Artificial Intelligence and Strategic Innovation in Contemporary Defense Systems
DOI:
https://doi.org/10.59890/ijir.v4i9.5Keywords:
Artificial Intelligence, Strategy Management, Strategic Innovation, Defense Systems, SEM-PLSAbstract
The transformation of defense technology demands that military organizations integrate artificial intelligence (AI) into strategy management to improve the innovation and adaptability of defense systems. This study analyzes the influence of the use of AI on strategic innovation and the effectiveness of contemporary defense systems. An explanatory quantitative approach was used through a survey of 186 purposively selected defense and strategic management professionals. Data were collected using a structured questionnaire and analyzed with Structural Equation Modeling–Partial Least Squares (SEM-PLS). The results show that the use of AI has a significant positive effect on strategic innovation and the effectiveness of defense systems, while strategic innovation mediates these relationships. The findings confirm that the integration of AI in strategic planning strengthens the adaptability, quality of decision-making, and responsiveness of defense organizations.
References
Bécue, A., Gama, J., & Brito, P. Q. (2024). AI’s effect on innovation capacity in the context of Industry 5.0: A scoping review. Artificial Intelligence Review, 57, Article 215. https://doi.org/10.1007/s10462-024-10864-6
Becker, J.-M., Cheah, J.-H., Gholamzade, R., Ringle, C. M., & Sarstedt, M. (2023). PLS-SEM's most wanted guidance. International Journal of Contemporary Hospitality Management, 35(1), 321–346. https://doi.org/10.1108/IJCHM-04-2022-0474
Belhadi, A., Mani, V., Kamble, S. S., Khan, S. A. R., & Verma, S. (2024). Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: An empirical investigation. Annals of Operations Research, 333, 627–652. https://doi.org/10.1007/s10479-021-03956-x
Biloslavo, R., Edgar, D., Aydin, E., & Bulut, C. (2025). Artificial intelligence (AI) and strategic planning process within VUCA environments: A research agenda and guidelines. Management Decision, 63(10), 3599–3624. https://doi.org/10.1108/MD-10-2023-1944
Blanchard, A., Thomas, C., & Taddeo, M. (2025). Ethical governance of artificial intelligence for defence: Normative tradeoffs for principle to practice guidance. AI & Society, 40, 185–198. https://doi.org/10.1007/s00146-024-01866-7
Enholm, I. M., Papagiannidis, E., Mikalef, P., & Krogstie, J. (2022). Artificial intelligence and business value: A literature review. Information Systems Frontiers, 24, 1709–1734. https://doi.org/10.1007/s10796-021-10186-w
Fosso Wamba, S., Queiroz, M. M., Pappas, I. O., & Sullivan, Y. (2024). Artificial intelligence capability and firm performance: A sustainable development perspective by the mediating role of data-driven culture. Information Systems Frontiers, 26, 2189–2203. https://doi.org/10.1007/s10796-023-10460-z
Ghosh, S. (2025). Developing artificial intelligence (AI) capabilities for data-driven business model innovation: Roles of organizational adaptability and leadership. Journal of Engineering and Technology Management, 75, 101851. https://doi.org/10.1016/j.jengtecman.2024.101851
Hair, J. F., Sarstedt, M., Ringle, C. M., Sharma, P. N., & Liengaard, B. D. (2024). Going beyond the untold facts in PLS-SEM and moving forward. European Journal of Marketing, 58(13), 81–106. https://doi.org/10.1108/EJM-08-2023-0645
Hoijtink, M. (2022). ‘Prototype warfare’: Innovation, optimisation, and the experimental way of warfare. European Journal of International Security, 7(3), 322–336. https://doi.org/10.1017/eis.2022.12
Horowitz, M. C., & Kahn, L. (2024). Bending the automation bias curve: A study of human and AI-based decision making in national security contexts. International Studies Quarterly, 68(2), sqae020. https://doi.org/10.1093/isq/sqae020
Jarrahi, M. H., Kenyon, S., Brown, A., Donahue, C., & Wicher, C. (2023). Artificial intelligence: A strategy to harness its power through organizational learning. Journal of Business Strategy, 44(3), 126–135. https://doi.org/10.1108/JBS-11-2021-0182
Kim, J.-S., & Seo, D. (2023). Foresight and strategic decision-making framework from artificial intelligence technology development to utilization activities in small-and-medium-sized enterprises. Foresight, 25(6), 769–787. https://doi.org/10.1108/FS-06-2022-0069
King, A. (2024). Digital targeting: Artificial intelligence, data, and military intelligence. Journal of Global Security Studies, 9(2), ogae009. https://doi.org/10.1093/jogss/ogae009
Kock, F., Berbekova, A., & Assaf, A. G. (2021). Understanding and managing the threat of common method bias: Detection, prevention and control. Tourism Management, 86, 104330. https://doi.org/10.1016/j.tourman.2021.104330
Kusumasari, B., & Yahya, B. N. (2025). Algorithmic governance and AI: Balancing innovation and oversight in Indonesian policy analyst. AI & Society, 40, 2479–2491. https://doi.org/10.1007/s00146-024-02002-1
Lee, C.-E., Baek, J., Son, J., & Ha, Y.-G. (2023). Deep AI military staff: Cooperative battlefield situation awareness for commander’s decision making. The Journal of Supercomputing, 79(6), 6040–6069. https://doi.org/10.1007/s11227-022-04882-w
Liang, X., Tian, N., Lopes da Silva, D., Scarazzato, L., Karim, Z. A., & Guiberteau Ricard, J. (2025). Trends in world military expenditure, 2024. Stockholm International Peace Research Institute. https://doi.org/10.55163/AVEC8366
Ma, L., & Chang, R. (2025). How big data analytics and artificial intelligence facilitate digital supply chain transformation: The role of integration and agility. Management Decision, 63(10), 3557–3598. https://doi.org/10.1108/MD-10-2023-1822
Mikalef, P., & Gupta, M. (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, 58(3), 103434. https://doi.org/10.1016/j.im.2021.103434
Mikalef, P., Lemmer, K., Schaefer, C., Ylinen, M., Fjørtoft, S. O., Torvatn, H. Y., Gupta, M., & Niehaves, B. (2023). Examining how AI capabilities can foster organizational performance in public organizations. Government Information Quarterly, 40(2), 101797. https://doi.org/10.1016/j.giq.2022.101797
Mishra, S., Ewing, M. T., & Cooper, H. B. (2022). Artificial intelligence focus and firm performance. Journal of the Academy of Marketing Science, 50, 1176–1197. https://doi.org/10.1007/s11747-022-00876-5
Neiroukh, S., Emeagwali, O. L., & Aljuhmani, H. Y. (2025). Artificial intelligence capability and organizational performance: Unraveling the mediating mechanisms of decision-making processes. Management Decision, 63(10), 3501–3532. https://doi.org/10.1108/MD-10-2023-1946
Parisini, E. (2025). Governing artificial intelligence in the defence sector: A comparative analysis of EU and US institutions. Global Public Policy and Governance, 5, 114–138. https://doi.org/10.1007/s43508-025-00115-x
Ruokonen, M., & Ritala, P. (2024). How to succeed with an AI-first strategy? Journal of Business Strategy, 45(6), 396–404. https://doi.org/10.1108/JBS-08-2023-0178
Schmid, S., Riebe, T., & Reuter, C. (2022). Dual-use and trustworthy? A mixed methods analysis of AI diffusion between civilian and defense R&D. Science and Engineering Ethics, 28, Article 12. https://doi.org/10.1007/s11948-022-00364-7
Sjödin, D., Parida, V., Palmié, M., & Wincent, J. (2021). How AI capabilities enable business model innovation: Scaling AI through co-evolutionary processes and feedback loops. Journal of Business Research, 134, 574–587. https://doi.org/10.1016/j.jbusres.2021.05.009




