Artificial intelligence has moved from experimental to essential. Tools powered by machine learning and generative AI are now embedded in workflows across industries—from finance and healthcare to marketing and software development. But as adoption grows, so do the risks. Systems can be manipulated, data can be exposed, and poorly secured AI models can create serious vulnerabilities. This has created a new demand: professionals who understand not just AI—but how to secure it. Why AI Security Is Becoming a Critical Skill AI systems introduce unique security challenges that traditional cybersecurity doesn’t fully cover: Data poisoning attacks that corrupt training datasets Model theft and reverse engineering Adversarial inputs designed to trick AI systems Privacy risks from sensitive training data Understanding these threats requires a blend of knowledge from cybersecurity, data science, and AI development. AI security certifications are designed to bridge that gap.…