Digital Transformation and Artificial Intelligence in Aviation Management: A Systematic Review of Emerging Trends and Business Implications

International Journal of Emerging Research in Science, Engineering, and Management
Vol. 2, SI1 (2026), pp. 110–117
Proceedings of Selected Papers from the
National Conference on Emerging Trends in Commerce and Management
NCETCM-2K26
2026-03-30 to 2026-03-31
Vijayawada, Andhra Pradesh, India
Organized by Andhra Loyola College, Vijayawada, India
eISSN: 3107-9075

This work is licensed under a Creative Commons Attribution 4.0 International License .

Digital Transformation and Artificial Intelligence in Aviation Management: A Systematic Review of Emerging Trends and Business Implications

1Siringi Avinash, 2P V S Sairam, 3G. Sravan Kumar

1Assistant Professor, Department of BBA Aviation Management, Andhra Loyola College(Autonomous), Andhra Pradesh, Vijayawada, India
2Professor, Department of Physics, Andhra Loyola College(Autonomous), Andhra Pradesh, Vijayawada, India
3Assistant Professor, Department of Business Administration, Andhra Loyola College(Autonomous), Andhra Pradesh, Vijayawada, India

Abstract

Digital transformation and artificial intelligence (AI) are transforming the aviation management field by improving its operations, safety, and decision-making. The current study is a systematized review of current literature aimed at investigating the new trends, approaches, and business implications of AI integration in the aviation business. Fifteen peer-reviewed articles were sampled and discussed using predetermined inclusion criteria. Review of literature reveals that the major areas of application are aviation safety, predictive maintenance, air traffic management, and workforce transformation. The findings demonstrate a prevalent application of machine learning and deep learning techniques in anomaly detection, forecasting, and decision support systems. Nevertheless, there are still certain issues associated with data quality and ethical considerations, as well as system integration, which can hinder the effectiveness of AI applications in these fields, such as biases in data leading to inaccurate predictions and challenges in ensuring compliance with ethical standards. The paper concludes that the digital transformation brought about by AI can be very promising in terms of innovation and efficiency, but strategic adoption and regulatory compatibility are of paramount importance to make the implementation sustainable .

Keywords: Artificial Intelligence, Digital Transformation, Aviation Management, Machine Learning, Air Traffic Control.

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DOI: 10.66710/ijersem.v2si1.14

Open Access • Peer Reviewed Article

References

  1. M. Abubakar, O. EriOluwa, M. Teyei, and F. Al-Turjman, “AI Application in the Aviation Sector,” in 2022 International Conference on Artificial Intelligence of Things and Crowdsensing (AIoTCs), Nicosia, Cyprus, 2022, pp. 52–55. https://doi.org/10.1109/AIoTCs58181.2022.00015
  2. J. Kahraman and D. R. Şahin, “PESTLE Analysis of Digitalization in Aviation Safety,” Transport Policy, vol. 178, p. 103945, Dec. 2025. https://doi.org/10.1016/j.tranpol.2025.103945
  3. N. M. Lopes, M. Aparicio, and F. T. Neves, “Challenges and Prospects of Artificial Intelligence in Aviation: A Bibliometric Study,” Data Science and Management, vol. 8, no. 2, pp. 207–223, Nov. 2024. https://doi.org/10.1016/j.dsm.2024.11.001
  4. M. AlMarri, Z. Bahroun, and N. M. Hassan, “Artificial Intelligence for Safety and Resilience in Airport Transportation Systems: A Systematic Review of Operational, Security, and Environmental Risks,” Transportation Research Interdisciplinary Perspectives, vol. 37, p. 101961, Apr. 2026. https://doi.org/10.1016/j.trip.2026.101961
  5. L. Li, “A Review of Data Science and Artificial Intelligence Applications in Air Transportation Systems,” Artificial Intelligence for Transportation, vol. 2, p. 100023, Sep. 2025. https://doi.org/10.1016/j.ait.2025.100023
  6. A. M. Geske, D. M. Herold, and S. Kummer, “Artificial Intelligence as a Driver of Efficiency in Air Passenger Transport: A Systematic Literature Review and Future Research Avenues,” Journal of the Air Transport Research Society, vol. 3, p. 100030, Jun. 2024. https://doi.org/10.1016/j.jatrs.2024.100030
  7. C.-H. Lee, C. Wang, X. Fan, F. Li, and C.-H. Chen, “Artificial Intelligence-Enabled Digital Transformation in Elderly Healthcare Field: Scoping Review,” Advanced Engineering Informatics, vol. 55, p. 101874, Jan. 2023. https://doi.org/10.1016/j.aei.2023.101874
  8. L. Bujalance-López, L. González-Serrano, M. P. L. Sancho, and P. Talon-Ballestero, “Restaurant Revenue Management: A Systematic Literature Review and Future Challenges,” British Food Journal, vol. 127, no. 6, pp. 2169–2196, Apr. 2025. https://doi.org/10.1108/BFJ-08-2024-0816
  9. K. K. Arthur, R. K. Bannor, P. Darko, O. Hlortu, and S. Adom, “Supply Chain Intelligence: Integration of Emerging Digital Innovations to Promote Sustainable Supply Chain Practices,” Journal of Digital Economy, vol. 5, pp. 125–148, Jan. 2026. https://doi.org/10.1016/j.jdec.2026.01.002
  10. J. W. Y. Chia, W. J. C. Verhagen, J. M. Silva, and I. S. Cole, “A Review and Outlook of Airframe Digital Twins for Structural Prognostics and Health Management in the Aviation Industry,” Journal of Manufacturing Systems, vol. 77, pp. 398–417, Oct. 2024. https://doi.org/10.1016/j.jmsy.2024.09.024
  11. S. Wei, L. Wang, R. Qi, T. Feng, T. Ma, and R. Yan, “How Digital Transformation Mindfulness Affects Digital Business Model Innovation: The Moderating Role of Digital Orientation,” Business Process Management Journal, vol. 32, no. 2, pp. 710–740, Apr. 2025. https://doi.org/10.1108/BPMJ-12-2024-1185
  12. D. Poreddy, K. Radhika, and K. Deepasri, “Role of Digital Technologies in Business Management: Opportunities and Challenges,” International Journal of Emerging Research in Science Engineering and Management, vol. 2, no. si1, pp. 103–109, May 2026. https://doi.org/10.66710/ijersem.v2si1.13
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This article is part of Volume 2, Special Issue 1 (May 2026)

2026-05-17