AI-powered Risk Mitigation and Intelligent Incident Response in Cybersecurity

Traditional security measures can no longer guarantee timeliness and effectiveness against imminent risk exposures due to the growing complexity and frequency of cyber threats. This chapter attempts to analyze how artificial intelligence is altering the cyber risk management landscape by enabling proactive threat detection, predictive risk assessment, and automated incident response. The chapter examines AI methodologies that include machine learning, deep learning, and natural language processing, and how these are being utilized in anomaly detection, incident workflow orchestration, and root cause analysis. The integration of AI with existing cybersecurity infrastructures like security information and event management and security orchestration, automation, and response platforms is also taken into account, particularly in terms of speed, accuracy, and scalability improvements. Barriers to AI are also discussed, such as issues with data bias, adversarial attacks, and ethical issues, together with interesting new developments like explainable AI and federated learning. Through relevant case studies and practical examples, the chapter will help readers get up to speed on how AI can be strategically deployed to bolster cyber resilience in modern-day digital ecosystems.