https://www.techzine.eu/news/devops/119440/qwiet-ai-programming-assistant-suggests-code-improvements-on-its-own/ What is agentic AI, and how does it differ from traditional AI in cybersecurity? Agentic AI refers to autonomous, goal-oriented systems that can perceive their environment, make decisions, and take actions to achieve specific objectives. Agentic AI is a more flexible and adaptive version of traditional AI. In cybersecurity, agentic AI enables continuous monitoring, real-time threat detection, and proactive response capabilities. What are some examples of real-world agentic AI in cybersecurity? Examples of agentic AI in cybersecurity include: Autonomous threat detection and response platforms that continuously monitor networks and endpoints for malicious activity AI-powered vulnerability scans that prioritize and identify security flaws within applications and infrastructure Intelligent threat intelligence systems gather data from multiple sources and analyze it to provide proactive protection against emerging threats Automated incident response tools can mitigate and contain cyber attacks without the need for human intervention AI-driven fraud detection solutions that identify and prevent fraudulent activities in real-time Agentic AI can help address the cybersecurity skills gap by automating many of the repetitive and time-consuming tasks that security professionals currently handle manually. By taking on tasks such as continuous monitoring, threat detection, vulnerability scanning, and incident response, agentic AI systems can free up human experts to focus on more strategic and complex security challenges. Additionally, the insights and recommendations provided by agentic AI can help less experienced security personnel make more informed decisions and respond more effectively to potential threats. What are the potential implications of agentic AI for compliance and regulatory requirements in cybersecurity? Agentic AI can help organizations meet complia