<![CDATA[This research aims to demonstrate the impact of Boundary Spanning processes on crisis management phases through the mediating role of artificial intelligence, specifically within the Diyala Governorate Office. The research stems from a central problem: the extent to which Boundary Spanning processes, with their dimensions of surveying, monitoring, prediction, and evaluation, can enhance crisis management phases—namely, early warning and detection, preparedness and prevention, crisis containment, recovery, and organizational learning—when employing artificial intelligence technologies. The research adopted a descriptive-analytical approach, deemed the most suitable for the nature and objectives of the study. It also utilized a quantitative approach through a questionnaire and a qualitative approach through semi-structured interviews and analysis of official documents. The research population consisted of 293 employees of the Diyala Governorate Office. A questionnaire, designed based on existing literature and previous studies, was used to measure the research variables and test the hypotheses. The research reached a number of conclusions, most notably the existence of a statistically significant correlation and influence between Boundary Spanning processes and crisis management phases, as well as a correlation and influence between artificial intelligence and crisis management phases. The results also showed that artificial intelligence plays a significant mediating role in enhancing the impact of Boundary Spanning processes during crisis management phases. The research concluded that the integration of Boundary Spanning processes and artificial intelligence technologies represents a modern strategic approach that can contribute to enhancing the preparedness of the Diyala Governorate Office to face crises and transitioning from reactive to proactive management based on prediction and intelligent data analysis.]]>
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