Your Updated Guide to AI in Cybersecurity: Adoption, Trends, Challenges, and The Future

This report provides a comprehensive overview of AI in cybersecurity, detailing defensive applications (threat detection and response, UEBA, threat hunting, predictive analytics, graph analysis) and adversarial misuse (deepfakes, AI-driven phishing/vishing, reconnaissance, model extraction, obfuscation, prompt injection, and data poisoning). It outlines key risks—data/model integrity, inconsistent AI decisions, ethical/privacy concerns, and fragmented regulation—and recommends governance frameworks, cross-functional alignment, updated IR playbooks, and AI-centric hygiene to adopt AI safely and strengthen resilience.