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This dissertation investigates the impact of Artificial Intelligence on decision-making
within the Military Administration, focusing on its influence on management processes,
specific applications for the Defense Sector, and the role of Large Language Models in
decision support. Based on a Systematic Literature Review and complemented by interviews
with military and private sector experts, the research shows that AI profoundly redefines how
organizations operate and make decisions.
The results indicate that Artificial Intelligence optimizes operational efficiency and
competitiveness by automating routine and complex tasks, allowing human resources to focus
on activities of greater strategic value. In the context of the Military Administration, Artificial
Intelligence is proving crucial for optimizing administrative processes, such as budget
management and document preparation. It has a growing role in decision support systems and
field operations through autonomous and semi-autonomous systems. Large Language Models,
in particular, demonstrate the ability to simplify the creation of complex documents,
summarize information, and analyze large volumes of data, providing insights that support
more informed and accurate decisions.
However, the implementation of Artificial Intelligence is not without significant
challenges. These include the need to qualify and train Human Resources with new digital and
critical skills, managing ethical issues such as the impact on employment, human dignity, and
data privacy, and mitigating risks associated with information security and model bias.
Technological infrastructure, especially the choice of on-premise solutions in the defense
sector, requires considerable investment and the definition of usage control policies to prevent
risks. Change management is a critical factor in the successful adoption of Artificial
Intelligence, and it is essential to involve users from the start of the process. In conclusion, the
positive impact of Artificial Intelligence on the Military Administration will depend on a
balanced approach, combining technological innovation with prudent risk management and
valuing human judgment.
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