Abstract
With the rapid expansion of digital technologies and interconnected systems, organizations face increasingly sophisticated cybersecurity threats that challenge traditional security approaches. Artificial intelligence (AI) has emerged as a key technology for enhancing cybersecurity through automated threat detection, predictive analytics, anomaly identification, and adaptive response mechanisms. This study conducts a systematic literature review to examine the role of AI in modern cybersecurity environments and assess its contribution to strengthening organizational cyber defense strategies. Following the PRISMA framework, relevant studies from major academic databases are analyzed to identify current trends in AI-driven applications such as intrusion detection, malware classification, and network anomaly detection. Overall, the study aims to provide a comprehensive perspective on the evolving relationship between AI and cybersecurity and highlights future directions for developing secure and resilient cyber defense frameworks.
Recommended Citation
Mannam, Jahnavi and Kuai, Le (Carol), "Artificial Intelligence in Cybersecurity: A Systematic Literature Review of AI-Driven Threat Detection and Organizational Defense" (2026). AMCIS 2026 TREOs. 173.
https://aisel.aisnet.org/treos_amcis2026/173