Evaluation of Intelligence Management Strategies in Improving National Security and Resilience Preparedness - Riyanto Wujarso; Guntur Eko Saputro (Goodwood Publishing, 2026)
Purpose: This study aims to evaluate the convergence between technology-based intelligence management, strategic risk mitigation, and national resilience in the face of increasingly complex contemporary threats. Methodology: Using the Systematic Literature Review (SLR) method, this study analyzed 40 selected articles from the Scopus and Association for Computing Machinery (ACM) Computing Survey databases published between 2023 and 2025. Results: The findings indicate that the integration of Artificial Intelligence (AI) and Big Data is a key pillar of modern intelligence transformation. The synchronization of strategic risk with defense policy and the synergy between cybersecurity and nonmilitary intelligence have proven crucial in effectively responding to hybrid threats. Conclusions: This study concludes that the adoption of AI has become imperative to strengthen early detection capabilities against rapidly moving threats. In addition, an adaptive risk framework is needed to mitigate volatile, non-military threats. Ultimately, robust national resilience depends heavily on the effectiveness of cross-sector collaboration to protect critical infrastructure from various disruptions in the digital age. Limitations: This study is limited to academic literature indexed in Scopus and ACM, thus not covering closed policy documents or gray literature. Contributions: This study provides a strategic foundation for the formulation of defense policies that are adaptive to technology and enriches the literature on national security in the digital age.