SavedAdd your journal

Journals / Yönetim Bilişim Sistemleri Dergisi / 2026 / Cilt: 12 Sayı: 1

AI-POWERED DIGITAL TRANSFORMATION ROADMAP IN THE AVIATION SECTOR

HAVACILIK SEKTÖRÜNDE YAPAY ZEKÂ DESTEKLİ DİJİTAL DÖNÜŞÜM YOL HARİTASI

Samet Gürsev(Turkish Technology)0000-0003-2609-4095
Pages
64–79
Publication Date
2026-06-25
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The proposed roadmap is aligned with Industry 4.0 principles, offers original contributions to the academic literature, and provides strategic guidance for practitioners.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Digital transformation has become a strategic imperative for the aviation industry due to increasing operational complexity, stringent security requirements, and pressures arising from global competition.
📊
Key Findings & Data:Technologies such as artificial intelligence (AI), big data analytics, the Internet of Things (IoT), and Industry 4.0 offer significant opportunities in areas including maintenance, operations, decision support, and passenger experience.
💡
Conclusion & Impact:The proposed roadmap is aligned with Industry 4.0 principles, offers original contributions to the academic literature, and provides strategic guidance for practitioners.
🔬Design:Review & Systematic Survey
📍Scope:Comprehensive Sample
⚙️Variables:Dijital Dönüşüm · Havacılık Sektörü · Yapay Zekâ

Abstract

Digital transformation has become a strategic imperative for the aviation industry due to increasing operational complexity, stringent security requirements, and pressures arising from global competition. Technologies such as artificial intelligence (AI), big data analytics, the Internet of Things (IoT), and Industry 4.0 offer significant opportunities in areas including maintenance, operations, decision support, and passenger experience. However, as the aviation industry is highly regulated and safety-critical, generic digital transformation models fail to adequately reflect the sector’s unique constraints. This study aims to develop an aviation-specific, governance-focused, and AI-enabled digital transformation roadmap. Within the scope of the research, a holistic approach is adopted, incorporating a global literature review, implementation examples spanning all continents, and corporate case analyses. As a result of the study, digital transformation in aviation is demonstrated to be a phased, capability-based process grounded in human–AI collaboration. The proposed roadmap is aligned with Industry 4.0 principles, offers original contributions to the academic literature, and provides strategic guidance for practitioners.

Özet

Dijital dönüşüm, artan operasyonel karmaşıklık, yüksek güvenlik gereksinimleri ve küresel rekabet baskıları nedeniyle havacılık sektörü için stratejik bir zorunluluk hâline gelmiştir. Yapay zekâ (YZ), büyük veri analitiği, Nesnelerin İnterneti (IoT) ve Endüstri 4.0 teknolojileri; bakım, operasyon, karar destek ve yolcu deneyimi gibi alanlarda önemli fırsatlar sunmaktadır. Bununla birlikte, havacılık sektörü yüksek düzeyde regülasyona tabi ve güvenlik-kritik bir alan olduğundan, genel dijital dönüşüm modelleri bu sektörün özgün kısıtlarını yeterince yansıtmamaktadır. Çalışmanın amacı havacılık sektörüne özgü, yönetişim odaklı ve yapay zekâ destekli bir dijital dönüşüm yol haritası geliştirmeyi sağlamaktır. Araştırma kapsamında küresel literatür taraması, tüm kıtaları kapsayan uygulama örnekleri ve kurumsal vaka analizleri bütüncül bir yaklaşımla ele alınmıştır. Çalışma sonucunda, havacılıkta dijital dönüşümün aşamalı, yetkinlik temelli ve insan–YZ iş birliğine dayalı bir süreç olduğu ortaya konulmuştur. Önerilen yol haritası, Endüstri 4.0 ilkeleri ile uyumlu olup, akademik literatüre özgün katkılar sunmakta ve uygulayıcılara stratejik rehberlik sağlamaktadır.

🔖

Cite This Article

Gürsev, S. (2026). AI-POWERED DIGITAL TRANSFORMATION ROADMAP IN THE AVIATION SECTOR. Yönetim Bilişim Sistemleri Dergisi, Cilt: 12 Sayı: 1, 64–79. https://ajindex.com/articles/1578453

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (33)

  1. Agarwal, R., & Dhar, V. (2014). Big data, data science, and analytics: The opportunity and challenge for information systems research. Information Systems Research, 25(3), 443–448. https://doi.org/10.1287/isre.2014.0546
  2. Aghion, P., Jones, B. F., & Jones, C. I. (2019). Artificial intelligence and economic growth. Journal of Economic Perspectives, 33(2), 3–30. https://doi.org/10.1257/jep.33.2.3
  3. Airbus. (2022). Digital transformation in aerospace manufacturing. Airbus Industry Report.
  4. Ardito, L., Messeni Petruzzelli, A., Panniello, U., & Garavelli, A. C. (2019). Towards Industry 4.0: Mapping digital technologies for supply chain management–marketing integration. Business Process Management Journal, 25(2), 323–346. https://doi.org/10.1108/BPMJ-04-2017-0088
  5. Baines, T., Ziaee Bigdeli, A., Bustinza, O. F., Shi, V. G., Baldwin, J., & Ridgway, K. (2017). Servitization: Revisiting the state-of-the-art and research priorities. International Journal of Operations & Production Management, 37(2), 256–278. https://doi.org/10.1108/IJOPM-06-2015-0312
  6. Bharadwaj, A., El Sawy, O. A., Pavlou, P. A., & Venkatraman, N. (2013). Digital business strategy: Toward a next generation of insights. MIS Quarterly, 37(2), 471–482. https://doi.org/10.25300/MISQ/2013/37:2.3
  7. Bresciani, S., Ferraris, A., & Del Giudice, M. (2018). The management of organizational ambidexterity through alliances in a new context of analysis. Technological Forecasting and Social Change, 136, 138–148. https://doi.org/10.1016/j.techfore.2017.03.002
  8. Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116.
  9. Deloitte. (2022). Aviation industry digital transformation outlook. Deloitte Insights.
  10. Dubey, R., Gunasekaran, A., Childe, S. J., Blome, C., & Papadopoulos, T. (2019). Big data and predictive analytics and manufacturing performance: Integrating institutional theory, resource-based view and big data culture. British Journal of Management, 30(2), 341–361. https://doi.org/10.1111/1467-8551.12355
  11. European Union Aviation Safety Agency. (2020). Annual Safety Review 2020. European Union Aviation Safety Agency. https://www.easa.europa.eu/en/annual-safety-review-2020
  12. Fornell, C., Rust, R. T., & Dekimpe, M. G. (2010). The effect of customer satisfaction on consumer spending growth. Journal of Marketing Research, 47(1), 28–35. https://doi.org/10.1509/jmkr.47.1.28
  13. Frank, A. G., Dalenogare, L. S., & Ayala, N. F. (2019). Industry 4.0 technologies: Implementation patterns in manufacturing companies. International Journal of Production Economics, 210, 15–26. https://doi.org/10.1016/j.ijpe.2019.01.004
  14. Gawer, A., & Cusumano, M. A. (2014). Industry platforms and ecosystem innovation. Journal of Product Innovation Management, 31(3), 417–433. https://doi.org/10.1111/jpim.12105
  15. GE Aviation. (2021). Title of the report or document [Report]. GE Aviation. https://www.geaviation.com/ Gobble, M. M. (2018). Digitalization, digitization, and innovation. Research-Technology Management, 61(4), 56–59. https://doi.org/10.1080/08956308.2018.1471280
  16. Hess, T., Matt, C., Benlian, A., & Wiesböck, F. (2016). Options for formulating a digital transformation strategy. MIS Quarterly Executive, 15(2), 123–139. Ransbotham
  17. International Civil Aviation Organization. (2020). ICAO Safety Report: 2020 edition (Safety Report No. 2020). Montreal, Quebec, Canada: International Civil Aviation Organization. https://www.icao.int/safety/Documents/ICAO_SR_2020_final_web.pdf
  18. Kane, G. C., Palmer, D., Phillips, A. N., Kiron, D., & Buckley, N. (2015). Strategy, not technology, drives digital transformation. MIT Sloan Management Review, 14(1), 1–25.
  19. Kshetri, N. (2021). Artificial intelligence in developing economies. Computer, 54(5), 42–50. https://doi.org/10.1109/MC.2021.3062996
  20. McAfee, A., Brynjolfsson, E., Davenport, T. H., Patil, D., & Barton, D. (2012). Big data: The management revolution. Harvard Business Review, 90(10), 60–68.
  21. Nambisan, S., Lyytinen, K., Majchrzak, A., & Song, M. (2017). Digital innovation management: Reinventing innovation management research in a digital world. MIS Quarterly, 41(1), 223–238. https://doi.org/10.25300/MISQ/2017/41:1.03
  22. Parasuraman, R., Sheridan, T. B., & Wickens, C. D. (2000). A model for types and levels of human interaction with automation. IEEE Transactions on systems, man, and cybernetics-Part A: Systems and Humans, 30(3), 286-297.Ross, J. W.,
  23. Schwab, K. (2016). The fourth industrial revolution. World Economic Forum.
  24. Siau, K., & Wang, W. (2018). Building trust in artificial intelligence. Journal of Database Management, 29(1), 1–8. https://doi.org/10.4018/JDM.2018010101
  25. Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350. https://doi.org/10.1002/smj.640
  26. Teece, D. J. (2018). Business models and dynamic capabilities. Long Range Planning, 51(1), 40–49. https://doi.org/10.1016/j.lrp.2017.06.007
  27. Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118–144. https://doi.org/10.1016/j.jsis.2019.01.003
  28. Warner, K. S. R., & Wäger, M. (2019). Building dynamic capabilities for digital transformation: An ongoing process of strategic renewal. Long Range Planning, 52(3), 326–349. https://doi.org/10.1016/j.lrp.2018.12.001
  29. World Economic Forum. (2021). The Global Risks Report 2021. https://www.weforum.org/
  30. Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). Sage Publications. Zhang, Y., Ren, S., Liu, Y., & Si, S. (2017). A big data analytics architecture for Industry 4.0. Journal of Manufacturing Systems, 46, 1–10. https://doi.org/10.1016/j.jmsy.2017.08.001
  31. Zhou, K., Liu, T., & Zhou, L. (2015). Industry 4.0: Towards future industrial opportunities. International Journal of Automation and Computing, 12(4), 396–404. https://doi.org/10.1007/s11633-015-0893-4
  32. Zuboff, S. (2019). The age of surveillance capitalism. PublicAffairs ISBN: 978-1610395694 pp704
  33. Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). Sage Publications. Zhang, Y., Ren, S., Liu, Y., & Si, S. (2017). A big data analytics architecture for Industry 4.0. Journal of Manufacturing Systems, 46, 1–10. https://doi.org/10.1016/j.jmsy.2017.08.001