THE ROLE OF AI IN ENHANCING CYBERSECURITY: A STUDY OF AI-POWERED THREAT DETECTION AND RESPONSE SYSTEMS

Abstract

The current study aimed to understand the impact of artificial intelligence on improving cybersecurity systems. Mixed-methods approach was employed to analyze the operational metrics of six AI cybersecurity platforms and semi-structured interviews with 45 professionals working in 500, government, and cybersecurity companies. Within case studies of three in addition to the implementation processes, the research focused on measuring the response times, accuracy, and detection of various category threats. Other efforts were made to capture the real operationalized implementation of AI in cyber systems. The results noted that AIs systems had a 94.7 detection accuracy rate, a 68% drop in false positives, and response times increased by 75% on average. Other results showed the machine-learning algorithm's superiority in determining zero-day attacks and advanced persistent threats. The study found serious challenges to cyber systems such as implementation cost, skill gap, and algorithmic bias. This study expands the scholarship on the usage of AI in cyber systems, providing practical recommendations to the organizations willing to integrate AI in their cyber systems. Findings indicate the increased capabilities of AI on cyber systems, leaves the issues of technical, organizational, and ethical challenges for consideration. This research lays groundwork for further studies on AI as well as practicality for professionals working in the field as it concerns the intersection of AI and cybersecurity.