AI-Driven Security: Redefining Security Informations Systems within Digital Governance

The increasing integration of Artificial Intelligence (AI) within Security Information Systems (SIS) presents a significant shift in digital governance, where governments rely heavily on secure digital infrastructures to manage public services. The escalating threat landscape has necessitated a proactive approach to cybersecurity, and AI is proving crucial in enhancing threat detection, automating responses, and minimizing human error. However, many governments, particularly in developing nations, are struggling to bridge the gap between their current security measures and the complex challenges posed by sophisticated cyber threats. This study aims to explore how AI can redefine SIS in digital governance by improving national resilience and addressing the gaps in traditional security protocols. The study employs a systematic literature review methodology, examining recent research to analyze AI’s role in enhancing SIS, with a particular focus on machine learning, deep learning, and adaptive security measures. Findings indicate that AI-driven security significantly enhances the speed and accuracy of threat detection, providing dynamic solutions that continuously adapt to evolving threats. Nonetheless, the study also highlights concerns around ethical governance, data privacy, and transparency, pointing to the need for robust regulatory frameworks to govern AI’s deployment in public sector security systems. The implications of this research are twofold: theoretically, it contributes to the broader understanding of AI’s role in cybersecurity resilience; practically, it offers insights for policymakers aiming to integrate AI into their governance strategies. The study concludes by recommending further empirical research, particularly in the context of developing nations, where AI-driven security solutions are needed to enhance national cybersecurity frameworks and protect critical public infrastructures.