The role of Artificial Intelligence in cybersecurity

AI implementation in cybersecurity frameworks became necessary due to rising cyber threat complexity and frequency that made standard security measures insufficient. This research analyzes how Artificial Intelligence helps security practitioners identify cyber threats at higher velocities and with greater accuracy than standard procedures. The paper studies how machine learning with natural language processing and behavioral analytics transforms cybersecurity systems by detecting irregularities while performing automatic threat defense operations. Through their qualitative research design and three specific real-world examples, including Darktrace, IBM Watson, and Cylance PROTECT, this article validates the extensive positive impact of AI tools on threat intelligence and incident response times within various industries. AI demonstrates its effectiveness through two key outcomes: real-time attack detection, preemptive containment, human analysis workload reduction, and attack response acceleration. Digital infrastructure security finds a future-oriented solution through AI even though limitations related to bias and explainability exist. This research highlights the urgent need to create new AI systems together with moral principles that will establish strong cybersecurity networks.