[100% OFF] Shadow AI: Security Risks, Policies and Governance

This course contains the use of artificial intelligence.

Your employees are already using AI. Some of those tools are approved. Others are downloaded, connected, or opened in a browser without anyone in IT or security knowing. A salesperson pastes a customer proposal into a chatbot. A developer connects an AI coding assistant to a private repository. A manager invites an unfamiliar AI meeting bot into a confidential discussion.

These shortcuts can save time, but they can also create risks that are easy to miss. That is the challenge of Shadow AI.

Shadow AI: Security Risks, Policies and Governance is a practical guide to understanding unsanctioned AI use and building a safer path forward. Instead of treating every employee who experiments with AI as a security problem, you will learn how to identify genuine exposure, assess business impact, set clear expectations, and offer approved alternatives that people will actually use in their everyday work.

We start with the fundamentals: what Shadow AI means, how it differs from Shadow IT, and why employees turn to unapproved tools. Then we explore the ways sensitive information can leave an organization through prompts, file uploads, browser extensions, meeting assistants, coding tools, agents, and third-party integrations.

You will examine privacy and cybersecurity concerns, including confidential data disclosure, intellectual property exposure, unsafe permissions, prompt injection, and vendor data practices. You will also learn how to evaluate AI providers, document risks, and distinguish high-priority issues from low-risk experimentation.

Throughout the course, you will learn to:

• Discover potential Shadow AI use through appropriate surveys, application inventories, and security telemetry.

• Build an AI tool inventory, risk register, and vendor evaluation scorecard.

• Write an understandable AI acceptable use policy with clear rules, approval pathways, and exceptions.

• Recommend safeguards such as identity controls, data loss prevention, secure AI gateways, and monitoring.

• Create an adoption plan that gives employees useful, approved AI options.

• Prepare an incident response plan and a practical governance roadmap.

The lessons follow Northstar Enterprises, a fictional organization dealing with the same questions many real companies face. Through hands-on scenarios, you will assess unapproved applications, trace a simulated data exposure, design policies, evaluate security controls, and work through an incident tabletop exercise. Downloadable templates help you turn those activities into materials you can adapt for your own environment.

We also connect the work to recognized references such as the NIST AI Risk Management Framework, ISO/IEC 42001, and OWASP guidance, without pretending that one framework fits every business or legal situation.

This course is designed for cybersecurity and IT professionals, risk and compliance teams, AI consultants, technology leaders, and anyone helping an organization adopt AI responsibly. No programming experience, paid security platform, or advanced cybersecurity background is required.

By the end, you will have more than a list of Shadow AI threats. You will have a structured approach for finding problems, making informed decisions, communicating policies, and enabling safer AI adoption.

The goal is not to stop people from using AI. It is to make AI use visible, responsible, and trustworthy.