Secure Generative AI in the Workplace: Risks, Policy, and Best Practices

Generative artificial intelligence is transforming how we work, but using these tools without clear security guidelines can expose your organization to major data leaks and compliance risks. This course helps you navigate the balance between AI productivity and robust data protection. You will gain a clear, practical framework for using large language models and other AI systems safely in your daily professional tasks, transitioning from using AI blindly to confidently applying risk-mitigation strategies. What you'll learn: Understand the core terminology, capabilities, and security risks of modern generative AI systems; Prevent corporate data leakage by implementing secure prompting techniques and understanding model training data policies; Recognize common AI-specific security threats, including prompt injection, shadow AI, and hallucinated information; Apply human-in-the-loop oversight to verify AI-generated outputs for accuracy, bias, and intellectual property compliance; Formulate practical AI guidelines and policy frameworks tailored to your team or organization's workflow. The course begins with foundational concepts of how generative models process data, followed by an in-depth exploration of privacy and security risks. You will then study practical safeguarding techniques and policy structures through clear, text-based scenarios. This course is designed for professionals, managers, and team leaders who want to use generative AI tools safely and effectively in their daily operations, with no technical background or prior programming experience required. Start reading today to secure your workflow and lead your team into the future of responsible AI.