Applying artificial intelligence within decision support systems and its role in improving proactive thinking and reducing security threats: The mediating role of data quality

The study aimed to identify the impact of applying artificial intelligence within decision support systems in improving the level of proactive thinking and reducing security threats in government institutions in the Arab Republic of Egypt, as well as to examine the mediating role of data quality in this relationship, at a significance level of (α ≤ 0.05). The study sample consisted of (360) participants working in the departments of information technology, decision support, and cybersecurity within government institutions and national authorities that rely on AI-enhanced decision support systems. The study adopted the descriptive analytical method and used a questionnaire as the primary tool for data collection. The findings revealed a statistically significant relationship between certain dimensions of artificial intelligence (predictive analytics systems, intelligent agents, and machine learning) and the level of proactive thinking. The results also showed a statistically significant relationship between artificial intelligence and the reduction of security threats. Furthermore, the study demonstrated a statistically significant mediating role of data quality in the relationship between artificial intelligence and proactive thinking, as well as between artificial intelligence and the reduction of security threats. The study recommended strengthening the use of artificial intelligence in decision support systems, improving data quality, and integrating these systems with cybersecurity measures to maximize predictive and preventive benefits within institutions. It also recommended identifying the theoretical foundations of artificial intelligence applications in decision support systems and their role in enhancing proactive thinking within security institutions, determining the most prominent AI applications used in such systems, and clarifying how previous literature interprets methods for promoting AI adoption in decision support systems to improve data quality in security institutions.