The Role of Artificial Intelligence in Strengthening Modern Cybersecurity Systems
TL;DR
The review finds that artificial intelligence enables proactive threat detection, anomaly identification, and the automation of analysis and response at a scale beyond human capacity, yet its effectiveness is constrained by adversarial machine learning, data quality and drift, false positives, opacity, and the dual use of generative models by attackers.
Abstract
Modern organizations face an expanding threat landscape of sophisticated malware, automated intrusions, and large-scale data breaches that outpace traditional signature-based defenses. This paper examines the role of artificial intelligence (AI) in strengthening modern cybersecurity systems and provides a structured and comprehensive synthesis of the field, covering the foundations and taxonomy of AI techniques, their application to proactive detection, incident response, and security operations across networks, endpoints, and cloud, and the benefits, challenges, sector specific applications, evaluation methods, ethical and workforce considerations, and the emerging role of generative artificial intelligence. The review finds that artificial intelligence enables proactive threat detection, anomaly identification, and the automation of analysis and response at a scale beyond human capacity, yet its effectiveness is constrained by adversarial machine learning, data quality and drift, false positives, opacity, and the dual use of generative models by attackers. It concludes that the most effective and responsible deployments integrate artificial intelligence with established controls, ground it in sound data and governance, and preserve human oversight, and it offers recommendations and identifies open challenges for researchers, practitioners, and policymakers.