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The Understanding and Managing AI Risk & Shadow AI in Organizations Course gives risk, governance, compliance, and technology professionals a comprehensive, structured framework for identifying, assessing, managing, and governing AI risk with particular focus on the growing challenge of Shadow AI and the organisational, ethical, legal, and reputational exposures it creates.
AI risk is no longer a future consideration it is a present operational reality. From biased decision-making and data privacy breaches to unmanaged generative AI tools used by employees without oversight, the risks created by AI in organisations are expanding faster than most governance frameworks are equipped to handle. Shadow AI — the informal, unapproved use of AI tools across business units is one of the most significant and least understood risk vectors organisations face today.
This course addresses that challenge directly covering the full spectrum of AI risk categories, Shadow AI identification and assessment methodologies, acceptable-use policies, human-in-the-loop controls, third-party vendor risk, incident response, governance frameworks, and a capstone action planning exercise. Every module is grounded in real-world risk scenarios and practical governance application.
The Understanding and Managing AI Risk & Shadow AI in Organizations Course is built for professionals who are accountable for managing AI risk responsibly — and who want the knowledge, tools, and governance frameworks to do it effectively before incidents occur.
The Understanding and Managing AI Risk & Shadow AI in Organizations Course is designed to develop comprehensive AI risk management and Shadow AI governance capability — from risk foundations and category assessment through identification, control design, and enterprise risk integration.
By the end of this course, participants will be able to:
The Understanding and Managing AI Risk & Shadow AI in Organizations Course is designed for risk, governance, compliance, technology, and HR professionals who are responsible for identifying, assessing, and managing AI-related risks including the increasingly significant challenge of Shadow AI across their organisations.
This course is suitable for:
The Understanding and Managing AI Risk & Shadow AI in Organizations Course is delivered through a structured, practically intensive learning approach that moves from AI risk foundations and Shadow AI concepts through risk category analysis, assessment methodology, control design, and governance framework development culminating in a capstone exercise where delegates create a complete AI risk and Shadow AI management action plan.
Case studies of real AI risk incidents, risk assessment workshops, policy design exercises, and governance mapping sessions are integrated throughout every day — ensuring delegates connect frameworks to the genuine risk management challenges they face in their own organisational contexts.
Delivery methods include:
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Common questions about our training courses
Shadow AI refers to the informal, unapproved use of AI tools by employees and business units without organisational oversight or governance including the use of consumer generative AI platforms, browser-based AI tools, and AI-enabled applications that bypass IT approval and data governance controls. Shadow AI is addressed throughout this course because it represents one of the fastest-growing and most underestimated AI risk vectors organisations face — creating data privacy, intellectual property, compliance, and reputational exposures that many organisations are not yet equipped to manage.
Day 3 covers AI and Shadow AI identification in full including how to map AI usage across business units, identify indicators and red flags of informal and unapproved AI usage, and classify AI use cases by risk profile. Delegates complete a hands-on risk assessment workshop that applies these methodologies to realistic organisational scenarios — leaving with a practical identification and mapping process they can deploy immediately within their own organisations.
Managing employee generative AI usage is addressed directly within Day 4 covering how to develop acceptable-use guidelines for generative AI tools, how to balance the productivity benefits of generative AI with data confidentiality and intellectual property risks, and how to build the monitoring and logging frameworks needed to maintain visibility of how generative AI is being used across the workforce. Delegates leave with a practical governance approach that manages generative AI risk without creating cultural resistance to AI adoption.
Day 2 covers the full spectrum of AI risk categories — including strategic and decision-making risks, operational and performance risks, data privacy and confidentiality risks, cybersecurity and intellectual property risks, ethical, bias, and fairness risks, legal and regulatory compliance risks, and reputational and trust-related risks. Delegates develop the ability to evaluate each risk category in the context of their own organisation's AI usage — and to understand how Shadow AI amplifies exposure across every one of these dimensions.
Day 4 covers AI risk control design in full including acceptable-use policy development, data governance and access controls, human-in-the-loop and human-on-the-loop oversight frameworks, monitoring and auditability requirements, and vendor and third-party AI risk management. Delegates complete a control design workshop — leaving with a practical, structured approach to building the policies and controls that reduce AI risk exposure without preventing the productive use of AI across the organisation.
Incident response and escalation for AI misuse are addressed within Day 4 — covering how to recognise when AI misuse has occurred or is at risk of occurring, what the immediate response priorities are, how to escalate within governance structures, and how to investigate and document AI incidents in a way that supports regulatory reporting and organisational learning. Delegates develop both the procedural knowledge and the leadership readiness to manage AI misuse incidents effectively when they arise.
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