Course Schedules

Classroom 6 Sessions
Online / Live
Live

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Introduction

Understanding and Managing AI Risk & Shadow AI in Organizations Training Course provides professionals with a structured approach to identifying, assessing, and controlling emerging risks associated with artificial intelligence. As organisations increasingly adopt AI tools across departments, many systems are introduced informally through employee-led initiatives, creating the phenomenon known as Shadow AI. This uncontrolled use can expose organisations to data privacy breaches, cybersecurity vulnerabilities, regulatory non-compliance, and reputational damage.

This AI Risk & Shadow AI Training Course explains how AI risk differs from traditional IT and digital risk, and why organisations must adopt governance frameworks that balance innovation with responsible oversight. Participants explore practical approaches to mapping AI use, assessing risk exposure, and implementing effective governance controls.

Through real organisational scenarios and risk-based frameworks, the course equips professionals to manage AI adoption safely, ensuring that innovation remains secure, ethical, and aligned with organisational objectives.

What are the Goals?

This AI Risk & Shadow AI Training Course develops the capability to identify, assess, and manage AI-related risks using a structured governance and risk management approach. It strengthens organisational readiness to oversee both approved AI systems and emerging Shadow AI usage.

Participants will:

  • Understand how AI risk differs from traditional IT and digital risk models

  • Explain the concept of Shadow AI and its implications for organisational governance

  • Identify AI and Shadow AI usage across business units and operational processes

  • Classify AI use cases according to potential risk exposure

  • Apply structured methodologies for AI risk assessment and evaluation

  • Design practical governance and control measures to mitigate AI-related risks

  • Integrate AI risk management into enterprise risk management (ERM) frameworks

  • Support responsible, secure, and compliant AI adoption across the organisation

Who is this Training Course for?

This Understanding and Managing AI Risk & Shadow AI in Organizations Training Course is designed for professionals responsible for governance, oversight, compliance, and risk management in environments where artificial intelligence tools are increasingly used.

The course is particularly valuable for organisations facing rapid AI adoption while responding to growing regulatory, ethical, and operational expectations around responsible AI use.

This training course will greatly benefit:

  • Senior executives and organisational decision-makers

  • Governance, Risk, and Compliance (GRC) professionals

  • Enterprise risk managers and internal auditors

  • IT, cybersecurity, and data protection specialists

  • Compliance and legal professionals

  • Digital transformation and innovation leaders

  • Public sector professionals and regulated industry specialists

  • Professionals responsible for AI oversight, governance, and accountability

How will this Training Course be Presented?

This AI Risk & Shadow AI Training Course uses a practical, governance-focused learning approach designed to connect theory with real organisational practice. Instructor-led sessions introduce the foundations of AI risk, Shadow AI dynamics, and governance frameworks in a structured and accessible way.

Participants examine case studies demonstrating how unmanaged AI usage can lead to operational disruptions, regulatory penalties, and reputational risks. Guided discussions encourage professionals to analyse how AI and Shadow AI appear within their own organisational environments.

Interactive workshops provide hands-on experience in identifying AI usage, conducting structured risk assessments, and designing proportionate governance controls. Participants also explore how AI risk management integrates with enterprise risk management, compliance processes, and cybersecurity practices.

This practical learning approach ensures participants can translate concepts into actionable governance strategies for secure and responsible AI adoption.

Course Content

Day 1

Day One: Foundations of AI Risk and Shadow AI

  • Overview of Artificial Intelligence in modern organizations
  • How AI is used across operations, services, and decision-making
  • Understanding AI risk: definitions, scope, and drivers
  • Differences between IT risk, digital risk, and AI risk
  • Introduction to Shadow AI: concepts, causes, and examples
  • Shadow AI versus Shadow IT
  • Why Shadow AI emerges in organizations
  • Introduction to AI governance and accountability
  • Discussion: Identifying AI and Shadow AI use within participants’ organizations
Day 2

Day Two: AI Risk Categories and Organizational Impact

  • 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
  • Reputational and trust-related risks
  • How Shadow AI amplifies AI risk exposure
  • Case Study: Lessons learned from AI risk incidents
Day 3

Day Three: Identifying and Assessing AI & Shadow AI Risks

  • Mapping AI use across business units
  • Identifying informal and unapproved AI usage
  • Indicators and red flags of Shadow AI
  • Risk classification of AI use cases
  • AI risk assessment methodologies
  • Impact and likelihood analysis
  • Risk registers and documentation requirements
  • Assessing risk in generative AI tools
  • Workshop: Conducting an AI and Shadow AI risk assessment
Day 4

Day Four: Managing and Controlling AI Risk

  • Principles of risk-based AI governance
  • AI acceptable-use policies and employee guidelines
  • Managing employee use of generative AI
  • Data governance and access controls
  • Human-in-the-loop (HITL) and human-on-the-loop (HOTL) controls
  • Monitoring, logging, and auditability
  • Managing third-party and vendor AI risks
  • Incident response and escalation for AI misuse
  • Workshop: Designing AI risk controls and mitigation actions
Day 5

Day Five: Governing Shadow AI and Embedding AI Risk Management

  • Shadow AI as a governance and cultural challenge
  • Bringing Shadow AI into controlled environments
  • Approved AI tools, platforms, and innovation sandboxes
  • Roles, responsibilities, and accountability for AI risk
  • Integrating AI risk into enterprise risk management (ERM)
  • Aligning AI risk management with ESG and organizational values
  • Measuring AI and Shadow AI risk maturity
  • Developing an AI risk and Shadow AI roadmap
  • Capstone Exercise: Creating an AI risk and Shadow AI management action plan
  • Course review and implementation next steps

The Certificate

Recognition
  • Anderson Certificate of Completion for delegates who attend and complete the training course
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