Traditional military training methods face persistent challenges, including high costs, physical safety risks inherent to live field exercises, and an inability to replicate the full complexity and dynamism of contemporary combat environments. These constraints reduce the operational readiness of military forces and limit their capacity to adapt to rapidly evolving threats. Artificial Intelligence (AI) offers promising solutions to these limitations through advanced simulation, adaptive learning, and data-driven decision support. This review study investigates the applications of AI in military simulation and training, with the goals of reducing training costs, increasing simulation realism, enhancing military decision-making under pressure, and identifying opportunities and barriers to AI adoption. Using a structured qualitative review methodology, the study analyzes AI-based technologies, including Virtual Reality (VR), Augmented Reality (AR), deep learning, and reinforcement learning algorithms, applied across a range of military training contexts. Evaluation dimensions encompass decision-making speed, threat-response accuracy, and reduction of human error. Findings indicate that AI significantly improves training efficiency, realism, and safety, while challenges related to cost, cybersecurity, and organizational resistance remain. The study concludes with recommendations for localized frameworks and future research priorities, with particular relevance for resource-constrained defense organizations.