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Artificial intelligence, or AI, is becoming an important part of modern defense systems. A 2026 study by Ferdinand Hasudungan Siagian, Nefra Firdaus, and Harri Dolli Hutabarat from the Republic of Indonesia Defense University and the Army Polytechnic found that AI can strengthen strategic innovation and improve the effectiveness of defense organizations. The findings are important because they show that the value of AI does not come only from advanced technology, but also from how well an organization uses that technology to improve strategy, planning, and decision-making.
The rapid development of AI has
changed how defense organizations respond to complex security challenges. AI is
now used to support intelligence analysis, situational awareness,
decision-making, cybersecurity, autonomous systems, and defense resource management.
In a changing global security environment, the ability to use digital
technology effectively has become an important factor in improving adaptability
and operational performance.
Previous studies have discussed
AI in defense from technical, ethical, institutional, and policy perspectives.
However, fewer studies have clearly explained how AI can lead to strategic
innovation and then improve defense system effectiveness. This study focused on
the relationship between AI utilization, strategic innovation, and the
effectiveness of contemporary defense systems.
The researchers used a
quantitative approach involving 186 professionals working in defense and
strategic management. The respondents were selected because they had relevant
knowledge and experience in defense organizations, strategic planning,
technology, and management. Data were collected through a structured
questionnaire and analyzed using Partial Least Squares Structural Equation
Modeling, or PLS-SEM. This method helped the researchers examine both
direct and indirect relationships between AI, innovation, and defense
effectiveness.
Most respondents had strong
professional and educational backgrounds. They worked in defense operations,
strategic planning and policy, defense technology, AI and data, as well as
defense research and education. This made the sample relevant to the study
because the respondents were familiar with both organizational strategy and the
use of technology in defense.
The study found that AI
utilization had a strong positive effect on strategic innovation. The
relationship had a coefficient of β = 0.680, making it the strongest
direct relationship in the research model. In simple terms, the more
effectively defense organizations use AI in strategic activities, the more
likely they are to improve their planning, information analysis,
decision-making processes, and organizational capabilities.
AI also had a positive and
significant direct effect on defense system effectiveness, with a coefficient
of β = 0.281. This means AI can help defense organizations process
information faster, improve situational awareness, use resources more
efficiently, and respond more effectively to changing conditions. However, this
direct effect was smaller than AI’s effect on strategic innovation.
Strategic innovation also played
an important role. It had a positive effect on defense system effectiveness,
with a coefficient of β = 0.522. This finding suggests that advanced
technology alone is not enough. Defense organizations also need to update their
strategies, improve coordination, adjust resource allocation, and develop
better ways of responding to new challenges.
One of the most important
findings was the role of strategic innovation as a bridge between AI and
defense effectiveness. The indirect effect of AI through strategic innovation
reached β = 0.355, while the total effect of AI on defense system
effectiveness was β = 0.636. This shows that AI creates greater value
when it first encourages strategic and organizational change. In other words,
buying or adopting AI technology is not enough. Organizations need to turn that
technology into better strategies and working processes.
The research model explained 46.2
percent of the variation in strategic innovation and 55.1 percent of the
variation in defense system effectiveness. All four hypotheses in the study
were supported by the data. The results consistently showed that AI supports
innovation, innovation supports effectiveness, and AI can also improve
effectiveness through strategic innovation.
The researchers also stressed that successful AI transformation depends on more
than software, algorithms, or digital infrastructure. Human skills, data
quality, organizational readiness, trust in AI systems, and technology
governance also matter. These factors influence whether AI becomes a useful
strategic capability or remains only a technical tool.
For defense leaders and
policymakers, the findings suggest that investment in AI should be combined
with investment in people and organizations. Defense institutions need stronger
human resource skills, better data integration, improved analytical capabilities,
flexible planning systems, organizational learning, and effective human–AI
decision-making mechanisms. Good governance is also necessary to ensure that AI
is used with accountability, transparency, security, and proper oversight.
Overall, the study shows that AI can support more adaptive and effective
defense systems, especially when it is integrated into strategic planning and
organizational innovation. The main message is clear: the success of AI in
defense depends not only on having advanced technology, but also on the ability
of organizations to use it wisely, strategically, and responsibly.
Author Profiles
Ferdinand Hasudungan Siagian
is affiliated with the Republic of Indonesia Defense University. The
article lists him as the corresponding author.
Nefra Firdaus is
affiliated with the Army Polytechnic.
Harri Dolli Hutabarat is
affiliated with the Republic of Indonesia Defense University.
Research Source
Siagian, F. H., Firdaus, N.,
& Hutabarat, H. D. (2026). “Artificial Intelligence and Strategic
Innovation in Contemporary Defense Systems.” International Journal of
Integrative Research (IJIR), Vol. 4, No. 9, pp. 775–794.
DOI: https://doi.org/10.59890/ijir.v4i9.5
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