The safety of transporting dangerous goods in military logistics is an integral component of the state security system, as it encompasses operational, organizational, legal, and informational aspects and involves risks with potentially far-reaching social and environmental consequences. The aim of this article is to analyze the determinants of the safety of such transports from a systemic perspective, with particular emphasis on data management and the application of artificial intelligence as tools supporting risk assessment and decision-making processes. The analysis is embedded in the regulatory framework arising from Directive 2008/68/EC and the ADR/RID/ADN regimes, implemented in Poland by the Act of 19 August 2011 on the transport of dangerous goods, as well as in the risk management approach consistent with ISO 31000. The study demonstrates that location, planning, and event data should be treated as a safety resource, as their completeness, consistency, timeliness, and integrity determine the effectiveness of transport monitoring and the quality of safety-related decisions under conditions of elevated risk. The application of artificial intelligence methods enables the automated analysis of large data sets, anomaly detection, and support for threat prediction; however, it does not eliminate the human’s primary role in interpreting information and bearing responsibility for safety decisions. A case study based on a risk matrix indicates that the highest levels of risk in a military scenario often result from data interruptions and inconsistencies, as well as from delays and decision-making errors, rather than solely from technical failures. The conclusions highlight the necessity of developing a coherent and accountable safety model in which artificial intelligence performs an analytical support function, integrated with procedures, information flows, and personnel competencies.