, M., Alrosan, A., Alomoush, W., & Gupta, B. B. (2022). Phishing website detection with semantic features based on machine learning classifiers: a comparative study. International Journal on Semantic Web and Information Systems (IJSWIS)18(1), 1-24.

Cite As:

Vajrobol V. (2024) AI for airline industries, Insights2Techinfo, pp.1

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