Securing Corporate AI: Threat Mitigation and Defense Checklists

The rapid adoption of artificial intelligence brings massive productivity gains, but it also introduces critical security vulnerabilities that traditional defense systems are not equipped to catch. Securing your organization requires a proactive approach to understanding and neutralizing these emerging vectors. This text-based course equips security professionals and IT administrators with the knowledge to safeguard corporate environments against AI-specific threats. You will transition from understanding basic AI risks to implementing systematic, actionable checklists that protect your proprietary data and digital infrastructure. What you'll learn: - Understand foundational AI security concepts, including data privacy risks and the challenges of shadow AI. - Identify vulnerabilities such as prompt injection, data poisoning, and model inversion in corporate systems. - Apply the OWASP Top 10 framework for Large Language Models to evaluate and secure your current deployments. - Establish secure governance policies for employee use of external generative AI tools. - Implement step-by-step security checklists to protect Retrieval-Augmented Generation pipelines and API integrations. - Monitor and audit AI inputs and outputs to prevent unauthorized data exfiltration. The course begins with essential terminology and the core mechanics of AI security before guiding you through structured, actionable checklists for threat prevention, monitoring, and governance. You will study practical scenarios and defense workflows entirely through clear, written analysis. This course is designed for information security officers, IT managers, and business leaders who need to secure their organization's AI adoption. No prior machine learning or programming background is required. Begin building your company's AI defense strategy today.