Development Training Course on
Understanding and Managing AI Risk & Shadow AI in Organizations
Identifying, Assessing, and Controlling AI Risks for Responsible and Secure AI Adoption
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Why Choose Us
The Understanding and Managing AI Risk & Shadow AI in Organizations training course provides risk, governance, compliance and technology professionals with a structured framework for responsible AI risk management. It explains how to identify, assess, manage and govern AI risks, with particular attention to the growing challenge of Shadow AI. These exposures can be organisational, ethical, legal and reputational, requiring effective governance before incidents occur. Participants gain the knowledge, tools and governance frameworks needed to manage AI risk responsibly and effectively.
AI risk is already an operational reality rather than a matter for future consideration. Current concerns include biased decision-making, data privacy breaches and employees using unmanaged generative AI tools without oversight. Shadow AI, meaning informal and unapproved AI use across business units, is among the most significant and least understood risk vectors. Coverage includes AI risk categories, Shadow AI identification and assessment, acceptable-use policies, human-in-the-loop controls and third-party vendor risk. It also addresses incident response, governance frameworks and a capstone action-planning exercise through real-world scenarios and practical governance application.
This Understanding and Managing AI Risk & Shadow AI in Organizations training course will highlight:
- Identifying and assessing key categories of AI risk
- Recognising and evaluating Shadow AI across business units
- Establishing acceptable-use policies for AI tools
- Applying human-in-the-loop controls to AI activities
- Managing third-party AI vendor risk and incident response
- Developing governance frameworks and practical action plans
How will this Training Course be Presented?
The Understanding and Managing AI Risk & Shadow AI in Organizations Course uses a structured, practice-intensive learning methodology that progresses from AI risk fundamentals and Shadow AI concepts to risk category analysis, assessment methods, control design, and governance framework development, concluding with a capstone exercise in which delegates produce a comprehensive AI risk and Shadow AI management action plan.
Real-world AI risk incident case studies, risk assessment workshops, policy development exercises, and governance mapping sessions are incorporated across each day, enabling delegates to relate the frameworks to the actual risk management challenges within their own organisational settings.
Delivery approaches include:
- Instructor-led sessions addressing AI risk definitions, Shadow AI concepts, risk category frameworks, and governance principles
- AI risk category analysis sessions exploring strategic, operational, data privacy, cybersecurity, ethical, legal, and reputational types of risk
- Shadow AI identification and mapping workshops that apply indicators, warning signs, and risk classification to realistic AI usage scenarios
- AI risk assessment workshops involving impact and likelihood analysis, risk register creation, and the evaluation of risks associated with generative AI tools
- A capstone action-planning exercise focused on creating a complete, organisation-specific action plan for managing AI risk and Shadow AI